{"paper_id":"e39347c6-b5d4-41aa-b5ba-9bfabc0f4dc5","body_text":"Genetically encoded biosensor enabled mining, characterisation and engineering of aromatic acid MFS transporters | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetically encoded biosensor enabled mining, characterisation and engineering of aromatic acid MFS transporters Philip Le Roy, Micaela Chacόn, Neil Dixon This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6931086/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Oct, 2025 Read the published version in Journal of Biological Engineering → Version 1 posted 14 You are reading this latest preprint version Abstract Active transport of chemical species across the cell membrane represents a critical biological and biotechnological function, allowing the cell to selectively import compounds of nutritional value whilst exporting potentially toxic compounds. Major facilitator superfamily (MFS) transporters represent a ubiquitous class able to uptake and export an array of different chemical species. When designing biosynthetic pathways within microbial hosts, for production or remediation, transport is often critical to the efficiency of the resulting engineered strain. However, transport is a commonly neglected node for characterisation and engineering given difficulties in producing, purifying and assaying membrane transport proteins outside of their native environment. Here, using syntenic analysis and genetically encoded biosensors a library of MFS transporters were screened for their ability to uptake the aromatic acids, protocatechuic acid and terephthalic acid. The structure activity relationships of the corresponding transporters, PcaK and TphK, were then assessed with library of aromatic acid effectors. Finally, the feasibility of protein engineering was assessed, by the creation of chimeric MFS transporters, revealing a degree of effector recognition plasticity and the modularity of core transmembrane domains. This study provides a library of validated MFS transporters and demonstrates the value of employing genetically encoded biosensors in the characterisation and engineering of this important transport function. Biosensors Major Facilitator Superfamily Protocatechuic acid Terephthalic acid Syntenic Analysis Aromatic Acid Transporters Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Microbial cell factories are foundational to the future bioeconomy, permitting the sustainable production of chemicals and materials from renewable and waste feedstocks. Efficient utilisation of these feedstocks is essential for process economics; however, this can be challenged by the compositional and chemical heterogeneity of an input stream. Here, the poor import of feedstock-derived substrates can impose large bottlenecks on strain productivity due to insufficient intracellular concentration of the substrate or through an inability to efficiently remove toxic compounds from the intracellular space. To overcome this, transporter engineering aimed at optimising the movement of substrates and intermediates across the microbial cell membrane and the coupling of transport to other cellular processes constitutes an important facet of strain development [ 1 – 4 ]. Further, engineering transporters for broader substrate scope can be used to expand the range of metabolically accessible compounds, permitting more complete utilisation of feedstocks and greater conversion efficiency [ 5 ]. Transport proteins are immensely diverse both in terms of structure and function, and are classified into many families based on these traits [ 6 ]. For the purpose of biomolecular engineering approaches concerning waste feedstocks such as lignocellulose however, this pool can be narrowed to the major facilitator superfamily (MFS) [ 7 – 13 ], ATP binding cassette (ABC) [ 14 – 17 ] family, tripartite ATP independent periplasmic (TRAP) transporters [ 18 ], and ion transporter superfamily (IT) [ 19 ] for lignin aromatics based on experimentally confirmed uptake of lignocellulosic substrates by these transporter classes. The MFS is the largest and most diverse family of secondary active transporters. This superfamily can be further categorised into 16 families and 89 subfamilies based on phylogeny and substrate scope [ 20 ]. The substrate scope of MFS’ encompasses a diverse array of substrates, such as: sugars (sugar porters), inorganic or organic anions or cations (anion:cation symporters), aromatic acids (aromatic acid symporters/exporters) and drug/hydrophobic substances (drug:proton(H + ) antiporters) [ 20 ]. Their ability to import and export valuable substrates such as sugars and organic acid make these transporters attractive targets for microbial strain engineering [ 1 , 21 – 23 ]. In addition to their valuable function, MFS proteins are generally quite small, typically consisting of 400–600 amino acids comprising 12–14 transmembrane helices, in addition to being driven by ion gradients instead of ATP hydrolysis, resulting in low cellular burden. More than three-quarters of transmembrane containing proteins, such as those belonging to the MFS class, are functionally unclassified, despite these proteins accounting for more than 20–30% of the total number of any one proteome [ 24 ]. Even in characterised model organisms, such as Escherichia coli , 53% of membrane transporters lack characterisation [ 6 ]. This is due to two major factors, firstly, the functional flexibility/redundancy of transporters makes sequence-function relationships challenging to ascertain [ 25 ]. As such, protein sequence homology-based approaches to for the discovery of transporters alone is ineffective [ 26 ]. Indeed, MFS transporters are known to display particularly poor sequence conservation, with identity typically ranging 12–18%, between members despite the conserved MFS fold; sequence [ 27 ]. Secondly, transport proteins within the MFS are inherently unstable outside of their native phospholipid environment and thus require specialist approaches for expression, purification and characterisation [ 20 ]. Direct vectorial measurement of transport requires labelled substrates, which can become prohibitively expensive for mid to high-throughput screens. For MFS’s that rely on H + symport, cheaper assays that utilise pH sensitive dyes are available, however these dyes can lack sensitivity for transporters with low turnover [ 20 ]. MFS transporters of the aromatic H + symporter class have been demonstrated to be critical for the uptake lignocellulose-derived substrates, in particular for lignin an aromatic rich component with great potential as a feedstock for microbial valorisation [ 25 ]. Lignin is highly enriched in hydroxycinnamoyl aromatics such as p- coumaroyl (H), coniferyl (G) and sinapyl (S) alcohols with acid derivates such as coumaric, ferulic, and synapic acid respectively liberated following treatment of the lignin [ 28 ]. Saprophytic strains of bacteria such as Pseudomonas putida KT2440, Rhodococcus jostii RHA1, Sphingobium sp. SYK-6 have evolved pathways for the uptake and subsequent utilisation of these aromatics for growth [ 28 ]. Of these pathways, coumaric and ferulic acid ultimately converge on protocatechuic acid (PCA) as a central node in aromatic catabolism before being directed to the TCA cycle [ 28 ]. Disruption of these aromatic catabolic pathways in hosts, can lead to the accumulation of value-added intermediates, such as vanillin and 4-hydroxybenzoic acid, protocatechuic acid (PCA) and β-ketoadipate [ 29 – 32 ]. Another aromatic-rich polymer, of anthropogenic origin, is polyethylene terephthalate (PET) plastic, which can microbially degraded and has been proposed as potential feedstock for microbial growth and bioproduction [ 33 ]. PET represents 12% (by weight) of total global solid waste [ 34 ], and is composed of a repeating unit of terephthalic acid (TPA) esterified to an ethylene glycol (EG), and finds its primary use in the manufacture of single use disposable packaging such as in bottles and food containers [ 35 ]. Recently, several bacteria including Rhodococcus jostii RHA1, Ideonella sakiensis , and Pseudomonas umsongensis amongst others, have been reported to possess the ability to import and utilise TPA, for growth, following import via an H + symporter MFS transporter opening up the possibility of applying this waste stream as a substrate for biotechnological processes [ 36 , 37 ]. The MFS-dependent uptake of PCA and TPA has been reported to occur via the action of two MFS transporters, PcaK and TphK (also known as TpaK in other literature, but referred to as TphK here from now onwards), respectively [ 11 , 38 , 39 ]. Strains deficient in PcaK universally exhibit reduced growth on PCA, while those deficient in TphK exhibit no growth on TPA [ 38 , 40 , 41 ]. Characterisation of PcaK using proteoliposomes has indicated this transporter has a substrate preference for PCA and 4-hydroxybenzoic acid (4HBA) [ 42 ], while there are no known reports for purification or in vivo characterisation of TphKs in the literature that we are aware of. Both transporters have demonstrated value in microbial strain engineering applications, with overexpression of the native pcaK from Sphingobium sp. SYK-6 enabling 30% higher conversion rate of PCA to the plastic precursor, 2-pyrone-4,6-dicarboxylate [ 10 ]. As well, heterologous expression of a tphK from Pseudomonas mandelii in P. putida permitting de novo production of the plastic polymer, polyhydroxyalkanoate (PHA), from a TPA and ethylene glycol co-feed has similarly been used in the production of β-ketoadipic acid [ 38 , 43 ]. Approaches such as these highlight the value of considering cellular transportation during strain engineering workflows. Furthermore, due to MFS proteins being a single polypeptide unit they do not require the stoichiometric balancing of other transporter subunits to correctly function. The structural uniformity of MFS proteins therefore lends itself well to engineering efforts, as adversely effecting other domains does not need to be considered. Collectively, this indicates that MFS transporters are ideal targets for use in heterologous whole cell factory hosts, and are amenable to protein engineering approaches [ 5 , 44 , 45 ]. For the technical challenge set out above, screening strategies that utilise facile, widely implementable synthetic biology techniques are an attractive alternative to mediate the high throughput identification and substrate specificity determination of transport systems. Small molecule responsive genetically encoded biosensors, comprised of allosteric transcription factors and riboswitches, can be coupled to optically detectable proxies (e.g. fluorescence) or cell survival in order to elucidate phenotypic responses. The amenability of such biosensor-based assays to high throughput screening has proven effective and highly selective for identifying optimal phenotypes in enzyme mutant libraries, and for the enrichment of strains with improved metabolic efficiency toward a desired product [ 46 , 47 ]. The application of biosensors towards the characterisation of transporters is relatively new compared to older methods that rely on large genomic disruption libraries or heterologous expression [ 48 ]. Using a CRISPR based method of genomic disruption a knockout library of transporters was developed in Saccharomyces cerevisiae ( S. cerevisiae ) totalling 361 transporter deletions [ 49 ]. Through integration of the catabolic cascade to convert glucose to cis,cis- muconic acid (cc-MA) and a previously developed cc-MA biosensor active in S. cerevisiae , screening of the deletion library was assessed via fluorescence activated cell sorting, identifying tpo2 as responsible for the uptake of cc-MA and PCA [ 49 ]. Further, a thiamine pyrophosphate responsive riboswitch was used in conjunction with metagenomic screening to identify several members of a new class of thiamine transporter, PnuT. The riboswitch was then replaced with one responsive to xanthine alkaloids to mine for xanthine importers, demonstrating the flexibility of the biosensor based approach [ 26 ]. In this study we demonstrate the application of genetically encoded biosensors for the identification and characterisation of aromatic acid H + symporter MFS transporters with specificity towards two molecules of biotechnological significance, protocatechuic acid (PCA) and terephthalic acid (TPA). Syntenic genome context analysis was initially performed, using catabolic genes/operons as the search query, to identify genomically associated novel putative PCA and TPA transporters (encoding PcaK and TphK, respectively). Transporter activity was verified using either a PCA or TPA responsive transcriptional biosensor coupled to GFP reporter output. Transporter substrate scope was explored via ligand panel screening, and the generation of chimeric transporters which were constructed and assessed to better understand structure activity relationships of the two types of MFS and ability to enable non-cognate substrate transport functions. Methods Phylogenetic analysis and homolog identification Preliminary searches for TphK and homologues were performed via Position-Specific Iterated BLAST (PSI-Blast) using the Blastp suite hosted on the National Center for Biotechnology Information (NCBI) server with the Ref Seq database using the Rhodococcus Jostii RHA1 TphK (Uniprot ID: Q0RWE8_RHOJR, (annotated as TpaK)) protein as a query sequence. Sequences resulting from this search were extracted and visualised via Jalview [ 50 ] and multiple sequence alignment was performed utilising MUSCLE. IQtree was used to create an initial phylogenetic tree which was later visualised using iTOL. To query the entire NCBI database, the Cblaster python package [ 51 ] was used in remote mode with the Rhodococcus jostii (NC_008270, Region: 190337–196425) TPA catabolic operon. Clusters were filtered by the presence of an MFS gene being present in the operon followed by the extraction of the MFS protein sequences. The Cdhit package [ 52 ] was used to remove redundant and duplicate sequences with a threshold of 0.95 (95%), followed by alignment and visualisation as stated above. PcaK searches were split according to the type of ring cleavage mechanism utilised in PCA catabolism. For the 2,3-ring cleavage pathway, the pra operon from Paenibacillus sp. JJ1B (AB505864) was utilised for cBlaster searching. For the 4,5 pathway the pmdEFDABC (AB462808) operon was utilised for cBlaster searching. For the 3,4 pathway no complete operon could be sourced, as such three exemplar MFS PcaK sequences were sourced from Uniprot for which significant experimental evidence existed: Pseudomonas aeruginosa (Q9I6Q3), Acinetobacter baylyi (Q43975) and Pseudomonas putida (Q51955). After visualisation via iTOL, representative sequences based on distance from root were selected from around the tree to cover a taxonomic range of putative transporters to screen. General Microbiology Escherichia coli and Pseudomonas putida were grown on standard LB miller broth and agar (Formedium #LMM20L, #LMM0204) at 37°C and 30°C with 180RPM of shaking. When appropriate, antibiotics were added to an appropriate inhibitory concentration (100µg/mL for E. coli and 500µg/mL for P. putida ) Strain Construction Escherichia coli DH5⍺ was used for DNA cloning and assembly of all constructs. Pseudomonas putida KT2440 was used in the characterisation of all PcaKs and TphKs. P. putida KT2440 genomic knock-outs of pcaK and fcs were constructed using a sucrose counter selection method as described previously [ 53 ]. Briefly, electrocompetent cells were transformed with 1 µg of the relevant pk18mobsacB plasmid possessing upstream and downstream homologous regions flanking the pcaK gene, plated onto LB agar supplemented with 20 µg/mL of kanamycin and incubated at 30°C. Individual colonies from the resulting plate were streaked onto YT agar supplemented with 25% sucrose (10 g/L yeast extract, 20 g/L tryptone, 250 g/L sucrose, 18 g/L agar) for counter selection. Colonies were screened with genomic primers to identify successful deletion of the pcaK or fcs gene. All chemicals used in substrate specificity screening can be found in Table S4&5 , all chemicals were prepared in sterile water or DMSO as appropriate. Plasmid construction All plasmids and primers used in this study can be found in Table S1 -2 , relevant genes encoding transporters including chimeric designs can be found in Table S3. The synthesis of all DNA oligonucleotide primers and gene fragments was performed by Integrated DNA Technologies (IDT). Amplification of plasmids or DNA fragments was performed using Q5 High fidelity polymerase (NEB, #M0491S). Assembly and ligation of DNA fragments for plasmid construction was performed using NEBuilder HiFi DNA Assembly Master Mix (NEB, #E2621S). Following assembly bacterial transformation was performed using chemically competent E. coli DH5⍺ cells, the resulting colonies were screened by colony PCR using Phire II Green polymerase master mix (Thermo Fisher, #F126S). Plasmid isolation was performed for positive colonies, and were used for assembly validation, by Sanger sequencing (Source Bioscience, United Kingdom). Biosensor based screening of MFS transporters Overnight cultures of P. putida KT2440 or P. putida Δ pcaK harbouring a relevant plasmid were sub-cultured to an OD 600 of 0.6 in 10 mL of LB media supplemented with 500 µg/ml carbenicillin before being aliquoted into 96 deep-well plates (DWP) prefilled with 50 µL of inducer (TPA or PCA respectively) to a final volume of 500 µL. The DWP were then transferred to a plate shaker incubator at 30°C or 37°C at 1000 rpm, 75% humidity. For PCA uptake assays, DWP cultures were incubated for 3 hours. For TPA uptake assays, DWP cultures were incubated for 16 hours. To measure OD 600 and fluorescence, culture pellets were washed and resuspended in 500 µL in PBS before being transferred to 96 well clear bottom microplates (Greiner). OD was measured at 600 nm, GFP was measured with λEx/λEm of 488/520nm using a ClarioStar microplate reader (BMG). Fluorescence was later normalised against the measured OD 600 for each well. Initial validation of transporter activity was performed via titration of the PcaK and TphK constructs using 0-1mM of TPA and 0-5mM of PCA as inducer plotting the dose response curve of normalised fluorescence with a variable slope hill function. PcaK and TphK constructs identified as functional in the primary screening assays were taken forwards for substrate specificity screening using concentrations of inducer that had been shown to elicit maximum response from the biosensor with either TPA (1mM) or PCA (5mM). All biosensor experimental data were processed as means of three biological replicates. Structure and Helix Modelling CC-TOP [ 54 ] was used to generate an overlapping map of helical topology using protein sequences of functionally verified TphKs and PcaKs from which a transmembrane helical consensus was determined. This consensus alignment was imported into Jalview and the Alphafold [ 55 ] model for PcaK (Alphafold: Q51955) aligned to confirm assignment of the secondary structural element regions. Chimeric transporter engineering Using the topological alignments of the helical regions of the P. putida PcaK and R. pyridinivorans as a guide, gblocks encoding PcaK and TphK with the helical regions 1, 4, 7, and 10 were designed in silico and ordered via IDT. These were subsequently assembled into PcaV and TB4 biosensor vector backbones respectively via isothermal assembly. Individual helical substitutions were performed via 2 fragment isothermal assembly using primers designed to amplify the wildtype TphK or PcaK MFS in its cognate biosensor backbone extruding the target helical region. A second set of primers with featuring homologous overhangs to the opposing transporter were then used to amplify the specific helical region to be substituted, in order to generate a chimeric MFS with this process repeated for helices 1,4,7 and 10. Following isothermal assembly and sequencing, the chimeric MFS genes were then reamplified and cloned into the opposing biosensor backbone generating the full set of constructs for testing. Predicted structures of the chimeric transporters were generated using alphafold 3 and annotated in ChimeraX [ 56 ]. Relative fold changes were calculated in two steps after collection of RFU/OD 600 data beginning with normalisation via the division of the RFU/OD 600 values for each ligand by the uninduced RFU/OD 600 to generate a normalised fold change per ligand for each construct. Relative fold change was then calculated on a per ligand basis by the division of each mutant fold change (FC mut ) by the fold change of the negative control (FC NoMFS ). These values were used for the plotting of heatmap data. For detailed statistics of significant effects please refer to Additional File. 1 ) Results Bioinformatic mining of putative TphK’s We initially sought to obtain a diverse pool of putative candidate transporters for screening to capture the full breadth of structure activity relationships that may have evolved within specific taxonomic groupings. Inferring functionality of MFS transporters is complicated by the generally low sequence identity between family members, creating the possibility of dataset contamination with transporters of divergent function. By contrast, neighbouring genes within MFS-encoding operons can display strong sequence homology [ 57 ]. tphK and pcaK are both known to cluster into operons containing genes related to the catabolism of TPA and PCA respectively. We therefore employed a “guilty by association” methodology to enhance the fidelity of our homolog search using the genetic context (presence, organisation, and proximity) of TPA/PCA catabolic genes as an indicator of potential transport activity. To achieve this, we queried the NCBI genomic database employing the cblaster multigene BLAST tool using the sequence of the entire TPA degradative operon from Rhodococcus jostii ( tphRKA 2 A 3 BA 1 ) as the query [ 51 ]. The resulting phylogenetic tree displayed only 44 non-redundant leaves for MFS homolog co-located with the TPA catabolic operon (Fig. 1 A). In contrast, a direct blastP homology search using the R. jostii TphK as the query resulted in a tree consisting of 530 leaves with some species that were not revealed in syntenic analysis ( Supp Fig. 1 A). Manual inspection of the results obtained from the direct BLAST search approach indicated that many of the MFS hits were not colocalised to TPA catabolic genes. For example, the MFS belonging to the genus Janthinobacterium , occurred 42 times in the direct blastP search yet demonstrated a genetic context indicating no relation to TPA catabolism ( Supp Fig. 1 B). Furthermore, no Janthinobacterium hits were present in the tree generated using cblaster, indicating that these MFS sequences did not carry any resemblance of TPA catabolic operon and were therefore unlikely to possess the desired functional activity. The tree generated from syntenic analysis of the R. jostii TPA degradation operon was rooted with respect to the TphK transporter protein, with the TphKs generated from cblaster plotted using their relative sequence identity to the query (Fig. 1 A). TPA catabolic operons typically differ based on the transporter type, with Comamonas sp. Strain E6 encoding a tripartite tricarboxylate transporter (TphC) and Rhodococcus jostii encoding an MFS (TphK) [ 57 ]. To our knowledge, this is the first report of tphK containing TPA catabolic operons in the alpha and beta proteobacteria classes, indicating the spread of TPA catabolism through a much broader range of bacteria than previously thought. Actinomycetia is the predominant class of bacteria (66%) encoding TphK homologues, with tight clustering to the root of the tree with lengths of 0.1–0.6 indicating high similarity to the query sequence. Some Actinomycetia sequences however clustered further from the root at branch lengths of ≥ 1.6, indicating greater sequence diversity. The remaining classes consisted of Alpha and Gammaproteobacteria (both 14%) as the next most abundant classes followed by betaproteobacteria (7%). Interestingly, the proteobacteria were noticeably less diverse at the genus level in comparison with Actinomycetia, with Gammaproteobacteria being represented solely by Pseudomonads , Alphaproteobacteria by Bradyrhizobium and Betaproteobacteria by Noviherbaspirillum and Cabellronia . We observed that the TphK sequences fell within 9 distinct bacterial genera with the bulk of representation within the tree originating from the Pseudomonas (N = 6), Pseudonocardia (N = 8), Bradyrhizobium (N = 5), Streptomyces (N = 6), Amycolatopsis (N = 7) and Rhodococcus (N = 3) genera. Notably the majority of species represented in the phylogenetic tree are saprophytic soil dwellers, with some originating from genera that have been previously validated as possessing the genes required for TPA catabolism, such as R. opacus and P. umsongensis but also encompass other previously unidentified soil dwellers like Bradyrhizobium and Sphingobium [ 29 ]. The limited spread of tph operon may be indicative of the recent evolution and therefore limited time to transfer the TPA catabolic operon through microbial communities. Putative TphK’s carried forward for evaluation were selected based on distance from the root of the tree and genera of origin in order to maximise sequence and context diversity. Selected TphK candidates are indicated by stars in Fig. 1 A and are listed in Fig. 1 C, they included those from: R. jostii , Rhodococcus opacus , Rhodococcus pyridinovorans , Pseudomonas umsongensis , Pseudomonas mandelii , Pseudonocardia bannensis , Bradyrhizobium pachyrhizi , Sphingobium napthae , Amycolatopsis acidiphilia , Saccharopolyspora hordei , and Streptomyces sp. HGB0020. Bioinformatic mining of putative PcaKs Following generation of a TphK phylogenetic tree we repeated the approach with the PCA catabolic operons. PCA catabolism is more widespread among bacteria than TPA catabolism, as it is a constituent of lignin degradation and a central node in diverse aromatic degradation pathways [ 28 ]. This is in contrast to TPA, which is of anthropogenic origin with only recent environmental exposure (1960-present) [ 28 , 58 ]. Indeed, studies have highlighted at least three distinct bacterial pathways through which PCA is subsequently assimilated and incorporated into central metabolism [ 59 – 61 ]. These pathways can be categorised by their PCA cleavage mechanism, which occurs either in the 4,5 ( meta ), 3,4 ( ortho ) or 2,3 ( para ) position. While these pathways all serve to funnel PCA to central metabolism, they achieve this through distinct enzymatic steps and intermediate metabolites (Fig. 2 A). Given this evolutionary divergence, we sought to explore the potential functional differences of PcaKs encoded in these three different pathways in our workflow. To this end, catabolic operons from strains encoding 2,3 and 4,5 extradiol pathways were selected from Comamonas sp. E6 (blue), and Paenibacillus sp. JJ1B (green) respectively as query sequences for cblaster (Fig. 2 A). The 3,4 intradiol pathway, unlike the extradiol pathways, however, appears to be discontinuous, with the degree of fragmentation varying between the organisms that were investigated. For instance, in P. putida , the operon is split into three distinct loci encoding upper, middle and lower parts of the pathway separately. Conversely Acinetobacter baylyi shows no fragmentation, instead encoding its 3,4 degradative operon in a single continuous loci, however the syntenic arrangement differs to that of P. putida (Fig. 2 A). As our operon synteny approach was incompatible with the degree of heterogeneity present in the 3,4 pathway, we instead incorporated PcaKs from experimentally verified strains known to possess the intradiol pathway into the phylogenetic analysis [ 11 , 42 , 62 ]. We elected to root the tree with respect the P. putida PcaK, as it had been previously experimentally verified and originated in the genome of the host strain P. putida KT2440 in which we intended to perform subsequent functional validation [ 25 ]. In total 88 PcaK sequences were retrieved from the three pathways 59, 3 and 26 from the 4,5, 3,4 and 2,3 pathways respectively (Fig. 2 B). Bioinformatic mining of PcaK’s belonging to the 4,5 -pathway revealed that this pathway consists primarily of Betaproteobacteria (N = 45/85), with the largest subsection attributable to the Comamonas genus. This was followed by Acidovorax (N = 4) in addition to a number of single genera, representing the wide spread of the Betaproteobacteria class. A smaller number of Alphaproteobacteria were also identified, consisting of Magnetospirillum (N = 3) and Bradyrhizobium (N = 3), as well as some single instances of Gammaproteobacteria (N = 5). Despite the variation in class and genus, there was strong clustering of the 4,5 pathway as a single clade on the tree with a 2.8 average distance from the root, indicating high sequence homology between members of the 4,5 pathway. The exception to this is the PcaK from P. duriflava , which appeared to cluster with the 3,4 pathways. The 2,3 pathway on the other hand was substantially smaller (N = 21) than the 4,5 dataset and was restricted to Bacilli. Furthermore, sequence variation was greater within this dataset with branch lengths from the root in the range of 4.2–11.9, indicating greater evolutionary diversity. In general, those belonging to the Bacillus genus demonstrated the closest sequence homology to the root, whilst other genera such as Paenibacillus, Alicyclobacillus and Metabacillus displayed branch lengths ~ 9 indicating significant sequence diversification from the root despite being closely related to the bacillus genera. Of the genera, Bacillus were the most abundant (N = 5) followed by Alkalihalobacillus and Metabacillus (N = 3 each), and finally Paenibacillus and Alicyclobacillus (N = 2). Similar to the 4,5 pathway, all members of the 2,3 pathway appear to share a common ancestor and cluster together, indicating greater sequence similarity to one another than to other pathways, despite the high sequence variation. Finally of the PcaK transporters selected to represent the 3,4 pathway, those from P. putida PRS2000 and P. aeroginosa clustered very closely to the root with branch lengths of 0.07 and 0.18, respectively, followed by A. baylyi with 0.6. Interestingly, despite belonging to the Pseudomonas genus, P. duriflava possessed a branch length relative to the root of 2.1, indicating significantly more sequence dissimilarity and placing it closer the 4,5 pathway. In total ten transporters were selected from the 3,4 (N = 3) and 2,3 (N = 3) and 4,5 (N = 4) pathways based on distinct genera to ensure maximum diversity for subsequent transport and functional analysis in order to assess the potential functional differences of putative PcaKs. These included those from: P. putida , P. aeruginosa , A. baylyi , Bacillus massiliglacei , Panaebacillus validis , Alicyclobacillus acidotolerans , Neiserria animalis , Bradyrhizogium sp. STM3843, Comamonas testeroni , and Acidovorax antarcticus (Fig. 2 C). Screening of putative MFSs via responsive biosensors Following the selection of putative TphK and PcaK transporters from the synteny-enriched phylogenetic analysis we next sought to validate their transport activity toward TPA and PCA, respectively. To accomplish this, the genes encoding the selected putative TphK and PcaK transporters were cloned into a plasmid containing either a TPA (TphR) or PCA (PcaV) responsive allosteric transcription factors along with the corresponding responsive promoters controlling the expression of sfGFP (Fig. 3 A). The TphR biosensor was based on the IclR-type transcriptional activator from Zhizhongheella caldifontis [ 63 ], while the PcaV biosensor was based on the MarR family transcriptional repressor from Streptomyces coelicolor [ 64 ]. Under neutral pH conditions, both PCA and TPA will be deprotonated (singly and doubly), which will impede their cellular uptake via membrane permeation in the absence of a transporter [ 65 ]. However, natively, P. putida is capable of assimilating PCA via an endogenous pcaK . To mitigate any endogenous transport, putative PcaKs were screened in a Δ pcaK genetic background, while putative TphKs were screened in the wild type P. putida genetic background. As such, any increase in GFP fluorescence observed by P. putida harbouring transporter-biosensor constructs, either TphK-TphR or PcaK-PcaV following exposure to TPA or PCA, can be attributed to the activity of the putative transporter. To further validate this, transporter-less versions of both biosensing constructs (TphK − ve and PcaK − ve ) were developed to account for any passive transport through the membrane. The library of 11 putative TPA transporter-biosensor (TphK-TphR) constructs was evaluated for the ability to import TPA against a ligand concentration gradient (ranging from 0.005–1 mM), and the resulting dose response curve were compared (Fig. 3 B). Of these, the transporters from Streptomyces. Sp. HGB0020, A. acidiphilia and P. bannensis were shown to be non-functional against TPA (data not shown) whilst the remaining transporters demonstrated a strong response relative to the TphK − ve control. TphKs from R. pyridinivorans (TphK R.Pyr ), R. opacus (TphK R.Op ), R. jostii (TphK R.Jos ), P. umsongensis (TphK P.Um ) and P. mandelii (TphK P.Man ) had been previously validated as TPA transporters [ 39 , 43 , 66 , 67 ], while those from B. pachyrhizi (TphK B.Pac ), S. napthae (TphK S.nap ) and S. hordei (TphK S.Hor ) were newly identified in this study (Fig. 3 B). The TphKs evaluated demonstrate similar operation sensing ranges (0.005–0.25mM), but with considerable variation in activation (max RFU/OD) and sensitivity (EC 50 ) to TPA. TphK R.Jos possessed the greatest sensitivity (EC 50 4.4 µM), TphK P.man possessed the greatest output dynamic range (2.7-fold) likely due to its tight basal activation, whilst TphK R.Pyr achieved the greatest activation TphKs (103,676 RFU/OD). Surprisingly, TphK R.Op demonstrated significantly lower sensitivity toward TPA (EC 50 79 µM) despite high homology with the other Rhodococcus TphKs which display greater sensitivity to TPA. Given the high sequence homology of the Rhodococcus sequences in the phylogenetic tree this result was surprising and could be due to differing expression levels. Evaluation of the library of putative PCA transporter-biosensor (PcaK-PcaV) constructs was performed in a P. putida Δ pcaK strain. It was found that the Δ pcaK strain was still able to utilise PCA for growth, however it displayed an extended lag phase of 4 hours (compared to 2 hours for the wild-type strain), during which time no PCA was consumed in line with previous studies [ 25 ]( Supp Fig. 2 ). As such, the PCA dose response assays were incubated for a maximum of 3 hours to avoid endogenous utilisation of PCA. PcaK-PcaV transporter-biosensors constructs were tested against an increasing concentration of PCA (ranging from 0.01-5 mM), and the resulting dose response curves were compared (Fig. 3 C). Unlike with the TphK − ve - construct, the PcaK − ve - construct did demonstrate a small increase in biosensor activation when PCA was supplemented at concentrations above 1 mM. This could be due to the action of promiscuous transporters encoded in the host genome or passive diffusion across the membrane. PCA has an single pKa (4.2), whereas TPA possesses two pKa’s (3.5 and 4.3), so the latter is more acidic and will be doubly negatively charged, thus less likely to diffuse cross the bacterial membrane [ 68 ]. Based on biosensor response, putative PcaKs appeared to cluster into 3 distinct subgroups, demonstrating weak, medium, and strong activation in response to PCA (Fig. 3 C). Transporters from B. massiliglacei (PcaK B.Mas ) and P. putida ( PcaK P.Put ) demonstrated the greatest overall activity in terms of max signal (> 30,000 RFU/OD), and fold change at 61-fold and 47-fold, albeit with low sensitivity to PCA (EC 50 = 1.7 mM and 2.05 mM), respectively. This in spite of the significant distance from one another in terms of sequence homology (Fig. 2 B). Transporters from A. antarcticus (PcaK A.Ant ), A. baylyi (PcaK A.Bay ), N. animalis (PcaK N.An ), and P. aeruginosa (PcaK P.Ae ) displayed the highest sensitivity to PCA (EC 50 between 0.73–1.25 mM), with a moderate response to PCA (14-50-fold). Finally, transporters from P. validus (PcaK P.Val ), Bradyrhizobium sp. STM3843 (PcaK B.STM ) and A. acidotolerans (PcaK A.Aci ) demonstrated the weakest response to PCA, with only margin activation above the negative control (PcaK − ve ), as such were assumed to be non-functional. The PcaK from C. testeroni (PcaK C.Tes ), surprisingly, was also inactive toward PCA (data not shown) despite the strain being reported to grow on 4-hydroxybenzoic acid (4HBA) as a sole carbon source and possessing an intact 4,5 PCA catabolic operon [ 69 ]. Substrate specificity of TphKs The variable activation of the different TphK-TphR and PcaK-PcaV biosensor constructs toward their cognate effectors alludes to variability in the substrate uptake capabilities of the different transporter homologues. Given the taxonomic diversity of their bacterial backgrounds, we reasoned that whilst the active transporters may transport the cognate ligands TPA and PCA, they may also possess extended substrate specificity. As such, we next sought to explore the structure activity relationships of the identified MFS transporters utilising a library of TPA and PCA effector analogues ( Supp Table. 1&2 ). To examine this, the TphKs: TphK R.Jos , TphK R.Pyr , TphK R.Op , TphK P.Man , TphK P.Um , TphK S.Hor , TphK S.Nap and TphK B.Pac were screened against a panel of 27 TPA analogues at a concentration of 1 mM comparing fold-change activation relative to the negative control (Fig. 3 D; Supp. Figure 3 A). Of those ligands screened, activity was observed towards compounds with substituents in the 2 positions of the benzene ring, including a hydroxyl- ( T13 ), bromo- ( T15 ), iodo- ( T16 ) and amino- ( T18 ) at this position in addition to a TPA control ( T3 ) (FC > 1.5). Interestingly, we also observed activity towards biphenyl-4,4-dicarboxylic acid ( T20 ) by all TphK transporters assessed (average FC ~ 2), a compound which is significantly longer than TPA. Analysis of supernatants of wildtype P. putida and P. putida encoding the MFS on the TB4 biosensor plasmid demonstrated that no depletion of 4,4-biphenyldicarboxlic acid had taken place over the course of 24 hours ( Supp Fig. 4 ), indicating the response was generated directly from the effector and not due to conversion of 4,4-biphenyldicarboxylic acid to TPA. TphK R.Jos and TphK S.Nap displayed the greatest substrate range, permitting uptake (and sensing) of six and five TPA analogues, respectively. Consistent with our previous observations of TPA transport (Fig. 3 B), TphK R.Op demonstrated the lowest activity towards those ligands screened, only responding to TPA and biphenyl-4,4-dicarboxylic acid (FC = 1.4 and 1.2). On average, substrate specificity for the TphK homologues can be ranked as: TPA (2.3-fold) > biphenyl-4,4-dicarboxylic acid (2.0-fold), > iodo-TPA (1.8-fold), > hydroxy-TPA (1.6-fold) > bromo-TPA (1.4-fold) > amino-TPA (1.3-fold). This seems to imply that the TphK-TphR transporter-biosensors have a strict preference for dicarboxylates, as monocarboxylates triggered no response ( Supp. Figure 3 A). Additionally, substitution at the 2-position of the ring appeared to be somewhat tolerated, with hydroxylation and halides being preferred to amino. These observation on substrate specificity of the TphK are caveated, however, as they rely also on the substrate specificity of the TphR-based biosensor, which may not entirely overlap. Substrate specificity of PcaKs To evaluate substrate specificity of the PcaKs, PcaK A.Ant , PcaK A.Bay , PcaK B.Mas , PcaK N.Ani , PcaK P.Aer and PcaK P.Put were screened against a panel of 28 PCA analogues at a concentration of 5 mM (Fig. 3 E; Supp Fig. 3 B). Ten analogues including PCA ( P2 ) were found to be transported by the majority of the putative PcaKs, with these ligands sharing structural similarities to PCA, such as hydroxylation at the 3 or 4 positions and the presence of a single carboxyl group. Example of this include 3-hydroxybenzoic acid ( P24 ) and 4-hydroxybenzoic acid ( P25 ). Interestingly, whilst P24 appeared to elicit a greater fold induction by all PcaKs than PCA (20- vs. 16-fold average); the negative control (PcaK − ve -PcaV) also demonstrated significant induction by 3-HBA (15-fold), indicating the potential involvement of a secondary transporter assisting uptake. Nevertheless, PcaK A.Ant , PcaK B.Mas , and PcaK P.Put demonstrated a significant activity relative to the negative control (19.2, 21.7 and 37.8-fold respectively) indicating these transporters improved the uptake of P24 . Biosensor activation in response to vanillic acid ( P25 ) was not statistically significant for all transporters when compared to negative control, with the exception of PcaK P.Put (7.9 vs 26.8-fold), indicating the specific activity of the PcaK transporter from P. putida for P25 uptake. Interestingly, PcaK B.Mas and PcaK P.Put appeared to demonstrate unique activity for 5 hydroxyl substitutions, with high activation observed by 3,5 dihydroxybenzoic acid ( P3 ) (30.9 and 14.8-fold, respectively) and gallic acid ( P28 ) (39.2 and 47.6-fold, respectively). Some strains of P. putida , including KT2440, have been shown to possess a gallic acid catabolic operon, yet are unable to grow on gallic acid as a sole carbon source due to a frameshift mutation resulting in a truncated form of the MFS gallic acid permease, GalT, [ 13 ]. Our results suggest that some PcaK transporters, from other strains of P. putida and B. massiliglacei , appear to have the ability to uptake both gallic acid and PCA. Some of the PCA analogues also induced smaller, but still significant, responses relative to the negative control, including: methyl-3,4-dihydroxybenzoic acid ( P15 ), to which PcaK P.Put responded; 3,4 dihydroxybenzamide ( P16 ), to which PcaK A.Ant , PcaK A.Bay , and PcaK P.Put responded; and benzaldehyde ( P17 ), to which PcaK A.Ant , PcaK A.Bay , PcaK B.Mas and PcaK P.Put responded (Fig. 3 D). These analogues have differing carbonyl groups, suggesting some flexibility at this position at the expense of drastically reduced activation. To rule out potential oxidation of the benzaldehyde to benzoic acid additional screening of the active PcaKs was performed against benzoic acid ( Supp Fig. 5 ), however no response was detected indicating activity was strictly toward the aldehyde functional group. Finally, partial activity towards, vanillic acid ( P26 ) and coumaric acid ( P27 ) was observed, which deviates from the structure activity relationship. P26 and P27 are natively metabolised by P. putida , with PCA being a pathway intermediate for both [ 28 ]. We reasoned that this activity may be a result of some degradation of coumaric and vanillic acid to PCA and/or 4-hydroxybenzoic acid ( P25 ), resulting in indirect activation of the biosensor. To investigate this, a Δ fcs (feruloyl-CoA synthetase) knock out strain was generated to abolish coumaric acid catabolism, and subsequently transformed with the PcaK p.put -PcaV construct ( Supp Fig. 6 ). No activation of this biosensor was observed in the Δ fcs knockout strain relative in the presence of coumaric acid except at high loading (5mM), indicating that biosensor activity observed in the WT strain was likely due to metabolism to P25 and/or PCA. Despite this we observed increased activation relative to the negative control (~ 1.5-fold) indicating that PcaK appears to contribute some import capability toward these two substrates. Cross reactivity of TphK and PcaK transporters Following substrate screening of the TPA and PCA transporters paired with their cognate biosensors, next sought to investigate the existence of overlapping activity between the TphK and PcaK transporters. As both TphK and PcaK are thought to belong to the aromatic H + symport subfamily we reasoned that comparing their abilities to uptake TPA- and PCA-like effectors could highlight some structure activity relationships that govern ligand recognition or substrate specificity. To accomplish this, the genes encoding the most active TphK and PcaK towards TPA and PCA (TphK R.Pyr and PcaK P.Put , respectively) were sub-cloned into the other biosensor backbone, generating the constructs TphK R.Pyr -PcaV and PcaK P.Put -TphR. These were then screened against the TPA and PCA analogue libraries. The TphK construct appeared to facilitate marginally better transport, than the negative control, towards ligands P2 , P24 , P25 and P27 , however no ability to import substrates other than what had been shown to be transported by PcaK P.put was observed ( Supp. Figure 7A ). The PcaK crossover construct however demonstrated a significant fold change induction toward 2,5-pyridine dicarboxylic acid ( T4 ) indicating some unforeseen functionality although the degree of fold change was minimal (~ 0.3-fold increase). Increased activity to 2-hydroxy TPA ( T13 ) was also observed however all other ligands were shown to be unresponsive ( Supp. Figure 7B ). Biosensor mediated screening of PcaK and TphK mutants Next, we sought to evaluate the ability of both biosensor-based detection systems to discern changes in the activity following protein engineering of the MFS transporters. This was performed in order to examine the specific role of primary sequence elements and/or structural motifs in ligand recognition/transport. As an initial step, to verify that our biosensor assays would be able to accurately report a mutagenic phenotype for a transporter of interest, three amino acid point mutations, previously shown to affect the efficiency of P25 uptake by PcaK from P. putida [ 70 ], were individually created. These residues at positions E144, R124, and R398 were replaced with alanine (A) in the PcaK P.Put -PcaV construct ( Supp Fig. 8C ), generating: PcaK-E144A P.Put -PcaV, PcaK P.Put -R124A-PcaV and PcaK P.Put -R398A-PcaV. These PcaK point mutant constructs were then evaluated against varying concentrations of both PCA and 4HBA to assess changes to dose response activity. Consistent with previous reports, the biosensor assay indicated that all three mutations led to near total abolition of PCA import and a strong decrease in 4HBA import ( Supp Fig. 8A&B ). The observed uptake of 4HBA by both the negative control and point mutants is consistent with earlier ligand screening, indicating an alternative P25 uptake mechanism by the P. putida Δ pcaK strain. Based on the previously observed overlapping substrate specificity of TphK R.Pyr -PcaV and PcaK P.Put -TphK ( Supp Fig. 7 ) we wished to further explore the sequence features that impart ligand specificity to TphK and PcaK. Given that the characteristic structural arrangement of MFS proteins consists of a classical 12 ⍺-helical bundle, we first generated a sequence alignment of the functional PcaK and TphK sequences using CC-TOP prediction to annotate the sequence alignment for the location of the 12 ⍺-helices ( Supp Fig. 9 ). In addition, an alpha fold model of P. putida PcaK (Q51955) was also used to annotate the multiple sequence alignment, with its 3D structural prediction matching closely to the CCTOP predictions made for each sequence ( Supp Fig. 9 : Annotated as PcaK_PSEPU Secondary structure). The sequences of each individual transmembrane (TM) helix were then compared using the functionally verified TphK and PcaK sequences ( Supp Fig. 10 ). Distinct conservation trends were noticeable in every TM however appeared to occur with greater abundance in TM’s corresponding to those that make up the central cavity of the protein (TM’s: 1, 4, 7, and 10) with these TM’s thought to comprise the majority of residues that govern substrate coordination and co-substrate coupling [ 71 ]. Generally, amino acid differences in these regions consisted of non-polar to polar substitutions (TM1: PcaK_Ala22 to TphK_Gln, TM4: PcaK_Thr24 to TphK_Ala), polar to charged (TM10: Ser/Asn20 to Lys) and aromatic to non-aromatic (TM1: Phe11 to Gly). Within the PcaKs however, no sequence features were immediately apparent so as to explain the apparent unique uptake of 3, 5 substituted benzoic acids. Given the number of individual residue substitutions and combinations, both at the intra and interhelical level, that would need to be reconstituted in order to elucidate those involved in substrate recognition, we decided to leverage the high throughput screening potential of biosensors to assess the functionality of full TM substitutions between the R. pyridinovrans TphK and the P. putida PcaK for those helices which form the core of both, namely: TM’s 1, 4, 7 and 10. With this in mind, we generated and screened chimeric MFS transporters with the entire core TM helical regions exchanged, resulting in PcaK TphK_TM1,4,7,10 -PcaV and TphK PcaK_TM1,4,7,10 -TphR. These chimeric transporters were tested in their cognate biosensor backgrounds against the PCA and TPA analogue libraries (Fig. 4 ). Interestingly, whilst TphK PcaK_TM1,4,710 -TphR appeared to lose activity toward its cognate ligand, TPA and biphenyl-4,4-dicarboxylic acid ( T20 ), it was still able to import 2-hydroxy- (1.4 vs 1.3), bromo- (1.0 vs 1.3), iodo- (1.3 vs 1.3) and amino-TPA (1.2 vs 1.3) (TphK wildtype vs TphK chimera), indicating some potential interactions from the PcaK helical regions in facilitating these interaction. Furthermore, a gain-of-function activity toward pyrazine-2,5-dicarboxylic acid ( T5 ) and naphthalene-2,6-dicarboxylic acid ( T21 ) was observed (Fig. 4 A) indicating the potential cooperation of other TM helices contributing to increased uptake of these non-cognate ligands. The loss of function encountered appeared to specifically impact structures containing dicarboxylate functionality with no other functionalisation such as TPA ( T3 ) and biphenyl-4,4-dicarboxylic acid ( T20 ) suggesting that the core TM helices are responsible for this recognition in wildtype TphK. The PcaK TphK_TM1,4,7,10 -PcaV chimera, appeared to result in a functional transporter maintaining some activity toward earlier established ligands such as P2 and P25 albeit with reduced import capability, indicating that the chimeric MFS was functional in vivo (Fig. 4 B). In addition, this chimera displays a significant gain of function over the WT in the form of increased uptake of coumaric acid ( P27 ) (9-fold). Activity toward PCA ( P2 ), benzaldehyde ( P17 ), 3HBA ( P24) , 4HBA ( P25 ) and vanillic acid ( P26 ) were shown to be higher than the negative control indicating some retained ability to uptake these compounds yet not as efficiently as the wildtype PcaK (Fig. 4 B). We also noted the apparent loss of ability to transport substrates possessing 5th position hydroxylation such as 3,5 dihydroxybenzoic acid ( P3 ) and gallic acid ( P28 ) indicating that the core PcaK domains are essential in order to transport these substrates. We therefore then moved to study the chimeras as single exchange mutants to better elucidate regions of the highest importance for substrate recognition. TM helices were swapped individually between TphK R.Pyr and PcaK P.Put (for a total of 15 chimeras) before being cloned into either the PcaV- or TphR-based biosensor background for the evaluation of gain or loss of function (Fig. 5 ). We first reconstituted the helical region swaps of the PcaK TphK_TM1,4,7,10 -PcaV chimera individually to elucidate the effects of individual swaps (Fig. 5 A). Surprisingly, activity towards the cognate ligand PCA ( P2 ) appeared to be greater in the TM1 mutant than in the complete swap, indicating that substitution of this region with TphK TM 1 was able to partially complement and enable PCA import. Consistent with this the degree of amino acid changes within TM 1 for TphK and PcaK is subtle (Fig. 5 E), with most of the solvent exposed core cavity facing mutations A46Q, G49S and F50Y clustering toward the periplasmic side of the core (Fig. 5 B). These mutations all introduced slightly larger and more polar residues into the core cavity. This had the effect of reducing activity towards PCA, relative to the parental transporter, whereas transport activity to other effectors appeared to be more significantly reduced, indicating that decreasing the size of the cavity may have negatively impacted the ability to recognise PCA analogues. Replacement of TM4 appeared to be generally well tolerated, permitting limited uptake of 5’ substituted effectors, both 3,5 dihydroxybenzoic acid ( P3 ) and gallic acid ( P28 ), a phenotype that was abolished in all other single helical exchanges (Fig. 5 A). This is reflected in the positive effect upon uptake, which was otherwise abolished in other mutants, suggesting that the residues for 5’ substituted hydroxyl recognition may be located in the other TM elements. Based on the predicted positions of residues side chains of TM 4, the most solvent accessible mutation in the core cavity consisted of a M134A substitution, which lead to a loss of activity towards PCA, as such methionine may play a role in stabilising interactions with aromatic residues. Overall, the generally lower impact of the TM 4 swap may be attributable to this helix having the fewest number of core cavity amino acid changes (Fig. 5 E &F ). TM’s 7 and 10 demonstrate largely similar phenotypes to one another, appearing to better uptake benzaldehyde ( P17 ) and 4-hydroxybenzoic acid ( P25 ) relative to TM 1 and 4 swaps. Initial inspection of the mutations of TM 7 and the corresponding structure suggests that Y272F would reduce a H-bonding capacity from the core cavity. However, the mutation of T283Q whilst bulkier, maintains this H-bonding capacity on the same face of core cavity. Collectively, Y272 and T283, along with the conserved N367 (TM10) and S371 (TM10) residues may have direct effects upon, with these residues clustering around helical turns 3–4, consistent with studies on the XylE MFS transporter which demonstrates similar positioning of its ligand coordinating residues [ 72 ](Fig. 5 B). These residues are mutated in the TM 10 to N367S and S371K, with the latter lysine residue carrying a positive charge in addition to protruding further into the core cavity (Fig. 5 B). The increased steric hinderance coupled with altered hydrogen bonding potential in TM 7 and 10 may therefore contribute towards the inability to accommodate 5’ hydroxylated ligands such as P3 and P28 . Replacement of every individual TM, along with the full cross, led to activation with 3-hydroxybenzoic acid ( P24 ) perhaps suggesting that none of the tested TM’s are directly responsible for the recognition of this effector. Notably, vanillic acid ( P26 ) and coumaric acid ( P27 ) uptake improved in the complete chimeric mutant PcaK_ TphK_TM1,4,7,10 however individually reconstituting the single TMs showed very little improvement. Given the general trend of exchanging the bulkier residues of the PcaK core helical domains for the smaller ones of TphK domains may suggest that the increased cavity size of the TphK core is responsible for permitting the import of bulkier substrates such as coumaric and vanillic acid (Fig. 5 A). The exchange of TM 1 in the TphK mutant appeared to have the most severe impact on effector recognition including to TPA ( T3 ) (Fig. 5 C). Despite this, most of the mutations that occur are structurally located at the periplasmic and cytoplasmic interfaces of the protein and not in the centre of the core cavity; specifically, the mutations Q42A, S45G and Y46F, all result in the loss of hydrogen bond donor/acceptors potentially disrupting interhelical contact points preventing the protein from undergoing conformational changes required for function (Fig. 5 D). The number of conserved amino acids targeted at this structural location may therefore provide explanation for the sharp reduction in effector recognition. In contrast, replacement of TM 4 appeared to indicate this TM was the primary driver of the previously observed activity towards pyrazine-2,5-dicarboxylic acid ( T5 ), and naphthalene dicarboxylic acid ( T21 ) (Fig. 4 A & Fig. 5 C). Mutations in this TM were quite minor as mentioned earlier, with the major change being the A131M mutation leading to the incorporation of a methionine side chain pointing into the core, as shown in the predicted PcaK structure (Fig. 5 B). This mutation may stabilise effector binding through an S-aromatic interaction with nearby helical residues enabling the non-cognate large aromatic effectors to be up-taken. The TM 7 mutant displayed good response towards most effectors apart from 2-amino terephthalic acid ( T18 ). Of the mutations occurring in the TM 7 helix, only the Q279T mutation was localised to the central core, with this mutation resulting in the loss of a potential hydrogen bond acceptor site, it is possible that this correlates the loss of activity toward 2-amino terephthalic acid (Fig. 5 D). The reduced activity for T18 could therefore be a result of this change, with bulkier substitutions like hydroxyl or halo groups still able to hydrogen bond with the shorter threonine residue at this position. Mutation of TM 10 appeared to have a greater impact on effector uptake, losing activity for iodo, bromo and amino terephthalate ( T15, T16, T18 ) yet possessing the strongest fold change response for hydroxy terephthalate ( T13 ) of all the single TM mutants (Fig. 5 C). Mutation of serine to asparagine (S354N) may explain the observed impact upon effector activity; as asparagine is bulkier than serine this mutation may not accommodate bulkier substrates such as iodo and bromo terephthalates explaining the reduced response. More interestingly however a conserved lysine residue is mutated to a serine (K268S) with the predicted structure of TphK showing this residue projecting up towards both S364 (Fig. 5 D). The positive charge provided by the lysine may be essential for the stabilisation of the additional carboxylate group of TPA like molecules, with mutation to serine abolishing this. Given the proximity of the residues however, they may act synergistically to coordinate potential effector binding. Interestingly, activity toward 2’ position substituted TPA homologues ( T13-18 ) appears to be significantly enhanced when all the PcaK core helices are present together, with individual helical substitution not reaching the same levels of biosensor activation. Replacement of any of the core TM helices of TphK apparently led to a loss of function toward TPA and biphenyl-4,4-dicarboxylic acid indicating the importance of these core helices in substrate recognition. This result likely suggests the PcaK TM regions can substitute the loss of the second carboxylate recognition site through the ability to recognise hydroxyl or halide substituents on the ring providing some explanation for the observed induction of the biosensors in these mutants. Consolidating results from both the full cross chimeras and single helical domain mutations implies that PcaK TM helices can serve as functional proxy to TphK components but only when all are substituted together, suggesting some inter-helical dependency for functionality. We then moved to assess the functionality of the same TphK chimeras when transferred into the PcaV biosensor background to screen for any gain of function toward PCA or its analogues ( Supp Fig. 11A ). Substitution of single PcaK helical regions into TphK appeared to have very little effect on the recognition of PCA like effectors, with the primary positive effect restricted to coumaric acid ( P27 ). This further corroborates the observed improvement in activity when the PcaK full cross was assayed against coumaric acid and suggests involvement of other TphK TM regions in its recognition also. Finally, we assessed the activity of PcaK TphK single helical exchange chimeras in the TphR biosensor background, except for PcaK TphK_TM1 -TphR which failed to clone ( Supp Fig. 11B ). No activity to any the TPA analogues screened was detected with any of the TM exchange chimeras however this result is consistent with the initial crossover experiments performed analysing the wildtype PcaK in the TphR biosensor background which also showed no ability to uptake any TPA like effectors. As such we can conclude that single replacement of PcaK TM structures with those from a TphK do not confer any activity to this effector set. Collectively, the results indicate that we have successfully generated a library of chimeric MFS proteins that are inserted within membrane and are functional with some demonstrating novel gains of function, highlighting the utility of such biosensor-based approaches to membrane transporter characterisation and engineering. Discussion Here we demonstrate that the development of a high throughput method for the screening and characterisation of MFS transporters is an important step towards the implementation of these and other transporters into strain engineering workflows. As such, screening strategies that take advantage of the rapidly expanding library of allosteric transcription factors as genetically encoded biosensors could pave the way for greater understanding of transport mechanisms, enabling deployment in microbial cell factories for bio-based production, and facilitate membrane protein engineering efforts. In this study, the aromatic acid, PCA and TPA, responsive transcriptional biosensors were employed to screen and characterise putative PCA and TPA transporters belonging to the MFS family, in the industrially relevant host, P. putida . Using the genetic context of transporter genomic loci has been implemented previously to aid in the elucidation of a novel citric acid export protein in Aspergillus niger based on its homology to an itaconic acid biosynthetic gene cluster [ 73 ]. Furthermore, similar methodologies have been applied specifically to the TPA catabolic operon to systematically search for such metabolism [ 57 ]. Applying such syntenic catabolic operon analysis paired with biosensor-based functional screening led to the identification of three novel PcaK’s from A. antarcticans, B. masiliglacei and N. animalis , and four novel TphK’s from B. pachyrhizi, R. pyridinivorans, S. hordei and S. naphthae . To the best of our knowledge these MFS transporters have never been characterised or reported previously. From syntenic analysis, the taxonomic distribution of TphK containing operons appears to be broader than previously thought with the activity of the transporters providing evidence for the existence of TPA catabolic operons in these genera. Analysis from Jimenez et al [ 57 ] used homology of the tph A2 gene to extract TPA catabolic operons from publicly available sequence databases, they attributed operon occurrences to a limited number of organisms including betaproteobacteria ( Comamonas, Ideonella and Ramlibacter ), gammaproteobacteria ( Pseudomonas ) and actinomycetes ( Rhodococcus ) with all betaproteobaceria utilising the TphC transporter. Our analysis demonstrates that genes encoding TphK may have a greater taxonomic spread than previously reported, as they appear in a greater number of species than first assumed as well as in a greater number of families, this may be due to the use of the entire operon including the tphK gene as a search query returning a more diverse selection of organisms. Interestingly we identified some betaproteobacteria that appeared to possess TphK encoding genes implying that tph operons in this class are not limited to only to those utilising TphC transport. The aforementioned TPA catabolic operon from Comamonas sp. Strain E6 encodes a tripartite tricarboxylate transporter instead of a TphK MFS [ 58 , 74 ] suggesting the possibility that two distinct transporter systems were acquired by the ancestral operon to enable TPA uptake. A possible explanation for the emergence of two transport systems with overlapping function could relate to the relative transport turnover of each system. Whilst both TphK and TphC are classified as secondary transporters, the latter relies on a solute binding protein which typically bind with high affinity for the substrate leading to its translocation across the membrane [ 75 ]. MFS proteins are known for their higher uptake rates of substrates however with generally lower affinity and specificity, whilst no direct comparison of uptake rates between these classes have been made the general trends of mechanism lend themselves to this concept [ 76 , 77 ]. As such the selection of transport system may relate to the preference of the host for TPA as a primary carbon source for growth or as an ancillary carbon source with the transporter systems representing different ecological niches in TPA rich environments. Whilst syntenic operon analysis is effective, this bioinformatics mining method is highly reliant on the co-localization of transporters to other genes in a functional context, making it inappropriate in the cases of orphan MFS proteins or exporters which are often located at random in genomes; making functional appraisal challenging [ 78 ]. Biosensor-enabled screening of the seven functional PcaK homologues revealed wide ranging sensitivity towards PCA, along with variable substrate specificity for PCA analogues possessing hydroxyl groups at positions 3 and 4 of the aromatic ring, and carboxylate, methyl ester-, amide- and aldehyde groups position 1. Interestingly, there did not appear to be a strong correlation with sequence similarity and substrate specificity with the PcaK from B. masilliglacei which clustered furthest from the P. putida PcaK but displayed the most similar substrate specificity to one another. Furthermore, PcaK P.Put and PcaK B.Mas demonstrated unique ability for the uptake 3,5-dihydroxybenzoic acid and gallic acid, indicating an activity towards position 5 hydroxyl groups which is not shared by the other screened PcaKs. In addition, the identification off this broader substate uptake scope also indicates a broader substrate scope for the PcaV transcription factor than previously reported [ 64 ]. The PcaK from A. baylyi has been previously purified and reconstituted in a proteoliposome, where it was reported to be able to take up salicylate, 2,4-dihydroxybenzoic, 4HBA and PCA in addition to vanillic acid and 3HBA [ 42 ]. Further, PcaKs from Acinetobacter sp. and Sphingobium sp. were also reported to be able to take up PCA, 4HBA, 3HBA, and to some extent vanillic acid, through genomic deletion and growth assays [ 10 , 42 ]. In this study, uptake of salicylate (2,4-dihydroxybenzoic acid) was not detected by any of the biosensor-mediated transporter assay. Presumably this is due to the inability of the PcaV biosensor to recognise these substrates rather than a lack of transport. This reveals a limitation of the proposed method, whereby the assay depends on both transporter and biosensor specificity a recognised challenge in biosensor development [ 79 ]. This could be remedied through the engineering of sensors to increase their substrate scope or through the incorporation of other allosteric transcription factors to further improve substrate breadth [ 64 ]. Further, in this study, determining substrate preference between PCA, 4HBA and 3HBA was made difficult due to the background uptake of 4HBA and 3HBA by P. putida , presumably through the action of promiscuous endogenous transporters. Any whole cell-based transporter assay will likely be challenged by background transport activity, highlighting the trade-off between scalability and ease of use versus the sensitivity of such a system. For the first time, the substrate specificity of TphK’s was also characterised, whereby it was found that they demonstrate a strict preference for para-substituted aromatic dicarboxylic acids, with a tolerance for polar substitutions in the 2nd ring position, such as: hydroxyl, nitro, amino and halogen groups. Unexpectedly, they also displayed the ability to take up biphenyl-4,4-dicarboxylic acid, an effector twice the length of the cognate ligand TPA [ 58 ]. We have previously characterised the tripartite tricarboxylate transporter, TphC, from the TPA catabolic operon of Comamonas sp. strain E6. In that study we explored ligand recognition by the solute binding protein of TphC, which was able to bind TPA ( T3 ), 2-hydroxy TPA ( T13 ), 2-amino TPA ( T18 ) and also biphenyl-4,4,-dicarboxylic acid ( T20 ) [ 58 ]. This substrate specificity overlaps with that of the TphK’s characterised in this work, intuitively suggesting that as both TphK- and TphC-type tph catabolic operons possess the same core activity, they therefore, likely have overlapping substrate transport recognition. However, the overlapping uptake of biphenyl-4,4-dicarboyxlic acid does raise questions of the functional origin of both TphK and TphC, whether these originated as bona fide transporters of TPA or perhaps related to transporters from biphenyl catabolic pathways, another anthropogenic carbon source. In addition, the identification of this broadened substate scope also indicates that the TphR transcription factor from Z. Caldifontis is activated by aromatic diacids with increased length. The main determining factor for the TphR activity appears to be the requirement to maintain the diacids in a co-planar arrangement [ 64 ]. Transporter-biosensor crossover assays identified that TphK R.Pyr displays some limited import activity towards PCA, along with 3HBA, resulting in significant biosensor activation. In contrast PcaK was unable to transport TPA but was active towards to 2-hydroxy TPA ( T13 ) and pyridine-2,5-dicarboxylic acid ( T4 ) although the degree of activation was quite low. TphK appears to have a substrate preference for the uptake of dicarboxylic acids yet is also able to transport some monocarboxylates with reduced activity. This stringency for dicarboxylic acids also appears to have made it less tolerant to other functional groups, such as aldehyde, methyl ester and amide. PcaK on the other hand responded to effector ligands that display similar substitution pattern to PCA. The size and ability to hydrogen bond may be important for ligand recognition in PcaK, as bulkier substitutions/altered H-bonding potential groups failed to be transport and/or elicit activation the biosensor (iodo, bromo, amino, and nitro). To further probe the potential of biosensors for membrane protein engineering applications, we evaluated the ability of the PcaV-sensor to detect the functional impact of point mutations made to PcaK. In previous studies, the evaluation of transporter point mutants has been performed using laborious techniques, relying on chromatography based approaches to measure the depletion of a compound in media by strains expressing the transporter variant or via harvesting of cells and exposure to 14 C labelled substrates followed by scintillation counting of cells [ 80 , 81 ]. Both of which are expensive approaches that require specialist knowledge and careful handling. Here, we reconstituted mutations in the critical 2–3 and 8–9 loop sequences of PcaK [ 80 ], and using the PcaV biosensor system showed these to be effective in abolishing transport of PCA and reducing transport of 4HBA, in agreement with previous studies. Currently, there are no reported crystal structures for any member of the aromatic acid H + symporter family. As such, information on the residues and/or structural features pertaining to ligand recognition and transport is minimal. Relying on primary sequence alignment of the transporters alone does not always guarantee functional relevance, with regions of functional similarity (substrate binding or ion binding sites) often display poor sequence alignment. In more distantly related transporters, residues with a similar functional role are often located far from each other in a primary sequence alignment [ 82 ]. Analysis by Wada et al hypothesised a possible ligand binding site in PcaK based on structural modelling using other MFS structures with some of these residues located on the core TM helices used in this study [ 25 ]. Thus, we opted to perform replacement of the core TM helices between TphK R.Pyr and PcaK P.Put to gauge which of these structural features may contain sequence elements pertinent to substrate recognition. A similar TM swap approach has been used before with the glucose transporters Hxt1 and 2, which enabled the identification of TM’s: 1, 5, 7 and 8 as being essential for glucose recognition and uptake [ 83 ]. Combination of rapid biosensor-enabled screening in tandem with predicted structure and sequence alignments suggests the involvement of a number of residues present in the core cavity which could be essential for effector recognition. All chimeras screened in their cognate biosensor background (Figs. 4 & 5 ) appeared to demonstrate functional transport albeit with some loss of activity relative to the wildtype. Gains of function were observed for the TphK PcaK_TM1,4,7,10 chimera toward 2,5 pyrazine dicarboxylic acid ( T5 ) and naphthalene 2,6 dicarboxylic acid ( T21 ) (Fig. 4 A), indicating a deviation away from the established preference for the general TPA structure exhibited by the transporters characterised in this study. Given the retained recognition of 2’ substituted TPA analogues it is plausible that introduction of PcaK helices enabled recognition of more highly decorated structures via introduction of more hydrogen bonding residues into the cavity. Similarly, incorporation of TphK core TM helices into a PcaK scaffold led to significant increases in activity for coumaric acid ( P27 ) a much bulkier effector than other PCA analogues validated in our earlier characterisation experiments, suggesting the both the TphK and PcaK cores have structurally adapted to the dimensions of the effectors they transport with TphKs featuring sterically less bulky side chains relative to PcaKs. Studies that have crystallised MFS proteins in complex with their substrate have shown a network of residues across multiple helices act in a coordinated manner to bind substrates. For example, the bacterial MFS XylE in complex with D-xylose is coordinated by a total of eight hydrogen bonds, via polar residues on TM’s 5, 7, 8 and 10 as well as by aromatic residues in the vicinity from TM1, 7 10 and 11 [ 72 ]. Interestingly, whilst Q288, Q289, and N294, which are all located on the solvent exposed helical turns 3–4 of TM 7 of XylE, contribute to hydrogen bonding with D-xylose; Y298 located at the helical turn 6 is also involved in ligand binding through water mediated hydrogen bonding [ 72 ]. Therefore, it is possible that some of the more distal conserved residues identified in our analysis such as T283 (PcaK) or Q279 (TphK) that underwent mutation in the TM swap may act in a similar manner. Similarly, it is more difficult to ascertain the effect of other mutations introduced during helix exchanges, which do not occupy the core cavity and instead likely function as contact points for interhelical interactions. It is plausible that many of the effects we observed in the screened mutants were as a result of indirect disruption of protein structural dynamics, as such future studies that focus on targeted mutations of these implicated residues may shed more light on their role in proper protein function. We also noted the apparent synergism that occurs when multiple TM structures are exchanged simultaneously rather than individually. Key amino acid residues involved in selective protonation in response to effector binding have been inextricably linked to substrate translocation with the ionic motive force driving reconfiguration of MFS transporters from outward to inward conformations [ 84 ]. Given our observations, it is plausible that exchanging of TM helices may disrupt titratable amino acid residues responsible for the relaying of protons following substrate binding; the effect of mutating such charge carrying residues has resulted in the conversion of MFS proteins from active to passive transporter, drastically reducing uptake rate through the decoupling of the proton motive force. Indeed, in the case of XylE, mutation of D27 abolished transporter function entirely whilst mutating R133, which stabilises D27, lead to considerably reduced transport function highlighting the importance of such titratable residues in MFS function [ 85 ]. We noted the presence of a conserved glutamate residue (E274) located in TM7 mutated to an isoleucine in PcaK which may represent such a titratable residue that was lost during mutation. Such results indicate the feasibility of performing not only protein engineering efforts with MFS transporters, but also to probe more fundamental questions as to the role of specific residues or structural motifs in transporter function, enabled with biosensors, to provide a sensitive means of detecting gains and losses of function. Future studies using more targeted approaches such as site directed mutagenesis or alanine scanning of core cavity amino acids may provide a facile means of building structure activity relationships for putative or unclassified MFS proteins and can enable rapid identification of critical residues for further investigation. Incorporating multiple biosensors in serial genetic circuits coupled to different fluorescent outputs could potentially allow for further multiplexing of the approach covering a much broader range of compounds permitting deeper characterisation of transporters and overcoming the substrate limitations of a single aTF [ 86 ]. Conclusion We report a novel aTF-biosensor based screening method for the identification and characterisation of MFS transporters. Bioinformatically mined putative PcaK and TphK protein sequences for transporters of aromatic acids, PCA and TPA, were combined with TPA and PCA responsive biosensors. This led to the identification of novel members of both classes of aromatic acid H + symporters. We report wider taxonomic spread of the tph catabolic operon than previously reported as well as the first studies functionally characterising TphK substrate scope. The substrate specificity profiles of both classes were compared, revealing novel functionality for PcaKs from P. putida and B. masilliglacei in contrast to TphKs which demonstrated a more defined set of substrate preferences. We highlight the capability of biosensors in performing phenotypic characterisation of both point mutants as well as chimeric membrane transporters. This resulted in apparent gain of function chimeras with PcaK chimeras demonstrating uptake of pyrazine-2,5-dicarboxylic acid and naphthalene-1,6-dicarboxylic acid whereas TphK chimeras demonstrated increased activity to coumaric acid. These changes in activity appear to be related to the exchange of conserved residues in the core cavity interface of the protein structure, which effect the number of hydrogen bonding contacts as well as modifying the size of the core pocket modulating effector recognition and uptake. Some of these effects were shown to be dependent upon the coordinated activity of multiple helical domains acting in tandem implicating the involvement of pairs of complementary helical pairs/bundles for correct transport function and effector recognition. This study provides a method for the usage of biosensors as screening tools for evaluating putative transporters, and library of validated MFS transporters for biotechnologically relevant aromatic substrates. Declarations Acknowledgements The authors declare no acknowledgements Ethics Approval and Consent to Participate Not applicable Consent for publication Not applicable Funding PLR was supported by a BBSRC DTP grant (BB/T008725/1) and BBSRC grant BB/Y004027/1. MC was supported byBBSRC grant BB/Y003276/1 Conflicts of interest None Additional Data Additional File 1.xlsx – Title: Mutant Data Processing, Description: raw data and processing including statistical testing of the data to support the conclusions of Fig. 4 & 5 References Thomik T, Wittig I, Choe J, Boles E, Oreb M. An artificial transport metabolon facilitates improved substrate utilization in yeast. Nat Chem Biol. 2017;13:1158–63. Protzko RJ, Latimer LN, Martinho Z, de Reus E, Seibert T, Benz JP, et al. Engineering Saccharomyces cerevisiae for co-utilization of D-galacturonic acid and D-glucose from citrus peel waste. Nat Commun. 2018;9:5059. Boyarskiy S, Davis López S, Kong N, Tullman-Ercek D. Transcriptional feedback regulation of efflux protein expression for increased tolerance to and production of n -butanol. Metab Eng. 2016;33:130–7. Wu W, Liu F, Singh S. Toward engineering E. coli with an autoregulatory system for lignin valorization. Proceedings of the National Academy of Sciences. 2018;115:2970–5. van der Hoek SA, Borodina I. Transporter engineering in microbial cell factories: the ins, the outs, and the in-betweens. Curr Opin Biotechnol. 2020;66:186–94. Ren Q, Chen K, Paulsen IT. TransportDB: a comprehensive database resource for cytoplasmic membrane transport systems and outer membrane channels. Nucleic Acids Res. 2007;35:D274–9. Chaudhry MT, Huang Y, Shen X-H, Poetsch A, Jiang C-Y, Liu S-J. Genome-wide investigation of aromatic acid transporters in Corynebacterium glutamicum. Microbiology. 2007;153:857–65. D’Arrigo I, Cardoso JGR, Rennig M, Sonnenschein N, Herrgård MJ, Long KS. Analysis of Pseudomonas putida growth on non-trivial carbon sources using transcriptomics and genome-scale modelling. Environ Microbiol Rep. 2019;11:87–97. D’Argenio DA, Segura A, Coco WM, Bünz PV, Ornston LN. The Physiological Contribution ofAcinetobacter PcaK, a Transport System That Acts upon Protocatechuate, Can Be Masked by the Overlapping Specificity of VanK. J Bacteriol. 1999;181:3505–15. Mori K, Kamimura N, Masai E. Identification of the protocatechuate transporter gene in Sphingobium sp. strain SYK-6 and effects of overexpression on production of a value-added metabolite. Appl Microbiol Biotechnol. 2018;102:4807–16. Harwood CS, Nichols NN, Kim MK, Ditty JL, Parales RE. Identification of the pcaRKF gene cluster from Pseudomonas putida: involvement in chemotaxis, biodegradation, and transport of 4-hydroxybenzoate. J Bacteriol. 1994;176:6479–88. Kallscheuer N, Vogt M, Kappelmann J, Krumbach K, Noack S, Bott M, et al. Identification of the phd gene cluster responsible for phenylpropanoid utilization in Corynebacterium glutamicum. Appl Microbiol Biotechnol. 2016;100:1871–81. Nogales J, Canales Á, Jiménez-Barbero J, Serra B, Pingarrón JM, García JL, et al. Unravelling the gallic acid degradation pathway in bacteria: the gal cluster from Pseudomonas putida. Mol Microbiol. 2011;79:359–74. Chen Z, Huang J, Wu Y, Wu W, Zhang Y, Liu D. Metabolic engineering of Corynebacterium glutamicum for the production of 3-hydroxypropionic acid from glucose and xylose. Metab Eng. 2017;39:151–8. MacLean AM, Haerty W, Golding GB, Finan TM. The LysR-type PcaQ protein regulates expression of a protocatechuate-inducible ABC-type transport system in Sinorhizobium meliloti. Microbiology. 2011;157:2522–33. Michalska K, Chang C, Mack JC, Zerbs S, Joachimiak A, Collart FR. Characterization of Transport Proteins for Aromatic Compounds Derived from Lignin: Benzoate Derivative Binding Proteins. J Mol Biol. 2012;423:555–75. Salmon RC, Cliff MJ, Rafferty JB, Kelly DJ. The CouPSTU and TarPQM Transporters in Rhodopseudomonas palustris: Redundant, Promiscuous Uptake Systems for Lignin-Derived Aromatic Substrates. PLoS ONE. 2013;8:e59844. Mulligan C, Fischer M, Thomas GH. Tripartite ATP-independent periplasmic (TRAP) transporters in bacteria and archaea. FEMS Microbiol Rev. 2011;35:68–86. Reverón I, Jiménez N, Curiel JA, Peñas E, López de Felipe F, de Las Rivas B, et al. Differential Gene Expression by Lactobacillus plantarum WCFS1 in Response to Phenolic Compounds Reveals New Genes Involved in Tannin Degradation. Appl Environ Microbiol. 2017;83:e03387–16. Drew D, North RA, Nagarathinam K, Tanabe M. Structures and General Transport Mechanisms by the Major Facilitator Superfamily (MFS). Chem Rev. 2021;121:5289–335. Ma C, Mu Q, Xue Y, Xue Y, Yu B, Ma Y. One major facilitator superfamily transporter is responsible for propionic acid tolerance in Pseudomonas putida KT2440. Microb Biotechnol. 2020;14:386–91. Srinivasan P, Smolke CD. Biosynthesis of medicinal tropane alkaloids in yeast. Nature. 2020;585:614–9. Bracher JM, Verhoeven MD, Wisselink HW, Crimi B, Nijland JG, Driessen AJM, et al. The Penicillium chrysogenum transporter PcAraT enables high-affinity, glucose-insensitive l-arabinose transport in Saccharomyces cerevisiae. Biotechnol Biofuels. 2018;11:63. Arai M, Okumura K, Satake M, Shimizu T. Proteome-wide functional classification and identification of prokaryotic transmembrane proteins by transmembrane topology similarity comparison. Protein Sci. 2004;13:2170–83. Wada A, Prates ÉT, Hirano R, Werner AZ, Kamimura N, Jacobson DA, et al. Characterization of aromatic acid/proton symporters in Pseudomonas putida KT2440 toward efficient microbial conversion of lignin-related aromatics. Metab Eng. 2021;64:167–79. Genee HJ, Bali AP, Petersen SD, Siedler S, Bonde MT, Gronenberg LS, et al. Functional mining of transporters using synthetic selections. Nat Chem Biol. 2016;12:1015–22. Madej MG, Sun L, Yan N, Kaback HR. Functional architecture of MFS d-glucose transporters. Proceedings of the National Academy of Sciences. 2014;111:E719–27. Weiland F, Kohlstedt M, Wittmann C. Guiding stars to the field of dreams: Metabolically engineered pathways and microbial platforms for a sustainable lignin-based industry. Metab Eng. 2022;71:13–41. Fleige C, Meyer F, Steinbüchel A. Metabolic Engineering of the Actinomycete Amycolatopsis sp. Strain ATCC 39116 towards Enhanced Production of Natural Vanillin. Appl Environ Microbiol. 2016;82:3410–9. Sainsbury PD, Hardiman EM, Ahmad M, Otani H, Seghezzi N, Eltis LD, et al. Breaking Down Lignin to High-Value Chemicals: The Conversion of Lignocellulose to Vanillin in a Gene Deletion Mutant of Rhodococcus jostii RHA1. ACS Chem Biol. 2013;8:2151–6. Suzuki Y, Otsuka Y, Araki T, Kamimura N, Masai E, Nakamura M, et al. Lignin valorization through efficient microbial production of β-ketoadipate from industrial black liquor. Bioresour Technol. 2021;337:125489. Kogure T, Suda M, Hiraga K, Inui M. Protocatechuate overproduction by Corynebacterium glutamicum via simultaneous engineering of native and heterologous biosynthetic pathways. Metab Eng. 2021;65:232–42. Gao R, Pan H, Kai L, Han K, Lian J. Microbial degradation and valorization of poly(ethylene terephthalate) (PET) monomers. World J Microbiol Biotechnol. 2022;38:89. Raheem AB, Noor ZZ, Hassan A, Abd Hamid MK, Samsudin SA, Sabeen AH. Current developments in chemical recycling of post-consumer polyethylene terephthalate wastes for new materials production: A review. J Clean Prod. 2019;225:1052–64. Benavides Fernández CD, Guzmán Castillo MP, Quijano Pérez SA. Carvajal Rodríguez LV. Microbial degradation of polyethylene terephthalate: a systematic review. SN Appl Sci. 2022;4:263. Tiso T, Narancic T, Wei R, Pollet E, Beagan N, Schröder K, et al. Towards bio-upcycling of polyethylene terephthalate. Metab Eng. 2021;66:167–78. Yoshida S, Hiraga K, Takehana T, Taniguchi I, Yamaji H, Maeda Y, et al. A bacterium that degrades and assimilates poly(ethylene terephthalate). Science. 2016;351:1196–9. Werner AZ, Clare R, Mand TD, Pardo I, Ramirez KJ, Haugen SJ et al. Tandem chemical deconstruction and biological upcycling of poly(ethylene terephthalate) to β-ketoadipic acid by Pseudomonas putida KT2440. Metabolic Engineering. 2021;67:250–61. Hara H, Eltis LD, Davies JE, Mohn WW. Transcriptomic Analysis Reveals a Bifurcated Terephthalate Degradation Pathway in Rhodococcus sp. Strain RHA1. J Bacteriol. 2007;189:1641–7. Brandenberg OF, Schubert OT, Kruglyak L. Towards synthetic PETtrophy: Engineering Pseudomonas putida for concurrent polyethylene terephthalate (PET) monomer metabolism and PET hydrolase expression. Microb Cell Fact. 2022;21:119. Ramos-González M-I, Godoy P, Alaminos M, Ben-Bassat A, Ramos J-L. Physiological Characterization of Pseudomonas putida DOT-T1E Tolerance to p-Hydroxybenzoate. Appl Environ Microbiol. 2001;67:4338–41. Pernstich C, Senior L, MacInnes K, Forsaith M, Curnow P. Expression, purification and reconstitution of the 4-hydroxybenzoate transporter PcaK from Acinetobacter sp. ADP1. Protein Exp Purif. 2014;101. Alvarez-Gonzalez G, Chacόn M, Berepiki A, Fisher K, Gosalvitr P, Cuéllar-Franca R et al. Complex waste stream valorisation through combined enzymatic hydrolysis and catabolic assimilation by Pseudomonas putida [Internet]. bioRxiv; 2024 [cited 2024 Aug 27]. p. 2023.02.13.528311. Available from: https://www.biorxiv.org/content/ 10.1101/2023.02.13.528311v2 Gao C, Hou J, Xu P, Guo L, Chen X, Hu G, et al. Programmable biomolecular switches for rewiring flux in Escherichia coli. Nat Commun. 2019;10:3751. Choi S-S, Seo S-Y, Park S-O, Lee H-N, Song J-S, Kim J-Y, et al. Cell Factory Design and Culture Process Optimization for Dehydroshikimate Biosynthesis in Escherichia coli. Front Bioeng Biotechnol. 2019;7:241. Alvarez-Gonzalez G, Dixon N. Genetically encoded biosensors for lignocellulose valorization. Biotechnol Biofuels. 2019;12:246. Chaisupa P, Wright RC. State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering. SLAS Technol. 2024;29:100113. Zhu Y, Zhou C, Wang Y, Li C. Transporter Engineering for Microbial Manufacturing. Biotechnol J. 2020;15:1900494. Wang G, Møller-Hansen I, Babaei M, D’Ambrosio V, Christensen HB, Darbani B, et al. Transportome-wide engineering of Saccharomyces cerevisiae . Metab Eng. 2021;64:52–63. Waterhouse AM, Procter JB, Martin DMA, Clamp M, Barton GJ. Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics. 2009;25:1189–91. Gilchrist CLM, Booth TJ, van Wersch B, van Grieken L, Medema MH, Chooi Y-H. cblaster: a remote search tool for rapid identification and visualization of homologous gene clusters. Bioinf Adv. 2021;1:vbab016. Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics. 2012;28:3150–2. Marx CJ. Development of a broad-host-range sacB-based vector for unmarked allelic exchange. BMC Res Notes. 2008;1:1. Dobson L, Reményi I, Tusnády GE. CCTOP: a Consensus Constrained TOPology prediction web server. Nucleic Acids Res. 2015;43:W408–12. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021;596:583–9. Meng EC, Goddard TD, Pettersen EF, Couch GS, Pearson ZJ, Morris JH, et al. UCSF ChimeraX: Tools for structure building and analysis. Protein Sci. 2023;32:e4792. Salvador M, Abdulmutalib U, Gonzalez J, Kim J, Smith AA, Faulon J-L, et al. Microbial Genes for a Circular and Sustainable Bio-PET Economy. Genes. 2019;10:373. Gautom T, Dheeman D, Levy C, Butterfield T, Alvarez Gonzalez G, Le Roy P, et al. Structural basis of terephthalate recognition by solute binding protein TphC. Nat Commun. 2021;12:6244. Harwood CS, Parales RE, THE β-KETOADIPATE, PATHWAY AND THE BIOLOGY OF SELF-IDENTITY. Annu Rev Microbiol. 1996;50:553–90. Kamimura N, Aoyama T, Yoshida R, Takahashi K, Kasai D, Abe T, et al. Characterization of the Protocatechuate 4,5-Cleavage Pathway Operon in Comamonas sp. Strain E6 and Discovery of a Novel Pathway Gene. Appl Environ Microbiol. 2010;76:8093–101. Kasai D, Fujinami T, Abe T, Mase K, Katayama Y, Fukuda M, et al. Uncovering the Protocatechuate 2,3-Cleavage Pathway Genes. J Bacteriol. 2009;191:6758–68. Stover CK, Pham XQ, Erwin AL, Mizoguchi SD, Warrener P, Hickey MJ, et al. Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen. Nature. 2000;406:959–64. Alvarez Gonzalez G, Chacón M, Butterfield T, Dixon N. Tuning the performance of a TphR-based terephthalate biosensor with a design of experiments approach. Metab Eng Commun. 2024;19:e00250. Machado FM, Currin L, Dixon A. Directed evolution of the PcaV allosteric transcription factor to generate a biosensor for aromatic aldehydes. J Biol Eng. 2019;13:91. Vermaas JV, Dixon RA, Chen F, Mansfield SD, Boerjan W, Ralph J et al. Passive membrane transport of lignin-related compounds. Proceedings of the National Academy of Sciences. 2019;116:23117–23. Narancic T, Salvador M, Hughes GM, Beagan N, Abdulmutalib U, Kenny ST, et al. Genome analysis of the metabolically versatile Pseudomonas umsongensis GO16: the genetic basis for PET monomer upcycling into polyhydroxyalkanoates. Microb Biotechnol. 2021;14:2463–80. Liu X, Jin J, Sun H, Li S, Zhang F, Yu X, et al. Perspectives on the microorganisms with the potentials of PET-degradation. Front Microbiol. 2025;16:1541913. NIAID Data Discovery Portal [Internet]. NIAID Data Discovery Portal. [cited 2024 Jul 24]. Available from: https://data.niaid.nih.gov Wilkes RA, Waldbauer J, Carroll A, Nieto-Domínguez M, Parker DJ, Zhang L, et al. Complex regulation in a Comamonas platform for diverse aromatic carbon metabolism. Nat Chem Biol. 2023;19:651–62. Ditty JL, Harwood CS. Charged Amino Acids Conserved in the Aromatic Acid/H + Symporter Family of Permeases Are Required for 4-Hydroxybenzoate Transport by PcaK from Pseudomonas putida. J Bacteriol. 2002;184:1444–8. Yan N. Structural advances for the major facilitator superfamily (MFS) transporters. Trends Biochem Sci. 2013;38:151–9. Sun L, Zeng X, Yan C, Sun X, Gong X, Rao Y, et al. Crystal structure of a bacterial homologue of glucose transporters GLUT1–4. Nature. 2012;490:361–6. Steiger MG, Rassinger A, Mattanovich D, Sauer M. Engineering of the citrate exporter protein enables high citric acid production in Aspergillus niger. Metab Eng. 2019;52:224–31. Sasoh M, Masai E, Ishibashi S, Hara H, Kamimura N, Miyauchi K, et al. Characterization of the terephthalate degradation genes of Comamonas sp. strain E6. Appl Environ Microbiol. 2006;72:1825–32. Rosa LT, Bianconi ME, Thomas GH, Kelly DJ. Tripartite ATP-Independent Periplasmic (TRAP) Transporters and Tripartite Tricarboxylate Transporters (TTT): From Uptake to Pathogenicity. Front Cell Infect Microbiol [Internet]. 2018 [cited 2025 May 6];8. Available from: https://www.frontiersin.orghttps://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/ 10.3389/fcimb.2018.00033/full Law CJ, Maloney PC, Wang D-N. Ins and Outs of Major Facilitator Superfamily Antiporters. Annu Rev Microbiol. 2008;62:289–305. Chen C, Beattie GA. Pseudomonas syringae BetT Is a Low-Affinity Choline Transporter That Is Responsible for Superior Osmoprotection by Choline over Glycine Betaine. J Bacteriol. 2008;190:2717–25. Møller-Hansen I, Sáez-Sáez J, van der Hoek SA, Dyekjær JD, Christensen HB, Wright Muelas M et al. Deorphanizing solute carriers in Saccharomyces cerevisiae for secondary uptake of xenobiotic compounds. Front Microbiol [Internet]. 2024 [cited 2024 Jul 22];15. Available from: https://www.frontiersin.org/journals/microbiology/articles/ 10.3389/fmicb.2024.1376653/full Shin S-M, Jha RK, Dale T. Tackling the Catch-22 Situation of Optimizing a Sensor and a Transporter System in a Whole-Cell Microbial Biosensor Design for an Anthropogenic Small Molecule. ACS Synth Biol. 2022;11:3996–4008. Ditty JL, Harwood CS. Conserved cytoplasmic loops are important for both the transport and chemotaxis functions of PcaK, a protein from Pseudomonas putida with 12 membrane-spanning regions. J Bacteriol. 1999;181:5068–74. Standaert RF, Giannone RJ, Michener JK. Identification of parallel and divergent optimization solutions for homologous metabolic enzymes. Metabolic Eng Commun. 2018;6:56–62. Madej MG, Kaback HR. Evolutionary mix-and-match with MFS transporters II. Proceedings of the National Academy of Sciences. 2013;110:E4831–8. Kasahara T, Kasahara M. Transmembrane segments 1, 5, 7 and 8 are required for high-affinity glucose transport by Saccharomyces cerevisiae Hxt2 transporter. Biochem J. 2003;372:247–52. Zhang XC, Zhao Y, Heng J, Jiang D. Energy coupling mechanisms of MFS transporters. Protein Sci. 2015;24:1560–79. Wisedchaisri G, Park M-S, Iadanza MG, Zheng H, Gonen T. Proton-coupled sugar transport in the prototypical major facilitator superfamily protein XylE. Nat Commun. 2014;5:4521. Meyer AJ, Segall-Shapiro TH, Glassey E, Zhang J, Voigt CA. Escherichia coli Marionette strains with 12 highly optimized small-molecule sensors. Nat Chem Biol. 2019;15:196–204. Additional Declarations No competing interests reported. Supplementary Files MFSSupplementalMaterial.docx AdditionalFile1.xlsx Cite Share Download PDF Status: Published Journal Publication published 31 Oct, 2025 Read the published version in Journal of Biological Engineering → Version 1 posted Editorial decision: Revision requested 15 Jul, 2025 Reviews received at journal 15 Jul, 2025 Reviews received at journal 13 Jul, 2025 Reviews received at journal 09 Jul, 2025 Reviews received at journal 03 Jul, 2025 Reviewers agreed at journal 25 Jun, 2025 Reviewers agreed at journal 25 Jun, 2025 Reviewers agreed at journal 23 Jun, 2025 Reviewers agreed at journal 23 Jun, 2025 Reviewers agreed at journal 23 Jun, 2025 Reviewers invited by journal 23 Jun, 2025 Editor assigned by journal 23 Jun, 2025 Submission checks completed at journal 23 Jun, 2025 First submitted to journal 19 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6931086\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":475291232,\"identity\":\"bd9172d7-492a-4fd8-8f6d-1d299de1f94b\",\"order_by\":0,\"name\":\"Philip Le Roy\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Manchester\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Philip\",\"middleName\":\"Le\",\"lastName\":\"Roy\",\"suffix\":\"\"},{\"id\":475291233,\"identity\":\"7680e020-74a4-4de9-b67a-9dcec96362ae\",\"order_by\":1,\"name\":\"Micaela Chacόn\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Manchester\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Micaela\",\"middleName\":\"\",\"lastName\":\"Chacόn\",\"suffix\":\"\"},{\"id\":475291234,\"identity\":\"c1cbec78-607d-4780-9be7-2ec6348f68dd\",\"order_by\":2,\"name\":\"Neil Dixon\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"\",\"institution\":\"University of Manchester\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Neil\",\"middleName\":\"\",\"lastName\":\"Dixon\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-06-19 12:08:36\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6931086/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6931086/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s13036-025-00568-y\",\"type\":\"published\",\"date\":\"2025-10-31T15:58:55+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":85394328,\"identity\":\"e4dd0181-8508-43cd-a9d6-c4d66f4f6b7c\",\"added_by\":\"auto\",\"created_at\":\"2025-06-25 10:56:30\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":846781,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003ePhylogenetic and taxonomic analysis of the \\u003c/strong\\u003e\\u003cem\\u003e\\u003cstrong\\u003etph \\u003c/strong\\u003e\\u003c/em\\u003e\\u003cstrong\\u003eoperon.\\u003c/strong\\u003e (\\u003cstrong\\u003eA\\u003c/strong\\u003e) TPA degradation operon (\\u003cem\\u003etphR \\u003c/em\\u003eIclR-type transcription factor, \\u003cem\\u003etphA2/3 \\u003c/em\\u003eTPA 1,2 dioxygenase large/small subunit, \\u003cem\\u003etphB \\u003c/em\\u003e1,2-dihydroxy-3,5-cyclohexadiene-1,4-dicarboxylate dehydrogenase \\u003cem\\u003etphA1 \\u003c/em\\u003ereductase component and \\u003cem\\u003etphK \\u003c/em\\u003eMFS)\\u003cem\\u003e \\u003c/em\\u003efrom \\u003cem\\u003eR. jostii \\u003c/em\\u003eused in multigene BLAST search as a query, showing configuration of genes, and the catabolic transformation is also displayed at the bottom of the figure. (\\u003cstrong\\u003eB\\u003c/strong\\u003e) Phylogenetic tree of putative TphK homologues generated from the cblaster multigene BLAST tool analysis, rooted with respect to \\u003cem\\u003eRhodococcus jostii\\u003c/em\\u003e TphK. Interior colour scheme designates genera, whilst the outer ring denotes the class of bacteria. Stars represent putative TphK’s carried forward for screening within the TPA responsive biosensor. (\\u003cstrong\\u003eC\\u003c/strong\\u003e) Selected putative TphK transporters including genus, class and distance from root.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6931086/v1/d1ebc2b54f428dfb25643c16.png\"},{\"id\":85394327,\"identity\":\"060ccc2d-b760-49af-aa13-afcb1b2e80b0\",\"added_by\":\"auto\",\"created_at\":\"2025-06-25 10:56:30\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1092351,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003ePhylogenetic analysis of PcaK transporters.\\u003c/strong\\u003e(\\u003cstrong\\u003eA\\u003c/strong\\u003e) \\u003cem\\u003epca\\u003c/em\\u003e catabolic operons from \\u003cem\\u003ePaenibacillus \\u003c/em\\u003esp. JJ1B and \\u003cem\\u003eComamonas\\u003c/em\\u003e sp. E6, utilised for initial cblaster screening, plus three operons selected to represent the \\u003cem\\u003e3,4\\u003c/em\\u003epathway. \\u0026nbsp;(\\u003cstrong\\u003eB\\u003c/strong\\u003e) Phylogenetic tree of PcaK transporters rooted with respect to \\u003cem\\u003eP. putida \\u003c/em\\u003eKT2440 PcaK (\\u003cem\\u003e3,4\\u003c/em\\u003e). Inner ring colours denote the PCA degradation pathway of origin, outer ring stratifies by bacterial class of the transporter host organism. Leaves are coloured by host genus. Black and grey rings represent branch length increments of 1.4. Bootstrapping values are indicated by the size of green circles at root branches. Transporters selected for cloning are indicated with stars. (\\u003cstrong\\u003eC\\u003c/strong\\u003e) Summary of host, genus, class, distance from root and pathway of origin of PcaKs selected for further analysis.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6931086/v1/eb3ba94f7fa29c9a34e0f5e6.png\"},{\"id\":85394330,\"identity\":\"b055c8c6-ca39-495b-9a8d-b38de41890b8\",\"added_by\":\"auto\",\"created_at\":\"2025-06-25 10:56:30\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":618927,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eBiosensor based characterisation of putative TphK and PcaK transporters and structure activity relationship screening against effector ligand analogues.\\u003c/strong\\u003e (\\u003cstrong\\u003eA\\u003c/strong\\u003e) Schematic representation of workflow beginning with the identification of putative transporters followed by cloning into plasmids containing appropriate responsive allosteric transcription factors (aTFs) coupled to \\u003cem\\u003esfgfp \\u003c/em\\u003eexpression to elucidate transporter functionality. (\\u003cstrong\\u003eB\\u003c/strong\\u003e) Dose response curve of TPA leading to expression of GFP normalised to cell density (RFU/OD600) for putative TphKs from 8 bacterial species. Each data point is representative of the mean and standard deviation of n = 3. (\\u003cstrong\\u003eC\\u003c/strong\\u003e) Dose response curve of putative PcaK transporters from 9 bacterial species normalised as for figure panel \\u003cstrong\\u003eC\\u003c/strong\\u003e. Each data point is representative of the mean and standard deviation of n = 3. (\\u003cstrong\\u003eD\\u003c/strong\\u003e) Significant TphK-TphR transporter-biosensor activation in response to TPA analogues in the \\u003cem\\u003eΔpcak\\u003c/em\\u003e \\u003cem\\u003eP. putida \\u003c/em\\u003ehost. (\\u003cstrong\\u003eE\\u003c/strong\\u003e)\\u003cstrong\\u003e \\u003c/strong\\u003eSignificant PcaK-PcaV transporter-biosensor activation in response to PCA analogues in the \\u003cem\\u003eΔpcak\\u003c/em\\u003e \\u003cem\\u003eP. putida \\u003c/em\\u003ehost. Bars are representative of means of n = 3 biological replicates. 2-way Anova was used to validate statistically significant responses induced by effector analogues. Analogues which did not induce significant fold change for any transporter are not plotted.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6931086/v1/7e2388d350de8cf75bea429b.png\"},{\"id\":85393127,\"identity\":\"d5cb9639-49a5-4fc8-ba1d-fbd3932a91e2\",\"added_by\":\"auto\",\"created_at\":\"2025-06-25 10:48:30\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":486378,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eStructure activity relationship screening of PcaK and TphK core helical domain mutants in cognate biosensor backgrounds. \\u003c/strong\\u003e(\\u003cstrong\\u003eA\\u003c/strong\\u003e) Plot of significant fold change induction by TPA analogues in TphK\\u003csub\\u003e-ve \\u003c/sub\\u003e(blue) wild type TphK (lilac), or TphK\\u003csub\\u003ePcaK_TM1,4,7,10\\u003c/sub\\u003e chimera (green) in the TphR biosensor background relative to the TphK\\u003csub\\u003e-ve\\u003c/sub\\u003e control. (\\u003cstrong\\u003eB\\u003c/strong\\u003e)\\u003cstrong\\u003e \\u003c/strong\\u003ePlot of significant fold change induction by PCA analogues in PcaK\\u003csub\\u003e-ve \\u003c/sub\\u003e(blue) wild type PcaK (lilac), or PcaK\\u003csub\\u003eTphK_TM1,4,7,10 \\u003c/sub\\u003echimera (green) mutant in the PcaV biosensor background relative to the PcaK\\u003csub\\u003e-ve \\u003c/sub\\u003econtrol. (\\u003cstrong\\u003eC\\u003c/strong\\u003e) A structural overlay of the predicted structures of the WT TphK (Red) and TphK\\u003csub\\u003ePcaKTM1,4,7,10 \\u003c/sub\\u003echimera (blue) generated with Alphafold. (\\u003cstrong\\u003eD\\u003c/strong\\u003e) A structural overlay of the predicted structures of the WT PcaK (Red) and PcaK\\u003csub\\u003ePcaK_TM1,4,7,10 \\u003c/sub\\u003echimera (blue) generated with Alphafold. All bars are fold change averages representative of 3 biological replicates calculated from raw RFU/OD\\u003csub\\u003e600 \\u003c/sub\\u003evalues.\\u0026nbsp;\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6931086/v1/7b81cf8f69db783c6f2ef7ae.png\"},{\"id\":85394329,\"identity\":\"77d2a9d5-c992-4c4d-b403-b2c4efa2ef4a\",\"added_by\":\"auto\",\"created_at\":\"2025-06-25 10:56:30\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":528391,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAssessment of single helical domain exchanges on portability of active substrates via relative fold change activation. \\u003c/strong\\u003e(\\u003cstrong\\u003eA\\u003c/strong\\u003e)\\u003cstrong\\u003e \\u003c/strong\\u003eHeatmap displaying statistically significant increase or decrease in transport (GFP activation) of PcaK chimeras relative to the PcaK\\u003csub\\u003e-ve \\u003c/sub\\u003econstruct against selected effectors. (\\u003cstrong\\u003eB\\u003c/strong\\u003e)\\u003cstrong\\u003e \\u003c/strong\\u003eA predicted structure of the PcaK wildtype protein with the core helical domains exchanged during mutagenesis colour coded, conserved amino acids that were exchanged are shown as ball and stick representations with those pointing into the core cavity labelled.\\u0026nbsp; (\\u003cstrong\\u003eC\\u003c/strong\\u003e)\\u0026nbsp; Heatmap displaying statistically significant increase or decrease in transport (GFP activation) of TphK chimeric mutants relative to TphK\\u003csub\\u003e-ve \\u003c/sub\\u003econstructs against selected effectors.\\u003cstrong\\u003e \\u003c/strong\\u003e(\\u003cstrong\\u003eD\\u003c/strong\\u003e) A predicted structure of the TphK wildtype protein with the core helical domains exchanged during mutagenesis colour coded, conserved amino acids that were exchanged are shown as ball and stick representations with those pointing into the core cavity labelled. (\\u003cstrong\\u003eE\\u003c/strong\\u003e) Mutations of conserved residues in PcaK introduced by exchange of core helical structures, with bold and starred mutations denoting those that occur in the solvent exposed core cavity of the protein. \\u003cstrong\\u003e(F) \\u003c/strong\\u003eMutations of conserved residues in TphK introduced by exchange of core helical structures, with bold and starred mutations denoting those that occur in the core cavity of the protein. All predicted structures are shown in the inward open conformation with a side view of the core cavity.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6931086/v1/e2f20b6f81c18b77e41b27de.png\"},{\"id\":95040625,\"identity\":\"1a9102c1-6b65-4e6d-b36b-ebf894ca4f85\",\"added_by\":\"auto\",\"created_at\":\"2025-11-03 16:09:59\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":5077312,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6931086/v1/b5458963-eab9-47ad-800b-dd82d6486c78.pdf\"},{\"id\":85393130,\"identity\":\"5eef1f8c-1f04-43fe-aba6-7cae18c601e3\",\"added_by\":\"auto\",\"created_at\":\"2025-06-25 10:48:30\",\"extension\":\"docx\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":4863297,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"MFSSupplementalMaterial.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6931086/v1/53b86a7a39a8bb3ec19cdb21.docx\"},{\"id\":85393125,\"identity\":\"b12b9dc1-d2f7-440a-baca-e6e9082588c4\",\"added_by\":\"auto\",\"created_at\":\"2025-06-25 10:48:30\",\"extension\":\"xlsx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":110364,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"AdditionalFile1.xlsx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6931086/v1/5e0fd07fa00e1e45faa2b741.xlsx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Genetically encoded biosensor enabled mining, characterisation and engineering of aromatic acid MFS transporters\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eMicrobial cell factories are foundational to the future bioeconomy, permitting the sustainable production of chemicals and materials from renewable and waste feedstocks. Efficient utilisation of these feedstocks is essential for process economics; however, this can be challenged by the compositional and chemical heterogeneity of an input stream. Here, the poor import of feedstock-derived substrates can impose large bottlenecks on strain productivity due to insufficient intracellular concentration of the substrate or through an inability to efficiently remove toxic compounds from the intracellular space. To overcome this, transporter engineering aimed at optimising the movement of substrates and intermediates across the microbial cell membrane and the coupling of transport to other cellular processes constitutes an important facet of strain development [\\u003cspan additionalcitationids=\\\"CR2 CR3\\\" citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. Further, engineering transporters for broader substrate scope can be used to expand the range of metabolically accessible compounds, permitting more complete utilisation of feedstocks and greater conversion efficiency [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. Transport proteins are immensely diverse both in terms of structure and function, and are classified into many families based on these traits [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. For the purpose of biomolecular engineering approaches concerning waste feedstocks such as lignocellulose however, this pool can be narrowed to the major facilitator superfamily (MFS) [\\u003cspan additionalcitationids=\\\"CR8 CR9 CR10 CR11 CR12\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e], ATP binding cassette (ABC) [\\u003cspan additionalcitationids=\\\"CR15 CR16\\\" citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e] family, tripartite ATP independent periplasmic (TRAP) transporters [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e], and ion transporter superfamily (IT) [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e] for lignin aromatics based on experimentally confirmed uptake of lignocellulosic substrates by these transporter classes.\\u003c/p\\u003e \\u003cp\\u003eThe MFS is the largest and most diverse family of secondary active transporters. This superfamily can be further categorised into 16 families and 89 subfamilies based on phylogeny and substrate scope [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. The substrate scope of MFS\\u0026rsquo; encompasses a diverse array of substrates, such as: sugars (sugar porters), inorganic or organic anions or cations (anion:cation symporters), aromatic acids (aromatic acid symporters/exporters) and drug/hydrophobic substances (drug:proton(H\\u003csup\\u003e+\\u003c/sup\\u003e) antiporters) [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Their ability to import and export valuable substrates such as sugars and organic acid make these transporters attractive targets for microbial strain engineering [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR22\\\" citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]. In addition to their valuable function, MFS proteins are generally quite small, typically consisting of 400\\u0026ndash;600 amino acids comprising 12\\u0026ndash;14 transmembrane helices, in addition to being driven by ion gradients instead of ATP hydrolysis, resulting in low cellular burden. More than three-quarters of transmembrane containing proteins, such as those belonging to the MFS class, are functionally unclassified, despite these proteins accounting for more than 20\\u0026ndash;30% of the total number of any one proteome [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. Even in characterised model organisms, such as \\u003cem\\u003eEscherichia coli\\u003c/em\\u003e, 53% of membrane transporters lack characterisation [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. This is due to two major factors, firstly, the functional flexibility/redundancy of transporters makes sequence-function relationships challenging to ascertain [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. As such, protein sequence homology-based approaches to for the discovery of transporters alone is ineffective [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. Indeed, MFS transporters are known to display particularly poor sequence conservation, with identity typically ranging 12\\u0026ndash;18%, between members despite the conserved MFS fold; sequence [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e]. Secondly, transport proteins within the MFS are inherently unstable outside of their native phospholipid environment and thus require specialist approaches for expression, purification and characterisation [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Direct vectorial measurement of transport requires labelled substrates, which can become prohibitively expensive for mid to high-throughput screens. For MFS\\u0026rsquo;s that rely on H\\u003csup\\u003e+\\u003c/sup\\u003e symport, cheaper assays that utilise pH sensitive dyes are available, however these dyes can lack sensitivity for transporters with low turnover [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eMFS transporters of the aromatic H\\u003csup\\u003e+\\u003c/sup\\u003e symporter class have been demonstrated to be critical for the uptake lignocellulose-derived substrates, in particular for lignin an aromatic rich component with great potential as a feedstock for microbial valorisation [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. Lignin is highly enriched in hydroxycinnamoyl aromatics such as \\u003cem\\u003ep-\\u003c/em\\u003ecoumaroyl (H), coniferyl (G) and sinapyl (S) alcohols with acid derivates such as coumaric, ferulic, and synapic acid respectively liberated following treatment of the lignin [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. Saprophytic strains of bacteria such as \\u003cem\\u003ePseudomonas putida\\u003c/em\\u003e KT2440, \\u003cem\\u003eRhodococcus jostii\\u003c/em\\u003e RHA1, \\u003cem\\u003eSphingobium\\u003c/em\\u003e sp. SYK-6 have evolved pathways for the uptake and subsequent utilisation of these aromatics for growth [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. Of these pathways, coumaric and ferulic acid ultimately converge on protocatechuic acid (PCA) as a central node in aromatic catabolism before being directed to the TCA cycle [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. Disruption of these aromatic catabolic pathways in hosts, can lead to the accumulation of value-added intermediates, such as vanillin and 4-hydroxybenzoic acid, protocatechuic acid (PCA) and β-ketoadipate [\\u003cspan additionalcitationids=\\\"CR30 CR31\\\" citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. Another aromatic-rich polymer, of anthropogenic origin, is polyethylene terephthalate (PET) plastic, which can microbially degraded and has been proposed as potential feedstock for microbial growth and bioproduction [\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. PET represents 12% (by weight) of total global solid waste [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e], and is composed of a repeating unit of terephthalic acid (TPA) esterified to an ethylene glycol (EG), and finds its primary use in the manufacture of single use disposable packaging such as in bottles and food containers [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. Recently, several bacteria including \\u003cem\\u003eRhodococcus jostii\\u003c/em\\u003e RHA1, \\u003cem\\u003eIdeonella sakiensis\\u003c/em\\u003e, and \\u003cem\\u003ePseudomonas umsongensis\\u003c/em\\u003e amongst others, have been reported to possess the ability to import and utilise TPA, for growth, following import via an H\\u003csup\\u003e+\\u003c/sup\\u003e symporter MFS transporter opening up the possibility of applying this waste stream as a substrate for biotechnological processes [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe MFS-dependent uptake of PCA and TPA has been reported to occur via the action of two MFS transporters, PcaK and TphK (also known as TpaK in other literature, but referred to as TphK here from now onwards), respectively [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. Strains deficient in PcaK universally exhibit reduced growth on PCA, while those deficient in TphK exhibit no growth on TPA [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. Characterisation of PcaK using proteoliposomes has indicated this transporter has a substrate preference for PCA and 4-hydroxybenzoic acid (4HBA) [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e], while there are no known reports for purification or \\u003cem\\u003ein vivo\\u003c/em\\u003e characterisation of TphKs in the literature that we are aware of. Both transporters have demonstrated value in microbial strain engineering applications, with overexpression of the native \\u003cem\\u003epcaK\\u003c/em\\u003e from \\u003cem\\u003eSphingobium\\u003c/em\\u003e sp. SYK-6 enabling 30% higher conversion rate of PCA to the plastic precursor, 2-pyrone-4,6-dicarboxylate [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. As well, heterologous expression of a \\u003cem\\u003etphK\\u003c/em\\u003e from \\u003cem\\u003ePseudomonas mandelii\\u003c/em\\u003e in \\u003cem\\u003eP. putida\\u003c/em\\u003e permitting \\u003cem\\u003ede novo\\u003c/em\\u003e production of the plastic polymer, polyhydroxyalkanoate (PHA), from a TPA and ethylene glycol co-feed has similarly been used in the production of β-ketoadipic acid [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. Approaches such as these highlight the value of considering cellular transportation during strain engineering workflows. Furthermore, due to MFS proteins being a single polypeptide unit they do not require the stoichiometric balancing of other transporter subunits to correctly function. The structural uniformity of MFS proteins therefore lends itself well to engineering efforts, as adversely effecting other domains does not need to be considered. Collectively, this indicates that MFS transporters are ideal targets for use in heterologous whole cell factory hosts, and are amenable to protein engineering approaches [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eFor the technical challenge set out above, screening strategies that utilise facile, widely implementable synthetic biology techniques are an attractive alternative to mediate the high throughput identification and substrate specificity determination of transport systems. Small molecule responsive genetically encoded biosensors, comprised of allosteric transcription factors and riboswitches, can be coupled to optically detectable proxies (e.g. fluorescence) or cell survival in order to elucidate phenotypic responses. The amenability of such biosensor-based assays to high throughput screening has proven effective and highly selective for identifying optimal phenotypes in enzyme mutant libraries, and for the enrichment of strains with improved metabolic efficiency toward a desired product [\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e]. The application of biosensors towards the characterisation of transporters is relatively new compared to older methods that rely on large genomic disruption libraries or heterologous expression [\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e]. Using a CRISPR based method of genomic disruption a knockout library of transporters was developed in \\u003cem\\u003eSaccharomyces cerevisiae\\u003c/em\\u003e (\\u003cem\\u003eS. cerevisiae\\u003c/em\\u003e) totalling 361 transporter deletions [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. Through integration of the catabolic cascade to convert glucose to \\u003cem\\u003ecis,cis-\\u003c/em\\u003emuconic acid (cc-MA) and a previously developed cc-MA biosensor active in \\u003cem\\u003eS. cerevisiae\\u003c/em\\u003e, screening of the deletion library was assessed via fluorescence activated cell sorting, identifying \\u003cem\\u003etpo2\\u003c/em\\u003e as responsible for the uptake of cc-MA and PCA [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. Further, a thiamine pyrophosphate responsive riboswitch was used in conjunction with metagenomic screening to identify several members of a new class of thiamine transporter, PnuT. The riboswitch was then replaced with one responsive to xanthine alkaloids to mine for xanthine importers, demonstrating the flexibility of the biosensor based approach [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eIn this study we demonstrate the application of genetically encoded biosensors for the identification and characterisation of aromatic acid H\\u003csup\\u003e+\\u003c/sup\\u003e symporter MFS transporters with specificity towards two molecules of biotechnological significance, protocatechuic acid (PCA) and terephthalic acid (TPA). Syntenic genome context analysis was initially performed, using catabolic genes/operons as the search query, to identify genomically associated novel putative PCA and TPA transporters (encoding PcaK and TphK, respectively). Transporter activity was verified using either a PCA or TPA responsive transcriptional biosensor coupled to GFP reporter output. Transporter substrate scope was explored via ligand panel screening, and the generation of chimeric transporters which were constructed and assessed to better understand structure activity relationships of the two types of MFS and ability to enable non-cognate substrate transport functions.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003ePhylogenetic analysis and homolog identification\\u003c/h2\\u003e \\u003cp\\u003ePreliminary searches for TphK and homologues were performed via Position-Specific Iterated BLAST (PSI-Blast) using the Blastp suite hosted on the National Center for Biotechnology Information (NCBI) server with the Ref Seq database using the \\u003cem\\u003eRhodococcus Jostii\\u003c/em\\u003e RHA1 TphK (Uniprot ID: Q0RWE8_RHOJR, (annotated as TpaK)) protein as a query sequence. Sequences resulting from this search were extracted and visualised via Jalview [\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e] and multiple sequence alignment was performed utilising MUSCLE. IQtree was used to create an initial phylogenetic tree which was later visualised using iTOL. To query the entire NCBI database, the Cblaster python package [\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e] was used in remote mode with the \\u003cem\\u003eRhodococcus jostii\\u003c/em\\u003e (NC_008270, Region: 190337\\u0026ndash;196425) TPA catabolic operon. Clusters were filtered by the presence of an MFS gene being present in the operon followed by the extraction of the MFS protein sequences. The Cdhit package [\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e] was used to remove redundant and duplicate sequences with a threshold of 0.95 (95%), followed by alignment and visualisation as stated above. PcaK searches were split according to the type of ring cleavage mechanism utilised in PCA catabolism. For the 2,3-ring cleavage pathway, the \\u003cem\\u003epra\\u003c/em\\u003e operon from \\u003cem\\u003ePaenibacillus sp. JJ1B\\u003c/em\\u003e (AB505864) was utilised for cBlaster searching. For the 4,5 pathway the \\u003cem\\u003epmdEFDABC\\u003c/em\\u003e (AB462808) operon was utilised for cBlaster searching. For the 3,4 pathway no complete operon could be sourced, as such three exemplar MFS PcaK sequences were sourced from Uniprot for which significant experimental evidence existed: \\u003cem\\u003ePseudomonas aeruginosa\\u003c/em\\u003e (Q9I6Q3), \\u003cem\\u003eAcinetobacter baylyi\\u003c/em\\u003e (Q43975) and \\u003cem\\u003ePseudomonas putida\\u003c/em\\u003e (Q51955). After visualisation via iTOL, representative sequences based on distance from root were selected from around the tree to cover a taxonomic range of putative transporters to screen.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eGeneral Microbiology\\u003c/h3\\u003e\\n\\u003cp\\u003e \\u003cem\\u003eEscherichia coli\\u003c/em\\u003e and \\u003cem\\u003ePseudomonas putida\\u003c/em\\u003e were grown on standard LB miller broth and agar (Formedium #LMM20L, #LMM0204) at 37\\u0026deg;C and 30\\u0026deg;C with 180RPM of shaking. When appropriate, antibiotics were added to an appropriate inhibitory concentration (100\\u0026micro;g/mL for \\u003cem\\u003eE. coli\\u003c/em\\u003e and 500\\u0026micro;g/mL for \\u003cem\\u003eP. putida\\u003c/em\\u003e)\\u003c/p\\u003e\\n\\u003ch3\\u003eStrain Construction\\u003c/h3\\u003e\\n\\u003cp\\u003e \\u003cem\\u003eEscherichia coli\\u003c/em\\u003e DH5⍺ was used for DNA cloning and assembly of all constructs. \\u003cem\\u003ePseudomonas putida\\u003c/em\\u003e KT2440 was used in the characterisation of all PcaKs and TphKs. \\u003cem\\u003eP. putida\\u003c/em\\u003e KT2440 genomic knock-outs of \\u003cem\\u003epcaK\\u003c/em\\u003e and \\u003cem\\u003efcs\\u003c/em\\u003e were constructed using a sucrose counter selection method as described previously [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e]. Briefly, electrocompetent cells were transformed with 1 \\u0026micro;g of the relevant pk18mobsacB plasmid possessing upstream and downstream homologous regions flanking the \\u003cem\\u003epcaK\\u003c/em\\u003e gene, plated onto LB agar supplemented with 20 \\u0026micro;g/mL of kanamycin and incubated at 30\\u0026deg;C. Individual colonies from the resulting plate were streaked onto YT agar supplemented with 25% sucrose (10 g/L yeast extract, 20 g/L tryptone, 250 g/L sucrose, 18 g/L agar) for counter selection. Colonies were screened with genomic primers to identify successful deletion of the \\u003cem\\u003epcaK\\u003c/em\\u003e or \\u003cem\\u003efcs\\u003c/em\\u003e gene. All chemicals used in substrate specificity screening can be found in \\u003cb\\u003eTable S4\\u0026amp;5\\u003c/b\\u003e, all chemicals were prepared in sterile water or DMSO as appropriate.\\u003c/p\\u003e\\n\\u003ch3\\u003ePlasmid construction\\u003c/h3\\u003e\\n\\u003cp\\u003eAll plasmids and primers used in this study can be found in \\u003cb\\u003eTable \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e-2\\u003c/b\\u003e, relevant genes encoding transporters including chimeric designs can be found in \\u003cb\\u003eTable S3.\\u003c/b\\u003e The synthesis of all DNA oligonucleotide primers and gene fragments was performed by Integrated DNA Technologies (IDT). Amplification of plasmids or DNA fragments was performed using Q5 High fidelity polymerase (NEB, #M0491S). Assembly and ligation of DNA fragments for plasmid construction was performed using NEBuilder HiFi DNA Assembly Master Mix (NEB, #E2621S). Following assembly bacterial transformation was performed using chemically competent \\u003cem\\u003eE. coli\\u003c/em\\u003e DH5⍺ cells, the resulting colonies were screened by colony PCR using Phire II Green polymerase master mix (Thermo Fisher, #F126S). Plasmid isolation was performed for positive colonies, and were used for assembly validation, by Sanger sequencing (Source Bioscience, United Kingdom).\\u003c/p\\u003e\\n\\u003ch3\\u003eBiosensor based screening of MFS transporters\\u003c/h3\\u003e\\n\\u003cp\\u003eOvernight cultures of \\u003cem\\u003eP. putida\\u003c/em\\u003e KT2440 or \\u003cem\\u003eP. putida\\u003c/em\\u003e Δ\\u003cem\\u003epcaK\\u003c/em\\u003e harbouring a relevant plasmid were sub-cultured to an OD\\u003csub\\u003e600\\u003c/sub\\u003e of 0.6 in 10 mL of LB media supplemented with 500 \\u0026micro;g/ml carbenicillin before being aliquoted into 96 deep-well plates (DWP) prefilled with 50 \\u0026micro;L of inducer (TPA or PCA respectively) to a final volume of 500 \\u0026micro;L. The DWP were then transferred to a plate shaker incubator at 30\\u0026deg;C or 37\\u0026deg;C at 1000 rpm, 75% humidity. For PCA uptake assays, DWP cultures were incubated for 3 hours. For TPA uptake assays, DWP cultures were incubated for 16 hours. To measure OD\\u003csub\\u003e600\\u003c/sub\\u003e and fluorescence, culture pellets were washed and resuspended in 500 \\u0026micro;L in PBS before being transferred to 96 well clear bottom microplates (Greiner). OD was measured at 600 nm, GFP was measured with λEx/λEm of 488/520nm using a ClarioStar microplate reader (BMG). Fluorescence was later normalised against the measured OD\\u003csub\\u003e600\\u003c/sub\\u003e for each well. Initial validation of transporter activity was performed via titration of the PcaK and TphK constructs using 0-1mM of TPA and 0-5mM of PCA as inducer plotting the dose response curve of normalised fluorescence with a variable slope hill function. PcaK and TphK constructs identified as functional in the primary screening assays were taken forwards for substrate specificity screening using concentrations of inducer that had been shown to elicit maximum response from the biosensor with either TPA (1mM) or PCA (5mM). All biosensor experimental data were processed as means of three biological replicates.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStructure and Helix Modelling\\u003c/h2\\u003e \\u003cp\\u003eCC-TOP [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e] was used to generate an overlapping map of helical topology using protein sequences of functionally verified TphKs and PcaKs from which a transmembrane helical consensus was determined. This consensus alignment was imported into Jalview and the Alphafold [\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e] model for PcaK (Alphafold: Q51955) aligned to confirm assignment of the secondary structural element regions.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eChimeric transporter engineering\\u003c/h3\\u003e\\n\\u003cp\\u003eUsing the topological alignments of the helical regions of the \\u003cem\\u003eP. putida\\u003c/em\\u003e PcaK and \\u003cem\\u003eR. pyridinivorans\\u003c/em\\u003e as a guide, gblocks encoding PcaK and TphK with the helical regions 1, 4, 7, and 10 were designed \\u003cem\\u003ein silico\\u003c/em\\u003e and ordered via IDT. These were subsequently assembled into PcaV and TB4 biosensor vector backbones respectively via isothermal assembly. Individual helical substitutions were performed via 2 fragment isothermal assembly using primers designed to amplify the wildtype TphK or PcaK MFS in its cognate biosensor backbone extruding the target helical region. A second set of primers with featuring homologous overhangs to the opposing transporter were then used to amplify the specific helical region to be substituted, in order to generate a chimeric MFS with this process repeated for helices 1,4,7 and 10. Following isothermal assembly and sequencing, the chimeric MFS genes were then reamplified and cloned into the opposing biosensor backbone generating the full set of constructs for testing. Predicted structures of the chimeric transporters were generated using alphafold 3 and annotated in ChimeraX [\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e]. Relative fold changes were calculated in two steps after collection of RFU/OD\\u003csub\\u003e600\\u003c/sub\\u003e data beginning with normalisation via the division of the RFU/OD\\u003csub\\u003e600\\u003c/sub\\u003e values for each ligand by the uninduced RFU/OD\\u003csub\\u003e600\\u003c/sub\\u003e to generate a normalised fold change per ligand for each construct. Relative fold change was then calculated on a per ligand basis by the division of each mutant fold change (FC\\u003csub\\u003emut\\u003c/sub\\u003e) by the fold change of the negative control (FC\\u003csub\\u003eNoMFS\\u003c/sub\\u003e). These values were used for the plotting of heatmap data. For detailed statistics of significant effects please refer to \\u003cb\\u003eAdditional File. 1\\u003c/b\\u003e)\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eBioinformatic mining of putative TphK\\u0026rsquo;s\\u003c/h2\\u003e \\u003cp\\u003eWe initially sought to obtain a diverse pool of putative candidate transporters for screening to capture the full breadth of structure activity relationships that may have evolved within specific taxonomic groupings. Inferring functionality of MFS transporters is complicated by the generally low sequence identity between family members, creating the possibility of dataset contamination with transporters of divergent function. By contrast, neighbouring genes within MFS-encoding operons can display strong sequence homology [\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e]. \\u003cem\\u003etphK\\u003c/em\\u003e and \\u003cem\\u003epcaK\\u003c/em\\u003e are both known to cluster into operons containing genes related to the catabolism of TPA and PCA respectively. We therefore employed a \\u0026ldquo;guilty by association\\u0026rdquo; methodology to enhance the fidelity of our homolog search using the genetic context (presence, organisation, and proximity) of TPA/PCA catabolic genes as an indicator of potential transport activity.\\u003c/p\\u003e \\u003cp\\u003eTo achieve this, we queried the NCBI genomic database employing the cblaster multigene BLAST tool using the sequence of the entire TPA degradative operon from \\u003cem\\u003eRhodococcus jostii\\u003c/em\\u003e (\\u003cem\\u003etphRKA\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sub\\u003e\\u003cem\\u003eA\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e3\\u003c/em\\u003e\\u003c/sub\\u003e\\u003cem\\u003eBA\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e1\\u003c/em\\u003e\\u003c/sub\\u003e) as the query [\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e]. The resulting phylogenetic tree displayed only 44 non-redundant leaves for MFS homolog co-located with the TPA catabolic operon (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA). In contrast, a direct blastP homology search using the \\u003cem\\u003eR. jostii\\u003c/em\\u003e TphK as the query resulted in a tree consisting of 530 leaves with some species that were not revealed in syntenic analysis (\\u003cb\\u003eSupp\\u003c/b\\u003e Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA). Manual inspection of the results obtained from the direct BLAST search approach indicated that many of the MFS hits were not colocalised to TPA catabolic genes. For example, the MFS belonging to the genus \\u003cem\\u003eJanthinobacterium\\u003c/em\\u003e, occurred 42 times in the direct blastP search yet demonstrated a genetic context indicating no relation to TPA catabolism (\\u003cb\\u003eSupp\\u003c/b\\u003e Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eB). Furthermore, no \\u003cem\\u003eJanthinobacterium\\u003c/em\\u003e hits were present in the tree generated using cblaster, indicating that these MFS sequences did not carry any resemblance of TPA catabolic operon and were therefore unlikely to possess the desired functional activity.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe tree generated from syntenic analysis of the \\u003cem\\u003eR. jostii\\u003c/em\\u003e TPA degradation operon was rooted with respect to the TphK transporter protein, with the TphKs generated from cblaster plotted using their relative sequence identity to the query (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA). TPA catabolic operons typically differ based on the transporter type, with \\u003cem\\u003eComamonas\\u003c/em\\u003e sp. Strain E6 encoding a tripartite tricarboxylate transporter (TphC) and \\u003cem\\u003eRhodococcus jostii\\u003c/em\\u003e encoding an MFS (TphK) [\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e]. To our knowledge, this is the first report of \\u003cem\\u003etphK\\u003c/em\\u003e containing TPA catabolic operons in the alpha and beta proteobacteria classes, indicating the spread of TPA catabolism through a much broader range of bacteria than previously thought. Actinomycetia is the predominant class of bacteria (66%) encoding TphK homologues, with tight clustering to the root of the tree with lengths of 0.1\\u0026ndash;0.6 indicating high similarity to the query sequence. Some Actinomycetia sequences however clustered further from the root at branch lengths of \\u0026ge;\\u0026thinsp;1.6, indicating greater sequence diversity. The remaining classes consisted of Alpha and Gammaproteobacteria (both 14%) as the next most abundant classes followed by betaproteobacteria (7%). Interestingly, the proteobacteria were noticeably less diverse at the genus level in comparison with Actinomycetia, with Gammaproteobacteria being represented solely by \\u003cem\\u003ePseudomonads\\u003c/em\\u003e, Alphaproteobacteria by \\u003cem\\u003eBradyrhizobium\\u003c/em\\u003e and Betaproteobacteria by \\u003cem\\u003eNoviherbaspirillum\\u003c/em\\u003e and \\u003cem\\u003eCabellronia\\u003c/em\\u003e. We observed that the TphK sequences fell within 9 distinct bacterial genera with the bulk of representation within the tree originating from the \\u003cem\\u003ePseudomonas\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;6), \\u003cem\\u003ePseudonocardia\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;8), \\u003cem\\u003eBradyrhizobium\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;5), \\u003cem\\u003eStreptomyces\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;6), \\u003cem\\u003eAmycolatopsis\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;7) and \\u003cem\\u003eRhodococcus\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;3) genera. Notably the majority of species represented in the phylogenetic tree are saprophytic soil dwellers, with some originating from genera that have been previously validated as possessing the genes required for TPA catabolism, such as \\u003cem\\u003eR. opacus\\u003c/em\\u003e and \\u003cem\\u003eP. umsongensis\\u003c/em\\u003e but also encompass other previously unidentified soil dwellers like \\u003cem\\u003eBradyrhizobium\\u003c/em\\u003e and \\u003cem\\u003eSphingobium\\u003c/em\\u003e [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]. The limited spread of \\u003cem\\u003etph\\u003c/em\\u003e operon may be indicative of the recent evolution and therefore limited time to transfer the TPA catabolic operon through microbial communities. Putative TphK\\u0026rsquo;s carried forward for evaluation were selected based on distance from the root of the tree and genera of origin in order to maximise sequence and context diversity. Selected TphK candidates are indicated by stars in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA and are listed in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eC, they included those from: \\u003cem\\u003eR. jostii\\u003c/em\\u003e, \\u003cem\\u003eRhodococcus opacus\\u003c/em\\u003e, \\u003cem\\u003eRhodococcus pyridinovorans\\u003c/em\\u003e, \\u003cem\\u003ePseudomonas umsongensis\\u003c/em\\u003e, \\u003cem\\u003ePseudomonas mandelii\\u003c/em\\u003e, \\u003cem\\u003ePseudonocardia bannensis\\u003c/em\\u003e, \\u003cem\\u003eBradyrhizobium pachyrhizi\\u003c/em\\u003e, \\u003cem\\u003eSphingobium napthae\\u003c/em\\u003e, \\u003cem\\u003eAmycolatopsis acidiphilia\\u003c/em\\u003e, \\u003cem\\u003eSaccharopolyspora hordei\\u003c/em\\u003e, and \\u003cem\\u003eStreptomyces\\u003c/em\\u003e sp. HGB0020.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eBioinformatic mining of putative PcaKs\\u003c/h2\\u003e \\u003cp\\u003eFollowing generation of a TphK phylogenetic tree we repeated the approach with the PCA catabolic operons. PCA catabolism is more widespread among bacteria than TPA catabolism, as it is a constituent of lignin degradation and a central node in diverse aromatic degradation pathways [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. This is in contrast to TPA, which is of anthropogenic origin with only recent environmental exposure (1960-present) [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e]. Indeed, studies have highlighted at least three distinct bacterial pathways through which PCA is subsequently assimilated and incorporated into central metabolism [\\u003cspan additionalcitationids=\\\"CR60\\\" citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e]. These pathways can be categorised by their PCA cleavage mechanism, which occurs either in the \\u003cem\\u003e4,5\\u003c/em\\u003e (\\u003cem\\u003emeta\\u003c/em\\u003e), \\u003cem\\u003e3,4\\u003c/em\\u003e (\\u003cem\\u003eortho\\u003c/em\\u003e) or \\u003cem\\u003e2,3\\u003c/em\\u003e (\\u003cem\\u003epara\\u003c/em\\u003e) position. While these pathways all serve to funnel PCA to central metabolism, they achieve this through distinct enzymatic steps and intermediate metabolites (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA). Given this evolutionary divergence, we sought to explore the potential functional differences of PcaKs encoded in these three different pathways in our workflow. To this end, catabolic operons from strains encoding \\u003cem\\u003e2,3\\u003c/em\\u003e and \\u003cem\\u003e4,5\\u003c/em\\u003e extradiol pathways were selected from \\u003cem\\u003eComamonas\\u003c/em\\u003e sp. E6 (blue), and \\u003cem\\u003ePaenibacillus\\u003c/em\\u003e sp. JJ1B (green) respectively as query sequences for cblaster (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA). The \\u003cem\\u003e3,4\\u003c/em\\u003e intradiol pathway, unlike the extradiol pathways, however, appears to be discontinuous, with the degree of fragmentation varying between the organisms that were investigated. For instance, in \\u003cem\\u003eP. putida\\u003c/em\\u003e, the operon is split into three distinct loci encoding upper, middle and lower parts of the pathway separately. Conversely \\u003cem\\u003eAcinetobacter baylyi\\u003c/em\\u003e shows no fragmentation, instead encoding its \\u003cem\\u003e3,4\\u003c/em\\u003e degradative operon in a single continuous loci, however the syntenic arrangement differs to that of \\u003cem\\u003eP. putida\\u003c/em\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA). As our operon synteny approach was incompatible with the degree of heterogeneity present in the \\u003cem\\u003e3,4\\u003c/em\\u003e pathway, we instead incorporated PcaKs from experimentally verified strains known to possess the intradiol pathway into the phylogenetic analysis [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e]. We elected to root the tree with respect the \\u003cem\\u003eP. putida\\u003c/em\\u003e PcaK, as it had been previously experimentally verified and originated in the genome of the host strain \\u003cem\\u003eP. putida\\u003c/em\\u003e KT2440 in which we intended to perform subsequent functional validation [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eIn total 88 PcaK sequences were retrieved from the three pathways 59, 3 and 26 from the \\u003cem\\u003e4,5, 3,4\\u003c/em\\u003e and \\u003cem\\u003e2,3\\u003c/em\\u003e pathways respectively (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB). Bioinformatic mining of PcaK\\u0026rsquo;s belonging to the \\u003cem\\u003e4,5\\u003c/em\\u003e-pathway revealed that this pathway consists primarily of Betaproteobacteria (N\\u0026thinsp;=\\u0026thinsp;45/85), with the largest subsection attributable to the \\u003cem\\u003eComamonas\\u003c/em\\u003e genus. This was followed by \\u003cem\\u003eAcidovorax\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;4) in addition to a number of single genera, representing the wide spread of the Betaproteobacteria class. A smaller number of Alphaproteobacteria were also identified, consisting of \\u003cem\\u003eMagnetospirillum\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;3) and \\u003cem\\u003eBradyrhizobium\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;3), as well as some single instances of Gammaproteobacteria (N\\u0026thinsp;=\\u0026thinsp;5). Despite the variation in class and genus, there was strong clustering of the \\u003cem\\u003e4,5\\u003c/em\\u003e pathway as a single clade on the tree with a 2.8 average distance from the root, indicating high sequence homology between members of the \\u003cem\\u003e4,5\\u003c/em\\u003e pathway. The exception to this is the PcaK from \\u003cem\\u003eP. duriflava\\u003c/em\\u003e, which appeared to cluster with the \\u003cem\\u003e3,4\\u003c/em\\u003e pathways.\\u003c/p\\u003e \\u003cp\\u003eThe \\u003cem\\u003e2,3\\u003c/em\\u003e pathway on the other hand was substantially smaller (N\\u0026thinsp;=\\u0026thinsp;21) than the \\u003cem\\u003e4,5\\u003c/em\\u003e dataset and was restricted to Bacilli. Furthermore, sequence variation was greater within this dataset with branch lengths from the root in the range of 4.2\\u0026ndash;11.9, indicating greater evolutionary diversity. In general, those belonging to the \\u003cem\\u003eBacillus\\u003c/em\\u003e genus demonstrated the closest sequence homology to the root, whilst other genera such as \\u003cem\\u003ePaenibacillus, Alicyclobacillus\\u003c/em\\u003e and \\u003cem\\u003eMetabacillus\\u003c/em\\u003e displayed branch lengths\\u0026thinsp;~\\u0026thinsp;9 indicating significant sequence diversification from the root despite being closely related to the bacillus genera. Of the genera, \\u003cem\\u003eBacillus\\u003c/em\\u003e were the most abundant (N\\u0026thinsp;=\\u0026thinsp;5) followed by \\u003cem\\u003eAlkalihalobacillus\\u003c/em\\u003e and \\u003cem\\u003eMetabacillus\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;3 each), and finally \\u003cem\\u003ePaenibacillus\\u003c/em\\u003e and \\u003cem\\u003eAlicyclobacillus\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;2). Similar to the \\u003cem\\u003e4,5\\u003c/em\\u003e pathway, all members of the \\u003cem\\u003e2,3\\u003c/em\\u003e pathway appear to share a common ancestor and cluster together, indicating greater sequence similarity to one another than to other pathways, despite the high sequence variation.\\u003c/p\\u003e \\u003cp\\u003eFinally of the PcaK transporters selected to represent the \\u003cem\\u003e3,4\\u003c/em\\u003e pathway, those from \\u003cem\\u003eP. putida\\u003c/em\\u003e PRS2000 and \\u003cem\\u003eP. aeroginosa\\u003c/em\\u003e clustered very closely to the root with branch lengths of 0.07 and 0.18, respectively, followed by \\u003cem\\u003eA. baylyi\\u003c/em\\u003e with 0.6. Interestingly, despite belonging to the \\u003cem\\u003ePseudomonas\\u003c/em\\u003e genus, \\u003cem\\u003eP. duriflava\\u003c/em\\u003e possessed a branch length relative to the root of 2.1, indicating significantly more sequence dissimilarity and placing it closer the \\u003cem\\u003e4,5\\u003c/em\\u003e pathway. In total ten transporters were selected from the \\u003cem\\u003e3,4\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;3) and \\u003cem\\u003e2,3\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;3) and \\u003cem\\u003e4,5\\u003c/em\\u003e (N\\u0026thinsp;=\\u0026thinsp;4) pathways based on distinct genera to ensure maximum diversity for subsequent transport and functional analysis in order to assess the potential functional differences of putative PcaKs. These included those from: \\u003cem\\u003eP. putida\\u003c/em\\u003e, \\u003cem\\u003eP. aeruginosa\\u003c/em\\u003e, \\u003cem\\u003eA. baylyi\\u003c/em\\u003e, \\u003cem\\u003eBacillus massiliglacei\\u003c/em\\u003e, \\u003cem\\u003ePanaebacillus validis\\u003c/em\\u003e, \\u003cem\\u003eAlicyclobacillus acidotolerans\\u003c/em\\u003e, \\u003cem\\u003eNeiserria animalis\\u003c/em\\u003e, \\u003cem\\u003eBradyrhizogium\\u003c/em\\u003e sp. STM3843, \\u003cem\\u003eComamonas testeroni\\u003c/em\\u003e, and \\u003cem\\u003eAcidovorax antarcticus\\u003c/em\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eC).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eScreening of putative MFSs via responsive biosensors\\u003c/h2\\u003e \\u003cp\\u003eFollowing the selection of putative TphK and PcaK transporters from the synteny-enriched phylogenetic analysis we next sought to validate their transport activity toward TPA and PCA, respectively. To accomplish this, the genes encoding the selected putative TphK and PcaK transporters were cloned into a plasmid containing either a TPA (TphR) or PCA (PcaV) responsive allosteric transcription factors along with the corresponding responsive promoters controlling the expression of \\u003cem\\u003esfGFP\\u003c/em\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA). The TphR biosensor was based on the IclR-type transcriptional activator from \\u003cem\\u003eZhizhongheella caldifontis\\u003c/em\\u003e [\\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e], while the PcaV biosensor was based on the MarR family transcriptional repressor from \\u003cem\\u003eStreptomyces coelicolor\\u003c/em\\u003e [\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eUnder neutral pH conditions, both PCA and TPA will be deprotonated (singly and doubly), which will impede their cellular uptake via membrane permeation in the absence of a transporter [\\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e]. However, natively, \\u003cem\\u003eP. putida\\u003c/em\\u003e is capable of assimilating PCA via an endogenous \\u003cem\\u003epcaK\\u003c/em\\u003e. To mitigate any endogenous transport, putative PcaKs were screened in a Δ\\u003cem\\u003epcaK\\u003c/em\\u003e genetic background, while putative TphKs were screened in the wild type \\u003cem\\u003eP. putida\\u003c/em\\u003e genetic background. As such, any increase in GFP fluorescence observed by \\u003cem\\u003eP. putida\\u003c/em\\u003e harbouring transporter-biosensor constructs, either TphK-TphR or PcaK-PcaV following exposure to TPA or PCA, can be attributed to the activity of the putative transporter. To further validate this, transporter-less versions of both biosensing constructs (TphK\\u003csub\\u003e\\u0026minus;\\u0026thinsp;ve\\u003c/sub\\u003e and PcaK\\u003csub\\u003e\\u0026minus;\\u0026thinsp;ve\\u003c/sub\\u003e) were developed to account for any passive transport through the membrane.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe library of 11 putative TPA transporter-biosensor (TphK-TphR) constructs was evaluated for the ability to import TPA against a ligand concentration gradient (ranging from 0.005\\u0026ndash;1 mM), and the resulting dose response curve were compared (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB). Of these, the transporters from \\u003cem\\u003eStreptomyces.\\u003c/em\\u003e Sp. HGB0020, \\u003cem\\u003eA. acidiphilia\\u003c/em\\u003e and \\u003cem\\u003eP. bannensis\\u003c/em\\u003e were shown to be non-functional against TPA (data not shown) whilst the remaining transporters demonstrated a strong response relative to the TphK\\u003csub\\u003e\\u0026minus;\\u0026thinsp;ve\\u003c/sub\\u003e control. TphKs from \\u003cem\\u003eR. pyridinivorans\\u003c/em\\u003e (TphK\\u003csub\\u003eR.Pyr\\u003c/sub\\u003e), \\u003cem\\u003eR. opacus\\u003c/em\\u003e (TphK\\u003csub\\u003eR.Op\\u003c/sub\\u003e), \\u003cem\\u003eR. jostii\\u003c/em\\u003e (TphK\\u003csub\\u003eR.Jos\\u003c/sub\\u003e), \\u003cem\\u003eP. umsongensis\\u003c/em\\u003e (TphK\\u003csub\\u003eP.Um\\u003c/sub\\u003e) and \\u003cem\\u003eP. mandelii\\u003c/em\\u003e (TphK\\u003csub\\u003eP.Man\\u003c/sub\\u003e) had been previously validated as TPA transporters [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e], while those from \\u003cem\\u003eB. pachyrhizi\\u003c/em\\u003e (TphK\\u003csub\\u003eB.Pac\\u003c/sub\\u003e), \\u003cem\\u003eS. napthae\\u003c/em\\u003e (TphK\\u003csub\\u003eS.nap\\u003c/sub\\u003e) and \\u003cem\\u003eS. hordei\\u003c/em\\u003e (TphK\\u003csub\\u003eS.Hor\\u003c/sub\\u003e) were newly identified in this study (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB).\\u003c/p\\u003e \\u003cp\\u003eThe TphKs evaluated demonstrate similar operation sensing ranges (0.005\\u0026ndash;0.25mM), but with considerable variation in activation (max RFU/OD) and sensitivity (EC\\u003csub\\u003e50\\u003c/sub\\u003e) to TPA. TphK\\u003csub\\u003eR.Jos\\u003c/sub\\u003e possessed the greatest sensitivity (EC\\u003csub\\u003e50\\u003c/sub\\u003e 4.4 \\u0026micro;M), TphK\\u003csub\\u003eP.man\\u003c/sub\\u003e possessed the greatest output dynamic range (2.7-fold) likely due to its tight basal activation, whilst TphK\\u003csub\\u003eR.Pyr\\u003c/sub\\u003e achieved the greatest activation TphKs (103,676 RFU/OD). Surprisingly, TphK\\u003csub\\u003eR.Op\\u003c/sub\\u003e demonstrated significantly lower sensitivity toward TPA (EC\\u003csub\\u003e50\\u003c/sub\\u003e 79 \\u0026micro;M) despite high homology with the other \\u003cem\\u003eRhodococcus\\u003c/em\\u003e TphKs which display greater sensitivity to TPA. Given the high sequence homology of the \\u003cem\\u003eRhodococcus\\u003c/em\\u003e sequences in the phylogenetic tree this result was surprising and could be due to differing expression levels.\\u003c/p\\u003e \\u003cp\\u003eEvaluation of the library of putative PCA transporter-biosensor (PcaK-PcaV) constructs was performed in a \\u003cem\\u003eP. putida\\u003c/em\\u003e Δ\\u003cem\\u003epcaK\\u003c/em\\u003e strain. It was found that the Δ\\u003cem\\u003epcaK\\u003c/em\\u003e strain was still able to utilise PCA for growth, however it displayed an extended lag phase of 4 hours (compared to 2 hours for the wild-type strain), during which time no PCA was consumed in line with previous studies [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e](\\u003cb\\u003eSupp\\u003c/b\\u003e Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). As such, the PCA dose response assays were incubated for a maximum of 3 hours to avoid endogenous utilisation of PCA. PcaK-PcaV transporter-biosensors constructs were tested against an increasing concentration of PCA (ranging from 0.01-5 mM), and the resulting dose response curves were compared (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eC). Unlike with the TphK\\u003csub\\u003e\\u0026minus;\\u0026thinsp;ve\\u003c/sub\\u003e- construct, the PcaK\\u003csub\\u003e\\u0026minus;\\u0026thinsp;ve\\u003c/sub\\u003e- construct did demonstrate a small increase in biosensor activation when PCA was supplemented at concentrations above 1 mM. This could be due to the action of promiscuous transporters encoded in the host genome or passive diffusion across the membrane. PCA has an single pKa (4.2), whereas TPA possesses two pKa\\u0026rsquo;s (3.5 and 4.3), so the latter is more acidic and will be doubly negatively charged, thus less likely to diffuse cross the bacterial membrane [\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e]. Based on biosensor response, putative PcaKs appeared to cluster into 3 distinct subgroups, demonstrating weak, medium, and strong activation in response to PCA (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eC).\\u003c/p\\u003e \\u003cp\\u003eTransporters from \\u003cem\\u003eB. massiliglacei\\u003c/em\\u003e (PcaK\\u003csub\\u003eB.Mas\\u003c/sub\\u003e) and \\u003cem\\u003eP. putida (\\u003c/em\\u003ePcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e) demonstrated the greatest overall activity in terms of max signal (\\u0026gt;\\u0026thinsp;30,000 RFU/OD), and fold change at 61-fold and 47-fold, albeit with low sensitivity to PCA (EC\\u003csub\\u003e50\\u003c/sub\\u003e\\u0026thinsp;=\\u0026thinsp;1.7 mM and 2.05 mM), respectively. This in spite of the significant distance from one another in terms of sequence homology (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB). Transporters from \\u003cem\\u003eA. antarcticus\\u003c/em\\u003e\\u003c/p\\u003e \\u003cp\\u003e(PcaK\\u003csub\\u003eA.Ant\\u003c/sub\\u003e), \\u003cem\\u003eA. baylyi\\u003c/em\\u003e (PcaK\\u003csub\\u003eA.Bay\\u003c/sub\\u003e), \\u003cem\\u003eN. animalis\\u003c/em\\u003e (PcaK\\u003csub\\u003eN.An\\u003c/sub\\u003e), and \\u003cem\\u003eP. aeruginosa\\u003c/em\\u003e (PcaK\\u003csub\\u003eP.Ae\\u003c/sub\\u003e) displayed the highest sensitivity to PCA (EC\\u003csub\\u003e50\\u003c/sub\\u003e between 0.73\\u0026ndash;1.25 mM), with a moderate response to PCA (14-50-fold). Finally, transporters from \\u003cem\\u003eP. validus\\u003c/em\\u003e (PcaK\\u003csub\\u003eP.Val\\u003c/sub\\u003e), \\u003cem\\u003eBradyrhizobium\\u003c/em\\u003e sp. STM3843 (PcaK\\u003csub\\u003eB.STM\\u003c/sub\\u003e) and \\u003cem\\u003eA. acidotolerans\\u003c/em\\u003e (PcaK\\u003csub\\u003eA.Aci\\u003c/sub\\u003e) demonstrated the weakest response to PCA, with only margin activation above the negative control (PcaK\\u003csub\\u003e\\u0026minus;\\u0026thinsp;ve\\u003c/sub\\u003e), as such were assumed to be non-functional. The PcaK from \\u003cem\\u003eC. testeroni\\u003c/em\\u003e (PcaK\\u003csub\\u003eC.Tes\\u003c/sub\\u003e), surprisingly, was also inactive toward PCA (data not shown) despite the strain being reported to grow on 4-hydroxybenzoic acid (4HBA) as a sole carbon source and possessing an intact \\u003cem\\u003e4,5\\u003c/em\\u003e PCA catabolic operon [\\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSubstrate specificity of TphKs\\u003c/h2\\u003e \\u003cp\\u003eThe variable activation of the different TphK-TphR and PcaK-PcaV biosensor constructs toward their cognate effectors alludes to variability in the substrate uptake capabilities of the different transporter homologues. Given the taxonomic diversity of their bacterial backgrounds, we reasoned that whilst the active transporters may transport the cognate ligands TPA and PCA, they may also possess extended substrate specificity. As such, we next sought to explore the structure activity relationships of the identified MFS transporters utilising a library of TPA and PCA effector analogues (\\u003cb\\u003eSupp Table. 1\\u0026amp;2\\u003c/b\\u003e). To examine this, the TphKs: TphK\\u003csub\\u003eR.Jos\\u003c/sub\\u003e, TphK\\u003csub\\u003eR.Pyr\\u003c/sub\\u003e, TphK\\u003csub\\u003eR.Op\\u003c/sub\\u003e, TphK\\u003csub\\u003eP.Man\\u003c/sub\\u003e, TphK\\u003csub\\u003eP.Um\\u003c/sub\\u003e, TphK\\u003csub\\u003eS.Hor\\u003c/sub\\u003e, TphK\\u003csub\\u003eS.Nap\\u003c/sub\\u003e and TphK\\u003csub\\u003eB.Pac\\u003c/sub\\u003e were screened against a panel of 27 TPA analogues at a concentration of 1 mM comparing fold-change activation relative to the negative control (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eD; \\u003cb\\u003eSupp.\\u003c/b\\u003e Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA). Of those ligands screened, activity was observed towards compounds with substituents in the \\u003cem\\u003e2\\u003c/em\\u003e positions of the benzene ring, including a hydroxyl- (\\u003cb\\u003eT13\\u003c/b\\u003e), bromo- (\\u003cb\\u003eT15\\u003c/b\\u003e), iodo- (\\u003cb\\u003eT16\\u003c/b\\u003e) and amino- (\\u003cb\\u003eT18\\u003c/b\\u003e) at this position in addition to a TPA control (\\u003cb\\u003eT3\\u003c/b\\u003e) (FC\\u0026thinsp;\\u0026gt;\\u0026thinsp;1.5). Interestingly, we also observed activity towards biphenyl-4,4-dicarboxylic acid (\\u003cb\\u003eT20\\u003c/b\\u003e) by all TphK transporters assessed (average FC\\u0026thinsp;~\\u0026thinsp;2), a compound which is significantly longer than TPA. Analysis of supernatants of wildtype \\u003cem\\u003eP. putida\\u003c/em\\u003e and \\u003cem\\u003eP. putida\\u003c/em\\u003e encoding the MFS on the TB4 biosensor plasmid demonstrated that no depletion of 4,4-biphenyldicarboxlic acid had taken place over the course of 24 hours (\\u003cb\\u003eSupp\\u003c/b\\u003e Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e), indicating the response was generated directly from the effector and not due to conversion of 4,4-biphenyldicarboxylic acid to TPA. TphK\\u003csub\\u003eR.Jos\\u003c/sub\\u003e and TphK\\u003csub\\u003eS.Nap\\u003c/sub\\u003e displayed the greatest substrate range, permitting uptake (and sensing) of six and five TPA analogues, respectively. Consistent with our previous observations of TPA transport (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB), TphK\\u003csub\\u003eR.Op\\u003c/sub\\u003e demonstrated the lowest activity towards those ligands screened, only responding to TPA and biphenyl-4,4-dicarboxylic acid (FC\\u0026thinsp;=\\u0026thinsp;1.4 and 1.2). On average, substrate specificity for the TphK homologues can be ranked as: TPA (2.3-fold)\\u0026thinsp;\\u0026gt;\\u0026thinsp;biphenyl-4,4-dicarboxylic acid (2.0-fold), \\u0026gt; iodo-TPA (1.8-fold), \\u0026gt; hydroxy-TPA (1.6-fold)\\u0026thinsp;\\u0026gt;\\u0026thinsp;bromo-TPA (1.4-fold)\\u0026thinsp;\\u0026gt;\\u0026thinsp;amino-TPA (1.3-fold). This seems to imply that the TphK-TphR transporter-biosensors have a strict preference for dicarboxylates, as monocarboxylates triggered no response (\\u003cb\\u003eSupp.\\u003c/b\\u003e Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA). Additionally, substitution at the 2-position of the ring appeared to be somewhat tolerated, with hydroxylation and halides being preferred to amino. These observation on substrate specificity of the TphK are caveated, however, as they rely also on the substrate specificity of the TphR-based biosensor, which may not entirely overlap.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSubstrate specificity of PcaKs\\u003c/h2\\u003e \\u003cp\\u003eTo evaluate substrate specificity of the PcaKs, PcaK\\u003csub\\u003eA.Ant\\u003c/sub\\u003e, PcaK\\u003csub\\u003eA.Bay\\u003c/sub\\u003e, PcaK\\u003csub\\u003eB.Mas\\u003c/sub\\u003e, PcaK\\u003csub\\u003eN.Ani\\u003c/sub\\u003e, PcaK\\u003csub\\u003eP.Aer\\u003c/sub\\u003e and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e were screened against a panel of 28 PCA analogues at a concentration of 5 mM (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eE; \\u003cb\\u003eSupp\\u003c/b\\u003e Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB). Ten analogues including PCA (\\u003cb\\u003eP2\\u003c/b\\u003e) were found to be transported by the majority of the putative PcaKs, with these ligands sharing structural similarities to PCA, such as hydroxylation at the 3 or 4 positions and the presence of a single carboxyl group. Example of this include 3-hydroxybenzoic acid (\\u003cb\\u003eP24\\u003c/b\\u003e) and 4-hydroxybenzoic acid (\\u003cb\\u003eP25\\u003c/b\\u003e). Interestingly, whilst \\u003cb\\u003eP24\\u003c/b\\u003e appeared to elicit a greater fold induction by all PcaKs than PCA (20- vs. 16-fold average); the negative control (PcaK\\u003csub\\u003e\\u0026minus;\\u0026thinsp;ve\\u003c/sub\\u003e-PcaV) also demonstrated significant induction by 3-HBA (15-fold), indicating the potential involvement of a secondary transporter assisting uptake. Nevertheless, PcaK\\u003csub\\u003eA.Ant\\u003c/sub\\u003e, PcaK\\u003csub\\u003eB.Mas\\u003c/sub\\u003e, and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e demonstrated a significant activity relative to the negative control (19.2, 21.7 and 37.8-fold respectively) indicating these transporters improved the uptake of \\u003cb\\u003eP24\\u003c/b\\u003e. Biosensor activation in response to vanillic acid (\\u003cb\\u003eP25\\u003c/b\\u003e) was not statistically significant for all transporters when compared to negative control, with the exception of PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e (7.9 vs 26.8-fold), indicating the specific activity of the PcaK transporter from \\u003cem\\u003eP. putida\\u003c/em\\u003e for \\u003cb\\u003eP25\\u003c/b\\u003e uptake. Interestingly, PcaK\\u003csub\\u003eB.Mas\\u003c/sub\\u003e and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e appeared to demonstrate unique activity for 5 hydroxyl substitutions, with high activation observed by 3,5 dihydroxybenzoic acid (\\u003cb\\u003eP3\\u003c/b\\u003e) (30.9 and 14.8-fold, respectively) and gallic acid (\\u003cb\\u003eP28\\u003c/b\\u003e) (39.2 and 47.6-fold, respectively). Some strains of \\u003cem\\u003eP. putida\\u003c/em\\u003e, including KT2440, have been shown to possess a gallic acid catabolic operon, yet are unable to grow on gallic acid as a sole carbon source due to a frameshift mutation resulting in a truncated form of the MFS gallic acid permease, GalT, [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Our results suggest that some PcaK transporters, from other strains of \\u003cem\\u003eP. putida\\u003c/em\\u003e and \\u003cem\\u003eB. massiliglacei\\u003c/em\\u003e, appear to have the ability to uptake both gallic acid and PCA.\\u003c/p\\u003e \\u003cp\\u003eSome of the PCA analogues also induced smaller, but still significant, responses relative to the negative control, including: methyl-3,4-dihydroxybenzoic acid (\\u003cb\\u003eP15\\u003c/b\\u003e), to which PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e responded; 3,4 dihydroxybenzamide (\\u003cb\\u003eP16\\u003c/b\\u003e), to which PcaK\\u003csub\\u003eA.Ant\\u003c/sub\\u003e, PcaK\\u003csub\\u003eA.Bay\\u003c/sub\\u003e, and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e responded; and benzaldehyde (\\u003cb\\u003eP17\\u003c/b\\u003e), to which PcaK\\u003csub\\u003eA.Ant\\u003c/sub\\u003e, PcaK\\u003csub\\u003eA.Bay\\u003c/sub\\u003e, PcaK\\u003csub\\u003eB.Mas\\u003c/sub\\u003e and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e responded (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eD). These analogues have differing carbonyl groups, suggesting some flexibility at this position at the expense of drastically reduced activation. To rule out potential oxidation of the benzaldehyde to benzoic acid additional screening of the active PcaKs was performed against benzoic acid (\\u003cb\\u003eSupp\\u003c/b\\u003e Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e), however no response was detected indicating activity was strictly toward the aldehyde functional group. Finally, partial activity towards, vanillic acid (\\u003cb\\u003eP26\\u003c/b\\u003e) and coumaric acid (\\u003cb\\u003eP27\\u003c/b\\u003e) was observed, which deviates from the structure activity relationship. \\u003cb\\u003eP26\\u003c/b\\u003e and \\u003cb\\u003eP27\\u003c/b\\u003e are natively metabolised by \\u003cem\\u003eP. putida\\u003c/em\\u003e, with PCA being a pathway intermediate for both [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. We reasoned that this activity may be a result of some degradation of coumaric and vanillic acid to PCA and/or 4-hydroxybenzoic acid (\\u003cb\\u003eP25\\u003c/b\\u003e), resulting in indirect activation of the biosensor. To investigate this, a Δ\\u003cem\\u003efcs\\u003c/em\\u003e (feruloyl-CoA synthetase) knock out strain was generated to abolish coumaric acid catabolism, and subsequently transformed with the PcaK\\u003csub\\u003ep.put\\u003c/sub\\u003e-PcaV construct (\\u003cb\\u003eSupp Fig.\\u0026nbsp;6\\u003c/b\\u003e). No activation of this biosensor was observed in the Δ\\u003cem\\u003efcs\\u003c/em\\u003e knockout strain relative in the presence of coumaric acid except at high loading (5mM), indicating that biosensor activity observed in the WT strain was likely due to metabolism to \\u003cb\\u003eP25\\u003c/b\\u003e and/or PCA. Despite this we observed increased activation relative to the negative control (~\\u0026thinsp;1.5-fold) indicating that PcaK appears to contribute some import capability toward these two substrates.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCross reactivity of TphK and PcaK transporters\\u003c/h2\\u003e \\u003cp\\u003eFollowing substrate screening of the TPA and PCA transporters paired with their cognate biosensors, next sought to investigate the existence of overlapping activity between the TphK and PcaK transporters. As both TphK and PcaK are thought to belong to the aromatic H\\u003csup\\u003e+\\u003c/sup\\u003e symport subfamily we reasoned that comparing their abilities to uptake TPA- and PCA-like effectors could highlight some structure activity relationships that govern ligand recognition or substrate specificity. To accomplish this, the genes encoding the most active TphK and PcaK towards TPA and PCA (TphK\\u003csub\\u003eR.Pyr\\u003c/sub\\u003e and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e, respectively) were sub-cloned into the other biosensor backbone, generating the constructs TphK\\u003csub\\u003eR.Pyr\\u003c/sub\\u003e-PcaV and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e-TphR. These were then screened against the TPA and PCA analogue libraries. The TphK construct appeared to facilitate marginally better transport, than the negative control, towards ligands \\u003cb\\u003eP2\\u003c/b\\u003e, \\u003cb\\u003eP24\\u003c/b\\u003e, \\u003cb\\u003eP25\\u003c/b\\u003e and \\u003cb\\u003eP27\\u003c/b\\u003e, however no ability to import substrates other than what had been shown to be transported by PcaK\\u003csub\\u003eP.put\\u003c/sub\\u003e was observed (\\u003cb\\u003eSupp. Figure\\u0026nbsp;7A\\u003c/b\\u003e). The PcaK crossover construct however demonstrated a significant fold change induction toward 2,5-pyridine dicarboxylic acid (\\u003cb\\u003eT4\\u003c/b\\u003e) indicating some unforeseen functionality although the degree of fold change was minimal (~\\u0026thinsp;0.3-fold increase). Increased activity to 2-hydroxy TPA (\\u003cb\\u003eT13\\u003c/b\\u003e) was also observed however all other ligands were shown to be unresponsive (\\u003cb\\u003eSupp. Figure\\u0026nbsp;7B\\u003c/b\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eBiosensor mediated screening of PcaK and TphK mutants\\u003c/h2\\u003e \\u003cp\\u003eNext, we sought to evaluate the ability of both biosensor-based detection systems to discern changes in the activity following protein engineering of the MFS transporters. This was performed in order to examine the specific role of primary sequence elements and/or structural motifs in ligand recognition/transport. As an initial step, to verify that our biosensor assays would be able to accurately report a mutagenic phenotype for a transporter of interest, three amino acid point mutations, previously shown to affect the efficiency of \\u003cb\\u003eP25\\u003c/b\\u003e uptake by PcaK from \\u003cem\\u003eP. putida\\u003c/em\\u003e [\\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e70\\u003c/span\\u003e], were individually created. These residues at positions E144, R124, and R398 were replaced with alanine (A) in the PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e-PcaV construct (\\u003cb\\u003eSupp Fig.\\u0026nbsp;8C\\u003c/b\\u003e), generating: PcaK-E144A\\u003csub\\u003eP.Put\\u003c/sub\\u003e-PcaV, PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e-R124A-PcaV and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e-R398A-PcaV. These PcaK point mutant constructs were then evaluated against varying concentrations of both PCA and 4HBA to assess changes to dose response activity. Consistent with previous reports, the biosensor assay indicated that all three mutations led to near total abolition of PCA import and a strong decrease in 4HBA import (\\u003cb\\u003eSupp Fig.\\u0026nbsp;8A\\u0026amp;B\\u003c/b\\u003e). The observed uptake of 4HBA by both the negative control and point mutants is consistent with earlier ligand screening, indicating an alternative \\u003cb\\u003eP25\\u003c/b\\u003e uptake mechanism by the \\u003cem\\u003eP. putida\\u003c/em\\u003e Δ\\u003cem\\u003epcaK\\u003c/em\\u003e strain.\\u003c/p\\u003e \\u003cp\\u003eBased on the previously observed overlapping substrate specificity of TphK\\u003csub\\u003eR.Pyr\\u003c/sub\\u003e-PcaV and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e-TphK (\\u003cb\\u003eSupp Fig.\\u0026nbsp;7\\u003c/b\\u003e) we wished to further explore the sequence features that impart ligand specificity to TphK and PcaK. Given that the characteristic structural arrangement of MFS proteins consists of a classical 12 ⍺-helical bundle, we first generated a sequence alignment of the functional PcaK and TphK sequences using CC-TOP prediction to annotate the sequence alignment for the location of the 12 ⍺-helices (\\u003cb\\u003eSupp Fig.\\u0026nbsp;9\\u003c/b\\u003e). In addition, an alpha fold model of \\u003cem\\u003eP. putida\\u003c/em\\u003e PcaK (Q51955) was also used to annotate the multiple sequence alignment, with its 3D structural prediction matching closely to the CCTOP predictions made for each sequence (\\u003cb\\u003eSupp Fig.\\u0026nbsp;9\\u003c/b\\u003e: Annotated as PcaK_PSEPU Secondary structure). The sequences of each individual transmembrane (TM) helix were then compared using the functionally verified TphK and PcaK sequences (\\u003cb\\u003eSupp Fig.\\u0026nbsp;10\\u003c/b\\u003e). Distinct conservation trends were noticeable in every TM however appeared to occur with greater abundance in TM\\u0026rsquo;s corresponding to those that make up the central cavity of the protein (TM\\u0026rsquo;s: 1, 4, 7, and 10) with these TM\\u0026rsquo;s thought to comprise the majority of residues that govern substrate coordination and co-substrate coupling [\\u003cspan citationid=\\\"CR71\\\" class=\\\"CitationRef\\\"\\u003e71\\u003c/span\\u003e]. Generally, amino acid differences in these regions consisted of non-polar to polar substitutions (TM1: PcaK_Ala22 to TphK_Gln, TM4: PcaK_Thr24 to TphK_Ala), polar to charged (TM10: Ser/Asn20 to Lys) and aromatic to non-aromatic (TM1: Phe11 to Gly). Within the PcaKs however, no sequence features were immediately apparent so as to explain the apparent unique uptake of 3, 5 substituted benzoic acids. Given the number of individual residue substitutions and combinations, both at the intra and interhelical level, that would need to be reconstituted in order to elucidate those involved in substrate recognition, we decided to leverage the high throughput screening potential of biosensors to assess the functionality of full TM substitutions between the \\u003cem\\u003eR. pyridinovrans\\u003c/em\\u003e TphK and the \\u003cem\\u003eP. putida\\u003c/em\\u003e PcaK for those helices which form the core of both, namely: TM\\u0026rsquo;s 1, 4, 7 and 10. With this in mind, we generated and screened chimeric MFS transporters with the entire core TM helical regions exchanged, resulting in PcaK\\u003csub\\u003eTphK_TM1,4,7,10\\u003c/sub\\u003e-PcaV and TphK\\u003csub\\u003ePcaK_TM1,4,7,10\\u003c/sub\\u003e-TphR. These chimeric transporters were tested in their cognate biosensor backgrounds against the PCA and TPA analogue libraries (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eInterestingly, whilst TphK\\u003csub\\u003ePcaK_TM1,4,710\\u003c/sub\\u003e-TphR appeared to lose activity toward its cognate ligand, TPA and biphenyl-4,4-dicarboxylic acid (\\u003cb\\u003eT20\\u003c/b\\u003e), it was still able to import 2-hydroxy- (1.4 vs 1.3), bromo- (1.0 vs 1.3), iodo- (1.3 vs 1.3) and amino-TPA (1.2 vs 1.3) (TphK wildtype vs TphK chimera), indicating some potential interactions from the PcaK helical regions in facilitating these interaction. Furthermore, a gain-of-function activity toward pyrazine-2,5-dicarboxylic acid (\\u003cb\\u003eT5\\u003c/b\\u003e) and naphthalene-2,6-dicarboxylic acid (\\u003cb\\u003eT21\\u003c/b\\u003e) was observed (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA) indicating the potential cooperation of other TM helices contributing to increased uptake of these non-cognate ligands. The loss of function encountered appeared to specifically impact structures containing dicarboxylate functionality with no other functionalisation such as TPA (\\u003cb\\u003eT3\\u003c/b\\u003e) and biphenyl-4,4-dicarboxylic acid (\\u003cb\\u003eT20\\u003c/b\\u003e) suggesting that the core TM helices are responsible for this recognition in wildtype TphK. The PcaK\\u003csub\\u003eTphK_TM1,4,7,10\\u003c/sub\\u003e-PcaV chimera, appeared to result in a functional transporter maintaining some activity toward earlier established ligands such as \\u003cb\\u003eP2\\u003c/b\\u003e and \\u003cb\\u003eP25\\u003c/b\\u003e albeit with reduced import capability, indicating that the chimeric MFS was functional \\u003cem\\u003ein vivo\\u003c/em\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eB). In addition, this chimera displays a significant gain of function over the WT in the form of increased uptake of coumaric acid (\\u003cb\\u003eP27\\u003c/b\\u003e) (9-fold). Activity toward PCA (\\u003cb\\u003eP2\\u003c/b\\u003e), benzaldehyde (\\u003cb\\u003eP17\\u003c/b\\u003e), 3HBA (\\u003cb\\u003eP24)\\u003c/b\\u003e, 4HBA (\\u003cb\\u003eP25\\u003c/b\\u003e) and vanillic acid (\\u003cb\\u003eP26\\u003c/b\\u003e) were shown to be higher than the negative control indicating some retained ability to uptake these compounds yet not as efficiently as the wildtype PcaK (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eB). We also noted the apparent loss of ability to transport substrates possessing 5th position hydroxylation such as 3,5 dihydroxybenzoic acid (\\u003cb\\u003eP3\\u003c/b\\u003e) and gallic acid (\\u003cb\\u003eP28\\u003c/b\\u003e) indicating that the core PcaK domains are essential in order to transport these substrates. We therefore then moved to study the chimeras as single exchange mutants to better elucidate regions of the highest importance for substrate recognition. TM helices were swapped individually between TphK\\u003csub\\u003eR.Pyr\\u003c/sub\\u003e and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e (for a total of 15 chimeras) before being cloned into either the PcaV- or TphR-based biosensor background for the evaluation of gain or loss of function (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eWe first reconstituted the helical region swaps of the PcaK\\u003csub\\u003eTphK_TM1,4,7,10\\u003c/sub\\u003e-PcaV chimera individually to elucidate the effects of individual swaps (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eA). Surprisingly, activity towards the cognate ligand PCA (\\u003cb\\u003eP2\\u003c/b\\u003e) appeared to be greater in the TM1 mutant than in the complete swap, indicating that substitution of this region with TphK TM 1 was able to partially complement and enable PCA import. Consistent with this the degree of amino acid changes within TM 1 for TphK and PcaK is subtle (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eE), with most of the solvent exposed core cavity facing mutations A46Q, G49S and F50Y clustering toward the periplasmic side of the core (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eB). These mutations all introduced slightly larger and more polar residues into the core cavity. This had the effect of reducing activity towards PCA, relative to the parental transporter, whereas transport activity to other effectors appeared to be more significantly reduced, indicating that decreasing the size of the cavity may have negatively impacted the ability to recognise PCA analogues. Replacement of TM4 appeared to be generally well tolerated, permitting limited uptake of 5\\u0026rsquo; substituted effectors, both 3,5 dihydroxybenzoic acid (\\u003cb\\u003eP3\\u003c/b\\u003e) and gallic acid (\\u003cb\\u003eP28\\u003c/b\\u003e), a phenotype that was abolished in all other single helical exchanges (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eA). This is reflected in the positive effect upon uptake, which was otherwise abolished in other mutants, suggesting that the residues for 5\\u0026rsquo; substituted hydroxyl recognition may be located in the other TM elements. Based on the predicted positions of residues side chains of TM 4, the most solvent accessible mutation in the core cavity consisted of a M134A substitution, which lead to a loss of activity towards PCA, as such methionine may play a role in stabilising interactions with aromatic residues. Overall, the generally lower impact of the TM 4 swap may be attributable to this helix having the fewest number of core cavity amino acid changes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eE\\u003cb\\u003e\\u0026amp;F\\u003c/b\\u003e). TM\\u0026rsquo;s 7 and 10 demonstrate largely similar phenotypes to one another, appearing to better uptake benzaldehyde (\\u003cb\\u003eP17\\u003c/b\\u003e) and 4-hydroxybenzoic acid (\\u003cb\\u003eP25\\u003c/b\\u003e) relative to TM 1 and 4 swaps. Initial inspection of the mutations of TM 7 and the corresponding structure suggests that Y272F would reduce a H-bonding capacity from the core cavity. However, the mutation of T283Q whilst bulkier, maintains this H-bonding capacity on the same face of core cavity. Collectively, Y272 and T283, along with the conserved N367 (TM10) and S371 (TM10) residues may have direct effects upon, with these residues clustering around helical turns 3\\u0026ndash;4, consistent with studies on the XylE MFS transporter which demonstrates similar positioning of its ligand coordinating residues [\\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e](Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eB). These residues are mutated in the TM 10 to N367S and S371K, with the latter lysine residue carrying a positive charge in addition to protruding further into the core cavity (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eB). The increased steric hinderance coupled with altered hydrogen bonding potential in TM 7 and 10 may therefore contribute towards the inability to accommodate 5\\u0026rsquo; hydroxylated ligands such as \\u003cb\\u003eP3\\u003c/b\\u003e and \\u003cb\\u003eP28\\u003c/b\\u003e. Replacement of every individual TM, along with the full cross, led to activation with 3-hydroxybenzoic acid (\\u003cb\\u003eP24\\u003c/b\\u003e) perhaps suggesting that none of the tested TM\\u0026rsquo;s are directly responsible for the recognition of this effector. Notably, vanillic acid (\\u003cb\\u003eP26\\u003c/b\\u003e) and coumaric acid (\\u003cb\\u003eP27\\u003c/b\\u003e) uptake improved in the complete chimeric mutant PcaK_\\u003csub\\u003eTphK_TM1,4,7,10\\u003c/sub\\u003e however individually reconstituting the single TMs showed very little improvement. Given the general trend of exchanging the bulkier residues of the PcaK core helical domains for the smaller ones of TphK domains may suggest that the increased cavity size of the TphK core is responsible for permitting the import of bulkier substrates such as coumaric and vanillic acid (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eA).\\u003c/p\\u003e \\u003cp\\u003eThe exchange of TM 1 in the TphK mutant appeared to have the most severe impact on effector recognition including to TPA (\\u003cb\\u003eT3\\u003c/b\\u003e) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eC). Despite this, most of the mutations that occur are structurally located at the periplasmic and cytoplasmic interfaces of the protein and not in the centre of the core cavity; specifically, the mutations Q42A, S45G and Y46F, all result in the loss of hydrogen bond donor/acceptors potentially disrupting interhelical contact points preventing the protein from undergoing conformational changes required for function (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eD). The number of conserved amino acids targeted at this structural location may therefore provide explanation for the sharp reduction in effector recognition. In contrast, replacement of TM 4 appeared to indicate this TM was the primary driver of the previously observed activity towards pyrazine-2,5-dicarboxylic acid (\\u003cb\\u003eT5\\u003c/b\\u003e), and naphthalene dicarboxylic acid (\\u003cb\\u003eT21\\u003c/b\\u003e) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA \\u003cb\\u003e\\u0026amp;\\u003c/b\\u003e Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eC). Mutations in this TM were quite minor as mentioned earlier, with the major change being the A131M mutation leading to the incorporation of a methionine side chain pointing into the core, as shown in the predicted PcaK structure (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eB). This mutation may stabilise effector binding through an S-aromatic interaction with nearby helical residues enabling the non-cognate large aromatic effectors to be up-taken. The TM 7 mutant displayed good response towards most effectors apart from 2-amino terephthalic acid (\\u003cb\\u003eT18\\u003c/b\\u003e). Of the mutations occurring in the TM 7 helix, only the Q279T mutation was localised to the central core, with this mutation resulting in the loss of a potential hydrogen bond acceptor site, it is possible that this correlates the loss of activity toward 2-amino terephthalic acid (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eD). The reduced activity for \\u003cb\\u003eT18\\u003c/b\\u003e could therefore be a result of this change, with bulkier substitutions like hydroxyl or halo groups still able to hydrogen bond with the shorter threonine residue at this position. Mutation of TM 10 appeared to have a greater impact on effector uptake, losing activity for iodo, bromo and amino terephthalate (\\u003cb\\u003eT15, T16, T18\\u003c/b\\u003e) yet possessing the strongest fold change response for hydroxy terephthalate (\\u003cb\\u003eT13\\u003c/b\\u003e) of all the single TM mutants (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eC). Mutation of serine to asparagine (S354N) may explain the observed impact upon effector activity; as asparagine is bulkier than serine this mutation may not accommodate bulkier substrates such as iodo and bromo terephthalates explaining the reduced response. More interestingly however a conserved lysine residue is mutated to a serine (K268S) with the predicted structure of TphK showing this residue projecting up towards both S364 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eD). The positive charge provided by the lysine may be essential for the stabilisation of the additional carboxylate group of TPA like molecules, with mutation to serine abolishing this. Given the proximity of the residues however, they may act synergistically to coordinate potential effector binding. Interestingly, activity toward 2\\u0026rsquo; position substituted TPA homologues (\\u003cb\\u003eT13-18\\u003c/b\\u003e) appears to be significantly enhanced when all the PcaK core helices are present together, with individual helical substitution not reaching the same levels of biosensor activation. Replacement of any of the core TM helices of TphK apparently led to a loss of function toward TPA and biphenyl-4,4-dicarboxylic acid indicating the importance of these core helices in substrate recognition. This result likely suggests the PcaK TM regions can substitute the loss of the second carboxylate recognition site through the ability to recognise hydroxyl or halide substituents on the ring providing some explanation for the observed induction of the biosensors in these mutants. Consolidating results from both the full cross chimeras and single helical domain mutations implies that PcaK TM helices can serve as functional proxy to TphK components but only when all are substituted together, suggesting some inter-helical dependency for functionality.\\u003c/p\\u003e \\u003cp\\u003eWe then moved to assess the functionality of the same TphK chimeras when transferred into the PcaV biosensor background to screen for any gain of function toward PCA or its analogues (\\u003cb\\u003eSupp Fig.\\u0026nbsp;11A\\u003c/b\\u003e). Substitution of single PcaK helical regions into TphK appeared to have very little effect on the recognition of PCA like effectors, with the primary positive effect restricted to coumaric acid (\\u003cb\\u003eP27\\u003c/b\\u003e). This further corroborates the observed improvement in activity when the PcaK full cross was assayed against coumaric acid and suggests involvement of other TphK TM regions in its recognition also. Finally, we assessed the activity of PcaK\\u003csub\\u003eTphK\\u003c/sub\\u003e single helical exchange chimeras in the TphR biosensor background, except for PcaK\\u003csub\\u003eTphK_TM1\\u003c/sub\\u003e-TphR which failed to clone (\\u003cb\\u003eSupp Fig.\\u0026nbsp;11B\\u003c/b\\u003e). No activity to any the TPA analogues screened was detected with any of the TM exchange chimeras however this result is consistent with the initial crossover experiments performed analysing the wildtype PcaK in the TphR biosensor background which also showed no ability to uptake any TPA like effectors. As such we can conclude that single replacement of PcaK TM structures with those from a TphK do not confer any activity to this effector set. Collectively, the results indicate that we have successfully generated a library of chimeric MFS proteins that are inserted within membrane and are functional with some demonstrating novel gains of function, highlighting the utility of such biosensor-based approaches to membrane transporter characterisation and engineering.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eHere we demonstrate that the development of a high throughput method for the screening and characterisation of MFS transporters is an important step towards the implementation of these and other transporters into strain engineering workflows. As such, screening strategies that take advantage of the rapidly expanding library of allosteric transcription factors as genetically encoded biosensors could pave the way for greater understanding of transport mechanisms, enabling deployment in microbial cell factories for bio-based production, and facilitate membrane protein engineering efforts. In this study, the aromatic acid, PCA and TPA, responsive transcriptional biosensors were employed to screen and characterise putative PCA and TPA transporters belonging to the MFS family, in the industrially relevant host, \\u003cem\\u003eP. putida\\u003c/em\\u003e.\\u003c/p\\u003e \\u003cp\\u003eUsing the genetic context of transporter genomic loci has been implemented previously to aid in the elucidation of a novel citric acid export protein in \\u003cem\\u003eAspergillus niger\\u003c/em\\u003e based on its homology to an itaconic acid biosynthetic gene cluster [\\u003cspan citationid=\\\"CR73\\\" class=\\\"CitationRef\\\"\\u003e73\\u003c/span\\u003e]. Furthermore, similar methodologies have been applied specifically to the TPA catabolic operon to systematically search for such metabolism [\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e]. Applying such syntenic catabolic operon analysis paired with biosensor-based functional screening led to the identification of three novel PcaK\\u0026rsquo;s from \\u003cem\\u003eA. antarcticans, B. masiliglacei\\u003c/em\\u003e and \\u003cem\\u003eN. animalis\\u003c/em\\u003e, and four novel TphK\\u0026rsquo;s from \\u003cem\\u003eB. pachyrhizi, R. pyridinivorans, S. hordei\\u003c/em\\u003e and \\u003cem\\u003eS. naphthae\\u003c/em\\u003e. To the best of our knowledge these MFS transporters have never been characterised or reported previously. From syntenic analysis, the taxonomic distribution of TphK containing operons appears to be broader than previously thought with the activity of the transporters providing evidence for the existence of TPA catabolic operons in these genera. Analysis from Jimenez et al [\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e] used homology of the \\u003cem\\u003etph\\u003c/em\\u003eA2 gene to extract TPA catabolic operons from publicly available sequence databases, they attributed operon occurrences to a limited number of organisms including betaproteobacteria (\\u003cem\\u003eComamonas, Ideonella\\u003c/em\\u003e and \\u003cem\\u003eRamlibacter\\u003c/em\\u003e), gammaproteobacteria (\\u003cem\\u003ePseudomonas\\u003c/em\\u003e) and actinomycetes (\\u003cem\\u003eRhodococcus\\u003c/em\\u003e) with all betaproteobaceria utilising the TphC transporter. Our analysis demonstrates that genes encoding TphK may have a greater taxonomic spread than previously reported, as they appear in a greater number of species than first assumed as well as in a greater number of families, this may be due to the use of the entire operon including the \\u003cem\\u003etphK\\u003c/em\\u003e gene as a search query returning a more diverse selection of organisms. Interestingly we identified some betaproteobacteria that appeared to possess TphK encoding genes implying that \\u003cem\\u003etph\\u003c/em\\u003e operons in this class are not limited to only to those utilising TphC transport. The aforementioned TPA catabolic operon from \\u003cem\\u003eComamonas\\u003c/em\\u003e sp. Strain E6 encodes a tripartite tricarboxylate transporter instead of a TphK MFS [\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR74\\\" class=\\\"CitationRef\\\"\\u003e74\\u003c/span\\u003e] suggesting the possibility that two distinct transporter systems were acquired by the ancestral operon to enable TPA uptake. A possible explanation for the emergence of two transport systems with overlapping function could relate to the relative transport turnover of each system. Whilst both TphK and TphC are classified as secondary transporters, the latter relies on a solute binding protein which typically bind with high affinity for the substrate leading to its translocation across the membrane [\\u003cspan citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e75\\u003c/span\\u003e]. MFS proteins are known for their higher uptake rates of substrates however with generally lower affinity and specificity, whilst no direct comparison of uptake rates between these classes have been made the general trends of mechanism lend themselves to this concept [\\u003cspan citationid=\\\"CR76\\\" class=\\\"CitationRef\\\"\\u003e76\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR77\\\" class=\\\"CitationRef\\\"\\u003e77\\u003c/span\\u003e]. As such the selection of transport system may relate to the preference of the host for TPA as a primary carbon source for growth or as an ancillary carbon source with the transporter systems representing different ecological niches in TPA rich environments. Whilst syntenic operon analysis is effective, this bioinformatics mining method is highly reliant on the co-localization of transporters to other genes in a functional context, making it inappropriate in the cases of orphan MFS proteins or exporters which are often located at random in genomes; making functional appraisal challenging [\\u003cspan citationid=\\\"CR78\\\" class=\\\"CitationRef\\\"\\u003e78\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eBiosensor-enabled screening of the seven functional PcaK homologues revealed wide ranging sensitivity towards PCA, along with variable substrate specificity for PCA analogues possessing hydroxyl groups at positions 3 and 4 of the aromatic ring, and carboxylate, methyl ester-, amide- and aldehyde groups position 1. Interestingly, there did not appear to be a strong correlation with sequence similarity and substrate specificity with the PcaK from \\u003cem\\u003eB. masilliglacei\\u003c/em\\u003e which clustered furthest from the \\u003cem\\u003eP. putida\\u003c/em\\u003e PcaK but displayed the most similar substrate specificity to one another. Furthermore, PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e and PcaK\\u003csub\\u003eB.Mas\\u003c/sub\\u003e demonstrated unique ability for the uptake 3,5-dihydroxybenzoic acid and gallic acid, indicating an activity towards position 5 hydroxyl groups which is not shared by the other screened PcaKs. In addition, the identification off this broader substate uptake scope also indicates a broader substrate scope for the PcaV transcription factor than previously reported [\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe PcaK from \\u003cem\\u003eA. baylyi\\u003c/em\\u003e has been previously purified and reconstituted in a proteoliposome, where it was reported to be able to take up salicylate, 2,4-dihydroxybenzoic, 4HBA and PCA in addition to vanillic acid and 3HBA [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. Further, PcaKs from \\u003cem\\u003eAcinetobacter\\u003c/em\\u003e sp. and \\u003cem\\u003eSphingobium\\u003c/em\\u003e sp. were also reported to be able to take up PCA, 4HBA, 3HBA, and to some extent vanillic acid, through genomic deletion and growth assays [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. In this study, uptake of salicylate (2,4-dihydroxybenzoic acid) was not detected by any of the biosensor-mediated transporter assay. Presumably this is due to the inability of the PcaV biosensor to recognise these substrates rather than a lack of transport. This reveals a limitation of the proposed method, whereby the assay depends on both transporter and biosensor specificity a recognised challenge in biosensor development [\\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e79\\u003c/span\\u003e]. This could be remedied through the engineering of sensors to increase their substrate scope or through the incorporation of other allosteric transcription factors to further improve substrate breadth [\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e]. Further, in this study, determining substrate preference between PCA, 4HBA and 3HBA was made difficult due to the background uptake of 4HBA and 3HBA by \\u003cem\\u003eP. putida\\u003c/em\\u003e, presumably through the action of promiscuous endogenous transporters. Any whole cell-based transporter assay will likely be challenged by background transport activity, highlighting the trade-off between scalability and ease of use versus the sensitivity of such a system.\\u003c/p\\u003e \\u003cp\\u003eFor the first time, the substrate specificity of TphK\\u0026rsquo;s was also characterised, whereby it was found that they demonstrate a strict preference for para-substituted aromatic dicarboxylic acids, with a tolerance for polar substitutions in the 2nd ring position, such as: hydroxyl, nitro, amino and halogen groups. Unexpectedly, they also displayed the ability to take up biphenyl-4,4-dicarboxylic acid, an effector twice the length of the cognate ligand TPA [\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e]. We have previously characterised the tripartite tricarboxylate transporter, TphC, from the TPA catabolic operon of \\u003cem\\u003eComamonas\\u003c/em\\u003e sp. strain E6. In that study we explored ligand recognition by the solute binding protein of TphC, which was able to bind TPA (\\u003cb\\u003eT3\\u003c/b\\u003e), 2-hydroxy TPA (\\u003cb\\u003eT13\\u003c/b\\u003e), 2-amino TPA (\\u003cb\\u003eT18\\u003c/b\\u003e) and also biphenyl-4,4,-dicarboxylic acid (\\u003cb\\u003eT20\\u003c/b\\u003e) [\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e]. This substrate specificity overlaps with that of the TphK\\u0026rsquo;s characterised in this work, intuitively suggesting that as both TphK- and TphC-type \\u003cem\\u003etph\\u003c/em\\u003e catabolic operons possess the same core activity, they therefore, likely have overlapping substrate transport recognition. However, the overlapping uptake of biphenyl-4,4-dicarboyxlic acid does raise questions of the functional origin of both TphK and TphC, whether these originated as bona fide transporters of TPA or perhaps related to transporters from biphenyl catabolic pathways, another anthropogenic carbon source. In addition, the identification of this broadened substate scope also indicates that the TphR transcription factor from \\u003cem\\u003eZ. Caldifontis\\u003c/em\\u003e is activated by aromatic diacids with increased length. The main determining factor for the TphR activity appears to be the requirement to maintain the diacids in a co-planar arrangement [\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eTransporter-biosensor crossover assays identified that TphK\\u003csub\\u003eR.Pyr\\u003c/sub\\u003e displays some limited import activity towards PCA, along with 3HBA, resulting in significant biosensor activation. In contrast PcaK was unable to transport TPA but was active towards to 2-hydroxy TPA (\\u003cb\\u003eT13\\u003c/b\\u003e) and pyridine-2,5-dicarboxylic acid (\\u003cb\\u003eT4\\u003c/b\\u003e) although the degree of activation was quite low. TphK appears to have a substrate preference for the uptake of dicarboxylic acids yet is also able to transport some monocarboxylates with reduced activity. This stringency for dicarboxylic acids also appears to have made it less tolerant to other functional groups, such as aldehyde, methyl ester and amide. PcaK on the other hand responded to effector ligands that display similar substitution pattern to PCA. The size and ability to hydrogen bond may be important for ligand recognition in PcaK, as bulkier substitutions/altered H-bonding potential groups failed to be transport and/or elicit activation the biosensor (iodo, bromo, amino, and nitro).\\u003c/p\\u003e \\u003cp\\u003eTo further probe the potential of biosensors for membrane protein engineering applications, we evaluated the ability of the PcaV-sensor to detect the functional impact of point mutations made to PcaK. In previous studies, the evaluation of transporter point mutants has been performed using laborious techniques, relying on chromatography based approaches to measure the depletion of a compound in media by strains expressing the transporter variant or via harvesting of cells and exposure to \\u003csup\\u003e14\\u003c/sup\\u003eC labelled substrates followed by scintillation counting of cells [\\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e80\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR81\\\" class=\\\"CitationRef\\\"\\u003e81\\u003c/span\\u003e]. Both of which are expensive approaches that require specialist knowledge and careful handling. Here, we reconstituted mutations in the critical 2\\u0026ndash;3 and 8\\u0026ndash;9 loop sequences of PcaK [\\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e80\\u003c/span\\u003e], and using the PcaV biosensor system showed these to be effective in abolishing transport of PCA and reducing transport of 4HBA, in agreement with previous studies.\\u003c/p\\u003e \\u003cp\\u003eCurrently, there are no reported crystal structures for any member of the aromatic acid H\\u003csup\\u003e+\\u003c/sup\\u003e symporter family. As such, information on the residues and/or structural features pertaining to ligand recognition and transport is minimal. Relying on primary sequence alignment of the transporters alone does not always guarantee functional relevance, with regions of functional similarity (substrate binding or ion binding sites) often display poor sequence alignment. In more distantly related transporters, residues with a similar functional role are often located far from each other in a primary sequence alignment [\\u003cspan citationid=\\\"CR82\\\" class=\\\"CitationRef\\\"\\u003e82\\u003c/span\\u003e]. Analysis by Wada et al hypothesised a possible ligand binding site in PcaK based on structural modelling using other MFS structures with some of these residues located on the core TM helices used in this study [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. Thus, we opted to perform replacement of the core TM helices between TphK\\u003csub\\u003eR.Pyr\\u003c/sub\\u003e and PcaK\\u003csub\\u003eP.Put\\u003c/sub\\u003e to gauge which of these structural features may contain sequence elements pertinent to substrate recognition. A similar TM swap approach has been used before with the glucose transporters Hxt1 and 2, which enabled the identification of TM\\u0026rsquo;s: 1, 5, 7 and 8 as being essential for glucose recognition and uptake [\\u003cspan citationid=\\\"CR83\\\" class=\\\"CitationRef\\\"\\u003e83\\u003c/span\\u003e]. Combination of rapid biosensor-enabled screening in tandem with predicted structure and sequence alignments suggests the involvement of a number of residues present in the core cavity which could be essential for effector recognition. All chimeras screened in their cognate biosensor background (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e \\u0026amp; \\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e) appeared to demonstrate functional transport albeit with some loss of activity relative to the wildtype. Gains of function were observed for the TphK\\u003csub\\u003ePcaK_TM1,4,7,10\\u003c/sub\\u003e chimera toward 2,5 pyrazine dicarboxylic acid (\\u003cb\\u003eT5\\u003c/b\\u003e) and naphthalene 2,6 dicarboxylic acid (\\u003cb\\u003eT21\\u003c/b\\u003e) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA), indicating a deviation away from the established preference for the general TPA structure exhibited by the transporters characterised in this study. Given the retained recognition of 2\\u0026rsquo; substituted TPA analogues it is plausible that introduction of PcaK helices enabled recognition of more highly decorated structures via introduction of more hydrogen bonding residues into the cavity. Similarly, incorporation of TphK core TM helices into a PcaK scaffold led to significant increases in activity for coumaric acid (\\u003cb\\u003eP27\\u003c/b\\u003e) a much bulkier effector than other PCA analogues validated in our earlier characterisation experiments, suggesting the both the TphK and PcaK cores have structurally adapted to the dimensions of the effectors they transport with TphKs featuring sterically less bulky side chains relative to PcaKs. Studies that have crystallised MFS proteins in complex with their substrate have shown a network of residues across multiple helices act in a coordinated manner to bind substrates. For example, the bacterial MFS XylE in complex with D-xylose is coordinated by a total of eight hydrogen bonds, via polar residues on TM\\u0026rsquo;s 5, 7, 8 and 10 as well as by aromatic residues in the vicinity from TM1, 7 10 and 11 [\\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e]. Interestingly, whilst Q288, Q289, and N294, which are all located on the solvent exposed helical turns 3\\u0026ndash;4 of TM 7 of XylE, contribute to hydrogen bonding with D-xylose; Y298 located at the helical turn 6 is also involved in ligand binding through water mediated hydrogen bonding [\\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e]. Therefore, it is possible that some of the more distal conserved residues identified in our analysis such as T283 (PcaK) or Q279 (TphK) that underwent mutation in the TM swap may act in a similar manner. Similarly, it is more difficult to ascertain the effect of other mutations introduced during helix exchanges, which do not occupy the core cavity and instead likely function as contact points for interhelical interactions. It is plausible that many of the effects we observed in the screened mutants were as a result of indirect disruption of protein structural dynamics, as such future studies that focus on targeted mutations of these implicated residues may shed more light on their role in proper protein function. We also noted the apparent synergism that occurs when multiple TM structures are exchanged simultaneously rather than individually. Key amino acid residues involved in selective protonation in response to effector binding have been inextricably linked to substrate translocation with the ionic motive force driving reconfiguration of MFS transporters from outward to inward conformations [\\u003cspan citationid=\\\"CR84\\\" class=\\\"CitationRef\\\"\\u003e84\\u003c/span\\u003e]. Given our observations, it is plausible that exchanging of TM helices may disrupt titratable amino acid residues responsible for the relaying of protons following substrate binding; the effect of mutating such charge carrying residues has resulted in the conversion of MFS proteins from active to passive transporter, drastically reducing uptake rate through the decoupling of the proton motive force. Indeed, in the case of XylE, mutation of D27 abolished transporter function entirely whilst mutating R133, which stabilises D27, lead to considerably reduced transport function highlighting the importance of such titratable residues in MFS function [\\u003cspan citationid=\\\"CR85\\\" class=\\\"CitationRef\\\"\\u003e85\\u003c/span\\u003e]. We noted the presence of a conserved glutamate residue (E274) located in TM7 mutated to an isoleucine in PcaK which may represent such a titratable residue that was lost during mutation. Such results indicate the feasibility of performing not only protein engineering efforts with MFS transporters, but also to probe more fundamental questions as to the role of specific residues or structural motifs in transporter function, enabled with biosensors, to provide a sensitive means of detecting gains and losses of function. Future studies using more targeted approaches such as site directed mutagenesis or alanine scanning of core cavity amino acids may provide a facile means of building structure activity relationships for putative or unclassified MFS proteins and can enable rapid identification of critical residues for further investigation. Incorporating multiple biosensors in serial genetic circuits coupled to different fluorescent outputs could potentially allow for further multiplexing of the approach covering a much broader range of compounds permitting deeper characterisation of transporters and overcoming the substrate limitations of a single aTF [\\u003cspan citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e86\\u003c/span\\u003e].\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eWe report a novel aTF-biosensor based screening method for the identification and characterisation of MFS transporters. Bioinformatically mined putative PcaK and TphK protein sequences for transporters of aromatic acids, PCA and TPA, were combined with TPA and PCA responsive biosensors. This led to the identification of novel members of both classes of aromatic acid H\\u003csup\\u003e+\\u003c/sup\\u003e symporters. We report wider taxonomic spread of the \\u003cem\\u003etph\\u003c/em\\u003e catabolic operon than previously reported as well as the first studies functionally characterising TphK substrate scope. The substrate specificity profiles of both classes were compared, revealing novel functionality for PcaKs from \\u003cem\\u003eP. putida\\u003c/em\\u003e and \\u003cem\\u003eB. masilliglacei\\u003c/em\\u003e in contrast to TphKs which demonstrated a more defined set of substrate preferences. We highlight the capability of biosensors in performing phenotypic characterisation of both point mutants as well as chimeric membrane transporters. This resulted in apparent gain of function chimeras with PcaK chimeras demonstrating uptake of pyrazine-2,5-dicarboxylic acid and naphthalene-1,6-dicarboxylic acid whereas TphK chimeras demonstrated increased activity to coumaric acid. These changes in activity appear to be related to the exchange of conserved residues in the core cavity interface of the protein structure, which effect the number of hydrogen bonding contacts as well as modifying the size of the core pocket modulating effector recognition and uptake. Some of these effects were shown to be dependent upon the coordinated activity of multiple helical domains acting in tandem implicating the involvement of pairs of complementary helical pairs/bundles for correct transport function and effector recognition. This study provides a method for the usage of biosensors as screening tools for evaluating putative transporters, and library of validated MFS transporters for biotechnologically relevant aromatic substrates.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no acknowledgements\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics Approval and Consent to Participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003ePLR was supported by a BBSRC DTP grant (BB/T008725/1) and BBSRC grant BB/Y004027/1. MC was supported byBBSRC grant BB/Y003276/1\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConflicts of interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNone\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAdditional Data\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAdditional File 1.xlsx – Title: Mutant Data Processing, Description: raw data and processing including statistical testing of the data to support the conclusions of \\u003cstrong\\u003eFig. 4 \\u0026amp; 5\\u003c/strong\\u003e\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eThomik T, Wittig I, Choe J, Boles E, Oreb M. An artificial transport metabolon facilitates improved substrate utilization in yeast. Nat Chem Biol. 2017;13:1158\\u0026ndash;63.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eProtzko RJ, Latimer LN, Martinho Z, de Reus E, Seibert T, Benz JP, et al. Engineering Saccharomyces cerevisiae for co-utilization of D-galacturonic acid and D-glucose from citrus peel waste. Nat Commun. 2018;9:5059.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBoyarskiy S, Davis L\\u0026oacute;pez S, Kong N, Tullman-Ercek D. Transcriptional feedback regulation of efflux protein expression for increased tolerance to and production of \\u003cem\\u003en\\u003c/em\\u003e-butanol. Metab Eng. 2016;33:130\\u0026ndash;7.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWu W, Liu F, Singh S. Toward engineering E. coli with an autoregulatory system for lignin valorization. Proceedings of the National Academy of Sciences. 2018;115:2970\\u0026ndash;5.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003evan der Hoek SA, Borodina I. Transporter engineering in microbial cell factories: the ins, the outs, and the in-betweens. Curr Opin Biotechnol. 2020;66:186\\u0026ndash;94.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRen Q, Chen K, Paulsen IT. TransportDB: a comprehensive database resource for cytoplasmic membrane transport systems and outer membrane channels. Nucleic Acids Res. 2007;35:D274\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChaudhry MT, Huang Y, Shen X-H, Poetsch A, Jiang C-Y, Liu S-J. Genome-wide investigation of aromatic acid transporters in Corynebacterium glutamicum. Microbiology. 2007;153:857\\u0026ndash;65.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eD\\u0026rsquo;Arrigo I, Cardoso JGR, Rennig M, Sonnenschein N, Herrg\\u0026aring;rd MJ, Long KS. Analysis of Pseudomonas putida growth on non-trivial carbon sources using transcriptomics and genome-scale modelling. Environ Microbiol Rep. 2019;11:87\\u0026ndash;97.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eD\\u0026rsquo;Argenio DA, Segura A, Coco WM, B\\u0026uuml;nz PV, Ornston LN. The Physiological Contribution ofAcinetobacter PcaK, a Transport System That Acts upon Protocatechuate, Can Be Masked by the Overlapping Specificity of VanK. J Bacteriol. 1999;181:3505\\u0026ndash;15.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMori K, Kamimura N, Masai E. Identification of the protocatechuate transporter gene in Sphingobium sp. strain SYK-6 and effects of overexpression on production of a value-added metabolite. Appl Microbiol Biotechnol. 2018;102:4807\\u0026ndash;16.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHarwood CS, Nichols NN, Kim MK, Ditty JL, Parales RE. Identification of the pcaRKF gene cluster from Pseudomonas putida: involvement in chemotaxis, biodegradation, and transport of 4-hydroxybenzoate. J Bacteriol. 1994;176:6479\\u0026ndash;88.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKallscheuer N, Vogt M, Kappelmann J, Krumbach K, Noack S, Bott M, et al. Identification of the phd gene cluster responsible for phenylpropanoid utilization in Corynebacterium glutamicum. Appl Microbiol Biotechnol. 2016;100:1871\\u0026ndash;81.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNogales J, Canales \\u0026Aacute;, Jim\\u0026eacute;nez-Barbero J, Serra B, Pingarr\\u0026oacute;n JM, Garc\\u0026iacute;a JL, et al. Unravelling the gallic acid degradation pathway in bacteria: the gal cluster from Pseudomonas putida. Mol Microbiol. 2011;79:359\\u0026ndash;74.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChen Z, Huang J, Wu Y, Wu W, Zhang Y, Liu D. Metabolic engineering of \\u003cem\\u003eCorynebacterium glutamicum\\u003c/em\\u003e for the production of 3-hydroxypropionic acid from glucose and xylose. Metab Eng. 2017;39:151\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMacLean AM, Haerty W, Golding GB, Finan TM. The LysR-type PcaQ protein regulates expression of a protocatechuate-inducible ABC-type transport system in Sinorhizobium meliloti. Microbiology. 2011;157:2522\\u0026ndash;33.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMichalska K, Chang C, Mack JC, Zerbs S, Joachimiak A, Collart FR. Characterization of Transport Proteins for Aromatic Compounds Derived from Lignin: Benzoate Derivative Binding Proteins. J Mol Biol. 2012;423:555\\u0026ndash;75.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSalmon RC, Cliff MJ, Rafferty JB, Kelly DJ. The CouPSTU and TarPQM Transporters in Rhodopseudomonas palustris: Redundant, Promiscuous Uptake Systems for Lignin-Derived Aromatic Substrates. PLoS ONE. 2013;8:e59844.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMulligan C, Fischer M, Thomas GH. Tripartite ATP-independent periplasmic (TRAP) transporters in bacteria and archaea. FEMS Microbiol Rev. 2011;35:68\\u0026ndash;86.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRever\\u0026oacute;n I, Jim\\u0026eacute;nez N, Curiel JA, Pe\\u0026ntilde;as E, L\\u0026oacute;pez de Felipe F, de Las Rivas B, et al. Differential Gene Expression by Lactobacillus plantarum WCFS1 in Response to Phenolic Compounds Reveals New Genes Involved in Tannin Degradation. Appl Environ Microbiol. 2017;83:e03387\\u0026ndash;16.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDrew D, North RA, Nagarathinam K, Tanabe M. Structures and General Transport Mechanisms by the Major Facilitator Superfamily (MFS). Chem Rev. 2021;121:5289\\u0026ndash;335.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMa C, Mu Q, Xue Y, Xue Y, Yu B, Ma Y. One major facilitator superfamily transporter is responsible for propionic acid tolerance in Pseudomonas putida KT2440. Microb Biotechnol. 2020;14:386\\u0026ndash;91.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSrinivasan P, Smolke CD. Biosynthesis of medicinal tropane alkaloids in yeast. Nature. 2020;585:614\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBracher JM, Verhoeven MD, Wisselink HW, Crimi B, Nijland JG, Driessen AJM, et al. The Penicillium chrysogenum transporter PcAraT enables high-affinity, glucose-insensitive l-arabinose transport in Saccharomyces cerevisiae. Biotechnol Biofuels. 2018;11:63.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eArai M, Okumura K, Satake M, Shimizu T. Proteome-wide functional classification and identification of prokaryotic transmembrane proteins by transmembrane topology similarity comparison. Protein Sci. 2004;13:2170\\u0026ndash;83.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWada A, Prates \\u0026Eacute;T, Hirano R, Werner AZ, Kamimura N, Jacobson DA, et al. Characterization of aromatic acid/proton symporters in \\u003cem\\u003ePseudomonas putida\\u003c/em\\u003e KT2440 toward efficient microbial conversion of lignin-related aromatics. Metab Eng. 2021;64:167\\u0026ndash;79.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGenee HJ, Bali AP, Petersen SD, Siedler S, Bonde MT, Gronenberg LS, et al. Functional mining of transporters using synthetic selections. Nat Chem Biol. 2016;12:1015\\u0026ndash;22.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMadej MG, Sun L, Yan N, Kaback HR. Functional architecture of MFS d-glucose transporters. Proceedings of the National Academy of Sciences. 2014;111:E719\\u0026ndash;27.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWeiland F, Kohlstedt M, Wittmann C. Guiding stars to the field of dreams: Metabolically engineered pathways and microbial platforms for a sustainable lignin-based industry. Metab Eng. 2022;71:13\\u0026ndash;41.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFleige C, Meyer F, Steinb\\u0026uuml;chel A. Metabolic Engineering of the Actinomycete Amycolatopsis sp. Strain ATCC 39116 towards Enhanced Production of Natural Vanillin. Appl Environ Microbiol. 2016;82:3410\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSainsbury PD, Hardiman EM, Ahmad M, Otani H, Seghezzi N, Eltis LD, et al. Breaking Down Lignin to High-Value Chemicals: The Conversion of Lignocellulose to Vanillin in a Gene Deletion Mutant of Rhodococcus jostii RHA1. ACS Chem Biol. 2013;8:2151\\u0026ndash;6.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSuzuki Y, Otsuka Y, Araki T, Kamimura N, Masai E, Nakamura M, et al. Lignin valorization through efficient microbial production of β-ketoadipate from industrial black liquor. Bioresour Technol. 2021;337:125489.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKogure T, Suda M, Hiraga K, Inui M. Protocatechuate overproduction by \\u003cem\\u003eCorynebacterium glutamicum\\u003c/em\\u003e via simultaneous engineering of native and heterologous biosynthetic pathways. Metab Eng. 2021;65:232\\u0026ndash;42.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGao R, Pan H, Kai L, Han K, Lian J. Microbial degradation and valorization of poly(ethylene terephthalate) (PET) monomers. World J Microbiol Biotechnol. 2022;38:89.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRaheem AB, Noor ZZ, Hassan A, Abd Hamid MK, Samsudin SA, Sabeen AH. Current developments in chemical recycling of post-consumer polyethylene terephthalate wastes for new materials production: A review. J Clean Prod. 2019;225:1052\\u0026ndash;64.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBenavides Fern\\u0026aacute;ndez CD, Guzm\\u0026aacute;n Castillo MP, Quijano P\\u0026eacute;rez SA. Carvajal Rodr\\u0026iacute;guez LV. Microbial degradation of polyethylene terephthalate: a systematic review. SN Appl Sci. 2022;4:263.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTiso T, Narancic T, Wei R, Pollet E, Beagan N, Schr\\u0026ouml;der K, et al. Towards bio-upcycling of polyethylene terephthalate. Metab Eng. 2021;66:167\\u0026ndash;78.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYoshida S, Hiraga K, Takehana T, Taniguchi I, Yamaji H, Maeda Y, et al. A bacterium that degrades and assimilates poly(ethylene terephthalate). Science. 2016;351:1196\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWerner AZ, Clare R, Mand TD, Pardo I, Ramirez KJ, Haugen SJ et al. Tandem chemical deconstruction and biological upcycling of poly(ethylene terephthalate) to β-ketoadipic acid by \\u003cem\\u003ePseudomonas putida\\u003c/em\\u003e KT2440. Metabolic Engineering. 2021;67:250\\u0026ndash;61.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHara H, Eltis LD, Davies JE, Mohn WW. Transcriptomic Analysis Reveals a Bifurcated Terephthalate Degradation Pathway in Rhodococcus sp. Strain RHA1. J Bacteriol. 2007;189:1641\\u0026ndash;7.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBrandenberg OF, Schubert OT, Kruglyak L. Towards synthetic PETtrophy: Engineering Pseudomonas putida for concurrent polyethylene terephthalate (PET) monomer metabolism and PET hydrolase expression. Microb Cell Fact. 2022;21:119.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRamos-Gonz\\u0026aacute;lez M-I, Godoy P, Alaminos M, Ben-Bassat A, Ramos J-L. Physiological Characterization of Pseudomonas putida DOT-T1E Tolerance to p-Hydroxybenzoate. Appl Environ Microbiol. 2001;67:4338\\u0026ndash;41.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePernstich C, Senior L, MacInnes K, Forsaith M, Curnow P. Expression, purification and reconstitution of the 4-hydroxybenzoate transporter PcaK from Acinetobacter sp. ADP1. Protein Exp Purif. 2014;101.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAlvarez-Gonzalez G, Chacόn M, Berepiki A, Fisher K, Gosalvitr P, Cu\\u0026eacute;llar-Franca R et al. Complex waste stream valorisation through combined enzymatic hydrolysis and catabolic assimilation by Pseudomonas putida [Internet]. bioRxiv; 2024 [cited 2024 Aug 27]. p. 2023.02.13.528311. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.biorxiv.org/content/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.biorxiv.org/content/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1101/2023.02.13.528311v2\\u003c/span\\u003e\\u003cspan address=\\\"10.1101/2023.02.13.528311v2\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGao C, Hou J, Xu P, Guo L, Chen X, Hu G, et al. Programmable biomolecular switches for rewiring flux in Escherichia coli. Nat Commun. 2019;10:3751.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChoi S-S, Seo S-Y, Park S-O, Lee H-N, Song J-S, Kim J-Y, et al. Cell Factory Design and Culture Process Optimization for Dehydroshikimate Biosynthesis in Escherichia coli. Front Bioeng Biotechnol. 2019;7:241.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAlvarez-Gonzalez G, Dixon N. Genetically encoded biosensors for lignocellulose valorization. Biotechnol Biofuels. 2019;12:246.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChaisupa P, Wright RC. State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering. SLAS Technol. 2024;29:100113.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhu Y, Zhou C, Wang Y, Li C. Transporter Engineering for Microbial Manufacturing. Biotechnol J. 2020;15:1900494.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWang G, M\\u0026oslash;ller-Hansen I, Babaei M, D\\u0026rsquo;Ambrosio V, Christensen HB, Darbani B, et al. Transportome-wide engineering of \\u003cem\\u003eSaccharomyces cerevisiae\\u003c/em\\u003e. Metab Eng. 2021;64:52\\u0026ndash;63.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWaterhouse AM, Procter JB, Martin DMA, Clamp M, Barton GJ. Jalview Version 2\\u0026mdash;a multiple sequence alignment editor and analysis workbench. Bioinformatics. 2009;25:1189\\u0026ndash;91.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGilchrist CLM, Booth TJ, van Wersch B, van Grieken L, Medema MH, Chooi Y-H. cblaster: a remote search tool for rapid identification and visualization of homologous gene clusters. Bioinf Adv. 2021;1:vbab016.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics. 2012;28:3150\\u0026ndash;2.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMarx CJ. Development of a broad-host-range sacB-based vector for unmarked allelic exchange. BMC Res Notes. 2008;1:1.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDobson L, Rem\\u0026eacute;nyi I, Tusn\\u0026aacute;dy GE. CCTOP: a Consensus Constrained TOPology prediction web server. Nucleic Acids Res. 2015;43:W408\\u0026ndash;12.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021;596:583\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMeng EC, Goddard TD, Pettersen EF, Couch GS, Pearson ZJ, Morris JH, et al. UCSF ChimeraX: Tools for structure building and analysis. Protein Sci. 2023;32:e4792.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSalvador M, Abdulmutalib U, Gonzalez J, Kim J, Smith AA, Faulon J-L, et al. Microbial Genes for a Circular and Sustainable Bio-PET Economy. Genes. 2019;10:373.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGautom T, Dheeman D, Levy C, Butterfield T, Alvarez Gonzalez G, Le Roy P, et al. Structural basis of terephthalate recognition by solute binding protein TphC. Nat Commun. 2021;12:6244.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHarwood CS, Parales RE, THE β-KETOADIPATE, PATHWAY AND THE BIOLOGY OF SELF-IDENTITY. Annu Rev Microbiol. 1996;50:553\\u0026ndash;90.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKamimura N, Aoyama T, Yoshida R, Takahashi K, Kasai D, Abe T, et al. Characterization of the Protocatechuate 4,5-Cleavage Pathway Operon in Comamonas sp. Strain E6 and Discovery of a Novel Pathway Gene. Appl Environ Microbiol. 2010;76:8093\\u0026ndash;101.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKasai D, Fujinami T, Abe T, Mase K, Katayama Y, Fukuda M, et al. Uncovering the Protocatechuate 2,3-Cleavage Pathway Genes. J Bacteriol. 2009;191:6758\\u0026ndash;68.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eStover CK, Pham XQ, Erwin AL, Mizoguchi SD, Warrener P, Hickey MJ, et al. Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen. Nature. 2000;406:959\\u0026ndash;64.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAlvarez Gonzalez G, Chac\\u0026oacute;n M, Butterfield T, Dixon N. Tuning the performance of a TphR-based terephthalate biosensor with a design of experiments approach. Metab Eng Commun. 2024;19:e00250.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMachado FM, Currin L, Dixon A. Directed evolution of the PcaV allosteric transcription factor to generate a biosensor for aromatic aldehydes. J Biol Eng. 2019;13:91.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVermaas JV, Dixon RA, Chen F, Mansfield SD, Boerjan W, Ralph J et al. Passive membrane transport of lignin-related compounds. Proceedings of the National Academy of Sciences. 2019;116:23117\\u0026ndash;23.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNarancic T, Salvador M, Hughes GM, Beagan N, Abdulmutalib U, Kenny ST, et al. Genome analysis of the metabolically versatile Pseudomonas umsongensis GO16: the genetic basis for PET monomer upcycling into polyhydroxyalkanoates. Microb Biotechnol. 2021;14:2463\\u0026ndash;80.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLiu X, Jin J, Sun H, Li S, Zhang F, Yu X, et al. Perspectives on the microorganisms with the potentials of PET-degradation. Front Microbiol. 2025;16:1541913.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNIAID Data Discovery Portal [Internet]. NIAID Data Discovery Portal. [cited 2024 Jul 24]. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://data.niaid.nih.gov\\u003c/span\\u003e\\u003cspan address=\\\"https://data.niaid.nih.gov\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWilkes RA, Waldbauer J, Carroll A, Nieto-Dom\\u0026iacute;nguez M, Parker DJ, Zhang L, et al. Complex regulation in a Comamonas platform for diverse aromatic carbon metabolism. Nat Chem Biol. 2023;19:651\\u0026ndash;62.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDitty JL, Harwood CS. Charged Amino Acids Conserved in the Aromatic Acid/H\\u0026thinsp;+\\u0026thinsp;Symporter Family of Permeases Are Required for 4-Hydroxybenzoate Transport by PcaK from Pseudomonas putida. J Bacteriol. 2002;184:1444\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYan N. Structural advances for the major facilitator superfamily (MFS) transporters. Trends Biochem Sci. 2013;38:151\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSun L, Zeng X, Yan C, Sun X, Gong X, Rao Y, et al. Crystal structure of a bacterial homologue of glucose transporters GLUT1\\u0026ndash;4. Nature. 2012;490:361\\u0026ndash;6.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSteiger MG, Rassinger A, Mattanovich D, Sauer M. Engineering of the citrate exporter protein enables high citric acid production in Aspergillus niger. Metab Eng. 2019;52:224\\u0026ndash;31.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSasoh M, Masai E, Ishibashi S, Hara H, Kamimura N, Miyauchi K, et al. Characterization of the terephthalate degradation genes of Comamonas sp. strain E6. Appl Environ Microbiol. 2006;72:1825\\u0026ndash;32.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRosa LT, Bianconi ME, Thomas GH, Kelly DJ. Tripartite ATP-Independent Periplasmic (TRAP) Transporters and Tripartite Tricarboxylate Transporters (TTT): From Uptake to Pathogenicity. Front Cell Infect Microbiol [Internet]. 2018 [cited 2025 May 6];8. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.frontiersin.orghttps://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.frontiersin.orghttps://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fcimb.2018.00033/full\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fcimb.2018.00033/full\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLaw CJ, Maloney PC, Wang D-N. Ins and Outs of Major Facilitator Superfamily Antiporters. Annu Rev Microbiol. 2008;62:289\\u0026ndash;305.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChen C, Beattie GA. Pseudomonas syringae BetT Is a Low-Affinity Choline Transporter That Is Responsible for Superior Osmoprotection by Choline over Glycine Betaine. J Bacteriol. 2008;190:2717\\u0026ndash;25.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eM\\u0026oslash;ller-Hansen I, S\\u0026aacute;ez-S\\u0026aacute;ez J, van der Hoek SA, Dyekj\\u0026aelig;r JD, Christensen HB, Wright Muelas M et al. Deorphanizing solute carriers in Saccharomyces cerevisiae for secondary uptake of xenobiotic compounds. Front Microbiol [Internet]. 2024 [cited 2024 Jul 22];15. Available from: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.frontiersin.org/journals/microbiology/articles/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.frontiersin.org/journals/microbiology/articles/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fmicb.2024.1376653/full\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fmicb.2024.1376653/full\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eShin S-M, Jha RK, Dale T. Tackling the Catch-22 Situation of Optimizing a Sensor and a Transporter System in a Whole-Cell Microbial Biosensor Design for an Anthropogenic Small Molecule. ACS Synth Biol. 2022;11:3996\\u0026ndash;4008.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDitty JL, Harwood CS. Conserved cytoplasmic loops are important for both the transport and chemotaxis functions of PcaK, a protein from Pseudomonas putida with 12 membrane-spanning regions. J Bacteriol. 1999;181:5068\\u0026ndash;74.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eStandaert RF, Giannone RJ, Michener JK. Identification of parallel and divergent optimization solutions for homologous metabolic enzymes. Metabolic Eng Commun. 2018;6:56\\u0026ndash;62.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMadej MG, Kaback HR. Evolutionary mix-and-match with MFS transporters II. Proceedings of the National Academy of Sciences. 2013;110:E4831\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKasahara T, Kasahara M. Transmembrane segments 1, 5, 7 and 8 are required for high-affinity glucose transport by Saccharomyces cerevisiae Hxt2 transporter. Biochem J. 2003;372:247\\u0026ndash;52.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhang XC, Zhao Y, Heng J, Jiang D. Energy coupling mechanisms of MFS transporters. Protein Sci. 2015;24:1560\\u0026ndash;79.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWisedchaisri G, Park M-S, Iadanza MG, Zheng H, Gonen T. Proton-coupled sugar transport in the prototypical major facilitator superfamily protein XylE. Nat Commun. 2014;5:4521.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMeyer AJ, Segall-Shapiro TH, Glassey E, Zhang J, Voigt CA. Escherichia coli Marionette strains with 12 highly optimized small-molecule sensors. Nat Chem Biol. 2019;15:196\\u0026ndash;204.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"journal-of-biological-engineering\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"jbie\",\"sideBox\":\"Learn more about [Journal of Biological Engineering](http://jbioleng.biomedcentral.com/)\",\"snPcode\":\"13036\",\"submissionUrl\":\"https://submission.nature.com/new-submission/13036/3\",\"title\":\"Journal of Biological Engineering\",\"twitterHandle\":\"@BioMedCentral\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Biosensors, Major Facilitator Superfamily, Protocatechuic acid, Terephthalic acid, Syntenic Analysis, Aromatic Acid Transporters\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6931086/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6931086/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eActive transport of chemical species across the cell membrane represents a critical biological and biotechnological function, allowing the cell to selectively import compounds of nutritional value whilst exporting potentially toxic compounds. Major facilitator superfamily (MFS) transporters represent a ubiquitous class able to uptake and export an array of different chemical species. When designing biosynthetic pathways within microbial hosts, for production or remediation, transport is often critical to the efficiency of the resulting engineered strain. However, transport is a commonly neglected node for characterisation and engineering given difficulties in producing, purifying and assaying membrane transport proteins outside of their native environment. Here, using syntenic analysis and genetically encoded biosensors a library of MFS transporters were screened for their ability to uptake the aromatic acids, protocatechuic acid and terephthalic acid. The structure activity relationships of the corresponding transporters, PcaK and TphK, were then assessed with library of aromatic acid effectors. Finally, the feasibility of protein engineering was assessed, by the creation of chimeric MFS transporters, revealing a degree of effector recognition plasticity and the modularity of core transmembrane domains. This study provides a library of validated MFS transporters and demonstrates the value of employing genetically encoded biosensors in the characterisation and engineering of this important transport function.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Genetically encoded biosensor enabled mining, characterisation and engineering of aromatic acid MFS transporters\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-06-25 10:48:25\",\"doi\":\"10.21203/rs.3.rs-6931086/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-07-15T16:48:46+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-07-15T06:26:40+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-07-13T08:24:23+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-07-09T22:52:21+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-07-03T17:46:44+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"7021521467617958410481720199868893391\",\"date\":\"2025-06-25T22:22:45+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"209132727187228108782212979541362891167\",\"date\":\"2025-06-25T14:59:50+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"241903670913433207768023011807060957373\",\"date\":\"2025-06-23T15:38:15+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"93946205114914292605047523896044396240\",\"date\":\"2025-06-23T14:30:09+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"250153718360372223025218460406326110515\",\"date\":\"2025-06-23T11:19:30+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-06-23T11:09:58+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-06-23T08:01:44+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-06-23T07:59:55+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Journal of Biological Engineering\",\"date\":\"2025-06-19T11:58:31+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"journal-of-biological-engineering\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"jbie\",\"sideBox\":\"Learn more about [Journal of Biological Engineering](http://jbioleng.biomedcentral.com/)\",\"snPcode\":\"13036\",\"submissionUrl\":\"https://submission.nature.com/new-submission/13036/3\",\"title\":\"Journal of Biological Engineering\",\"twitterHandle\":\"@BioMedCentral\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"e9391081-9858-4867-b576-ef484993e5a1\",\"owner\":[],\"postedDate\":\"June 25th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-11-03T16:06:32+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-6931086\",\"link\":\"https://doi.org/10.1186/s13036-025-00568-y\",\"journal\":{\"identity\":\"journal-of-biological-engineering\",\"isVorOnly\":false,\"title\":\"Journal of Biological Engineering\"},\"publishedOn\":\"2025-10-31 15:58:55\",\"publishedOnDateReadable\":\"October 31st, 2025\"},\"versionCreatedAt\":\"2025-06-25 10:48:25\",\"video\":\"\",\"vorDoi\":\"10.1186/s13036-025-00568-y\",\"vorDoiUrl\":\"https://doi.org/10.1186/s13036-025-00568-y\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6931086\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6931086\",\"identity\":\"rs-6931086\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}