{"paper_id":"26dcaf83-031b-4012-b416-90bf8ecbc0f0","body_text":"UTILIZING SEQUENCE SIMILARITY NETWORKS FOR CROSS SPECIES ELICITOR \nIDENTIFICATION OF STREPTOMYCES REGULATORY PROTIENS  \n \nEmilee Pattersona, Audrey Birdwellb, Andrew Sabatinoa, Carzon Williamsc and Allison Walkera,d \n \naDepartment of Biological Sciences, Vanderbilt University, Nashville, TN, USA, bThe University of \nTennessee Health Science Center, Memphis, TN, USA, cHillsboro High School, Nashville, TN, USA, \ndDepartment of Chemistry, Vanderbilt University, Nashville, TN, USA \n \naddress correspondence to: allison.s.walker@vanderbilt.edu \n \nIMPORTANCE \n \nStreptomyces are a genus of bacteria known for their ability to produce a variety of natural products \nwith therapeutic value such as antibiotics. However, most of the genes responsible for producing these \ncompounds are not expressed under laboratory conditions. These genes are often controlled by \nregulatory proteins that respond to small molecules, known as elicitors. Though many regulators have \nbeen characterized, their cognate elicitors remain unknown, limiting our ability to exploit this interaction \nfor targeted gene expression. In this study, we used sequence similarity networks to group related \nregulator proteins and demonstrate that proteins with similar sequences respond to the same elicitors. \nBy showing that elicitor responsiveness of a regulator can be predicted, we open a pathway for \nactivation of silent genes without genetic manipulation. This enables the transfer of elicitor knowledge \nacross Streptomyces species, expanding access to their chemical diversity and biosynthetic potential. \n \nABSTRACT  \nStreptomyces bacteria produce a variety of secondary metabolites that hold clinical and agricultural \nvalue, yet their biosynthetic potential remains unrealized as many biosynthetic gene clusters are not \nexpressed under standard laboratory conditions. Expression of these clusters is tightly regulated, often \nby cluster situated transcription factors. The TetR family are regulators whose activity is modulated by \nsmall molecule elicitors. Although many TetRs have been characterized, elicitors have only been \nidentified for a small fraction of them. This lack of data presents a limitation in our ability to exploit \nelicitor-regulator pairs for activation of silent clusters and underscores the need for predictive and \ntestable strategies for elicitor identification. In this work, we test the use of sequence similarity networks \n(SSNs) as a predictor of elicitor identity using the well characterized TetR protein, JadR2, that has a \nknown elicitor, chloramphenicol. We utilized SSNs to identify JadR2 homologs that may also be elicited \nby chloramphenicol. We developed a heterologous Escherichia coli reporter system in which regulator \nactivity was monitored using an EGFP readout of DNA binding activity. Using this system, we screened \nJadR2 and four homologs for responsiveness to chloramphenicol. We found that 3 homologs were \nelicited by chloramphenicol, all of which were formerly uncharacterized. These results demonstrate that \nTetR-family proteins can share elicitor responsiveness and that SSNs can be used to prioritize \nregulators for functional screening. This work establishes a genomics-informed and bioinformatics-\nguided framework for linking elicitors to their regulator, expanding the toolkit for natural product \ndiscovery by unlocking regulatory information across Streptomyces.   \nINTRODUCTION  \nStreptomyces are a metabolically prolific genus of bacteria renowned for their ability to produce natural \nproducts with a variety of structures and activities(1, 2). These natural products are therapeutically and \nagriculturally valuable, with activities that treat cancer and microbial infections, or act as pesticides \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 8, 2026. ; https://doi.org/10.64898/2026.05.07.723685doi: bioRxiv preprint \n\netc.(3–6). However, only a small fraction of Streptomyces biosynthetic potential has been realized. \nGenome sequencing and bioinformatic analyses suggest that a typical Streptomyces genome encodes \nan average of 40 biosynthetic gene clusters (BGCs) with a variety of predicted activities, yet it is \nestimated that up to 90% of these clusters are not expressed under standard laboratory conditions(7, \n8). The mismatch between predicted and expressed BGCs highlights the need for continued research \ninto Streptomyces for their biosynthetic potential and continued use as a reservoir for biologically active \nsecondary metabolites.  \nAdvances in genome sequencing and multi-omics approaches have expanded our understanding of \nStreptomyces genomes however, translating this genomic information into chemical output remains a \nsignificant challenge(9–11). BGC expression is often tightly controlled by complex regulatory networks \nthat are poorly understood(12). Across all sequenced Streptomyces genomes there are hundreds of \ntranscription factors, many of which are uncharacterized. Regulation of secondary metabolism can be \nhighly context dependent, in some cases, the same transcription factor may act differently depending \non environmental cues or genomic context, making regulatory outcomes difficult to predict(13–15). \nMost BGCs encode one or more cluster situated regulators that govern their expression(16). Traditional \nstrategies to activate silent or cryptic BGCs frequently rely on genetic manipulation of these regulators, \nsuch as overexpression of positive regulators or deletion or repression of negative regulators(17, 18). \nWhile successful in some cases, these approaches often require extensive cloning and strain \nengineering that may not be feasible for many Streptomyces species. As a result, there is a need for \nthe development of more broadly accessible strategies for targeting and activating secondary \nmetabolism. \nOne prominent class of cluster situated regulators is the TetR family of transcriptional regulators. TetR \nproteins are characterized by an N-terminal helix-turn-helix DNA-binding domain and a C-terminal \nligand-binding domain(19). TetRs typically bind promoter regions within BGCs and repress \ntranscription. Upon binding to a small molecule ligand, referred to here as elicitors, the protein \nundergoes a conformational change that reduces DNA-binding affinity, resulting in the activation of \ntranscription(20, 21). Although thousands of TetRs have been described, only a small number of \nelicitor-regulator pairs have been experimentally characterized(22, 23). The dearth of elicitor data \npresents a major challenge in exploiting the activity of TetRs for targeted activation of silent BGCs. \nActivation of secondary metabolism using elicitors has been explored through untargeted approaches \nthat utilize mass spectrometry to identify changes in the metabolomic profile after treatment with a \nlibrary of potential small molecule elicitors. The High-Throughput Elicitor Screening (HiTES) method \nhas been particularly powerful in this context by enabling identification of compounds that induce \nsecondary metabolite production(24). Though robust, these methods do not directly link elicitors to their \ncognate regulators, making it challenging to generalize findings across species or to predict regulatory \nactivity based on genome sequence alone. \nIn contrast, directly identifying elicitor-regulator pairs provides a targeted and potentially more \ngeneralizable strategy for BGC activation. With the expectation that homologous transcription factors \nmay share regulatory mechanisms, linking specific elicitors to defined regulator families could enable \ncross-species predictions. If a silent BGC contains a regulator homologous to one with a known elicitor, \npathway activation may be possible through treatment with that elicitor, eliminating the need for genetic \nmanipulation or elicitor screening. This approach is particularly exciting for organisms that are difficult \nto genetically engineer and could offer an alternative option for transcription factor knockouts or \noverexpression strategies. \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 8, 2026. ; https://doi.org/10.64898/2026.05.07.723685doi: bioRxiv preprint \n\nRecent work has demonstrated that Streptomyces cluster-situated regulators can be functionally \nreconstituted in heterologous Escherichia coli systems as fluorescent biosensors responsive to known \nsignaling molecules(25). These studies establish that pathway associated regulators can retain function \noutside their native host and highlight the utility of heterologous reporter systems for studying small-\nmolecule sensing. However, these approaches have primarily focused on previously characterized \nligand and receptor relationships and have not been widely applied to the discovery of new elicitor-\nregulator pairs. \nIn this work, we combine bioinformatics and genomics to predict and validate new elicitor-regulator \npairs within the TetR family. Sequence similarity networks (SSNs) are a powerful bioinformatic tool \nused to group proteins and potentially infer function. In previous work, SSN were used to successfully \npredict enzyme function (26) , here, we expect to use the same tool to predict elicitor-regulator pairs. \nWe constructed a SSN of Streptomyces TetR proteins obtained from the antiSMASH database and \nfocused on a cluster containing the well-characterized regulator JadR2, found in the jadomycin B (JdB) \nbiosynthetic gene cluster of Streptomyces venezuelae (27). JadR2 represses JdB biosynthesis by \nbinding to the promoter of jadR1, a positive regulator of JdB expression. JadR2 has to characterized \nelicitors, jadomycin B and the antibiotic chloramphenicol (Cm)(28). Binding of either ligand causes \nJadR2 to release DNA, allowing expression of the JdB cluster. \nTo test if SSN clusters share elicitor identity, we employed a heterologous E. coli expression system in \nwhich JadR2 homologs from five Streptomyces species were heterologously expressed with an \ninducible promoter and, on a second plasmid, the S. venezuelae JadR2 promotor binding site was \ncloned upstream of an EGFP reporter. This system enabled direct monitoring of regulator activity and \nelicitor responsiveness using EGFP expression as a readout of regulator activity while also eliminating \nthe need for native host manipulation. An advantage of this system is that we utilized a known JadR2 \noperator sequence for functional screening of each homolog. This is both a modular and scalable \nsystem that does not require knowledge of the native DNA-binding site for each regulator, resulting in \nstreamlined elicitor identification. By screening JadR2 homologs, we demonstrate that SSNs can \nsuccessfully predict shared elicitors, providing a framework for targeted activation of silent BGCs \nthrough elicitor treatment.  \n  \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 8, 2026. ; https://doi.org/10.64898/2026.05.07.723685doi: bioRxiv preprint \n\nRESULTS \n \n \n \n \n \n \n \nFigure 1. Workflow for identification of elicitor-regulator pairs using a heterologous reporter assay.  \n(1) TetR-family regulators are selected based on sequence similarity to a characterized reference protein and a \ntwo-plasmid system is constructed consisting of a reporter plasmid containing a regulator binding site upstream \nof an EGFP gene and an expression pl asmid encoding the regulator under inducible control. (2) Plasmids are \ndouble transformed into BL21 (DE3) E. coli. (3) Cultures are grown in EZ Rich Defined Medium overnight. (4a) \nCultures treated with IPTG for induction, the expressed regulator binds to i ts binding sequence upstream of \nEGFP, repressing expression. (4b) Cultures are treated with IPTG followed by candidate elicitor. Binding of the \nelicitor to responsive regulators relieves repression, resulting in increased EGFP expression. (5) EGFP \nfluorescence normalized to OD600 is measured as a quantitative readout of regulator DNA- binding activity and \nelicitor responsiveness. \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 8, 2026. ; https://doi.org/10.64898/2026.05.07.723685doi: bioRxiv preprint \n\nDevelopment of a heterologous reporter assay. To assess regulator function, we developed a \nheterologous reporter system in E. coli. This system consisted of a reporter plasmid containing the \nJadR2 binding site upstream of an EGFP gene and an expression plasmid encoding either JadR2, a \nhomolog, or an empty vector control under IPTG-inducible expression. Double transformants were \nverified by PCR (Fig S1). EGFP fluorescence normalized to optical density was used as a readout of \ntranscriptional activity (Fig. 1).  \nKnown elicitor-regulator pair, JadR2 and Cm, used as a benchmark for expression and elicitor \ntesting in E. coli. Induction of JadR2 expression resulted in a reduction in EGFP fluorescence relative \nto the empty vector control (Fig 2A). Addition of Cm restored EGFP expression in a concentration-\ndependent manner (Fig 2B). These results confirm that JadR2 retains both DNA-binding and elicitor-\nresponsive activity in the heterologous system.  \nA \nFigure 2. JadR2 retains repression activity and Cm responsiveness in E. coli. \nThe JadR2 protein from Streptomyces venezuelae (SV JadR2) was used as a benchmark for method \ndevelopment. A. IPTG-induced JadR2 expression represses EGFP expression. Bar heights reflect EGFP signal \nnormalized to OD600 at 4 hours post-IPTG treatment. EV indicates the empty vector control. B. Cm treatment \nrestores GFP expression after IPTG induced expression of JadR2. Bar heights reflect EGFP signal normalized \nto OD600 at 6 hours post-CM treatment. EV indicates the empty vector control. \nB \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 8, 2026. ; https://doi.org/10.64898/2026.05.07.723685doi: bioRxiv preprint \n\nSSN may be predictive of \nelicitor identity. To identify \ncandidate TetR-family \nregulators for elicitor \nscreening, we constructed a \nSSN using protein sequences \nfrom the antiSMASH \ndatabase (29) and clustered \nthem using the University of \nIllinois at Urbana-Champaign \nEnzyme Similarity Tool (30) \nand Cytoscape (31). Within \nthis network, JadR2 grouped \nwith several protein \nhomologs, suggesting \npotential functional \nconservation (Fig 3). Four \nrepresentative homologs from \nthis cluster were selected for \nfurther study based on the \npercent identity to JadR2. \nThese homologs were derived \nfrom Streptomyces \nglobisporus, Streptomyces \nexfoliatus, Streptomyces \nbicolor and Streptomyces \nbaarensis. Sequence \nalignment revealed \nconservation within the \npredicted DNA-binding \ndomain and divergence in \nregions corresponding to the \nligand-binding domain (Fig 4). \n \nHomologs of JadR2 \nselected from SSN for \nfurther study. We next \nevaluated the activity of \nJadR2 homologs in the \nreporter system. Four \nhomologs were selected from \nthe SSN JadR2 cluster \ndisplaying varying degrees of \nsequence homolog (Fig 4). \nThree homologs repressed \nEGFP expression following \nIPTG induction, indicating \nconserved DNA-binding \nactivity (Fig 5A). Treatment \nwith Cm resulted in increased \nEGFP expression for the \nsame three homologs, \nFigure 3 SSN reveals JadR2 homologs selected for use in study. \nSSN of all TetR proteins from Streptomyces. Arrow pointing to the cluster in \nwhich JadR2 from S. venezuelae groups. \nPercent idenƟ ty to SV JadR2  \n80% \n 50% \nFigure 4 JadR2 Homologs with varying degrees of sequence homology \nselected.  \nJadR2 homologs from S. globisporus (80% homology), S. exfoliatus (79% \nhomology), S. bicolor (64% homology) and S. baarensis (54% homology) were \nused for elicitor screening. Protein structure predicted using AlphaFold3 and \nregions of divergence were mapped in their respective color.  \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 8, 2026. ; https://doi.org/10.64898/2026.05.07.723685doi: bioRxiv preprint \n\nalthough the magnitude of response varied. One homolog did not respond under the tested conditions \n(Fig 5B). These results identify three previously uncharacterized elicitor-regulator pairs involving Cm \nresponsive TetR homologs. This demonstrates that sequence similarity can be used to prioritize \nregulators for elicitor screening and supports the use of heterologous reporter systems for functional \nannotation of transcription factors.   \nA \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 8, 2026. ; https://doi.org/10.64898/2026.05.07.723685doi: bioRxiv preprint \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \nDISCUSSION \nIn this study, we combined sequence similarity network analysis with a heterologous reporter system \nto investigate elicitor responsiveness among TetR-family regulators. Using JadR2 as a benchmark, we \ndemonstrate that both repressor activity and elicitor responsiveness are maintained outside the native \nStreptomyces host. Furthermore, three homologs of JadR2 were able to repress transcriptional activity \nby binding to the native JadR2 operator sequence, characterized by a reduction in EGFP expression. \nAdditionally, those three homologs responded to Cm, characterized by a return of EGFP expression. \nThese experiments expand the number of known elicitor-regulator relationships and highlight the use \nof SSNs as a predictive tool for elicitor discovery.  \nThese findings support that regulators within biosynthetic gene clusters may be conserved across \nspecies, even if the biosynthetic gene cluster they regulate may differ. Hundreds of TetR family \nregulators are encoded across Streptomyces genomes and most lack functional annotation. Strategies \nthat enable prioritization of likely elicitors are essential for leveraging the elicitor-regulator pair \nrelationship to induce expression of silent BGCs, enabling the discovery of novel natural products. Our \napproach addresses a key limitation of traditional elicitor discovery methods such as untargeted small \nmolecule screening, where changes in metabolite production can be difficult to attribute to specific \nFigure 5. A. IPTG-induced JadR2 and JadR2 homolog expression represses EGFP expression via promoter \nbinding. Bar heights reflect EGFP signal normalized to OD600 at 4 hours post-IPTG treatment.  B. Cm treatment \nrestores EGFP expression after IPTG induced expression of J adR2 and homologs. Bar heights reflect EGFP \nsignal normalized to OD600 at 4 hours post-Cm treatment. \nB \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 8, 2026. ; https://doi.org/10.64898/2026.05.07.723685doi: bioRxiv preprint \n\ntranscription factors. By directly linking elicitors to their cognate regulators, this work establishes a \nregulator centered strategy that may allow predictions to extend across species. If homologous \nregulators share elicitor responsiveness, then small molecules identified in one organism may be used \nto activate silent biosynthetic gene clusters in related organisms without the need for genetic \nmanipulation or additional elicitor screening campaigns. \nThis concept is particularly valuable given the challenges associated with genetic engineering in many \nStreptomyces species(32). Traditional approaches to activating silent biosynthetic gene clusters \nfrequently involve overexpression of positive regulators, deletion of repressors, or changing promotors \nbut these methods require cloning, strain engineering, and species-specific optimization that can be \ntime consuming and ineffective. In contrast, elicitor guided activation offers a potentially more \naccessible alternative in which pathway activation may be achieved through targeted small molecule \ntreatment alone. As genome sequencing continues to reveal large numbers of cryptic biosynthetic gene \nclusters, approaches that eliminate the need for genetic manipulation could substantially accelerate \nnatural product discovery. \nThe observation that one JadR2 homolog did not repress EGFP expression or respond to \nchloramphenicol highlights an important limitation of this strategy. Homologs must be able to bind to \nthe same sequence as a known regulator to reduce EGFP expression to test elicitor specificity. While \nsequence similarity can narrow the search for regulators with shared function, DNA or ligand specificity \nmay still diverge due to subtle differences in ligand binding domains or regulatory context. This result \nhighlights the importance of experimental validation while also suggesting that sequence similarity \nnetworks may be most powerful as prioritization tools rather than definitive predictors of function. \nIntegration of computational transcription factor binding site prediction tools such as COMMBAT(33) \nmay be able to address this limitation by enabling rapid identification of transcription factor binding sites \nfor uncharacterized regulators. Integration of computational DNA-binding site predictions with \nheterologous elicitor screening could rapid discovery of novel elicitor-regulator pairs from genome \nsequence alone. \nSeveral limitations of this study provide opportunities for future work. First, this study focused on a \nsingle elicitor. Broader chemical screening will be necessary to fully define ligand specificity across \nhomologous regulators. Second, although the E. coli reporter system provides a tractable platform for \nidentifying elicitor responsiveness, regulatory behavior in native Streptomyces hosts may be influenced \nby additional transcription factors and other regulatory mechanisms. Third, while the reporter assay \nmeasures transcription factor regulatory activity, it does not directly confirm activation of natural product \nbiosynthesis. Future validation in native hosts will therefore be necessary to directly link elicitor \ntreatment to metabolite production. \nFuture work will expand this framework by incorporating additional regulator families, including GntR, \nMarR, and LysR regulators, which also play important roles in biosynthetic gene cluster regulation. \nExpanding SSN guided approaches across regulator families could provide a generalizable strategy \nfor studying elicitor-regulator relationships on a larger scale. In addition, combining this approach with \nmetabolomics and transcriptomics in native hosts will allow direct validation of pathway activation and \nimprove understanding of how elicitor responsiveness translates into chemical output. \nMore broadly, this work highlights the opportunity to integrate genomics, bioinformatics, and functional \nscreening to better understand microbial gene regulation. As the number of sequenced Streptomyces \ngenomes grows, the number of uncharacterized regulatory proteins does as well. Approaches such as \nthe one described here provide a path toward connecting these regulators with the small molecule \nelicitors that influence them. By enabling transfer of regulatory knowledge across species and reducing \nreliance on genetic manipulation, this strategy may help access the large reservoir of cryptic natural \nproducts encoded in Streptomyces genomes. \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprint (whichthis version posted May 8, 2026. ; https://doi.org/10.64898/2026.05.07.723685doi: bioRxiv preprint \n\nMATERIALS AND METHODS  \nSequence Similarity Network Analysis \nTetR-family regulator protein sequences were retrieved from antiSMASH annotations from predicted \nStreptomyces BGCs the antiSMASH database (downloaded Aug, 2020). A sequence file was submitted \nto the Enzyme Function Initiative Enzyme Similarity Tool (EFI-EST), and sequence similarity networks \n(SSNs) were generated at selected alignment score thresholds. Networks were visualized and \nprocessed in Cytoscape (v3.10.3). \nPlasmid Construction \nA reporter plasmid was constructed containing the DNA-binding sequence of interest upstream of \nEGFP, codon-optimized for expression in E. coli  (synthesized by Twist Bioscience). Expression \nplasmids encoding JadR2 or homologs were synthesized (Twist Bioscience) and placed under the \ncontrol of an IPTG-inducible promoter. Backbone plasmids were pTwist Amp Medium Copy and pET-\n28a(+), respectively. An expression plasmid lacking an insert was also generated to act as an empty \nvector control. \nThe upstream regulatory sequence used in the EGFP plasmid was derived from the intergenic region \nbetween jadR1 and jadR2 from the jadomycin biosynthetic gene cluster of S. venezuelae. To generate \nSV_Pro_EGFP_E.coli, this Streptomyces promoter region was modified upstream of EGFP to optimize \nexpression in an E. coli  host. The engineered sequence introduced consensus bacterial promoter \nelements, including a -35 element (TTGACA) and a -10 element (TATAAC) separated by a 17-bp \nspacer. A Shine-Dalgarno-like ribosome binding site (GAGGAG) was positioned upstream of the EGFP \nstart codon. The EGFP coding sequence was unchanged.  \nBacterial Strains and Transformations \nAll experiments were performed in E. coli BL21 (DE3) strains were grown in EZ Rich Medium (EZRDM), \ncontaining 100 μg/ml carbenicillin and 50 μg/ml kanamycin as needed. Reporter and expression \nplasmids were double transformed using standard protocols. Successful double transformations were \nconfirmed by PCR with plasmid specific primers. \nFluorescence Reporter Assays \nOvernight cultures were grown in EZ Rich Defined Medium (EZRDM) at 37 °C with shaking at 250 rpm. \nCultures were diluted 1:10 into fresh EZRDM (5 mL) and grown to mid-log phase (OD 600 0.6-0.8). \nProtein expression was induced with 50 mM IPTG. EGFP fluorescence and OD 600 were measured in \n96-well plate using a plate reader at 2, 3, and 4 h post-induction. Each condition included three \nbiological replicates with and without IPTG. Fluorescence values were normalized to OD 600 to account \nfor differences in cell density. \nChemical Elicitor Assays \nFor elicitor testing, chloramphenicol (0, 1, or 5 mg/mL) was added one hour after IPTG induction. EGFP \nfluorescence and OD600 were monitored as described above. \nData Analysis and Statistics \nFluorescence data were analyzed after normalization to OD 600. Biological replicates (n = 3) were \naveraged, and values are reported as mean ± standard deviation unless otherwise indicated. Statistical \n.CC-BY 4.0 International licenseavailable under a \nwas not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. 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