Systematic engineering of synthetic serine cycles in Pseudomonas putida uncovers emergent topologies for methanol assimilation

Systematic engineering of synthetic serine cycles in Pseudomonas putida uncovers emergent topologies for methanol assimilation | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Systematic engineering of synthetic serine cycles in Pseudomonas putida uncovers emergent topologies for methanol assimilation Òscar Puiggené , Jaime Muñoz-Triviño , Laura Civil-Ferrer , Line Gille , Helena Schulz-Mirbach , Daniel Bergen , Tobias J. Erb , View ORCID Profile Birgitta E. Ebert , View ORCID Profile Pablo I. Nikel doi: https://doi.org/10.1101/2025.02.17.638773 Òscar Puiggené a The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark , Kongens Lyngby, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jaime Muñoz-Triviño a The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark , Kongens Lyngby, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Laura Civil-Ferrer a The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark , Kongens Lyngby, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Line Gille a The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark , Kongens Lyngby, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site Helena Schulz-Mirbach b Department of Biochemistry and Synthetic Metabolism, Max Planck Institute for Terrestrial Microbiology , Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Daniel Bergen c Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland , Brisbane, Queensland, Australia d Advanced Engineering Biology Future Science Platform , CSIRO, Brisbane, Queensland, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tobias J. Erb b Department of Biochemistry and Synthetic Metabolism, Max Planck Institute for Terrestrial Microbiology , Marburg, Germany e Center for Synthetic Microbiology (SYNMIKRO) , Marburg, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Birgitta E. Ebert c Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland , Brisbane, Queensland, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Birgitta E. Ebert Pablo I. Nikel a The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark , Kongens Lyngby, Denmark Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Pablo I. Nikel For correspondence: pabnik{at}biosustain.dtu.dk Abstract Full Text Info/History Metrics Supplementary material Preview PDF ABSTRACT The urgent need for a circular carbon economy has driven research into sustainable substrates, including one-carbon (C 1 ) compounds. The non-pathogenic soil bacterium Pseudomonas putida is a promising host for exploring synthetic methylotrophy due to its versatile metabolism. In this work, we implemented synthetic serine cycle variants in P. putida for methanol assimilation combining modular engineering and growth-coupled selection, whereby methanol assimilation supported biosynthesis of the essential amino acid serine. The serine cycle forms acetyl-coenzyme A from C 1 molecules without carbon loss but has bottlenecks that hinder engineering efforts. We adopted three synthetic variants (serine-threonine cycle, homoserine cycle, and modified serine cycle) that yield serine in a methanol-dependent fashion to overcome these challenges. By dividing these metabolic designs into functional modules, we systematically compared their performance for implementation in vivo . Additionally, we harnessed native pyrroloquinoline quinone-dependent dehydrogenases for engineering methylotrophy. Recursive rewiring of synthetic and native activities revealed novel metabolic topologies for methanol utilization, termed enhanced serine-threonine cycle, providing a blueprint for engineering C 1 assimilation in non-model heterotrophic bacteria. Download figure Open in new tab INTRODUCTION Climate change, driven by anthropogenic greenhouse gas emissions, poses an existential threat to virtually all species inhabiting planet Earth. Despite recurrent warnings from leading experts, a prevailing economy of overconsumption and affluence supported by inaction of governments and public institutions, especially in developed countries, exacerbated the climate crisis [ 1 ]. Mitigating this global crisis requires reducing current emissions, developing innovative CO 2 capture technologies, and efficiently transitioning to renewable energy sources [ 2 , 3 ]. The urgent need for global decarbonization and rising oil prices have spurred substantial research into alternative, sustainable substrates for industrial production. One-carbon (C 1 ) compounds, e.g., methanol and formate, are promising substrates for microbial bioproduction, as they can be derived from methane or CO 2 using renewable electricity or sunlight [ 4 – 9 ]. However, the model organisms typically used in bioprocesses, e.g., Escherichia coli or Saccharomyces cerevisiae , do not grow on C 1 compounds naturally (with the exception of the methylotroph Komagataella phaffii ) [ 10 ]. Methylotrophs, while capable of utilizing C 1 substrates, are notoriously difficult to metabolically engineer, and current product titers through natural C 1 assimilation pathways are far from industrial competitiveness [ 11 – 13 ]. The last decade witnessed major breakthroughs to achieve synthetic methylotrophy in a few model bacterial species ( E. coli and Cupriavidus necator ) [ 14 - 20 ] owing to the extensive knowledge about their metabolism, established genetic engineering toolsets, and potential for industrial applications [ 21 ]. Despite impressive progress in synthetic C 1 assimilation, designing and implementing efficient pathways for formatotrophy and methylotrophy remains a largely artisanal endeavor. This challenge is further compounded when engineering pathways in non-canonical organisms, for which knowledge of central carbon metabolism is limited. The soil bacterium Pseudomonas putida is a consolidated biotechnological host due to its enhanced tolerance to physicochemical stresses [ 22 – 25 ], availability of tools for genetic and genomic engineering [ 26 ], and potential for producing fine chemicals (e.g., new-to-nature products [ 27 – 29 ]) while valorizing waste streams [ 30 ]. Although P. putida does not naturally assimilate C 1 feedstocks, we recently showed that methanol, formaldehyde, and formate are oxidized through a set of convergent and peripheral dehydrogenases to generate reducing power [ 31 ], and we engineered synthetic formatotrophy in this species through the reductive glycine pathway (rGlyP) [ 32 ]. The versatile metabolism of P . putida , reflecting its extreme adaptability to diverse environments, makes this bacterium an ideal candidate for exploring synthetic methylotrophy, a capability that has yet to be realized. Unlike other bacteria previously engineered for methanol assimilation, P . putida encodes pyrroloquinoline quinone (PQQ)-dependent alcohol dehydrogenases (MeDHs) [ 33 ] that also recognize methanol. However, selecting an adequate set of reactions for methanol assimilation in a non-canonical bacterium is a daunting task. The architecture of the central carbon metabolism in P . putida , comprising the EDEMP cycle, the tricarboxylic acid (TCA) cycle, and the pyruvate shunt, provides an attractive biochemical template to engineer cyclic C 1 assimilation pathways [ 34 – 36 ]. The serine cycle (SC) is a natural oxygen-insensitive pathway mediating acetyl-coenzyme A (CoA) synthesis directly from C 1 molecules ( Fig. 1 a ) without carbon loss [ 37 – 39 ]. It was the first pathway identified in methylotrophic bacteria for methanol-dependent growth, yet the last to be fully characterized [ 40 ]. Several features make the SC a prime target for engineering C 1 assimilation in strictly aerobic heterotrophs (e.g., P . putida ), including (i) autocatalytic nature, which could support substantial growth, (ii) operation at ambient CO 2 conditions, (iii) oxygen tolerance, and (iv) small number of heterologous genes required to establish the full cycle [ 41 ]. Additionally, a theoretical study concluded that the SC displays high energetic efficiency [ 42 ]. However, compared to other C 1 assimilation pathways, the SC is ATP- and NADH-demanding, yields the toxic intermediate 3-hydroxypyruvate [ 43 ], and requires some reactions (e.g., malyl-CoA synthetase and lyase) that could interfere with the native metabolism of the host [ 44 ]. Synthetic SC variants have been designed to overcome these hurdles ( Fig. 1 b–d ). These include the homoserine cycle (HSC), the most energy-efficient but requiring assimilation of two formaldehyde molecules ( Fig. 1 b ); the modified serine cycle (mSC), encompassing fewer enzymes and consuming less reducing power ( Fig. 1 c ); and the serine-threonine cycle (STC) that, in spite of requiring more energy ( Fig. 1 d ), highly resembles the CCM of most model organisms and could sustain formatotrophy in E. coli upon extended adaptive laboratory evolution (ALE) [ 41 , 45 , 46 ]. These three variants require less ATP and NAD(P)H than the natural cycle and bypass 3-hydroxypyruvate. However promising, these synthetic cycles have been only implemented in E . coli to different degrees of completion [ 45 – 47 ]. A concerted effort to systematically compare their operativity is missing, essential for guiding the engineering of non-canonical heterotrophs into methylotrophs. Download figure Open in new tab Figure 1. The native serine cycle and its synthetic variants for methanol assimilation. The (a) native serine cycle (SC) found in methylotrophic bacteria has been engineered as (b) the homoserine cycle (HSC), (c) the modified serine cycle (mSC), and (d) the serine-threonine cycle (STC). For enzyme abbreviations, see Table S1 . Dashed lines represent pooled reactions; orange-colored enzymes represent reactions exogenous to P . putida . (e) Number of enzymes (or reactions) [endogenous as darker colors and total amount as lighter and darker combined in each cycle] and (f) NAD(P)H and ATP costs calculated from methanol to acetyl-CoA via the shortest route (PycAB instead of PykA and Ppc) in the metabolic context of P . putida . One NADH equivalent has been factored to replenish the amino donor for each transamination event in the three modified serine cycles. (g) Max-min driving force (MDF) of the SC, HSC, mSC, and STC in comparison to the reductive glycine pathway (rGlyP) and ribulose monophosphate (RuMP) pathway. MDF were calculated with eQuilibrator-API [ 89 ] with and without NADH- or PQQ-dependent methanol dehydrogenases (no MeDH versus NADH-MeDH or PQQ-MeDH). No MeDH indicates the usage of formaldehyde as a substrate, thereby bypassing the thermodynamic constraints of methanol oxidation (especially with NAD-MeDH). Details on MDF calculations are provided in Table S2 . To address these challenges, in this work we implemented all synthetic variants of the SC in P. putida for methanol assimilation using modular engineering and growth-coupled selection. By dividing the three synthetic SC designs into functional modules, we systematically compared their performance to identify the most promising variant for in vivo implementation. Furthermore, we demonstrate that key extant biochemical activities, e.g., PQQ-dependent dehydrogenases and robust gluconeogenesis, can be harnessed for rational engineering of methylotrophy. This recursive rewiring of synthetic and native activities uncovered novel metabolic topologies, dubbed enhanced STC (eSTC), for efficient methanol utilization, providing a blueprint for engineering C 1 assimilation in non-model heterotrophic bacteria. RESULTS In silico analysis highlights the relevance of serine cycles for efficient methanol conversion To investigate the potential of all SC variants for synthetic methylotrophy in P . putida , we examined the pathway demands in terms of enzymes requirements ( Fig. 1 e , Table S1 ), ATP and NAD(P)H costs ( Fig. 1 f ), thermodynamics under physiological conditions, using maximum-minimum driving force (MDF) analysis ( Note S1 ), and predicted specific growth rates (μ) using flux balance analysis (FBA; Fig. 1 g , Tables S2 - S3 ). We compared the SC variants with each other and other pathways engineered for methanol assimilation, i.e., the rGlyP [ 14 , 32 , 48 ] and the ribulose monophosphate (RuMP) pathway [ 49 , 50 ]. All six pathways were modelled in the biochemical context of P. putida KT2440 ( Fig. 2 ), considering either methanol or formaldehyde as C 1 substrate. For methanol oxidation, either NADH- or PQQ-dependent MeDHs (with Δ r G′ = 34.2 and −24.8 kJ mol −1 , respectively) were included in the simulation ( Fig. 1 g and Table S2 ). Download figure Open in new tab Figure 2. Native metabolism of P. putida growing on glucose. The diagram shows the reactions around the amino acids serine, glycine, and threonine, critical for the serine cycles in this study. Enzyme abbreviations are indicated in Table S1 . The simulations showed a broader, favorable thermodynamic range for all SC variants (MDFs ∼7.5-9 kJ mol −1 ) compared to the rGlyP and RuMP pathways (MDFs ∼6-7 kJ mol −1 ). The HSC was the most thermodynamically favorable variant, whether using formaldehyde (i.e. No MeDH in Fig. 1 g ) or methanol with PQQ-dependent MeDHs, surpassing all other pathways by at least 2-fold ( Fig. 1 g and Table S2 ). Due to decreased alcohol oxidation performance by NADH-dependent MeDH, some pathways (e.g., the HSC or RuMP pathway) appeared less feasible. We also used MDF to identify thermodynamic bottlenecks in the SC variants ( Fig. S1 ). The primary bottleneck for all routes was predicted to be the condensation of glycine and 5,10-methylene-tetrahydrofolate (5,10-methylene-THF). For the HSC, the condensation of pyruvate and formaldehyde was the main thermodynamic barrier. Replenishing glycine from C 3 intermediates was another bottleneck for the STC, with oxaloacetate transamination and subsequent reactions being thermodynamically unfavorable ( Fig. 1 d and Fig. S1 ). These biochemical bottlenecks were addressed in designing the functional modules for synthetic C 1 assimilation. Next, FBA was used to investigate intrinsic differences among the SC variants to support C 1 -trophic growth ( Tables S3-S4 ). To this end, we curated the latest genome-scale metabolic model of P . putida KT2440 [ 51 , 52 ] and added the synthetic reactions for C 1 assimilation in each pathway [ 53 ]. The natural SC and the mSC, with similar energy and NAD(P)H demand ( Fig. 1 e–f ), predicted similar specific growth rates that correlated with their favorable thermodynamics ( Table S3 ). Formate oxidation (i.e., metabolic turnover , with CO 2 emission as proxy) reflected the energetic demand of the corresponding cycle variant, as formate oxidation was only required for NAD(P)H generation. The STC supported the slowest growth among all variants tested, reflecting its unfavorable thermodynamics. Furthermore, the HSC, as the most energy-efficient variant, surpassed the performance of the natural SC ( Table S3 ). These results indicate that engineering the SC and its synthetic variants in P . putida is not only possible but also favored by the presence of native PQQ-dependent alcohol oxidation that could facilitate methylotrophy. A detailed FBA comparison of individual modules is discussed in the corresponding sections below. Growth-coupled selection schemes and modular testing of serine cycles P.inputida To standardize the comparison of each SC, we employed growth-coupled selections [ 54 ] and modular engineering in strain SEM11 [ 55 ], a genome-reduced derivative of wild-type P. putida KT2440 [ 56 ]. We first identified structural commonalities among the three SC variants to generate different functional modules ( Fig. 3 ). Module 1 (M 1 ) encompasses the assimilation of a C 1 moiety from glycine to serine, whereas module 2 (M 2 ) closes the cycle by transforming pyruvate back to glycine, including another round of carbon assimilation ( Fig. 3 ). Serine and glycine auxotrophs were designed to test C 1 assimilation by M 1 , while serine, acetyl-CoA, or homoserine auxotrophies were implemented to select M 2 . All selection schemes were designed in silico , utilizing FBA to explore the long-term stability of the metabolic interventions prior to engineering efforts ( Table S5 ). A detailed roadmap of all modifications implemented in P . putida SEM11, including gene deletions, gene insertions, and overexpression of genes from the chromosome or in plasmids, is presented in Fig. S2 . Download figure Open in new tab Figure 3. Metabolic maps for the three modified serine cycles implemented for synthetic C 1 assimilation. The modified serine cycle (mSC, left), the serine-threonine cycle (STC, middle), and the homoserine cycle (HSC, right) have been split into two modules. Module 1 (M 1 ) comprises the assimilation from glycine to serine, and Module 2 (M 2 ) involves the production of glycine from pyruvate. M 2 was also split into sub-modules, which are represented in the lower part of the figure. All reactions and their cognate genes are listed in Table S1 . Dashed lines represent pooled reactions; yellow-colored arrows represent reactions exogenous to P. putida . Designing, building, and testing M 1 — Formate and formaldehyde assimilation inLt-oserine The assimilation of C 1 moieties via THF requires expression of ftfL (formate-THF ligase), fch (methenyl-THF cyclohydrolase), and mtdA (5,10-methylene-THF dehydrogenase) from Methylobacterium extorquens AM1, producing 5,10-methylene-THF [ 32 ]. M 1 requires 1 NADPH and 1 ATP for each formate assimilated as part of the mSC and the STC ( Fig. 1 c–d and Fig. 3 ). Threonine aldolases can utilize formaldehyde for glycine aldolization to serine (serine aldolase), required for the HSC [ 20 ], in an ATP and NAD(P)H-independent fashion. Since methanol (rather than formate) was our target substrate, MeDH genes should be overexpressed to provide formaldehyde, generating one reducing equivalent (NADH or PQQH 2 ) per methanol oxidized. Endogenous oxidation activities in P . putida [ 31 ] catalyze the subsequent oxidation of formaldehyde to formate, as required for the mSC or STC. In silico analysis indicated that M 1 could support methylotrophic growth via the mSC/STC and HSC configurations with similar performance with glucose as cosubstrate ( Tables S6 and S7 ). At high methanol uptake rates, M 1 of the HSC (henceforth referred to as M 1 ·HSC) was predicted to outperform the M 1 ·mSC/STC ( Table S4 ). Based on these designs, we constructed a strain that can support C1 assimilation through M 1 ·HSC. A low specificity l -threonine aldolase [ 1 M·HSC] restores growth of a serine and glycine auxotroph We constructed a serine and glycine auxotroph ( serA glyA) to select a l -serine aldolase activity, further deleting frmAC ( PP_1616-7 ) to avoid formaldehyde detoxification at low methanol concentrations [ 31 ]. The resulting strain ( P . putida serA glyA frmAC) was transformed with a low-copy-number plasmid (pSEVA621 [ 57 , 58 ]) constitutively expressing Ec ltaE and the CT4-1 methanol dehydrogenase gene from C. necator ( Cn mdh ), engineered to display enhanced activity [ 59 ]. Control plasmids harboring only Ec ltaE or Cn mdh were also tested ( Fig. 4 b ). The serine pool in the serA glyA frmAC strain incubated in de Bont minimal (DBM) medium with 20 mM glucose, 10 mM glycine, and 250-500 mM methanol was replenished, relieving the auxotrophy, when Ec ltaE and Cn mdh were overexpressed ( Fig. 4 ), supporting μ ∼ 0.3 h −1 ( Fig. 4 c ). As expected, plasmid pSEVA621· Cn mdh alone did not revert the auxotrophy. Expressing Ec ltaE alone supported growth when serine was supplied ( Fig. 4 b ), and we concluded that Ec LtaE can cleave serine to glycine and formaldehyde. Furthermore, overexpressing Ec ltaE alone promoted growth at high methanol concentrations ( Fig. 4 b – c), which we attribute to several endogenous, broad-range alcohol dehydrogenases acting on methanol at > 250-500 mM [ 31 ]. Encouraged by the activity of Ec LtaE as l -serine aldolase, we assessed whether LtaEs from other species could provide higher catalytic activities. Download figure Open in new tab Figure 4. Testing M 1 of the homoserine cycle in P. putida . M 1 ·HSC relies on the formaldehyde-assimilative l -serine aldolase (SAL) reaction via the side-reaction of LtaE from E. coli. (a) The auxotrophic strain serA glyA frmAC was employed to test the capacity of Ec ltaE to assimilate formaldehyde and glycine into serine. (b) Structure of plasmid maps used to relieve the auxotrophy (pS621· Cn mdh· Ec ltaE), including the control vectors pS621· Cn mdh and pS621· Ec ltaE, and growth profile of the serA glyA frmAC strain carrying such plasmids in DBM medium supplemented with 20 mM glucose and serine, glycine, or methanol as indicated. A canonical RBS was used (5’-AGG AGG AAA AAC AT-3’) in these constructs. Both (b) cell densities (estimated as the optical density measured at 600 nm, OD 600 ) and (c) specific growth rates (μ, h −1 ) are indicated as average values ± standard deviation of three biological replicates. Individual data points are shown whenever relevant. Ec LtaE outperforms a library of aldolase variants for formaldehyde assimilation We used P . putida serA glyA frmAC as selection strain to test a library of low-specificity l -threonine aldolases, encompassing variants from heterotrophic bacteria ( E. coli, P. putida , and Vibrio natriegens ), C 1 -trophic bacteria ( M. extorquens AM1 and C. necator ) and yeast ( K. phaffii ), and heterotrophic yeasts ( S. cerevisiae and Yarrowia lipolytica )( Fig. S3 ). The ltaE variants were individually expressed in a pSEVA621 backbone alongside Cn mdh , and the ΔserA glyA frmAC strain harboring the plasmid library was tested in DBM medium with 20 mM glucose, 10 mM glycine, and 60-500 mM methanol ( Fig. S3 ). Ec LtaE outperformed all other variants, and only the enzymes from E. coli , V. natriegens , and Y. lipolytica supported l -serine aldolase activity ( Fig. S3 ). Moreover, all LtaE variants executed the reverse aldolase reaction (serine to glycine and formaldehyde), enabling growth when serine was supplied. Hence, Ec LtaE was retained for further engineering SC variants in P. putida . Rewiring the transcriptional regulation of genes encoding PQQ-dependent, broad-range alcohol dehydrogenases The growth of the engineered P . putida strain at high methanol concentrations in the absence of exogenous MeDH s expressed ( Fig. 4 ) could be attributed to endogenous broad-range alcohol dehydrogenases. This oxidative activity has been previously linked to PedE and PedH, two periplasmic, PQQ-dependent MeDHs that utilize calcium (Ca 2+ ) and rare-earth elements (REEs, usually lanthanides, La 3+ ) as cofactors, respectively [ 33 ]. The expression of the ped cluster is tightly regulated and activated by several alcohols and the presence of REEs [ 60 – 62 ]. PedE and PedH exhibit complementary functions depending on cofactor availability: pedE is expressed when short-chain organic alcohols are supplemented in the absence of REEs [ 62 ], whereas pedH is expressed in the presence of La 3+ ( Fig. 5 b ). YiaY (PP_2682) has been recently proposed to act as a transcriptional activator for the ped cluster alongside downstream neighboring histidine kinase, PP_2683 [ 61 ]. Together, they resemble the signaling system for ethanol oxidation in P. aeruginosa , the two-component system ErcAS [ 61 ]. To test if we could use the endogenous MeDHs for synthetic methylotrophy, we investigated the transcriptional regulation of pedE and pedH in a strain constitutively expressing yiaY ( Fig. 5 a ). We transformed wild-type P . putida and its P yiaY ::P 14G (BCD10) derivative with reporter plasmids harboring the promoters of pedE , pedH , and yiaY cloned in front of a monomeric superfolder GFP ( msfGFP ) gene ( Fig. 5 c ). By recording msfGFP fluorescence under different cultivation regimes, we aimed to understand the regulatory effect of YiaY on the transcription of the pedE , pedH , and yiaY genes. Download figure Open in new tab Figure 5. Constitutive expression of native PQQ-dependent alcohol dehydrogenase genes via yiaY overexpression. (a) Organization of the ped cluster, including the two PQQ-dependent MeDHs pedE and pedH, a putative NAD-MeDH, and the yiaY regulator with its downstream neighbor PP_2683. Constitutive expression of yiaY was achieved by promoter engineering. (b) Simplified regulatory model scheme for the ped cluster based on Wehrmann et al. [ 62 ] and Bator et al. [ 61 ], including the potential regulatory function of YiaY as a methanol sensor. Downstream in the signaling cascade, the presence of rare-earth elements (REEs, e.g., lanthanide salts, La 3+ ) modulates the activity of PedE and PedH. (c) Biosensor plasmids, harboring a monomeric superfolder GFP gene (msfGFP) expressed by the native promoters of yiaY, pedE or pedH, or a dummy promoter (negative control). (d) Normalized fluorescence plots (arbitrary units, A.U., normalized to the optical density at 600 nm, OD 600 ) for strains EM42 P yiaY ::P 14G (BCD10), with yiaY overexpression, or the wild-type (WT) control, harboring the biosensor plasmids shown in panel (c). All strains were grown in DBM medium with 20 mM glucose supplemented with formate (for), methanol, or sarcosine (sarc, used as a formaldehyde donor). (e) Same as in panel (d), but with the additional supplementation of LaCl 3 at 10 nM. Average values for normalized fluorescence ± 95% confidence intervals of at least three biological replicates are represented in all cases, together with individual data points. Statistical analysis indicated P-values < 0.05 for all pairwise comparisons where error bars do not overlap. The reporter strains were grown in DBM medium with 20 mM glucose and varying concentrations of C 1 molecules (i.e., formate, methanol, or formaldehyde derived from sarcosine) in the presence or absence of LaCl 3 as REE ( Fig. 5 d–e ). In the wild-type strain, pedE expression strongly depended on the methanol or formaldehyde (sarcosine) concentration when REEs were absent ( Fig. 5 d ). However, pedE was expressed at high levels with constitutive yiaY expression, regardless of the methanol or formaldehyde concentration ( Fig. 5 d ). A similar trend was observed for pedH in the presence of 10 nM LaCl 3 , where constitutive yiaY expression resulted in a 1.5- to 3-fold increase in pedH expression with varying methanol or formaldehyde levels ( Fig. 5 e ). Hence, YiaY (and possibly PP_2683) orchestrates a transcriptional response that regulates PQQ-MeDHs in a C 1 substrate-dependent manner, overcoming the regulatory effect of REEs. Hence, constitutively overexpressing yiaY upregulated PQQ-MeDH– encoding genes independently of the C 1 substrate, which provides a basis for further engineering efforts. Endogenous PQQ-dependent methanol dehydrogenases provide formaldehyd 1 ·eST[MC·mSC] To implement M 1 of the STC, shared with the mSC ( Fig. 1 c–d ), we integrated the C 1 assimilation module in the phaC1ZC2DFI locus of strain SEM11, resulting in P . putida serA gcvTHP pha::ftfL-mtdA-fch (termed ΔSGG-C 1 ; Fig. 6 a ). In initial experiments, we assessed if the pool of methylated THF and, subsequently, serine could be restored in strain ΔSGG-C 1 incubated in DBM medium with 20 mM glucose, 10 mM glycine, and varying formate concentrations ( Fig. 6 b ). This was indeed the case, with specific growth rates and maximum cell density (optical density at 600 nm, OD 600 ) of μ ∼ 0.6 h −1 and 2.5-3, respectively; similar to the values observed when supplementing glycine and serine (positive control, Fig. 6 c ). Download figure Open in new tab Figure 6. Testing the assimilative M 1 of the serine-threonine and modified serine cycles via the C 1 moiety-carrier molecule tetrahydrofolate (THF). (a) The auxotrophic serA gcvTHP strain (termed ΔSGG) was employed to test one-carbon (shown as C 1 ) assimilation via FtfL, Fch, and MtdA. Such assimilation pathway was introduced in the genome at the phaC1ZC2DFI locus under the expression of a strong P 4 promoter (indicated as P 4 *). Methanol oxidation was facilitated by plasmid-based overexpression of different endogenous methanol dehydrogenases (MeDH, indicated as M). (b) Growth profile of strain ΔSGG-C 1 in DBM medium supplemented with 20 mM glucose, 10 mM glycine and, when appropriate, 10 mM serine (positive control) or 30-60 mM formate. (c) Specific growth rates for the experiments shown in panel (b). (d) Plasmid maps for overexpressing methanol dehydrogenases (MeDH) genes in the ΔSGG-C 1 strain (yielding ΔSGG-C 1 -M). (e) Maximum cell density (optical density measured at 600 nm, OD 600 ) and specific growth rates of strain ΔSGG-C 1 -M with MeDH overexpression (yiaY, pedE, and pedH) compared to an empty vector (eV). Strains were grown in DBM medium with 20 mM glucose and 10 mM glycine, as well as varying concentrations of methanol, or 60 mM formate as a positive control [as shown in panel (b)]. When indicated, 10 nM LaCl 3 was tested as a cofactor for the PQQ-dependent alcohol dehydrogenase PedH. Average values for cell densities (OD 600 ) and specific growth rates (μ, in h −1 ) ± standard deviation of three biological replicates are represented in all cases; individual data points are shown whenever relevant. A library of native and heterologous MeDH genes, constitutively expressed from a pSEVA621 backbone as explained in the previous section, was tested in strain ΔSGG-C 1 to explore synthetic methylotrophy at different substrate levels ( Fig. 6 d , Fig. S4 d). Incubating these strains in DBM medium with 20 mM glucose, 10 mM glycine, and 15-500 mM methanol revealed that NADH-dependent MeDHs, e.g., Bs Mdh, Cn Mdh, Bm Mdh2, or the native AdhP had no activity below 125 mM methanol, compatible with previous reports [ 63 – 66 ]. Moreover, strain ΔSGG-C 1 harboring these NADH-dependent MeDHs grew slowly, with μ < 0.25 h −1 ( Fig. S4 d). In contrast, overexpressing xoxFGJ , encoding a PQQ-dependent MeDH from M. extorquens AM1 [ 67 ], resulted in higher cell densities (OD 600 ∼ 3) at low methanol concentrations, with similar μ values as supported by NADH-MeDHs ( Fig. S4 ). The native PQQ-dependent, broad-range alcohol dehydrogenases [ 33 ] were also tested ( Fig. 6 d–e ). We overexpressed pedE , pedH , and yiaY from a plasmid in strain ΔSGG-C 1 ( Fig. 6 d–e ), incubated in DBM medium with 20 mM glucose, 10 mM glycine, and 15-500 mM methanol. Strains overproducing PedH and YiaY outperformed all NADH-dependent MeDHs ( Fig. S4 ) in the presence of LaCl 3 , with μ ∼ 0.35 h −1 and reaching OD 600 > 3 ( Fig. 6 e ). Whilst PedE did not promote growth, alcohol oxidation in the strain carrying the empty vector occurred at high methanol concentrations, especially when lanthanides were present. Without added LaCl 3 , yiaY overexpression still promoted similar specific growth rates but the cell density was lower (OD 600 ∼ 1.5, Fig. 6 e ), indicative of pedE upregulation and pedH repression [ 33 ]. These experiments confirm that sufficient methanol oxidation to formaldehyde can be achieved through the endogenous PQQ-dependent dehydrogenases of P. putida viayiaY overexpression—even more efficiently than with NADH-dependent MeDHs, typically used in metabolic engineering of C 1 assimilation. Designing, building, and testing M 2 — C 3 carboxylation and replenishment of the glycine pool by C 4 cleavage Given that l -serine deamination to pyruvate is an activity native to P. putida , we focused on implementing M 2 for converting pyruvate to glycine. Serine or glycine auxotrophs (Δ serA or ΔΔ glyA ) were used for selection, yet the glycine auxotroph had growth defects, and we adopted the serine auxotroph for testing the activity of M 2 . Glycine, formed from pyruvate by M 2 , is used for l -serine synthesis via the endogenous GcvTHP and GlyA activities. Hence, a serine auxotroph would only grow if M 2 provides glycine from C 1 assimilation. Also, carbon assimilation relies on pyruvate condensation with a C 1 moiety. In the mSC and STC, this carboxylation could proceed with HCO 3 − via the native pyruvate carboxylase (PycAB) and/or PEP carboxylase (Ppc). In the HSC, in contrast, a non-native reaction condenses pyruvate with formaldehyde to produce 4-hydroxy-2-oxobutanoate (HOB, Fig. 1 b–d , Fig. 3 ). HOB is transaminated to homoserine, subsequently phosphorylated and hydrated to l -threonine ( Fig. 1 b , Fig. 3 ). This amino acid is broken down into glycine and acetaldehyde, and the C 2 pool is used for growth via activation to acetyl-CoA. M 2 of the HSC requires 3 ATP per acetyl-CoA formed. The STC partly relies on the same circularization as indicated for the HSC (i.e., homoserine to glycine), except that homoserine is produced via l -aspartate, stemming from oxaloacetate. This pathway is endogenous to P. putida yet has a high energy and reducing power cost, with a total of 5 ATP and 2 NAD(P)H per acetyl-CoA formed ( Fig. 1 d , Fig. 3 ). The mSC resembles the natural SC, where PEP (or pyruvate) is carboxylated to oxalacetate and reduced to malate, reversing the TCA cycle. Malate is then activated to malyl-CoA and broken down into glyoxylate and acetyl-CoA ( Fig. 1 c , Fig. 3 ). While acetyl-CoA is assimilated into biomass, glyoxylate replenishes glycine by transamination. This M 2 requires 2 NADH, but only 2 ATP per acetyl-CoA formed. Our FBA simulations indicated that C 3 carboxylation and glycine replenishment via the different M 2 configurations could occur efficiently in all three SC designs ( Tables S6 - S7 ), with the mSC outperforming the STC and HSC. The predicted growth rate for the HSC was the slowest among the cycles due to enforcement of the homoserine auxotrophy (i.e., blocking anaplerotic pathways) that compromises glycine regeneration if intermediates within the module are drained to support growth (e.g., homoserine or l -threonine; Tables S3 - S4 ). The next step was to compare the three module variants in vivo to regenerate glycine from the C 3 pool. Glycine from the C 3 pool via the endogenous serine-threonine cycle module [ 2 M·STC] Theoretically, P. putida could support the STC via oxaloacetate (carboxylating the C 3 pool, e.g., pyruvate or PEP from the EDEMP cycle), l -aspartate, homoserine, l -threonine, and glycine via the endogenous LtaE. However, the serA or glyA auxotrophs could not grow in DBM medium with glucose, indicating that this pathway connectivity is either inactive or does not carry enough flux to support growth. Hence, we initially overexpressed the native l -threonine aldolase ( Pp LtaE), encoding the final step in the cycle, in the serA or glyA strain ( Fig. 7 a ). The native LtaE was unable to replenish the pool of serine ( Fig. 7 b–c ) or glycine ( Fig. 7 d ) at the endogenous expression levels in DBM medium with 20 mM glucose. Growth was restored when supplemented with 10 mM l -threonine or homoserine. Overexpressing Pp ltaE supported growth of both Δ serA and ΔΔ glyA auxotrophs under all cultivation conditions ( Fig. 7 a–e ). P . putida SEM11Δ serA overexpressing Pp ltaE grew at μ ∼ 0.25 h −1 and reached OD 600 ∼ 2 ( Fig. 7 b–c ), while P . putida ΔΔ glyA transformed with the same plasmid grew as fast but reached half the maximum OD 600 . Hence, overexpression of the endogenous Pp ltaE proved sufficient to promote flux from the C 3 pool to glycine through M 2 ·STC. Download figure Open in new tab Figure 7. Testing M 2 of the serine-threonine cycle to yield glycine or serine from the C 3 and C 4 pool. (a) Growth of a ΔserA mutant in DBM medium supplemented with 20 mM glucose to test serine production from glycine, l -threonine, and homoserine, with or without constitutive overexpression of Pp ltaE in a pSEVA221 vector (pS221), compared to an empty vector (eV). (b) Testing the same conditions as in panel (a) but directly from glucose, which yields pyruvate or PEP. (c) Specific growth rates corresponding to the experiments plotted in panels (a) and (b). (d) Growth of a ΔΔglyA mutant in DBM medium supplemented with 20 mM glucose to test glycine production from l -threonine or glucose, with or without constitutive overexpression of Pp ltaE compared to an empty vector (eV). (e) Specific growth rates corresponding to the experiments plotted in panel (d). Average values for bacterial growth (estimated as the optical density measured at 600 nm, OD 600 ), and specific growth rate (μ, in h −1 ) ± standard deviation of three biological replicates are represented in all cases. Individual data points are shown in all cases. Except for glycine supplementation in panel (c), all comparisons were statistically significant with P-values < 0.01. HOB transaminase occurs endogenously inP. putida [M 2 ·HSC] M 2 of the HSC produces HOB via a HOB aldolase (HAL), followed by transamination to homoserine by a HOB transaminase (HAT) ( Fig. 1 b , Fig. 3 , Fig. 8 ). Homoserine is converted into glycine via l -threonine, yielding acetyl-CoA in the same manner as within the STC ( Fig. 7 ). To test HAT and HAL activities, we constructed a homoserine auxotroph ( Fig. 8 a , Fig. S5 ). Rather than merely eliminating Asd (aspartate-semialdehyde dehydrogenase, which requires diaminopimelate supplementation [ 20 ]), we deleted hom and PP_0664 (encoding homoserine dehydrogenase). The resulting P . putida strain, Δ hom Δ PP_0664 , was auxotrophic for homoserine. With this selection strain, we tested whether HOB transaminase activity is endogenous to P. putida . We screened a set of genes encoding putative HATs ( aspC , alaC A142P Y275D , and ilvE from E. coli ; and ilvE from P. putida KT2440) constitutively expressed in a pSEVA221 vector as explained in the previous sections ( Fig. S5 a). This HAT library was introduced in P . putida SEM11 Δ hom Δ PP_0664 , and the cells were grown in DBM medium with 20 mM glucose, supplemented with 2 mM homoserine or HOB ( Fig. S5 b). None of the overexpressed putative HAT genes supported a substantial increase in growth parameters, except for a slightly higher μ in cells transformed with the Ec aspC or Ec ilvE constructs ( Fig. S5 c). Moreover, overexpression of either E. coli gene was detrimental when homoserine was supplemented ( Fig. S5 b–c). In view of these results, we decided to proceed without HAT upregulation and rely on the endogenous transaminase activity. Download figure Open in new tab Figure 8. Screening of HOB aldolase activity. (a) Strain Δhom PP_0664 (lacking homoserine dehydrogenase activity) was employed as a homoserine auxotroph to identify candidates that perform the HOB aldolase (HAL) activity coupled to transamination. Formaldehyde can be produced from methanol via MeDHs or from sarcosine via the soxBDAG operon of P. putida. (b) Structure of the plasmids used to overexpress the CT4-1 MeDH from C. necator ( Cn mdh) and three putative HOB aldolase genes (yfaU, garL, and yjhH from E. coli) as compared to an empty vector control. (c) Growth profiles of the selection strain Δhom PP_0664 in DBM medium with 20 mM glucose supplemented with 3 mM 4-hydroxy-2-oxobutanoate (HOB), 60 mM sarcosine, or 500 mM methanol. The tested strains harbor the pSEVA621 plasmids constitutively overexpressing Cn mdh as well as the different HAT candidates or the empty vector (eV) control. (d) Growth rates corresponding to the growth profiles indicated in panel (c). Average values for bacterial growth (estimated as the optical density measured at 600 nm, OD 600 ), and specific growth rate (μ, in h −1 ) ± standard deviation of three biological replicates are represented in all cases and individual data points are shown. GarL fromE. coli can act as a HOB aldolase inP. putida [M 2 ·HSC] The next step was selecting a suitable HAL by screening a library of putative HAL genes cloned in pSEVA621 and constitutively expressed alongside Cn mdh ( Fig. S6 a, Fig. 8 a–b ). We tested aldolases that use pyruvate as a substrate from different heterotrophic bacteria, i.e., GarL, YfaU, YjhH, and DapA from E. coli ; GllC, PanB, PP_1791, and Eda from P. putida ; and HpaI from P. aeruginosa . P . putida Δhom PP_0664 containing the library of aldolase genes was grown on DBM medium with 20 mM glucose, supplemented with 3 mM HOB (positive control), 60 mM sarcosine (as a source of formaldehyde), or 500 mM methanol. Methylotrophic growth was only observed with Ec garL overexpression (μ ∼ 0.15 h −1 and maximum OD 600 ∼2.5) and partially for Pp panB with 60 mM sarcosine ( Fig. S6 –b, Fig. 8 c–d ). No candidate showed growth in methanol ( Fig. 8 c ). Since sarcosine, a source of intracellular formaldehyde, also yields glycine, we did not test the entirety of M 2 ·HSC. Nevertheless, the homoserine-to-glycine submodule has already been shown to be active in M 2 ·STC regardless of LtaE upregulation ( Fig. 7 a–c ). Thus, combining the previous efforts could drive enough flux through the HOB aldolase from methanol, resulting in full activity of M 2 ·HSC in P. putida . Heterologous expression of alanine-glyoxylate transaminase complements the glycine and serine auxotrophy [M 2 ·mSC] M 2 of the mSC relies on carboxylation of pyruvate or PEP to oxalacetate, oxidation to malate, and activation to malyl-CoA by malate thiokinase (Mtk). Malyl-CoA is then broken down into acetyl-CoA and glyoxylate by malyl-CoA lyase (Mcl). Glyoxylate is finally transaminated into glycine by alanine-glyoxylate transaminases (Agt, Fig. 1 c ). Since Agt, Mtk, and Mcl are exogenous to P. putida , we first targeted the submodule for glyoxylate transamination and explored Agts from H. sapiens ( Hs agxt1 ), S. cerevisiae ( Sc agx1 ), and P. denitrificans ( Pd bhcA ), as well as thiO from P. putida ( Fig. 9 a ). The four candidates were constitutively expressed in a pSEVA221 backbone in the glycine and serine auxotroph ( P . putida Δ serA ). The resulting strains were grown in DBM medium with 20 mM glucose, supplemented with 10 mM glycine or glyoxylate ( Fig. 9 b ). Except for Pp thiO , the three Agts complemented the glycine and serine auxotrophy. Among these, Sc agx1 performed best with μ ∼ 0.25 h −1 and a cell density of OD 600 ∼ 2.5 with glyoxylate supplementation ( Fig. 9 b–c ). We proceeded with this variant to implement the entire M 2 of the mSC. Download figure Open in new tab Figure 9. Heterologous transamination from glyoxylate to glycine, as well as expression of malate thiokinase and malyl-CoA lyase, rescues glycine and serine auxotrophy. (a) A ΔserA strain was employed as a serine-glycine auxotroph to identify AGT candidates that perform the alanine-glyoxylate transamination. (b) Structure of plasmids used to overexpress putative AGT genes (thiO from P. putida, agxt1 from H. sapiens, agx1 from S. cerevisiae, and bhcA from P. denitrificans). (c) Growth profiles of the ΔserA selection strain in DBM medium with 20 mM glucose supplemented with 10 mM glycine or 10 mM glyoxylate. The tested strains harbor pSEVA221 plasmids constitutively overexpressing AGT candidates or the empty vector (eV) control. (d) Growth rates corresponding to the growth profiles shown in panel (c). (e) Metabolic map of the auxotrophic strain ΔltaE glyA used as a glycine and C 1 auxotroph to test malyl-CoA lyase (Mcl) and malate thiokinase (MtkAB) activities. (f) Structure of the plasmid used to overexpress mtkBA and mcl under control of the P trc promoter and a strong RBS (RBS A, top), and genomic integration of the best AGT gene ( Sc agx1) by Tn5 transposition (bottom). (g) Growth profiles of the ΔltaE glyA g Sc agx1 strain in DBM medium with 20 mM glucose supplemented with 10 mM glycine or 10 mM glyoxylate. A strain containing the empty vector (eV) is also plotted as a control. (h) Specific growth rates corresponding to the growth profiles shown in panel (g). Average values for bacterial growth (estimated as the optical density measured at 600 nm, OD 600 ), and specific growth rate (μ, in h −1 ) ± standard deviation of three biological replicates are represented in all cases. Individual data points are also shown in panel (c). Glycine auxotrophy is rescued after adaptation and expression of malate thiokinase and malyl-CoA lyase as the complete module 2 of the modified serine cycle 2 ·m[MSC] Besides alanine-glyoxylate transamination, the mSC also relies on Mtk and Mcl ( Fig. 1 c ). We tested the variants from Methylococcus capsulatu a s nd Rhodobacter sphaeroide in s a small expression library. The three genes ( Mc mtkB , Mc mtkA , and Rs mcl ) were constitutively expressed with different RBSs in an acetyl-CoA auxotrophic strain (Δ aceEF ; Fig. S7 a–b). P. putida Δ aceEF cannot synthetize acetyl-CoA or run the TCA cycle for biomass precursors and energy [ 68 ]. Expression of Mc mtkBA and Rs mcl complemented the Δ aceEF auxotrophy in DBM medium with 20 mM glucose, although with a low cell density (OD 600 < 0.3, Fig. S7 c). To reduce the carbon demand of this submodule and implement the full M 2 of the mSC, we added the Agt activity, randomly integrating the Sc agx1 gene via Tn 5 transposition [ 69 ] into a glycine and C 1 auxotroph (Δ ltaE ΔΔ glyA , Fig. 9 e–f ). After a few selective passages, the Δ ltaE ΔΔ glyA g Sc agx1 strain grew in DBM medium with 20 mM glucose and 10 mM glyoxylate ( Fig. 9 a–d ). Next, the strongest RBSs for expression of mtk-mc c l loned in a pSEVA621 backbone was tested in the Δ ltaE ΔΔ glyA g Sc agx1 strain for its ability to produce glyoxylate ( Fig. 9 e–f ). When these combined activities were tested in DBM medium with 20 mM glucose, growth complementation was observed after a few selective passages ( Note S2 ). Expectedly, supplementing the medium with glyoxylate or glycine restored growth of all strains ( Fig. 9 g–h ). Thus, M 2 of the mSC resulted in comparable growth parameters to the STC in DBM medium with 20 mM glucose, with μ ∼ 0.2 h −1 and maximum cell density (OD 600 ) ∼ 2 ( Fig. 9 g–h ). These results underscore the potential for implementing the full mSC in P. putida . Endogenous and heterologous activities lead to a fully active serine-threonine cycle in engineeredP. putida After successfully implementing all module variants for the three synthetic SC, we concluded that the STC had the highest in vivo potential in P. putida . To build a consolidated and stable methylotrophic P . putida strain, we engineered all necessary activities expressed from the genome of P . putida ΔSGG-C 1 . In addition to the C 1 assimilation module from methylotrophic bacteria, we overexpressed both the native ltaE to regenerate glycine and yiaY to upregulate endogenous PQQ-dependent MeDHs ( Fig. 10 a–b ). We also deleted thiO , a FAD-dependent glycine/D-amino acid oxidase that produces glyoxylate [ 32 ] and could decrease flux through the STC competing with biomass formation. Finally, since we observed substantial biomass aggregation in media containing high methanol concentrations, we deleted the genes encoding the biofilm-producing adhesins LapA and LapF [ 70 , 71 ]. Download figure Open in new tab Figure 10. A combination of endogenous and heterologous activities activates the serine threonine cycle (STC) and a novel architecture for C 1 assimilation, the enhanced STC. (a) A serine and glycine auxotrophic strain with further modifications (M 1 ·STC, ΔSGG-C1) to overexpress the endogenous ltaE and yiaY. LtaE overproduction yields glycine from central metabolism whereas YiaY promotes methanol oxidation by derepressing the activity of endogenous PQQ-dependent alcohol dehydrogenases. This P. putida strain was termed STC1. (b) Genomic constitutive overexpression of the endogenous ltaE and yiaY via promoter exchange with the strong, constitutive P trc and P 14G promoters, respectively. (c) Growth profile of strain STC1 in DBM medium with 20 mM glucose and 10 nM LaCl 3 supplemented with 10 mM glycine, serine (positive control), or 2 mM homoserine. When needed, 60 mM formate or 500 mM methanol were also supplemented. (d) Specific growth rates corresponding to the growth profiles shown in panel (c). (e) Metabolic map for strain STC1 harboring the plasmids indicated in panel (f), encoding M 1 of the HSC. Increasing the assimilation of C 1 compounds directly via formaldehyde leads to a new synthetic metabolism, termed enhanced STC (eSTC). (f) Structure of plasmids used to overexpress Ec ltaE and the new variant Ec ltaE* (C188Y [ 72 ]) under the constitutive expression of P trc and the canonical RBS. (g) Growth profiles of strain STC1 harboring pS621· Ec ltaE / Ec ltaE* (C188Y) in DBM medium with 20 mM glucose, 10 nM LaCl 3 , and 500 mM methanol. The strain transformed with an empty vector (eV) is also plotted as a control. (h) Specific growth rates corresponding to the experiments shown in panel (g). Average values for bacterial growth (estimated as the optical density measured at 600 nm, OD 600 ), and specific growth rate (μ, in h −1 ) ± standard deviation of three biological replicates are represented in all cases. Individual data points are shown. Error bars in panel (h) correspond to 95% confidence intervals (CI), with P-values < 0.05 for all pairwise comparisons where error bars do not overlap. The resulting strain was termed P . putida STC1, and the detailed engineering steps are summarized in Fig. S2 . We tested if P . putida STC1 can assimilate methanol into l -serine and regenerate glycine from pyruvate or oxaloacetate (i.e., M 1 and M 2 of STC, respectively, Fig. 10 a ). When strain STC1 was incubated in DBM medium with 20 mM glucose and 10 nM LaCl 3 , both formate and methanol were efficiently assimilated and promoted growth, with μ ∼ 0.3 h −1 and 0.28 h −1 and maximum OD 600 ∼ 2.4 and 2.1, respectively ( Fig. 10 c–d ). Thus, while the implementation of the STC was insufficient to support growth on methanol alone, the mixotrophic growth of P . putida STC1 when supplemented with C1 molecules indicates that the full STC is functionally active in this strain. STC was realized in P. putida via overproduction of the endogenous PQQ-MeDH and l -threonine aldolase as well as heterologous C 1 -assimilation via THF. An enhanced serine-threonine cycle, encompassing a serine aldolase activity, outperforms the parental pathway Feedstock oxidation to CO 2 cannot be completely abolished in an aerobic heterotroph, and we hypothesized that adding extra entry points for C 1 moieties into central carbon metabolism could improve the ability of the engineered strain to utilize C 1 substrates ( Fig. 10 e ). Since the M 1 variants from the STC or HSC are not mutually exclusive, including M 1 ·HSC (i.e., serine aldolase activity) in the STC architecture could enable additional carbon assimilation at the formaldehyde level. To test this scenario, we transformed P . putida STC1, where all relevant STC genes are stably integrated in the chromosome, with plasmid pSEVA621· Ec ltaE ( Fig. 10 f ). We also tested Ec ltaE *, a variant of the aldolase carrying the C188Y point mutation described to display faster kinetics [ 72 ]. When the fully engineered strain was incubated in DBM medium with 20 mM glucose, 10 nM LaCl 3 , and 500 mM methanol, all growth parameters improved compared to P . putida STC1. A decreased lag phase was observed, with faster growth (μ ∼ 0.21 h −1 for Ec ltaE *), and increased maximum cell density (OD 600 ∼ 3, Fig. 10 g–h ). The wild-type Ec ltaE supported a similar growth profile as Ec ltaE *, albeit the growth rate was equivalent to the STC1 strain ( Fig. 10 g–h ). We named the new cycle enhanced serine-threonine cycle (eSTC). A calibration assay was performed to identify the concentration range at which methanol is assimilated ( Fig. S8 ). We tested the STC1 strain harboring either Ec ltaE or Ec ltaE* in DBM medium with 20 mM glucose and 10 nM LaCl 3 at different methanol concentrations ( Fig. S8 ). No growth was observed for any of the variants when methanol was omitted, highlighting the need for a C 1 substrate to complement the l -serine auxotrophy. Importantly, PedH, the native PQQ-MeDH, supported synthetic methylotrophy even at low (7.8 mM) methanol concentrations. Hence, both eSTC variants (with either Ec ltaE or Ec ltaE* ) outperformed the parental STC in terms of maximum cell growth (OD 600 ) and lag phase reduction, exhibiting more consistent growth profiles at lower methanol concentrations. Since specific growth rates and maximum cell densities were not substantially affected by the methanol concentration, further engineering efforts could be used to overcome other potential bottlenecks (e.g., glycine regeneration, Fig. S8 b–c). DISCUSSION The SC is a natural, oxygen-insensitive pathway that synthesizes acetyl-CoA from C 1 molecules without carbon loss [ 16 ]. This is an attractive pathway to establish synthetic C 1 assimilation, but engineering efforts thus far have been hindered by inherent bottlenecks, e.g., cycle efficiency, toxicity of intermediates, and interference with central metabolism in the host [ 16 , 47 ]. To address these challenges, we explored three synthetic SC variants, the STC, the HSC, and the mSC, systematically comparing their performance both in silico and in vivo through growth-coupled selection and modular engineering in a genome-reduced P . putida strain. P . putida has a highly flexible metabolism with a native architecture that aligns with implementing SCs. Indeed, the substantial fluxes through carboxylation reactions from pyruvate or PEP [ 73 ], producing oxaloacetate and assimilating CO 2 (i.e., in M 2 of the STC or mSC), favor the implementation of these synthetic C 1 modules. Additionally, P . putida contains multiple copies of most endogenous enzymes involved in the cycles, including three homologs of serine deaminase (TdcG) and several C 1 dehydrogenases [ 56 ]. Pathway modularization was essential for our engineering efforts. M 1 covers carbon assimilation from glycine to serine, common to all synthetic cycles. This metabolic step is supported either by the THF-moiety from formate in the STC or mSC, or directly from formaldehyde via the serine aldolase reaction in the HSC. We engineered both variants in serine and glycine auxotrophs of P . putida using methanol and, as predicted by FBA ( Tables S6 – S7 ), both C 1 entry points performed similarly well. However, the choice of MeDH significantly impacted the performance of the C 1 assimilative module ( Table 1 ). M 2 , on the other hand, involves the condensation of an additional C 1 moiety (HCO 3 − or formaldehyde) with pyruvate to produce oxaloacetate or homoserine. These intermediates are then cleaved by lyases to replenish the glycine pool and generate acetyl-CoA, which can be used for biomass formation and energy regeneration. Glycine is used to initiate a new cycle through M 1 , since the SCs are autocatalytic. To compare the three variants of this module, we utilized serine and/or glycine auxotrophies ( Table 1 ). Our in-silico analysis indicated that M 2 of the HSC should outperform the mSC variant, while the STC is the longest and most ATP- and NAD(P)H-demanding route. However, the STC leverages native pathways of P . putida , whereas the other cycle variants require extensive engineering [ 16 , 20 , 45 – 47 ]. Interestingly, E. coli GarL assimilated formaldehyde to complement the homoserine auxotrophy in the HSC ( Notes S3 and S4 ). The M 2 variants of the STC and the mSC were predicted to operate with similar growth parameters, with the mSC being slightly more efficient. In a glycine auxotroph (ΔΔ glyA ), the mSC variant showed better yields (cell density, OD 600 ) compared to the STC ( Table 1 ). However, the mSC requires extensive flux rewiring, since glycine is derived from the TCA cycle intermediates glyoxylate and malate. In contrast, M 2 of the STC relies on existing pathways in P . putida and overexpressing the later enzyme in the module (LtaE) was sufficient to elicit module activity. View this table: View inline View popup Download powerpoint Table 1. Module comparison of the three synthetic serine cycles tested in this work. Another advantage of using P. putida as a host for synthetic methanol assimilation is its inherent alcohol oxidation capacities. Methanol oxidation is a major bottleneck in methylotrophic growth due to unfavorable thermodynamics, particularly since most synthetic methylotrophic engineering relies on NADH-dependent MeDH [ 16 , 20 , 45 – 47 ]. While NAD-MeDH may result in higher biomass yields, reaction thermodynamics are compromised, leading to a significant MDF decrease also observed during implementation of the HSC. Using PQQ-dependent MeDHs can overcome this bottleneck with increased thermodynamic favorability, resulting in higher growth rates [ 12 , 74 , 75 ]. We successfully engineered methanol oxidation using either a heterologous NAD-MeDH or the methanol activity of the native, broad-range PQQ-dependent alcohol dehydrogenases of P. putida (PedE and PedH). PQQ-MeDH activity was achieved by overexpressing yiaY , encoding its putative regulator [ 61 ]. Additionally, the presence of REEs (lanthanides) determined which dehydrogenase was expressed [ 33 , 62 ]. PedH activity, upregulated in the presence of lanthanides, yielded better growth parameters compared to PedE in the absence of LaCl 3 . No efforts to engineer full methylotrophy in synthetic hosts have used PQQ-dependent MeDHs. Only a recent study utilized PedE under mixotrophic conditions to implement a module of the reductive glycine pathway [ 76 ]. Unlike E. coli , which lacks the PQQ biosynthesis pathway, P. putida facilitates the engineering of methanol oxidation through PQQ-MeDH for both native and heterologous enzymes [ 77 ], including the M. extorquen A s M1 XoxFGJ reported in this work. Building on the modularization efforts and endogenous methanol oxidation, we selected the STC as the highest potential for methylotrophy. Although energetically demanding, this cycle closely resembles the native metabolism, and it supported synthetic formatotrophy in engineered E . coli [ 47 ]. Hence, we constructed a streamlined, stable STC1 strain, incorporating the optimized STC modules into the genome of P. putida . This strain displayed efficient C 1 assimilation (both formate and methanol) and fully replenished serine through the synthetic cycle. We showed that the STC relieved serine and glycine auxotrophies using its original module architecture. We envision that different module combinations, e.g., M 1 ·HSC and M 2 ·STC (or M 1 ·HSC and M 2 ·mSC), could also be implemented in P. putida . Finally, we identified a new variant of the STC through module combination that outperforms the original STC. This new cycle, termed the enhanced serine-threonine cycle (eSTC), incorporates the serine aldolase activity from M 1 ·HSC into the STC design. The eSTC not only mediated faster growth but also promoted higher cell densities. We infer that these improved growth parameters are due to increased C 1 assimilation, as formaldehyde is also condensed directly by the eSTC. Therefore, increasing the scope of entry points for C 1 substrates can enhance substrate availability, yields, and specific growth rates by reducing wasteful substrate oxidation. We also present the first direct comparison of engineered cycles in a heterotrophic organism. The results of this study, summarized in Table 1 , offer interesting insights into the relative performance of these routes for C 1 assimilation. Expanding the biochemical repertoire of P . putida to include C 1 feedstocks paves the way for achieving a sustainable and truly circular carbon economy through synthetic assimilation. This approach will also guide future efforts in establishing synthetic metabolism in other heterotrophs of industrial interest. CONCLUDING REMARKS Methanol, a cost-effective and renewable feedstock derived from CO₂ capture or renewable resources such as biomass, offers a promising alternative to petroleum-based substrates. In this sense, one-carbon feedstocks have strong potential to contribute to a circular carbon bioeconomy, enabling the production of bio-based plastics, green chemicals, and biofuels. When coupled with metabolically versatile and robust bacterial hosts, e.g. P . putida , these feedstocks hold promise for reducing the carbon footprint of industrial processes. Inspired by these features, in this work we demonstrated the use of three synthetic serine cycles integrated with the native activity of PQQ-dependent alcohol dehydrogenases, enabling the design of an enhanced cycle for methanol assimilation. Additionally, we expanded the synthetic biology toolkit by identifying and characterizing methanol-inducible promoters, which can be leveraged for engineering methylotrophy in non-canonical microbial hosts. These efforts constitute a substantial contribution to the metabolic engineering of P . putida for methanol utilization, introducing a novel serine cycle variant and contributing to a broader range of engineered microbes for sustainable biotechnology. The engineering strategies presented here pave the way for transforming methanol into valuable biochemicals, materials, and fuels through microbial biomanufacturing. This work addresses critical global challenges, including resource depletion, competition for food and feed, and climate change, by advancing the potential of methanol as a sustainable industrial feedstock. AUTHOR′S CONTRIBUTIONS O.P. and P.I.N. conceived the project and designed the experiments. O.P. performed MDF. D.B. and O.P. performed and analyzed FBA. O.P., J.M.T, L.F.C., L.G. and H.S.M. performed the experiments leading to the results described in the article. All the authors analyzed the data and participated in the discussions included in this study. O.P. and P.I.N. wrote the manuscript, H.S.M. assisted in drafting the manuscript, with contributions from all the other authors. DECLARATION OF INTERESTS The authors declare no competing interests. MATERIALS AND METHODS Bacterial strains, medium composition and culture conditions All bacterial strains and plasmids are listed in Table S8 and Table S9 , respectively. E . coli DH5α λ pir [ 78 ] was used as cloning host, while the reduced-genome P. putida strain SEM11 [ 55 ] was selected for quantitative physiology and engineering purposes unless indicated otherwise. Lysogeny broth (LB) complex medium (containing 10 g L −1 tryptone, 5 g L −1 yeast extract, and 10 g L −1 NaCl) and de Bont minimal (DBM) medium were used for all cultivations [ 79 ]. DBM medium contained 3.88 g L −1 K 2 HPO 4 , 1.63 g L −1 NaH 2 PO 4 , 2 g L −1 (NH 4 ) 2 SO 4 , and 0.1 g L −1 MgCl 2 ·6H 2 O with the initial pH adjusted at 7.0 and supplemented with a trace elements solution [10 mg L −1 ethylenediaminetetraacetic acid (EDTA), 2 mg L −1 ZnSO 4 ·7H 2 O, 1 mg L −1 CaCl 2 ·2H 2 O, 5 mg L −1 FeSO 4 ·7H 2 O, 0.2 mg L −1 Na 2 MoO 4 ·2H 2 O, 0.2 mg L −1 CuSO 4 ·5H 2 O, 0.4 mg L −1 CoCl 2 ·6H 2 O, and 1 mg L −1 MnCl 2 ·2H 2 O] [ 80 ]. When needed, kanamycin (Km) and gentamicin (Gm) were supplied at 50 μg mL −1 and 10 μg mL −1 , respectively. Overnight cultures in LB medium were diluted 1/100 to inoculate a 5-mL preculture of DBM medium with 20 mM glucose in a 50-mL culture tube and incubated at 30°C and 250 rpm for ca. 18 h. This overnight culture was washed with DBM medium without any carbon source prior to the inoculation of the main culture in 96-well microtiter plates with the appropriate carbon source(s) as described in the text. All growth assays were performed in the presence of antibiotics, unless the strain did not harbor any plasmid. For cultivations in 96-well microtiter plates, 150 μL of a cell suspension at an OD 600 of 0.05 were incubated in an Epoch2 microtiter plate reader (BioTek Instruments Inc.; Winooski, VT, USA) with 50 μL of mineral oil to prevent evaporation. Measurements obtained with microtiter plate readers were calibrated against a tabletop spectrophotometer. The specific growth rate (μ) and, when relevant, the extension of the lag phase (λ) were calculated using QurvE ( www.qurveanalysis.com ) by performing a smooth spline fit on the growth data [ 81 ]. Construction of (deletion) plasmids The suicide plasmids and overexpression plasmids noted in Table S9 were constructed using USER cloning [ 82 – 85 ]. For deletion plasmids, DNA fragments, consisting of ca. 500-bp upstream and downstream regions around the locus to be eliminated, were amplified with Phusion U Hot Start TM DNA polymerase (ThermoFisher Scientific Co.) using uracil-containing primers. The pGNW2 backbone [ 86 ] was digested with Dpn I prior to mixing 1 μL of Dpn I-treated vector with 100 ng of each PCR fragment and 1 μL of USER TM enzyme (New England BioLabs) in a final volume of 10 μL. The reaction was incubated for 30 min at 37°C, followed by a temperature decrease over 3 min (from 28°C to 20°C, 1°C per step) and a final incubation step at 10°C for at least 10 min. Finally, chemically-competent E . coli DH5α λ pir cells were transformed via heat shock with 5 μL of the USER mix; upon recovery, the cell suspension was plated onto selective LB medium agar plates containing the corresponding antibiotic. Construction of mutant P. p utida strains The corresponding suicide pGNW2-derivative plasmid was delivered into the cells by triparental conjugation with the corresponding DH5α λ pir harboring the specific suicide plasmid, the P. putida strain of interest, and the E. coli helper strain E. coli HB101 carrying plasmid pRK2013 [ 87 ]. The three strains were incubated in LB plates for over 5 h at 30°C and subsequently plated in LB plates supplemented with the antibiotic of interest and Irgasan. Positive co-integration events were further transformed with pQURE6·H ( Table S9 ), a conditionally-replicative plasmid bearing the meganuclease gene I-SceI [ 88 ]. I-SceI cuts pGNW2 co-integrants within the chromosome, thus forcing a second homologous recombination event. This was performed by electroporating 50 ng of plasmid DNA into 50 μL of freshly-prepared electrocompetent P . putida cells, previously washed three times with 300 mM sucrose. Electroporation was performed with a Gene Pulser XCell (Bio-Rad) set to 2.5 kV, 25 μF capacitance and 200 Ω resistance in a 2-mm gap cuvette. Cells were recovered in 1 mL of LB medium supplemented with 2 mM of 3-methylbenzoate (3- m Bz) for at least 3 h at 30°C and plated onto LB medium agar containing the corresponding antibiotic(s) and 1 mM 3- m Bz to induce both plasmid replication and I- Sce I expression. Positive clones were identified by colony PCR, verified by DNA sequencing, and cured from the resolving plasmid by serial dilution under non-selective conditions. All sequences used were native with the exception of Hs agxt1 and Sc agx1 which were codon-optimized. Maximum-minimum driving force (MDF) analysis MDF analysis [ 89 ] was applied to evaluate and compare the different natural and modified SC in the context of P. putida KT2440 using eQuilibrator-API [ 90 ]. We also compared these metabolisms to the reductive glycine pathway (rGlyP) and the ribulose monophosphate (RuMP) pathway [ 17 , 32 , 91 ]. Metabolite concentrations were constrained to the range of 1-10 mM [ 89 , 92 ] with a few exceptions: (i) the upper bound for formaldehyde was constrained to 1 mM, the highest concentration tolerated by P. putida KT2440 [ 93 ]; (ii) l -glutamate and 2-ketoglutarate were set as amino-donors at 100 mM and 0.5 mM, respectively [ 20 , 94 ]; (iii) the intracellular pH was set to 7.8 [ 95 ]; (iv) the ionic strength and –log 10 [Mg 2+ ] (pMg) were assumed to be 0.25 M and 3, respectively [ 20 , 92 , 96 ]; (v) since the MHPT oxidation of formaldehyde is not supported by e Quilibrator [ 20 ], we adopted the glutathione-independent oxidation reaction for the SCs instead (except for the HSC), (vi) all carboxylations were assumed to use CO 2 as a substrate to simplify the calculations, given that such reactions are pH-independent, unlike those involving bicarbonate [ 92 ]. The low (ambient CO 2 ) and high CO 2 concentrations in solution were set to 10 μM and 1 mM, respectively. High CO 2 concentrations are needed, for instance, by the rGlyP [ 97 ]. All pathways used methanol as a sole carbon source and acetyl-CoA or pyruvate as a substrate. Given that the number of carbons differs in each substrate, the MDF per C-mol is reported in kJ C-mol −1 [ 91 ]. The scripts and further details on these calculations can be found at https://github.com/puiggene07/PubSuppl within the 2024_Ser_Cycles_P_putida directory. Flux Balance Analysis (FBA) For in silico comparison of the different SC modules, FBA was performed with the COBRApy python package [ 98 , 99 ]. Simulations were run with a curated version of the latest genome-scale metabolic model available for strain KT2440 [ 51 , 52 ]. The model was further refined based on the following considerations: (i) the reversibility of GlyA (GHMT2) in glycine metabolism; (ii) our experimental evidence demonstrating that homoserine dehydrogenase (HSDy) operates irreversibly in P . putida during threonine regeneration, as observed in E. coli [ 20 ]; and (iii) the lack of natural formatotrophy via PurU in purine/pyrimidine biosynthesis in P . putida [ 32 ], leading to GARFT being set as irreversible. In addition, autotrophy based on CO 2 assimilation via the lipoamide-dependent complexes (including AKGDa and PDHa) was prevented by setting the reactions as irreversible. The formaldehyde dismutase (FALDM) reaction was deactivated as this activity was never isolated in P. putida . Finally, genes borne by the TOL plasmid (reactions with pWW0 gene IDs) were eliminated and nickel (Ni 2+ ) was removed from the biomass function, as P. putida does not have that requirement for growth [ 100 ]. For the C 1 assimilation modules, the respective reactions were introduced in the model. The in-silico comparison of the different synthetic modules was based on their capability of assimilating C 1 substrates, their predicted maximal biomass formation rate, as well as the amount of directly oxidized C 1 compounds (equal to the rate of the native formate dehydrogenase reaction), and the total CO 2 emission rate. CO 2 formation is a primary result of NAD(P)H generation; hence, it can be adopted as an indirect indicator for the energy demand of the respective pathway. Conditions were tested for co-utilization of glucose and methanol, full methylotrophy, and growth solely in glucose. Carbon equimolar uptake rates were set for the respective primary substrates (30 mmol g −1 h −1 ). For co-utilization of glucose and methanol, methanol uptake rates were additionally set to 5 mmol g −1 h −1 (high methanol uptake) or 2 mmol g −1 h −1 (low methanol uptake). Reactions were disabled according to the different in vivo selection schemes via the COBRApy function mode.genes.id.knockout(). Chemicals and reagents Chemicals were purchased from Sigma-Aldrich Co. (St. Louis, MO, USA) unless otherwise indicated, and oligonucleotides were synthesized by Integrated DNA Technologies Inc. (Coralville, IA, USA). DNA sequencing was performed at Eurofins Genomics (Ebersberg, Germany). All primers used in this study are listed in Table S10 . PCR reactions were performed using Phusion U Hot Start TM DNA polymerase, purchased from ThermoFisher Scientific Co. (Waltham, MA, USA). The commercial One Taq TM master mix from New England BioLabs (Ipswich, MA, USA) was used for colony PCRs. 4-Hydroxy-2-oxobutanoate (HOB, in its lactone form) was purchased from Synthenova (France). Statistical analysis Data analysis was performed using Prism 9.0.2 (GraphPad Software Inc.; San Diego, CA, USA). All reported values are indicated as averages ± standard deviation of at least three independent biological replicates as specified in the legend of the corresponding figures. Considering that most negative controls (i.e., strains transformed with empty vectors) did not show any growth, enzyme variants that restored methylotrophic growth were considered to be statistically significant [ 101 ]. LIST OF ABBREVIATIONS AGT Alanine-glyoxylate transaminase ALE Adaptive laboratory evolution C1 One-carbon (substrate/moiety) DBM medium de Bont minimal medium EDEMP cycle Entner-Doudoroff–Embden-Meyerhof-Parnas–pentose phosphate cycle eSTC Enhanced serine threonine cycle FBA Flux balance analysis HOB 4-Hydroxy-2-oxobutanoate HAL HOB aldolase HAT HOB transaminase MDF Maximum-minimum driving force MeDH Methanol dehydrogenase mSC Modified serine cycle M1 Module 1 M2 Module 2 MTK Malate thiokinase MCL Malyl-coenzyme A lyase NAD(P)+/H Nicotinamide adenine dinucleotide (phosphate) (oxidized/reduced) NAD-MeDH NAD(P)H-dependent methanol dehydrogenases OD600 Maximal bacterial cell density PDH Pyruvate dehydrogenase PQQ Pyrroloquinoline quinone PQQ-MeDH PQQ-dependent methanol dehydrogenase REEs Rare earth elements rGlyP Reductive glycine pathway RuMP pathway Ribulose monophosphate pathway SAL Serine aldolase SC Serine cycle sM1/2 Sub-module of Module 1/2 STC Serine threonine cycle TCA cycle Tricarboxylic acid cycle THF Tetrahydrofolate μ Specific growth rate (h–1) ACKNOWLEDGEMENTS We thank Justine Turlin for fruitful discussions, Vittorio Rainaldi for providing the NADH-MeDH library, Lennart Schada von Borzyskowski for sharing Pd bhcA, Hai He for feedback on implementation of M2·HSC, and Elad Noor for his help with MDF calculations. D.B. acknowledges funding from CSIRO through the CSIRO Postgraduate Top-Up Scholarship, supported by the Advanced Engineering Biology Future Science Platform. The financial support from The Novo Nordisk Foundation through TARGET (grant NNF21OC0067996) to P.I.N. is gratefully acknowledged. REFERENCES 1. ↵ Ripple WJ , Wolf C , Gregg JW , Levin K , Rockström J , Newsome TM , Betts MG , Huq S , Law BE , Kemp L , et al : World scientists’ warning of a climate emergency 2022 . BioScience 2022 , 72 : 1149 – 1155 . doi: 10.1093/biosci/biac083 . OpenUrl CrossRef 2. ↵ Rogelj J , Geden O , Cowie A , Reisinger A : Net-zero emissions targets are vague: three ways to fix . Nature 2021 , 591 : 365 – 368 . doi: 10.1038/d41586-021-00662-3 . OpenUrl CrossRef PubMed 3. ↵ Matthews HD , Zickfeld K , Dickau M , MacIsaac AJ , Mathesius S , Nzotungicimpaye CM , Luers A : Temporary nature-based carbon removal can lower peak warming in a well-below 2°C scenario . Commun. Earth Environ . 2022 , 3 : 65 . doi: 10.1038/s43247-022-00391-z . OpenUrl CrossRef 4. ↵ Schrader J , Schilling M , Holtmann D , Sell D , Filho MV , Marx A , Vorholt JA : Methanol-based industrial biotechnology: current status and future perspectives of methylotrophic bacteria . Trends Biotechnol . 2009 , 27 : 107 – 115 . doi: 10.1016/j.tibtech.2008.10.009 . OpenUrl CrossRef PubMed Web of Science 5. Zhang W , Song M , Yang Q , Dai Z , Zhang S , Xin F , Dong W , Ma J , Jiang M : Current advance in bioconversion of methanol to chemicals . Biotechnol. Biofuels 2018 , 11 : 260 . doi: 10.1186/s13068-018-1265-y . OpenUrl CrossRef PubMed 6. Olah GA : Beyond oil and gas: the methanol economy . Angew. Chem. Int. Ed. Engl . 2005 , 44 : 2636 – 2639 . doi: 10.1002/anie.200462121 . OpenUrl CrossRef PubMed 7. Pfeifenschneider J , Brautaset T , Wendisch VF : Methanol as carbon substrate in the bio-economy: metabolic engineering of aerobic methylotrophic bacteria for production of value-added chemicals . Biofuels Bioprod. Biorefining 2017 , 11 : 719 – 731 . doi: 10.1002/bbb.1773 . OpenUrl CrossRef 8. Claassens NJ , He H , Bar-Even A: Synthetic methanol and formate assimilation via modular engineering and selection strategies . Curr. Issues Mol. Biol . 2019 , 33 : 237 – 248 . doi: 10.21775/cimb.033.237 . OpenUrl CrossRef PubMed 9. ↵ Ruttinger AW , Tavakkoli S , Shen H , Wang C , Jordaan SM : Designing an innovation system to support profitable electro- and bio-catalytic carbon upgrade . Energy Environ. Sci . 2022 , 15 : 1222 – 1233 . doi: 10.1039/D1EE03753F . OpenUrl CrossRef 10. ↵ Sanford PA , Woolston BM : Synthetic or natural? Metabolic engineering for assimilation and valorization of methanol . Curr. Opin. Biotechnol . 2022 , 74 : 171 – 179 . doi: 10.1016/j.copbio.2021.12.001 . OpenUrl CrossRef PubMed 11. ↵ Claassens NJ , Sousa DZ , Martins dos Santos VAP , de Vos WM , van der Oost J : Harnessing the power of microbial autotrophy . Nat. Rev. Microbiol . 2016 , 14 : 692 – 706 . doi: 10.1038/nrmicro.2016.130 . OpenUrl CrossRef PubMed 12. ↵ Whitaker WB , Sandoval NR , Bennett RK , Fast AG , Papoutsakis ET : Synthetic methylotrophy: engineering the production of biofuels and chemicals based on the biology of aerobic methanol utilization . Curr. Opin. Biotechnol . 2015 , 33 : 165 – 175 . doi: 10.1016/j.copbio.2015.01.007 . OpenUrl CrossRef PubMed 13. ↵ Yishai O , Lindner SN , González de la Cruz J , Tenenboim H , Bar-Even A: The formate bio-economy . Curr. Opin. Chem. Biol . 2016 , 35 : 1 – 9 . doi: 10.1016/j.cbpa.2016.07.005 . OpenUrl CrossRef PubMed 14. ↵ Claassens NJ , Bordanaba-Florit G , Cotton CAR , de Maria A , Finger-Bou M , Friedeheim L , Giner-Laguarda N , Munar-Palmer M , Newell W , Scarinci G , et al : Replacing the Calvin cycle with the reductive glycine pathway in Cupriavidus necator . Metab. Eng . 2020 , 62 : 30 – 41 . doi: 10.1016/j.ymben.2020.08.004 . OpenUrl CrossRef PubMed 15. Müller JEN , Meyer F , Litsanov B , Kiefer P , Potthoff E , Heux S , Quax WJ , Wendisch VF , Brautaset T , Portais JC , Vorholt JA : Engineering Escherichia coli for methanol conversion . Metab. Eng . 2015 , 28 : 190 – 201 . doi: 10.1016/j.ymben.2014.12.008 . OpenUrl CrossRef 16. ↵ Yu H , Liao JC : A modified serine cycle in Escherichia coli coverts methanol and CO 2 to two-carbon compounds . Nat. Commun . 2018 , 9 : 3992 . doi: 10.1038/s41467-018-06496-4 . OpenUrl CrossRef 17. ↵ Chen FYH , Jung HW , Tsuei CY , Liao JC : Converting Escherichia coli to a synthetic methylotroph growing solely on methanol . Cell 2020 , 182 : 933 – 946 .e14. doi: 10.1016/j.cell.2020.07.010 . OpenUrl CrossRef PubMed 18. Bang J , Hwang CH , Ahn JH , Lee JA , Lee SY : Escherichia coli is engineered to grow on CO2 and formic acid . Nat. Microbiol . 2020 , 5 : 1459 – 1463 . doi: 10.1038/s41564-020-00793-9 . OpenUrl CrossRef 19. Meyer F , Keller P , Hartl J , Gröninger OG , Kiefer P , Vorholt JA : Methanol-essential growth of Escherichia coli . Nat. Commun . 2018 , 9 : 1508 . doi: 10.1038/s41467-018-03937-y . OpenUrl CrossRef PubMed 20. ↵ He H , Höper R , Dodenhöft M , Marlière P , Bar-Even A: An optimized methanol assimilation pathway relying on promiscuous formaldehyde-condensing aldolases in E. coli . Metab. Eng . 2020 , 60 : 1 – 13 . doi: 10.1016/j.ymben.2020.03.002 . OpenUrl CrossRef PubMed 21. ↵ Antoniewicz MR : Synthetic methylotrophy: strategies to assimilate methanol for growth and chemicals production . Curr. Opin. Biotechnol . 2019 , 59 : 165 – 174 . doi: 10.1016/j.copbio.2019.07.001 . OpenUrl CrossRef PubMed 22. ↵ Calero P , Nikel PI : Chasing bacterial chassis for metabolic engineering: a perspective review from classical to non-traditional microorganisms . Microb. Biotechnol . 2019 , 12 : 98 – 124 . doi: 10.1111/1751-7915.13292 . OpenUrl CrossRef PubMed 23. Weimer A , Kohlstedt M , Volke DC , Nikel PI , Wittmann C : Industrial biotechnology of Pseudomonas putida: advances and prospects . Appl. Microbiol. Biotechnol . 2020 , 104 : 7745 – 7766 . doi: 10.1007/s00253-020-10811-9 . OpenUrl CrossRef 24. de Lorenzo V , Pérez-Pantoja D , Nikel PI : Pseudomonas putida KT2440: the long journey of a soil-dweller to become a synthetic biology chassis . J. Bacteriol . 2024 , 206 : e00136 – 24 . doi: 10.1128/jb.00136-24 . OpenUrl CrossRef PubMed 25. ↵ Cros A , Alfaro-Espinoza G , de Maria A , Wirth NT , Nikel PI : Synthetic metabolism for biohalogenation . Curr. Opin. Biotechnol . 2022 , 74 : 180 – 193 . doi: 10.1016/j.copbio.2021.11.009 . OpenUrl CrossRef PubMed 26. ↵ Martínez-García E , de Lorenzo V : Pseudomonas putida as a synthetic biology chassis and a metabolic engineering platform . Curr. Opin. Biotechnol . 2024 , 85 : 103025 . doi: 10.1016/j.copbio.2023.103025 . OpenUrl CrossRef PubMed 27. ↵ Nikel PI , de Lorenzo V : Pseudomonas putida as a functional chassis for industrial biocatalysis: From native biochemistry to trans-metabolism . Metab. Eng . 2018 , 50 : 142 – 155 . doi: 10.1016/j.ymben.2018.05.005 . OpenUrl CrossRef 28. Calero P , Volke DC , Lowe PT , Gotfredsen CH , O’Hagan D , Nikel PI : A fluoride-responsive genetic circuit enables in vivo biofluorination in engineered Pseudomonas putida . Nat. Commun . 2020 , 11 : 5045 . doi: 10.1038/s41467-020-18813-x . OpenUrl CrossRef PubMed 29. ↵ Wirth NT , Nikel PI : Combinatorial pathway balancing provides biosynthetic access to 2-fluoro-cis,cis-muconate in engineered Pseudomonas putida . Chem Catal . 2021 , 1 : 1234 – 1259 . doi: 10.1016/j.checat.2021.09.002 . OpenUrl CrossRef PubMed 30. ↵ Sullivan KP , Werner AZ , Ramirez KJ , Ellis LD , Bussard JR , Black BA , Brandner DG , Bratti F , Buss BL , Dong X , et al : Mixed plastics waste valorization through tandem chemical oxidation and biological funneling . Science 2022 , 378 : 207 – 211 . doi: 10.1126/science.abo4626 . OpenUrl CrossRef PubMed 31. ↵ Turlin J , Puiggené Ò , Donati S , Wirth NT , Nikel PI : Core and auxiliary functions of one-carbon metabolism in Pseudomonas putida exposed by a systems-level analysis of transcriptional and physiological responses . mSystems 2023 , 8 : e00004 – 23 . doi: 10.1128/msystems.00004-23 . OpenUrl CrossRef PubMed 32. ↵ Turlin J , Dronsella B , De Maria A , Lindner SN , Nikel PI : Integrated rational and evolutionary engineering of genome-reduced Pseudomonas putida strains promotes synthetic formate assimilation . Metab. Eng . 2022 , 74 : 191 – 205 . doi: 10.1016/j.ymben.2022.10.008 . OpenUrl CrossRef PubMed 33. ↵ Wehrmann M , Billard P , Martin-Meriadec A , Zegeye A , Klebensberger J : Functional role of lanthanides in enzymatic activity and transcriptional regulation of pyrroloquinoline quinone-dependent alcohol dehydrogenases in Pseudomonas putida KT2440 . mBio 2017 , 8 : 00570 – 17 . doi: 10.1128/mBio.00570-17 . OpenUrl CrossRef 34. ↵ Nieto-Domínguez M , Nikel PI : Intersecting xenobiology and neo-metabolism to bring novel chemistries to life . ChemBioChem 2020 , 21 : 2551 – 2571 . doi: 10.1002/cbic.202000091 . OpenUrl CrossRef PubMed 35. Nikel PI , Chavarría M , Danchin A , de Lorenzo V : From dirt to industrial applications: Pseudomonas putida as a Synthetic Biology chassis for hosting harsh biochemical reactions . Curr. Opin. Chem. Biol . 2016 , 34 : 20 – 29 . doi: 10.1016/j.cbpa.2016.05.011 . OpenUrl CrossRef PubMed 36. ↵ Nikel PI , Fuhrer T , Chavarría M , Sánchez-Pascuala A , Sauer U , de Lorenzo V: Reconfiguration of metabolic fluxes in Pseudomonas putida as a response to sub-lethal oxidative stress . ISME J . 2021 , 15 : 1751 – 1766 . doi: 10.1038/s41396-020-00884-9 . OpenUrl CrossRef 37. ↵ Crowther GJ , Kosály G , Lidstrom ME : Formate as the main branch point for methylotrophic metabolism in Methylobacterium extorquens AM1 . J. Bacteriol . 2008 , 190 : 5057 – 5062 . doi: 10.1128/jb.00228-08 . OpenUrl Abstract / FREE Full Text 38. Kalyuzhnaya MG , Lidstrom ME : QscR-mediated transcriptional activation of serine cycle genes in Methylobacterium extorquens AM1 . J. Bacteriol . 2005 , 187 : 7511 – 7517 . doi: 10.1128/jb.187.21.7511-7517.2005 . OpenUrl Abstract / FREE Full Text 39. ↵ Šmejkalová H , Erb TJ , Fuchs G : Methanol assimilation in Methylobacterium extorquens AM1: demonstration of all enzymes and their regulation . PLoS One 2010 , 5 : e13001 . doi: 10.1371/journal.pone.0013001 . OpenUrl CrossRef PubMed 40. ↵ Anthony C : How half a century of research was required to understand bacterial growth on C1 and C2 compounds; the story of the serine cycle and the ethylmalonyl-CoA pathway . Sci. Prog . 2011 , 94 : 109 – 137 . doi: 10.3184/003685011x13044430633960 . OpenUrl CrossRef PubMed 41. ↵ Bar-Even A : Formate assimilation: the metabolic architecture of natural and synthetic pathways . Biochemistry 2016 , 55 : 3851 – 3863 . doi: 10.1021/acs.biochem.6b00495 . OpenUrl CrossRef PubMed 42. ↵ Claassens NJ , Cotton CAR , Kopljar D , Bar-Even A: Making quantitative sense of electromicrobial production . Nat. Catal . 2019 , 2 : 437 – 447 . doi: 10.1038/s41929-019-0272-0 . OpenUrl CrossRef 43. ↵ Danchin A : In vivo, in vitro and in silico: an open space for the development of microbe-based applications of synthetic biology . Microb. Biotechnol . 2021 , 15 : 42 – 64 . doi: 10.1111/1751-7915.13937 . OpenUrl CrossRef PubMed 44. ↵ Danchin A : Coping with inevitable accidents in metabolism . Microb. Biotechnol . 2017 , 10 : 57 – 72 . doi: 10.1111/1751-7915.12461 . OpenUrl CrossRef PubMed 45. ↵ Bouzon M , Perret A , Loreau O , Delmas V , Perchat N , Weissenbach J , Taran F , Marlière P : A synthetic alternative to canonical one-carbon metabolism . ACS Synth. Biol . 2017 , 6 : 1520 – 1533 . doi: 10.1021/acssynbio.7b00029 . OpenUrl CrossRef PubMed 46. ↵ Yishai O , Goldbach L , Tenenboim H , Lindner SN , Bar-Even A : Engineered assimilation of exogenous and endogenous formate in Escherichia coli . ACS Synth. Biol . 2017 , 6 : 1722 – 1731 . doi: 10.1021/acssynbio.7b00086 . OpenUrl CrossRef PubMed 47. ↵ Wenk S , Rainaldi V , Schann K , He H , Bouzon M , Döring V , Lindner SN , Bar-Even A : Evolution-assisted engineering of E. coli enables growth on formic acid at ambient CO2 via the serine threonine cycle . Metab. Eng . 2024 , 88 : 14 – 24 . doi: 10.1016/j.ymben.2024.10.007 . OpenUrl CrossRef 48. ↵ Kim S , Lindner SN , Aslan S , Yishai O , Wenk S , Schann K , Bar-Even A : Growth of E. coli on formate and methanol via the reductive glycine pathway . Nat. Chem. Biol . 2020 , 16 : 538 – 545 . doi: 10.1038/s41589-020-0473-5 . OpenUrl CrossRef PubMed 49. ↵ Keller P , Reiter MA , Kiefer P , Gassler T , Hemmerle L , Christen P , Noor E , Vorholt JA : Generation of an Escherichia coli strain growing on methanol via the ribulose monophosphate cycle . Nat. Commun . 2022 , 13 : 5243 . doi: 10.1038/s41467-022-32744-9 . OpenUrl CrossRef PubMed 50. ↵ Reiter MA , Bradley T , Büchel LA , Keller P , Hegedis E , Gassler T , Vorholt JA : A synthetic methylotrophic Escherichia coli as a chassis for bioproduction from methanol . Nat. Catal . 2024 , 7 : 560 – 573 . doi: 10.1038/s41929-024-01137-0 . OpenUrl CrossRef PubMed 51. ↵ Bujdoš D , Popelářová B , Volke DC , Nikel PI , Sonnenschein N , Dvořák P : Engineering of Pseudomonas putida for accelerated co-utilization of glucose and cellobiose yields aerobic overproduction of pyruvate explained by an upgraded metabolic model . Metab. Eng . 2023 , 75 : 29 – 46 . doi: 10.1016/j.ymben.2022.10.011 . OpenUrl CrossRef PubMed 52. ↵ Nogales J , Mueller J , Gudmundsson S , Canalejo FJ , Duque E , Monk J , Feist AM , Ramos JL , Niu W , Palsson BØ : High-quality genome-scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities . Environ. Microbiol . 2020 , 22 : 255 – 269 . doi: 10.1111/1462-2920.14843 . OpenUrl CrossRef 53. ↵ Bergen D , Puiggené Ò , Marcellin E , Speight RE , Nikel PI , Ebert BE : Co-substrate free valorisation of lignin monomers by assimilation of C1 and C2 by-products . In preparation , 2025 . 54. ↵ Orsi E , Claassens NJ , Nikel PI , Lindner SN : Growth-coupled selection of synthetic modules to accelerate cell factory development . Nat. Commun . 2021 , 12 : 5295 . doi: 10.1038/s41467-021-25665-6 . OpenUrl CrossRef PubMed 55. ↵ Wirth NT , Rohr K , Danchin A , Nikel PI : Recursive genome engineering decodes the evolutionary origin of an essential thymidylate kinase activity in Pseudomonas putida KT2440 . mBio 2023 , 14 : e01081 – 23 . doi: 10.1128/mbio.01081-23 . OpenUrl CrossRef PubMed 56. ↵ Belda E , van Heck RGA , López-Sánchez MJ , Cruveiller S , Barbe V , Fraser C , Klenk HP , Petersen J , Morgat A , Nikel PI , et al : The revisited genome of Pseudomonas putida KT2440 enlightens its value as a robust metabolic chassis . Environ. Microbiol . 2016 , 18 : 3403 – 3424 . doi: 10.1111/1462-2920.13230 . OpenUrl CrossRef PubMed 57. ↵ Martínez-García E , Fraile S , Algar E , Aparicio T , Velázquez E , Calles B , Tas H , Blázquez B , Martín B , Prieto C , et al : SEVA 4.0: An update of the Standard European Vector Architecture database for advanced analysis and programming of bacterial phenotypes . Nucleic Acids Res . 2023 , 51 : D1558 – D1567 . doi: 10.1093/nar/gkac1059 . OpenUrl CrossRef PubMed 58. ↵ Silva-Rocha R , Martínez-García E , Calles B , Chavarría M , Arce-Rodríguez A , de las Heras A , Páez-Espino AD , Durante-Rodríguez G , Kim J , Nikel PI , et al : The Standard European Vector Architecture (SEVA): a coherent platform for the analysis and deployment of complex prokaryotic phenotypes . Nucleic Acids Res . 2013 , 41 : D666 – D675 . doi: 10.1093/nar/gks1119 . OpenUrl CrossRef PubMed Web of Science 59. ↵ Wu TY , Chen CT , Liu JT , Bogorad IW , Damoiseaux R , Liao JC : Characterization and evolution of an activator-independent methanol dehydrogenase from Cupriavidus necator N-1 . Appl. Microbiol. Biotechnol . 2016 , 100 : 4969 – 83 . doi: 10.1007/s00253-016-7320-3 . OpenUrl CrossRef 60. ↵ Li WJ , Jayakody LN , Franden MA , Wehrmann M , Daun T , Hauer B , Blank LM , Beckham GT , Klebensberger J , Wierckx N : Laboratory evolution reveals the metabolic and regulatory basis of ethylene glycol metabolism by Pseudomonas putida KT2440 . Environ. Microbiol . 2019 , 21 : 3669 – 3682 . doi: 10.1111/1462-2920.14703 . OpenUrl CrossRef 61. ↵ Bator I , Karmainski T , Tiso T , Blank LM : Killing two birds with one stone—Strain engineering facilitates the development of a unique rhamnolipid production process . Front. Bioeng. Biotechnol . 2020 , 8 : 899 . doi: 10.3389/fbioe.2020.00899 . OpenUrl CrossRef PubMed 62. ↵ Wehrmann M , Berthelot C , Billard P , Klebensberger J : The PedS2/PedR2 two-component system is crucial for the rare Earth element switch in Pseudomonas putida KT2440 . mSphere 2018 , 3 : e00376 – 18 . doi: 10.1128/mSphere.00376-18 . OpenUrl CrossRef PubMed 63. ↵ Roth TB , Woolston BM , Stephanopoulos G , Liu DR : Phage-assisted evolution of Bacillus methanolicus methanol dehydrogenase 2 . ACS Synth. Biol . 2019 , 8 : 796 – 806 . doi: 10.1021/acssynbio.8b00481 . OpenUrl CrossRef PubMed 64. Wenk S , Schann K , He H , Rainaldi V , Kim S , Lindner SN , Bar-Even A: An “energy-auxotroph” Escherichia coli provides an in vivo platform for assessing NADH regeneration systems . Biotechnol. Bioeng . 2020 , 117 : 3422 – 3434 . doi: 10.1002/bit.27490 . OpenUrl CrossRef PubMed 65. Kotrbova-Kozak A , Kotrba P , Inui M , Sajdok J , Yukawa H : Transcriptionally regulated adhA gene encodes alcohol dehydrogenase required for ethanol and n-propanol utilization in Corynebacterium glutamicum R . Appl. Microbiol. Biotechnol . 2007 , 76 : 1347 – 1356 . doi: 10.1007/s00253-007-1094-6 . OpenUrl CrossRef PubMed 66. ↵ Whitaker WB , Jones JA , Bennett RK , González JE , Vernacchio VR , Collins SM , Palmer MA , Schmidt S , Antoniewicz MR , Koffas MA , Papoutsakis ET : Engineering the biological conversion of methanol to specialty chemicals in Escherichia coli . Metab. Eng . 2017 , 39 : 49 – 59 . doi: 10.1016/j.ymben.2016.10.015 . OpenUrl CrossRef PubMed 67. ↵ Schmidt S , Christen P , Kiefer P , Vorholt JA : Functional investigation of methanol dehydrogenase-like protein XoxF in Methylobacterium extorquens AM1 . Microbiology 2010 , 156 : 2575 – 2586 . doi: 10.1099/mic.0.038570-0 . OpenUrl CrossRef PubMed 68. ↵ Wirth NT , Gurdo N , Krink N , Vidal-Verdú A , Donati S , Fernández-Cabezón L , Wulff T , Nikel PI : A synthetic C2 auxotroph of Pseudomonas putida for evolutionary engineering of alternative sugar catabolic routes . Metab. Eng . 2022 , 74 : 83 – 97 . doi: 10.1016/j.ymben.2022.09.004 . OpenUrl CrossRef PubMed 69. ↵ Martínez-García E , Aparicio T , de Lorenzo V , Nikel PI : New transposon tools tailored for metabolic engineering of Gram-negative microbial cell factories . Front. Bioeng. Biotechnol . 2014 , 2 : 46 . doi: 10.3389/fbioe.2014.00046 . OpenUrl CrossRef PubMed 70. ↵ Martínez-Gil M , Yousef-Coronado F , Espinosa-Urgel M: LapF, the second largest Pseudomonas putida protein, contributes to plant root colonization and determines biofilm architecture . Mol. Microbiol . 2010 , 77 : 549 – 561 . doi: 10.1111/j.1365-2958.2010.07249.x . OpenUrl CrossRef PubMed 71. ↵ Martínez-Gil M , Quesada JM , Ramos-González MI , Soriano MI , de Cristóbal RE , Espinosa-Urgel M: Interplay between extracellular matrix components of Pseudomonas putida biofilms . Res. Microbiol . 2013 , 164 : 382 – 389 . doi: 10.1016/j.resmic.2013.03.021 . OpenUrl CrossRef PubMed 72. ↵ Schann K , Bakker J , Boinot M , Kuschel P , He H , Nattermann M , Paczia N , Erb T , Bar-Even A , Wenk S : Design, construction and optimization of formaldehyde growth biosensors with broad application in biotechnology . Microb. Biotechnol . 2024 , 17 : e14527 . doi: 10.1111/1751-7915.14527 . OpenUrl CrossRef PubMed 73. ↵ Chavarría M , Kleijn RJ , Sauer U , Pflüger-Grau K , de Lorenzo V: Regulatory tasks of the phosphoenolpyruvate-phosphotransferase system of Pseudomonas putida in central carbon metabolism . mBio 2012 , 3 : e00028 – 12 . doi: 10.1128/mBio.00028-12 . OpenUrl CrossRef PubMed 74. ↵ Cotton CA , Claassens NJ , Benito-Vaquerizo S , Bar-Even A: Renewable methanol and formate as microbial feedstocks . Curr. Opin. Biotechnol . 2020 , 62 : 168 – 180 . doi: 10.1016/j.copbio.2019.10.002 . OpenUrl CrossRef PubMed 75. ↵ Krüsemann JL , Rainaldi V , Cotton CA , Claassens NJ , Lindner SN : The cofactor challenge in synthetic methylotrophy: bioengineering and industrial applications . Curr. Opin. Biotechnol . 2023 , 82 : 102953 . doi: 10.1016/j.copbio.2023.102953 . OpenUrl CrossRef PubMed 76. ↵ Bruinsma L , Wenk S , Claassens NJ , Martins dos Santos VAP: Paving the way for synthetic C1 metabolism in Pseudomonas putida through the reductive glycine pathway . Metab. Eng . 2023 , 76 : 215 – 224 . doi: 10.1016/j.ymben.2023.02.004 . OpenUrl CrossRef PubMed 77. ↵ Yang XP , Zhong GF , Lin JP , Mao DB , Wei DZ : Pyrroloquinoline quinone biosynthesis in Escherichia coli through expression of the Gluconobacter oxydans pqqABCDE gene cluster . J. Ind. Microbiol. Biotechnol . 2010 , 37 : 575 – 580 . doi: 10.1007/s10295-010-0703-z . OpenUrl CrossRef PubMed 78. ↵ Platt R , Drescher C , Park SK , Phillips GJ : Genetic system for reversible integration of DNA constructs and lacZ gene fusions into the Escherichia coli chromosome . Plasmid 2000 , 43 : 12 – 23 . doi: 10.1006/plas.1999.1433 . OpenUrl CrossRef PubMed Web of Science 79. ↵ Hartmans S , Smits JP , van der Werf MJ , Volkering F , de Bont JA: Metabolism of styrene oxide and 2-phenylethanol in the styrene-degrading Xanthobacter strain 124X . Appl. Environ. Microbiol . 1989 , 55 : 2850 – 2855 . doi: 10.1128/aem.55.11.2850-2855.1989 . OpenUrl Abstract / FREE Full Text 80. ↵ Nikel PI , Pérez-Pantoja D , de Lorenzo V: Pyridine nucleotide transhydrogenases enable redox balance of Pseudomonas putida during biodegradation of aromatic compounds . Environ. Microbiol . 2016 , 18 : 3565 – 3582 . doi: 10.1111/1462-2920.13434 . OpenUrl CrossRef 81. ↵ Wirth NT , Funk J , Donati S , Nikel PI : QurvE: user-friendly software for the analysis of biological growth and fluorescence data . Nat. Protoc . 2023 , 18 : 2401 – 2403 . doi: 10.1038/s41596-023-00850-7 . OpenUrl CrossRef PubMed 82. ↵ Volke DC , Friis L , Wirth NT , Turlin J , Nikel PI : Synthetic control of plasmid replication enables target- and self-curing of vectors and expedites genome engineering of Pseudomonas putida . Metab. Eng. Commun . 2020 , 10 : e00126 . doi: 10.1016/j.mec.2020.e00126 . OpenUrl CrossRef 83. Volke DC , Martino RA , Kozaeva E , Smania AM , Nikel PI : Modular (de)construction of complex bacterial phenotypes by CRISPR/nCas9-assisted, multiplex cytidine base-editing . Nat. Commun . 2022 , 13 : 3026 . doi: 10.1038/s41467-022-30780-z . OpenUrl CrossRef 84. Fernández-Cabezón L , Cros A , Nikel PI : Spatiotemporal manipulation of the mismatch repair system of Pseudomonas putida accelerates phenotype emergence . ACS Synth. Biol . 2021 , 10 : 1214 – 1226 . doi: 10.1021/acssynbio.1c00031 . OpenUrl CrossRef PubMed 85. ↵ Fernández-Cabezón L , Rosich i Bosch B , Kozaeva E , Gurdo N , Nikel PI : Dynamic flux regulation for high-titer anthranilate production by plasmid-free, conditionally-auxotrophic strains of Pseudomonas putida . Metab. Eng . 2022 , 73 : 11 – 25 . doi: 10.1016/j.ymben.2022.05.008 . OpenUrl CrossRef PubMed 86. ↵ Wirth NT , Kozaeva E , Nikel PI : Accelerated genome engineering of Pseudomonas putida by I-SceI―mediated recombination and CRISPR-Cas9 counterselection . Microb. Biotechnol . 2020 , 13 : 233 – 249 . doi: 10.1111/1751-7915.13396 . OpenUrl CrossRef 87. ↵ Figurski DH , Helinski DR : Replication of an origin-containing derivative of plasmid RK2 dependent on a plasmid function provided in trans . Proc. Natl. Acad. Sci. USA 1979 , 76 : 1648 – 1652 . doi: 10.1073/pnas.76.4.1648 . OpenUrl Abstract / FREE Full Text 88. ↵ Volke DC , Wirth NT , Nikel PI : Rapid genome engineering of Pseudomonas assisted by fluorescent markers and tractable curing of plasmids . Bio-protocol 2021 , 11 : e3917 . doi: 10.21769/BioProtoc.3917 . OpenUrl CrossRef 89. ↵ Noor E , Bar-Even A , Flamholz A , Reznik E , Liebermeister W , Milo R : Pathway thermodynamics highlights kinetic obstacles in central metabolism . PLoS Comput. Biol . 2014 , 10 : e1003483 . doi: 10.1371/journal.pcbi.1003483 . OpenUrl CrossRef PubMed 90. ↵ Noor E , Haraldsdóttir HS , Milo R , Fleming RM : Consistent estimation of Gibbs energy using component contributions . PLoS Comput. Biol . 2013 , 9 : e1003098 . doi: 10.1371/journal.pcbi.1003098 . OpenUrl CrossRef PubMed 91. ↵ Bachleitner S , Ata Ö , Mattanovich D : The potential of CO2-based production cycles in biotechnology to fight the climate crisis . Nat. Commun . 2023 , 14 : 6978 . doi: 10.1038/s41467-023-42790-6 . OpenUrl CrossRef 92. ↵ Luo S , Diehl C , He H , Bae Y , Klose M , Claus P , Cortina NS , Fernández CA , Schulz-Mirbach H , McLean R , et al : Construction and modular implementation of the THETA cycle for synthetic CO 2 fixation . Nat. Catal . 2023 , 6 : 1228 – 1240 . doi: 10.1038/s41929-023-01079-z . OpenUrl CrossRef 93. ↵ Roca A , Rodríguez-Herva JJ , Duque E , Ramos JL : Physiological responses of Pseudomonas putida to formaldehyde during detoxification . Microb. Biotechnol . 2008 , 1 : 158 – 169 . doi: 10.1111/j.1751-7915.2007.00014.x . OpenUrl CrossRef PubMed 94. ↵ Bennett BD , Kimball EH , Gao M , Osterhout R , Van Dien SJ , Rabinowitz JD : Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli . Nat. Chem. Biol . 2009 , 5 : 593 – 599 . doi: 10.1038/nchembio.186 . OpenUrl CrossRef PubMed Web of Science 95. ↵ Arce-Rodríguez A , Volke DC , Bense S , Häussler S , Nikel PI : Non-invasive, ratiometric determination of intracellular pH in Pseudomonas species using a novel genetically encoded indicator . Microb. Biotechnol . 2019 , 12 : 799 – 813 . doi: 10.1111/1751-7915.13439 . OpenUrl CrossRef PubMed 96. ↵ Alberty RA , Cornish-Bowden A , Goldberg RN , Hammes GG , Tipton K , Westerhoff HV : Recommendations for terminology and databases for biochemical thermodynamics . Biophys. Chem . 2011 , 155 : 89 – 103 . doi: 10.1016/j.bpc.2011.03.007 . OpenUrl CrossRef PubMed 97. ↵ Löwe H , Kremling A : In-depth computational analysis of natural and artificial carbon fixation pathways . BioDesign Res . 2021 , 2021 : 9898316 . doi: 10.34133/2021/9898316 . OpenUrl CrossRef 98. ↵ Ebrahim A , Lerman JA , Palsson BØ , Hyduke DR : COBRApy: COnstraints-Based Reconstruction and Analysis for Python . BMC Syst. Biol . 2013 , 7 : 74 . doi: 10.1186/1752-0509-7-74 . OpenUrl CrossRef PubMed 99. ↵ Heirendt L , Arreckx S , Pfau T , Mendoza SN , Richelle A , Heinken A , Haraldsdóttir HS , Wachowiak J , Keating SM , Vlasov V , et al : Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0 . Nat. Protoc . 2019 , 14 : 639 – 702 . doi: 10.1038/s41596-018-0098-2 . OpenUrl CrossRef PubMed 100. ↵ Nikel PI , Chavarría M , Fuhrer T , Sauer U , de Lorenzo V: Pseudomonas putida KT2440 strain metabolizes glucose through a cycle formed by enzymes of the Entner-Doudoroff, Embden-Meyerhof-Parnas, and pentose phosphate pathways . J. Biol. Chem . 2015 , 290 : 25920 – 25932 . doi: 10.1074/jbc.M115.687749 . OpenUrl Abstract / FREE Full Text 101. ↵ Ferreira JA : The Benjamini-Hochberg method in the case of discrete test statistics . Int. J. Biostat . 2007 , 3 : 11 . doi: 10.2202/1557-4679.1065 . OpenUrl CrossRef 102. Neidhardt FC , Ingraham JL , Schaechter M : Physiology of the bacterial cell: a molecular approach . 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Share Systematic engineering of synthetic serine cycles in Pseudomonas putida uncovers emergent topologies for methanol assimilation Òscar Puiggené , Jaime Muñoz-Triviño , Laura Civil-Ferrer , Line Gille , Helena Schulz-Mirbach , Daniel Bergen , Tobias J. Erb , Birgitta E. Ebert , Pablo I. Nikel bioRxiv 2025.02.17.638773; doi: https://doi.org/10.1101/2025.02.17.638773 Share This Article: Copy Citation Tools Systematic engineering of synthetic serine cycles in Pseudomonas putida uncovers emergent topologies for methanol assimilation Òscar Puiggené , Jaime Muñoz-Triviño , Laura Civil-Ferrer , Line Gille , Helena Schulz-Mirbach , Daniel Bergen , Tobias J. Erb , Birgitta E. Ebert , Pablo I. 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