Optimization of a T7 RNA polymerase expression system for high-yield protein production in Cupriavidus necator H16

Optimization of a T7 RNA polymerase expression system for high-yield protein production in Cupriavidus necator H16 | 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 Optimization of a T7 RNA polymerase expression system for high-yield protein production in Cupriavidus necator H16 View ORCID Profile Matteo Vajente , View ORCID Profile Hendrik Ballerstedt , View ORCID Profile Lars Mathias Blank , View ORCID Profile Sandy Schmidt doi: https://doi.org/10.1101/2025.11.17.688765 Matteo Vajente a Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen , Antonius Deusinglaan 1, Groningen 9713AV, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Matteo Vajente Hendrik Ballerstedt b Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University , Worringerweg 1, 52074 Aachen, Germany , WSS research centre “catalaix”. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hendrik Ballerstedt Lars Mathias Blank b Institute of Applied Microbiology (iAMB), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University , Worringerweg 1, 52074 Aachen, Germany , WSS research centre “catalaix”. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lars Mathias Blank Sandy Schmidt a Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen , Antonius Deusinglaan 1, Groningen 9713AV, The Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sandy Schmidt For correspondence: s.schmidt{at}rug.nl Abstract Full Text Info/History Metrics Preview PDF Abstract Many chemical manufacturing routes are being replaced with enzymatic processes to improve sustainability and reduce the use of harmful chemicals. Enzyme production is often the main bottleneck of the process, and proteins are frequently produced using the workhorse E. coli BL21(DE3) and its derivatives. However, other bacteria with beneficial characteristics can also be engineered for this purpose. Cupriavidus necator H16 ( C. necator ), for example, is a Gram-negative bacterium well-known for its lithoautotrophic metabolism and high polyhydroxybutyrate (PHB) accumulation. Previous studies have demonstrated high-yield protein production without inclusion body formation, which is one of the main challenges when producing enzymes in E. coli . Nevertheless, high-yield protein production in C. necator remains an understudied field. Here, we optimized a T7 RNA polymerase genetic system to improve protein production in C. necator . We investigated the impact of codon usage, different inducible promoters, and several genetic elements by expressing the fluorescent reporter protein GFP. Codon usage was the main factor limiting protein production in C. necator . Tuning the RBS strength also strongly reduced leakiness of the promoter. As an application, we compared the performance of our engineered C. necator T7 RNA polymerase-based system to that of an E. coli -based T7 system using the ene-reductase YqjM from Bacillus subtilis . The optimized protein expression system in C. necator outperformed the gold standard, E. coli BL21(DE3), in producing soluble, FMN-loaded enzyme. This result highlights the potential of non-model bacteria to achieve high-yield enzyme production and promote the transition to biocatalysis-driven chemical synthesis. Highlights T7 RNA polymerase-driven protein expression in the bacterium Cupriavidus necator ( C. necator ) Codon usage tuning was essential to increase protein production in C. necator RBS tuning influenced both leakiness and maximum expression T7 RNA polymerase activation decreased the final OD 600 considerably C. necator produced more FMN-loaded enzyme than E. coli BL21(DE3) Download figure Open in new tab Graphical abstract 1 INTRODUCTION Biocatalysis has emerged as a cornerstone of biotechnology, offering efficient alternatives to traditional chemical synthesis by harnessing the high selectivity and reactivity of enzymes. Central to advancing biocatalysis is the reliable and cost-effective production of enzymes, which requires not only optimization of the specific protein but also careful selection of the host system in which it is produced. Different microbial and eukaryotic hosts offer distinct advantages in terms of expression yield, post-translational modifications, scalability and economic feasibility ( Tripathi and Shrivastava, 2019 ). Since the first application in 1986, Escherichia coli ( E. coli ) strains from the B lineage containing T7 RNA polymerase (T7RNAP) have become the golden standard for protein production in prokaryotic organisms ( Studier and Moffatt, 1986 ). The T7 system allows easy induction and strong orthogonal expression of specific genes of interest. While novel E. coli strains have been developed to address shortcomings of the first system (e.g. leakiness) ( Rosano et al., 2019 ), growing E. coli to high-cell density still suffers from various drawbacks including the formation of organic acids, proteolysis and inclusion-body formation ( Choi et al., 2006 ; Shiloach and Fass, 2005 ). Moreover, several heterologous proteins such as formate dehydrogenases or hydrogenases have been troublesome to produce in E. coli due to a lack of appropriate chaperones or maturation factors ( Ryu et al., 2024 ; Schiffels et al., 2013 ). Other non-model bacteria, such as Cupriavidus necator ( C. necator , formerly known as Ralstonia eutropha ), are currently attracting attention because of their autotrophic metabolism and potential applications in C1-based biotechnology. However, efficient protein production is still underdeveloped in such non-model strains. C. necator is an attractive host for protein production due to its versatile proteome ( Jahn et al., 2021 ) and its lithoautotrophic metabolism. It is able to grow autotrophically on “Knallgas”, a mixture of H 2 , O 2 and CO 2 , and engineered strains have shown production of various metabolites from CO 2 ( Pan et al., 2021 ). Enzyme production has been demonstrated and quantified in both heterotrophic and autotrophic conditions, proving that protein production in autotrophic conditions is feasible ( Arhar et al., 2024 ). In addition, the native formatotrophic metabolism of C. necator enables growth on formic acid, which can be synthesized from CO 2 through electroreduction ( Jhong et al., 2013 ). Recently, formate-based production of enzymes for biocatalysis in this host has also been reported ( Hallamaa et al., 2025 ). Therefore, C. necator is a suitable chassis for upgrading CO 2 -rich effluents into proteins of interest for more sustainable biochemical synthesis. Food proteins are another promising market sector for hydrogen-oxidizing bacteria ( Angenent et al., 2022 ; Bernal-Cabas et al., 2025 ), as C. necator is generally recognized as safe (GRAS). This microorganism can be grown at high cell densities in both autotrophic and heterotrophic conditions ( Srinivasan et al., 2002 ; Tanaka et al., 1995 ). Its high protein content, which can account for up to 83% of cell dry weight depending on the carbon source and growth conditions ( Ismail et al., 2025 , 2024 ), emphasizes its potential for producing recombinant proteins, either as a whole-cell biocatalyst or for further protein purification. Interestingly, C. necator has been shown to express enzymes that E. coli is not able to produce or that cause the formation of inclusion bodies ( Ryu et al., 2024 ; Srinivasan et al., 2002 ). Thus far, the best-performing recombinant expression method in C. necator used a T7RNAP-based system; however, it relied on a proprietary strain derived from H16 ( Barnard et al., 2004 ; Byrom, 1994 ). A recent attempt to establish a T7-based system in C. necator H16 was unsuccessful, as the T7-driven system yielded the same amount of Red Fluorescent Protein (RFP) as a plasmid carrying the P BAD arabinose-inducible promoter ( Hu et al., 2020 ). An ideal production strain should exhibit strong gene expression and translation, leading to high yield of soluble, cofactor-loaded enzyme. In addition, it should also be tightly regulated to separate the biomass accumulation phase from the protein production phase. This is especially important when the energy or carbon source is limited by process parameters, such as growth under autotrophic conditions. This separation could decrease plasmid loss during biomass accumulation, a known problem in C. necator ( Ehsaan et al., 2021 ). Several engineering iterations have successfully improved these parameters for E. coli BL21(DE3) and derivatives, but no optimization has yet been attempted for protein production in C. necator . Although several studies have demonstrated its ability to synthesize small molecules from CO 2 ( Pan et al., 2021 ), few have quantified heterologous enzyme production ( Arhar et al., 2024 ; Assil-Companioni et al., 2019 ; Barnard et al., 2004 ; Gruber et al., 2016 ; Ryu et al., 2024 ). In this study, we describe the establishment of an inducible T7 RNA polymerase system in C. necator . During several rounds of iterative engineering, we examined the impact of RBS strength and codon usage on the expression of T7RNAP and green fluorescent protein (GFP). We investigated different inducible promoters (rhamnose and salicylate) and variants of the T7 promoter. Finally, we evaluated the performance of our system by producing YqjM, a flavin-dependent ene-reductase of biocatalytic interest. This improved recombinant protein production system enables the easy expression of genes of interest and expands the array of prokaryotic chassis for protein production. This is especially true given the vast genome and availability of maturation cofactors in C. necator . Furthermore, its native lithoautotrophic metabolism enables enzyme production directly from CO 2 or formate, making C. necator a promising chassis for C1-based biocatalysis. 2 Materials and Methods Chemicals, Bacterial Strains, and Culture Conditions All chemicals used were purchased from Sigma−Aldrich Ltd., VWR International LLC, or Carl Roth GmbH in the highest available purity. The strains, plasmids, primers, genetic elements, and gene sequences used in this study are listed in Tables 1 , S1 , S3 , and S6 . C. necator and E. coli were grown in lysogeny broth (LB, 10 g/L tryptone, 10 g/L NaCl, 5 g/L yeast extract) at 30 °C ( C. necator ) and 37 °C ( E. coli ), shaking orbitally at 200 rpm. Agar agar was added to a final concentration of 2% to obtain LB agar. When appropriate, media was supplemented with antibiotics at the specified concentrations: kanamycin ( E. coli : 50 μg/mL, C. necator : 200 μg/mL (routine cultivations) or 400 μg/mL (selection after electroporation)), tetracycline ( E. coli , C. necator : 15 μg/mL), and gentamicin ( C. necator : 20 μg/mL). View this table: View inline View popup Table 1: Strains used and created in this study. Cloning and plasmid assembly Plasmid DNA was purified using QIAprep Spin Miniprep Kit (Qiagen). DNA purification from PCR reaction mixtures was performed using QIAquick PCR Purification Kit (Qiagen Ltd., UK). Microbial genomic DNA was extracted using the NucleoSpin Microbial DNA Kit (Macherey-Nagel). Oligonucleotide primers were synthesized by Eurofins Genomics (Ebersberg, Germany). Plasmids were sequenced by Sanger sequencing or whole plasmid nanopore sequencing (Macrogen Europe). BsaI-HFv2, BbsI-HF, and T4 DNA ligase were purchased from New England BioLabs (NEB). DpnI FastDigest was purchased from Thermo Scientific. Plasmids from the Golden Standard library were kindly provided by the authors ( Blázquez et al., 2022 ). Plasmid pLO3 ( Lenz and Friedrich, 1998 ) was kindly provided by Dr. Oliver Lenz (TU Berlin, Germany). A derivative plasmid without restriction patterns was used, according to a previous study ( Vajente et al., 2024 ). Plasmid pET28a-YqjM was kindly provided by Prof. Frank Hollmann (TU Delft, The Netherlands) ( Pesic et al., 2017 ). All genetic parts were PCR-amplified, synthesized from Twist Bioscience, or synthesized as oligonucleotides. DNA was amplified by PCR using Q5 High-Fidelity DNA Polymerase (NEB) following the manufacturer’s instructions. After PCR amplification, template DNA was removed by adding 0.5 μL of DpnI to the PCR mix and incubating the mixture at 37 °C for 1 h. To anneal oligonucleotides, equimolar amounts of complementary primers (final concentration: 30 μM) were mixed in annealing buffer (10 mM Tris, 50 mM NaCl, 1 mM EDTA, pH 7.5) and incubated in a thermocycler for 2 min at 95 °C. The temperature was then decreased by 1 °C per cycle for 70 cycles (40 s each). All plasmids were assembled using Golden Gate assembly ( Engler et al., 2008 ). Briefly, 75 ng of PCR-amplified backbone or acceptor plasmid were mixed with linear fragments in a 1:2 molar ratio, with donor plasmids in a 1:1 molar ratio, or with annealed oligonucleotides in a 1:10 molar ratio. Golden Gate reactions were carried out in a total volume of 10 μL by mixing the DNA, ultrapure water, T4 DNA ligase buffer, T4 DNA ligase (200 U), and BsaI-HFv2 or BbsI-HF (6 U). The mixture was then incubated in a thermocycler using the following program: (37 °C, 5 min → 16 °C, 5 min) × 15-30 cycles → 60 °C, 5 min. Finally, the assembled plasmids were used to transform competent E. coli DH5α cells. In Tables S2 - S3 the DNA fragments used to assemble each plasmid are described in detail. Plasmid maps are included in the Supplementary Information as GenBank files. Codon usage and Codon Adaptation Index analysis T7RNAP and YqjM were codon harmonized for C. necator using a previously reported codon-harmonization tool ( https://codonharmonizer.systemsbiology.nl/ ) ( Claassens et al., 2017 ). Codon usage tables were calculated from the coding sequences of the genomes on the Galaxy web platform, using cusp (EMBOSS) on the public server at usegalaxy.eu ( Rice et al., 2000 ; The Galaxy Community et al., 2024). Accession numbers of the genomes used for calculations are reported in the Supplementary Information ( Table S4 ). Codon Adaptation Index (CAI) values were calculated using cai custom (EMBOSS) on usegalaxy.eu. Nucleic sequences and CAI values for all genes used in this manuscript are available in the Supplementary Information ( Tables S3 , S5 ). GFPmut3 was codon optimized (the genome of the original organism was unavailable at the time) using the codon-optimization tool from Geneious Prime (Dotmatics) and the C. necator codon usage table calculated as described above. E. coli Transformation For E. coli transformations, 50 μL of chemically competent cells prepared following a previously published method ( Inoue et al., 1990 ) were mixed with plasmid DNA, incubated on ice for 30 min, followed by a heat shock at 42 °C for 45 s and a subsequent incubation on ice for 2 min. Cells were recovered in 950 μL of Super Optimal broth with Catabolite repression (SOC) medium at 37 °C for 1 h, plated on LB agar with the appropriate antibiotic, and incubated overnight at 37 °C. C. necator Electroporation Electroporation of C. necator was performed as previously described ( Vajente et al., 2024 ). Briefly, C. necator was streaked onto a LB agar plate and grown at 30 °C for 40 h. A single colony was then cultivated in SOB supplemented with 20 μg/mL gentamicin for 16 h at 30 °C. Fresh SOB supplemented with gentamicin was inoculated with the preculture at an initial OD 600 of 0.1 and cultivated at 30 °C. When the cells reached an OD 600 of 0.6, they were transferred onto ice and chilled for 5−10 min. The cells were then transferred to 50 mL tubes and centrifuged at 6000 x g at 4 °C for 2 min. The supernatant was removed, and the cells were resuspended in 25 mL of 50 mM CaCl 2 by briefly vortexing. They were then incubated on ice for 15 min. The cells were then centrifuged at 6500 x g at 4 °C for 2 min, and the supernatant was removed. Cells were washed twice using 25 and 15 mL of ice-cold 0.2 M sucrose, respectively. At the end of each wash, cells were centrifuged at 6500 x g at 4 °C for 2−3 min, and the supernatant was decanted. The cell pellet was finally resuspended in 1/100 of the initial volume (e.g., 100 mL initial cell culture to 1 mL final resuspension volume). Aliquots of competent cells were transferred into microcentrifuge tubes, frozen in liquid nitrogen and stored at −80 °C until further use. For electroporation, each aliquot was thawed on ice for 20 min, transferred into a pre-chilled 1 mm electroporation cuvette, mixed with 50−200 ng of plasmid DNA and electroporated (25 μF, 200 Ω, 1.15 kV). Super Optimal Broth (950 μL; 20 g/L tryptone, 5 g/L yeast extract, 0.5 g/L NaCl, 2.5 mM KCl, 20 mM MgSO 4 , pH 7) supplemented with fructose (20 mM) was immediately added and the cells were transferred to a 2 mL centrifuge tube for outgrowth at 30 °C for 2 h. After the outgrowth, cells were diluted and plated on appropriate selective media. Genome editing Knock-in and knock-out plasmids were used for C. necator H16 genome modification by double homologous recombination, as explained previously ( Vajente et al., 2024 ). Most plasmids were introduced by electroporation following the method described above. Colonies that underwent the first recombination were selected on LB supplemented with 15 μg/mL tetracycline. Positive colonies were picked and grown overnight in 5 mL of low-salt LB (LSLB) without any supplementation (10 g/L tryptone, 5 g/L NaCl, 5 g/L yeast extract). Different dilutions were plated on LSLB-agar supplemented with 180 g/L sucrose to select for sacB -negative colonies. When selecting for ΔnagR strains ( C. necator ΔnagR , T7R, T7S), different dilutions were plated on minimum media supplemented with glucose. Colony PCR was performed to screen for double-crossover insertion and deletion mutants. Genomic DNA was extracted from the promising clones to PCR-amplify the targeted region and confirm insertion or deletion by amplicon sequencing. All plasmids were successfully introduced by electroporation (pLONagR, pLOT7R, pLOT7S, pLOT7R2) apart from pLOT7RT. In that case, the strain E. coli S17-1 was used for conjugation. Briefly, E. coli S17-1 was transformed with plasmid pLOT7RT as explained above. The donor and acceptor strains were grown overnight in LB supplemented with the appropriate antibiotics. Then, 200 μL of each saturated solution were centrifuged and washed with LSLB before resuspension in 100 μL LSLB. The cultures were mixed and plated on LSLB without antibiotics and incubated overnight at 30 °C. The biomass was then scraped from the plate, resuspended in LB and plated on LB agar supplemented with 15 μg/mL tetracycline and 20 μg/mL gentamicin, then grown for 2 days at 30 °C. Then, positive colonies were picked, grown overnight, and tested as above. Fluorescence Measurement Precultures were cultivated overnight at 30 °C at 200 rpm in 96-deep well plate wells (Greiner, Masterblock, 96 well, 2 mL, PP, V-bottom) containing 0.5 mL of LB supplemented with 200 μg/mL kanamycin when necessary. The deep well plates were sealed using a gas-permeable membrane (Diversified Biotech, Breathe-Easy). The following day, the OD 600 was measured using a spectrophotometer (biochrom, Ultrospec 10). The cultures were then centrifuged (3400 x g , 30 min, 4 °C), and each culture was resuspended to OD 600 2 using fresh medium. A new 96-deep well plate was prepared with 0.45 mL in each well. Then, each well was inoculated to an initial OD 600 0.2 by adding 50 μL of pre-culture. The plate was then sealed with a permeable membrane and grown at 30 °C, 200 rpm for 3 h. Each culture was then induced adding sterile solutions of L-rhamnose, sodium salicylate, or theophylline. To measure uninduced expression, some cultures were left uninduced. The deep well plate was then incubated at 30 °C, 200 rpm for 22 h. Appropriate dilutions were transferred to a 96-well black walled plate (Greiner, 96 well, PS, F-bottom µCLEAR®). Fluorescence of GFPmut3 was measured from the top at an excitation wavelength of 485 nm and an emission wavelength of 535 nm with a gain of 80 in a BioTek Synergy H1 plate reader. Biomass was determined at 600 nm as scattered light. Each value was blanked using empty media (with or without kanamycin). To determine specific fluorescence, fluorescence intensity was divided by scattered light. To normalize our results, fluorescein sodium salt was used to create a calibration curve. To measure GFP expression driven by constitutive promoters, the same protocol was followed without the induction step. Two-sample t test was used when comparing two samples. When comparing multiple conditions, one-way ANOVA and Tukey’s multiple comparison test were used. * = adjusted p-value <0.05; ** = adjusted p-value <0.01; *** = adjusted p-value <0.001; **** = adjusted p-value <0.0001. In Figure 2 , the results of the statistical analysis are reported in compact letter display: results have statistically different means (adjusted p-value <0.05) if they do not share any letter. YqjM expression in C. necator Pre-cultures were cultivated overnight at 30 °C, 200 rpm in 50 mL tubes containing 5 mL of LB supplemented with 200 μg/mL kanamycin. LB without antibiotics was used to cultivate the wild type control strains. The following day, 250 mL non-baffled Erlenmeyer flasks were filled with 50 mL of media. The pre-cultures OD 600 was measured, and the flasks were inoculated at an initial OD 600 = 0.1. The cultures were grown at 30 °C, 200 rpm until they reached the induction OD 600 (0.4, 0.8, 1.2). Then, they were induced by adding rhamnose (final concentration: 10 mM). Depending on the experiment, FMN (riboflavin 5ʹ-monophosphate sodium salt hydrate, 73-79%, fluorimetric, Sigma) was added to a final concentration of 1 μM. The cultures were then grown at the chosen temperature (22 °C, 26 °C, 30 °C) for 22 h. The final OD 600 was measured, then the cultures were centrifuged (3400 x g , 30 min, 4 °C), and the wet pellet was weighted. Cell pellets were stored at −20 °C until further analysis. Cell pellets were thawed on ice and resuspended in lysis buffer (20 mM Tris, 150 mM NaCl, pH 7.5, lysozyme), depending on the wet pellet weight (20 mL/g wet pellet). The resuspended cultures were incubated on ice for 20 min, then lysed by sonication (Branson Sonifier 450, intensity 8, duty cycle 40%, 4 cycles of 30 s sonication followed by 1 min on ice). The lysate was then centrifuged (1:15 h, 18 500 x g , 4 °C) to obtain the soluble extract. YqjM expression in E. coli BL21(DE3) Pre-cultures were cultivated overnight at 37 °C at 200 rpm in 50 mL tubes containing 5 mL of LB supplemented with 50 μg/mL kanamycin. LB without antibiotics was used to cultivate the control strain. The following day, 250 mL non-baffled Erlenmeyer flasks were filled with 50 mL of LB supplemented with 50 μg/mL kanamycin. Then, the flasks were inoculated at an initial OD 600 = 0.1. The cultures were grown at 37 °C and 200 rpm until they reached OD 600 = 0.6. Then, they were induced by adding IPTG (final concentration 1 mM). The cultures were then grown at 20°C for 20 h. The final OD 600 was measured, then the cultures were centrifuged (3400 x g , 30 min, 4 °C), and the wet pellet weight was measured. Cell pellets were stored at −20 °C until further analysis. Cell pellets were thawed on ice and resuspended in lysis buffer (20 mM Tris, 150 mM NaCl, pH 7.5, lysozyme), depending on the wet pellet weight (20 mL/g wet pellet). The resuspended cultures were incubated on ice for 20 min, then lysed by sonication (Branson Sonifier 450, intensity 8, duty cycle 40%, 4 cycles of 30 s sonication followed by 1 min on ice). The lysate was then centrifuged for 1:15 h (18 500 x g , 4 °C) to obtain the soluble extract. FMN determination The fresh soluble extract samples were used to determine FMN concentration by measuring the absorbance at 452 nm using a spectrophotometer (Jasco V-650, quartz cuvette). To compare the samples, the values were normalized. For each sample, the absorbance volume was multiplied by the lysis buffer amount (to obtain the total FMN produced in the whole culture), then divided by the final OD (to obtain the specific FMN produced per OD unit). Soluble extracts from wild-type strains without YqjM expression were used as blank. A calibration curve using FMN (riboflavin 5ʹ-monophosphate sodium salt hydrate, 73-79%, fluorimetric, Sigma) was used to convert absorbance to FMN concentration values. In order to convert FMN concentration to predicted yield, we counted each molecule of FMN as a single protein molecule. SDS-PAGE analysis Each fresh soluble fraction sample was analysed using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Samples were prepared by mixing Laemmli Sample Buffer (Bio-rad) and incubating at 95 °C for 10 min. Each sample was added to a pre-cast SDS-PAGE gel (Invitrogen, NuPage, 4-12% Bis-Tris, 10 wells). PageRuler (PageRuler™ Prestained Protein Ladder, 10 to 180 kDa, Thermo Scientific™) was used as a protein ladder. The gels were run in fresh MOPS buffer (Invitrogen, NuPAGE MOPS SDS Running Buffer 20x) for 15 min at 50 V, then for 1:10 h at 150 V. The SDS-PAGE gels were stained using Rapid Protein Stain Coomassie Blue (Westburg Life Sciences) and imaged using a ChemiDoc Imaging System (Bio-Rad). To compare the amount of YqjM produced by C. necator in each culture condition, the Analyze/Gel tool from Fiji was used to perform gel-based quantification. To minimize the influence of loading variability in the analysis, the intensity of the YqjM band (approximately 40 kDa) was normalized using the intensity of another reference protein band ( Figure S5 ). 3 Results 3.1 T7 rna polymerase is expressed in Cupriavidus necator H16 under the control of two inducible promoters T7RNAP was integrated into the genome and expressed in C. necator under the control of two inducible promoters, activated by rhamnose and salicylate, respectively. The rhamnose inducible promoter was selected due to its tightness and its orthogonal nature in C. necator ( Alagesan et al., 2018 ; Sydow et al., 2017 ) (yielding strain C. necator T7R, Figures 1A , S1 ). The native salicylate promoter was selected due to its tightness and high dynamic range ( Hanko et al., 2020 ) ( C. necator T7S, Figures 1A , S1 ). We speculated that using a native inducible system could lead to tighter regulation due to the optimized titration of the activator protein (NahR). We decided to integrate the two systems into the nagR locus, while deleting the nagR gene. This deletion has previously been shown to allow glucose utilization by C. necator , which might be advantageous when using mixed carbon sources or second-generation biomasses ( Orita et al., 2012 ). We used this glucose-growing phenotype as a selection method for successful deletion-integration. C. necator ΔnagR was created and used as a negative control. After integration of the two constructs, GFPmut3 (GFP) fluorescence was used to determine protein expression level. The expression of the GFPmut3 gene was driven by a plasmid under the control of a T7 consensus promoter and RBS B0034m, previously investigated in C. necator ( Keating and Young, 2023 ). We used our recently developed plasmid system (pMVRha) as a benchmark ( Vajente et al., 2024 ) ( Figure 1A ). GFP was successfully expressed in both T7 strains using multiple concentrations of rhamnose and salicylate ( Figure 1B ). The strain C. necator T7S exhibited growth stop after induction with salicylate concentrations higher than 10 μM ( Figure 1C ). While this could be caused by metabolic burden, the fluorescence (and therefore the GFP amount) did not increase. High concentrations of salicylate decreased final OD 600 in the other strains as well, but not as drastically ( Figure 1D ). This suggests that a feedback mechanism may be responsible for the growth inhibition. However, this behavior was not observed in previous experiments with the same promoter and may therefore be attributed to the expression of T7RNAP using a native promoter ( Hanko et al., 2020 ). We decided not to pursue this strain further due to the potential impact of the native metabolism in future experiments. The rhamnose-inducible promoter yielded the highest GFP expression at 10 mM inducer concentration. However, the maximum fluorescence was comparable to that of the plasmid-based system. This is intriguing, since T7RNAP usually delivers higher protein levels due to the higher mRNA transcription rate ( Studier and Moffatt, 1986 ). If the bottleneck lies in the translation phase, however, increasing the amount of mRNA would not influence the final protein yield. We speculated that this was the case in our C. necator T7R strain. Download figure Open in new tab Figure 1: C. necator strains containing genomically-integrated T7 RNA polymerase and producing GFP at different levels after induction with either rhamnose or salicylate as inducer. A) Genetic constructs introduced by genomic integration and plasmid transformation in the C. necator strains. C. necator ΔnagR carrying the pMVRha plasmid was used as a benchmark. B) Fluorescence values 22 hours after induction with different amounts of inducers, measured by plate reader. C) OD600 of different C. necator strains 22 hours after addition of different amounts of inducers, measured by plate reader. D) OD600 of different C. necator strains 22 hours after addition of different amounts of salicylate, measured by plate reader. For all figures, arithmetic means and standard deviations of three biological replicates are reported. Fluorescence is reported as GFU (Green Fluorescent Units: fluorescein equivalent units over OD600). 3.2 CODON USAGE IS THE LIMITING FACTOR FOR HIGH-YIELD PROTEIN PRODUCTION IN CUPRIAVIDUS NECATOR We speculated that protein translation was limited by low ribosome occupancy (low RBS strength), or depletion of the cytoplasmic pool of charged tRNAs (non-optimal codon usage). We assembled multiple genetic constructs to investigate which variable was the bottleneck. Four plasmids were assembled, expressing GFP under the control of two RBSs (B0034m: 34; RBS A: A) ( Figure 2A ; Figure 5C ). Two different GFPmut3 genetic sequences were cloned, one from the original GoldenStandard library (Ec) and one codon-optimized for C. necator (Cn). All plasmids were introduced into C. necator T7R and analyzed for GFP production ( Figure 2B ). We could observe a striking increase in fluorescence (4-fold) when the codon-optimized gene was used, showing that codon usage (and tRNA pool depletion) was the process bottleneck. Even when using the pMVRha expression plasmid, codon optimization led to 2-fold increase in final fluorescence. On the other hand, increasing the strength of the RBS only slightly increased final fluorescence when using a suboptimal amount of inducer. Stronger RBSs also increased uninduced GFP expression, leading to higher leakiness. Download figure Open in new tab Figure 2: Genetic sequences are expressed at low level in C. necator when not codon optimized. A) Genetic parts analyzed in this study. B) Fluorescence values after 22 hours of strain C. necator T7R expressing different GFP genetic sequences under the control of different RBS. For all figures, arithmetic means and standard deviations of three biological replicates are reported. Fluorescence is reported as GFU (Green Fluorescent Units: fluorescein equivalent units over OD600). 3.3 CUPRIAVIDUS NECATOR CONTAINS MORE RARE CODONS COMPARED TO ESCHERICHIA COLI When we designed a codon-optimized GFPmut3 sequence for C. necator , we found that the CAI for E. coli remained high ( Figure 3A ) ( Sharp and Li, 1987 ). Thus, sequences that were optimal for C. necator were also optimal for E. coli , but not vice versa. This discrepancy could be traced to the codon usage of both organisms. We observed that the ratio of synonymous codons for each amino acid was balanced in E. coli . In contrast, it was common to encounter amino acids with imbalanced codon distributions in C. necator , with one codon prevalent and the others barely present in the genome. An example of this behaviour is shown in Figure 3B (the complete analysis can be found in Table S4 ). To quantify this phenomenon properly, we counted the number of codons at each frequency ( Figure 3C ). In C. necator , 23 codons were rare (used less than 10%), whereas in E. coli , this number decreased to six. This highlights the importance of codon usage in C. necator , as previously reported ( Mishra et al., 2024 ). The high number of rare codons suggests that many charged tRNAs may be present in lower quantities, potentially creating bottlenecks during protein production. Download figure Open in new tab Figure 3: C. necator contains a higher number of rare codons compared to E. coli. A) Codon Adaptation Index (CAI) and GC percentage (both total - %GC; and of the third base of the codon - %GC3) of the two GFPmut3 genetic sequences in E. coli and C. necator. The original GFP sequence (GFP (Ec)) showed high CAI for E. coli, while the sequence optimized for C. necator (GFP (Cn)) showed high CAI for both organisms. B) Codon frequency of synonymous codons encoding serine and valine in both E. coli and C. necator. C) Number of codons present at each frequency in C. necator and E. coli. C. necator shows many codons with low and high frequencies, while in E. coli most codons are located in the intermediate range, showing a more balanced distribution. 3.4 Newly designed T7 expression strains reduced leaky expression of the system Although the maximum GFP production was satisfactory, the uninduced expression of the T7 system was higher than the one from pMVRha. Building on the knowledge gathered in our previous round of experiments, we thus proceeded to optimize the T7RNAP genetic construct. Our original system contained a non-codon-optimized T7RNAP sequence under the control of a strong RBS (RBS A). We hypothesized that codon-harmonizing the gene and selecting a weaker RBS would increase both maximum induction and tightness, and constructed a new strain with these modifications ( C. necator T7R2, Figures 4A , S1). A new system for tightly regulating endonuclease expression in C. necator was recently established (Della Valle et al., 2025). Based on that work, we introduced a Self-splicing Intron-Based Riboswitch (SIBR) inside the T7RNAP coding sequence to increase tightness. The coding sequence was only complete when theophylline was added to the medium, due to SIBR self-catalysed excision. Accordingly, we planned two new strains: one with both induction systems ( C. necator T7RT, Figures 4A , S1 ) and one with only SIBR, with the T7RNAP gene under the control of a strong constitutive promoter. Unfortunately, we could not assemble the second strain and decided to abandon this strategy. The novel genetic circuits were integrated near the nagR locus. We chose not to delete nagR , since we initially suspected that our previous modification was responsible for the reduced rhamnose sensitivity observed in the C. necator T7R strain compared to pMVRha. However, this hypothesis proved to be incorrect ( Figure S3 ). The reduced response is probably caused by lower copy number of the rhaRS responsive element. We induced GFP expression in C. necator T7RT with different concentrations of rhamnose and theophylline to identify the optimal conditions for this strain ( Figure 4B ). GFP expression proved tight, requiring high concentrations of both inducers to observe fluorescence production. This is consistent with the reported data from a similar system in E. coli (Della Valle et al., 2025). However, the maximum fluorescence obtained with strain C. necator T7RT was drastically lower than that obtained with the plasmid-based system. Conversely, strain C. necator T7R2 maintained the same maximum fluorescence as C. necator T7R while decreasing system leakiness by half ( Figure 5C ). Download figure Open in new tab Figure 4: Strain C. necator T7R2 maintains maximum GFP expression and has lower leakiness compared to the parent strain. A) Genetic constructs introduced by genomic integration in the new C. necator strains. B) Fluorescence expression values 22 hours after induction with different amounts of rhamnose and theophylline in strain C. necator T7RT carrying plasmid pT7A-Cn. C) Fluorescence values after 22 hours of different C. necator strains expressing GFP under the control of plasmids pT734-Cn and pT7A-Cn. For all figures, arithmetic means and standard deviations of three biological replicates are reported. Fluorescence is reported as GFU (Green Fluorescent Units: fluorescein equivalent units over OD600). 3.5 Optimization of genetic parts in the expression plasmid can further improve the system After obtaining an optimized strain, we turned our attention to the expression plasmid. We assessed two new T7 promoter variants identified in previous studies for their higher performance compared to the consensus promoter ( Conrad et al., 2020 ; Jones et al., 2015 ). We also designed a synthetic RBS derived from the highly efficient RBS present in the pET plasmid series, which has a slightly different Epsilon sequence that reflects the rRNA sequence in C. necator (RBS C) ( Figure S2 ) ( Olins and Rangwala, 1989 ). However, this RBS did not increase GFP expression compared to RBS A under the control of a constitutive promoter ( Figure 5C ). When applied in our T7 system, maximum fluorescence did not change drastically, while uninduced expression almost doubled ( Figure 4B ). These results confirmed our previous findings that increasing RBS strength increases leakiness. Increasing RBS strength from B0034m to RBS A increased both uninduced and induced expression. However, when we increased the RBS strength further, from RBS A to RBS C, only the uninduced expression increased significantly. This could indicate that another bottleneck in protein translation has been reached. Interestingly, both new T7 promoters were able to maintain the maximum protein expression; one variant also increased tightness ( Figure 5A ). Therefore, it was essential to optimize both the integrated genetic circuit and the plasmid-based expression system to achieve the desired effect. We introduced the best-performing plasmid (pT72A-Cn) into E. coli BL21(DE3) to compare the performance of our strain to the most widely used strain for bacterial protein production. When expressing GFP with this plasmid, our strain outperformed E. coli in terms of maximum expression and tightness ( Figure 5D ). Download figure Open in new tab Figure 5: An optimized T7 promoter decreased leakiness while maintaining maximum fluorescence production. A) Fluorescence values after 22 hours of strain C. necator T7R2 expressing GFP under the control of different T7 promoter variants. The best performing construct (as shown in Figure 4 ) is bold and used as reference. B) Fluorescence values after 22 hours of strain C. necator T7R2 expressing GFP under the control of different RBSs. The best performing construct (as shown in Figure 4 ) is bold and used as reference. C) Fluorescence expressed by constitutive promoter J23106 with the three different RBS analyzed in this study. D) Fluorescence values after 22 h of strains C. necator T7R2 and E. coli BL21(DE3) transformed with plasmid pT72A-Cn. C. necator was induced with 10 mM rhamnose, E. coli with 1 mM IPTG. Due to different autofluorescence in the two strains, measurements were blanked using a non-GFP producing strain. For all figures, arithmetic means and standard deviations of three biological replicates are reported. Fluorescence is reported as GFU (Green Fluorescent Units: fluorescein equivalent units over OD600). 3.6 ENE-REDUCTASE YQJM CAN BE EXPRESSED AT HIGH YIELD IN C. NECATOR After optimizing C. necator for GFP expression, we used our highest-performing strain for enzyme production. We selected YqjM, a FMN-dependent ene-reductase from Bacillus subtilis , as a model enzyme due to its previous production in both E. coli ( Pesic et al., 2017 ) and C. necator ( Assil-Companioni et al., 2019 ; Vajente et al., 2025 ). We used our optimized system ( C. necator T7R2, carrying plasmid pT72A with C. necator codon-harmonized yqjM ) for the expression of YqjM, and to determine the most favourable culture conditions for producing this enzyme in C. necator . Thus, cultures were induced at different ODs (0.4, 0.8, 1.2) and incubated at various temperatures after induction (22 °C, 26 °C, 30 °C). In addition, we used our plasmid-based expression system (pMVRha) to express both E. coli codon-optimized (Ec) and C. necator codon-harmonized (Cn) yqjM ( Vajente et al., 2024 ) to confirm whether codon usage plays such an important role in enzyme expression. To compare our systems with a widely used expression strain, we produced the same protein in E. coli BL21(DE3) carrying the E. coli codon-optimized gene in plasmid pET28a. To determine the amount of active protein produced, we used a spectrophotometer-based quantification of the FMN cofactor produced in the soluble extract and calculated both specific FMN concentration (amount of FMN produced per OD unit) and total FMN concentration (amount of FMN produced by the whole culture). Wild-type strains were used as blanks, and we assumed that all the FMN produced by our cultures was bound to YqjM, yielding FMN-cofactor loaded protein. YqjM forms a tetramer in its active form, with one FMN molecule binding to each subunit ( Kitzing et al., 2005 ). Surprisingly, the amount of FMN produced was higher in C. necator than in E. coli BL21(DE3) ( Figure 6A ). Thus, almost all growth conditions yielded a higher amount of active protein than the most commonly used protein expression strain E. coli BL21(DE3). Inducing at an earlier time point (OD i 0.4) resulted in the highest FMN production per OD unit, but the final OD 600 after 24 hours was lower compared to the other growth conditions ( Figure S4B ). Surprisingly, the highest amount of active enzyme (total FMN) was produced with our previously developed pMVRha plasmid carrying the codon-harmonized yqjM gene, as this culture reached a higher OD 600 compared to the T7-based strain ( Figure S4B ). pMVRha expressing the codon-harmonized gene produced 3-fold more FMN-loaded enzyme compared to the non-harmonized one ( Figure 6A ), confirming the importance of codon usage tuning. According to our SDS-PAGE analysis, E. coli BL21(DE3) produced approximately twice as much soluble protein as our C. necator strains ( Figure 6B ). However, although E. coli produced more soluble enzyme, C. necator produced more FMN-loaded enzyme. Assuming one FMN molecule is equivalent to one YqjM subunit, the highest theoretical yield reached by C. necator was 106 mg/L of culture ( Figure S4A ). A thorough SDS-PAGE analysis quantification can be found in the Supplementary Information ( Figure S5 ). Download figure Open in new tab Figure 6: C. necator T7R2 shows the highest yield of FMN-bound soluble enzyme produced per OD600 of culture, but pMVRha produced the highest absolute amount of FMN-loaded enzyme. A) FMN concentration in the soluble extract of C. necator T7R2 and other strains under different expression conditions. To calculate the specific FMN production, the total FMN quantity was divided by the final OD600 reached by each culture. FMN absorbance of each wild type strain without expression plasmid was used to blank the values. T[°C]: incubation temperature after induction; ODi: induction OD; FMN: in one experiment (+), FMN was supplemented to the culture at a final concentration of 1 μM; YqjM: two sequences with different codon usages were used (Ec, Cn) (see Table S5 for CAI and Table S3 for sequences). Arithmetic means and standard deviations of two biological replicates are reported. FMN quantity is reported in mmol FMN/L of culture. B) SDS-PAGE analysis of the soluble extracts analyzed in Figure 6A . A gel-based normalized quantification of soluble protein production can be observed in the Supplementary Information ( Figure S5 ). 4 Discussion Given the high potential of C. necator for biocatalytic applications and C1-based manufacturing, there is an urgent need to develop more efficient protein production systems for this non-model host. In this study, we successfully integrated T7RNAP driven by two different inducible promoters. The native salicylate-based inducible promoter (NahR) was induced with micromolar amounts of inducer; however, higher amounts inhibited growth. Notably, this phenomenon has been observed not to be attributable to salicylate toxicity as previous studies have demonstrated that up to 5 mM of salicylate has been shown to be beneficial for growth ( Hanko et al., 2020 ). In contrast, this was not the case in our study, even for the non-engineered strains. The difference in media composition may explain this discrepancy. The growth inhibition was unlikely due to the metabolic burden of T7RNAP or GFP production, as the cultures with impaired growth did not exhibit increased GFP fluorescence ( Figure 1 ). Another previous attempt to use a heterologous salicylate promoter in C. necator achieved no protein production, further demonstrating that different genetic systems may interact differently with the native metabolism ( Mishra et al., 2024 ). Since our goal was to develop a robust and reliable system, we decided to abandon the salicylate promoter and focus on the rhamnose-inducible strain. Although cell growth was maintained at all inducer concentrations, the maximum fluorescence obtained was comparable to that of our plasmid pMVRha. Previous attempts to establish a T7-based system in C. necator failed to overcome this challenge ( Hu et al., 2020 ). We speculated that the high level of mRNA produced by the T7RNAP was not successfully translated into protein, creating a bottleneck in protein production. Thus, we focused our investigation on two variables: RBS strength and codon usage of the gene of interest. Using a stronger RBS increased uninduced expression considerably in our system while only slightly increasing maximum GFP fluorescence ( Figures 2 and 5 ). This trade-off was disadvantageous, because tightness of the promoter is an essential quality in a production strain. Typically, separating the biomass accumulation phase from the protein production phase reduces the metabolic burden during growth, increases plasmid retention and final biomass, and leads to a higher protein yield. The main bottleneck in protein production was caused by the codon usage of the gene of interest. Optimizing the sequence of GFPmut3 increased the maximum fluorescence by 4-fold compared to the non-optimized gene ( Figure 2 ). Interestingly, our plasmid control also benefited from codon optimization, with a 2-fold increase in fluorescence. This indicates that protein translation was already a bottleneck when using the pMVRha plasmid. Another recent study also observed the role of codon tuning in protein production in C. necator ( Mishra et al., 2024 ), and we confirmed that this bottleneck is relevant to both GFP production ( Figure 2 ) and enzyme expression ( Figure 5 ). By simply harmonizing the codons in the YqjM genetic sequence, the production of active enzyme using the pMVRha plasmid increased by almost 3-fold ( Figure 5 ). While the role of codon usage in heterologous protein production has proven elusive in E. coli , with different proteins benefiting from codon optimization, harmonization, or non-optimized sequences ( Claassens et al., 2017 ), the importance of this variable has been emphasized repeatedly ( Liu et al., 2021 ). We found that most amino acids in C. necator show a strong bias towards specific codons. Conversely, E. coli ’s synonymous codons are distributed more evenly ( Figure 3 ). Each rare codon (used less than 10%) can impede protein production, and C. necator has almost four times more rare codons than E. coli ( Figure 3 ). Building on this knowledge, we developed two new T7 strains using a weaker RBS to drive expression of a codon-harmonized T7RNAP. These modifications were intended to reduce uninduced T7RNAP expression while potentially increasing maximum protein production. The first goal was achieved with a 50% reduction in uninduced GFP fluorescence ( Figure 4 ). However, an attempt to increase tightness using a newly developed theophylline-responsive system (SIBR2.0) (Della Valle et al., 2025) was unsuccessful because the system was tight but not responsive to induction. This was unexpected because T7RNAP only requires low expression to drive high-level mRNA transcription. To further optimize our expression plasmid, we identified a T7 promoter variant that reduced uninduced expression and generated a tighter system ( Figure 4 ). Our in-depth investigation of the genetic elements involved in the system revealed the importance of each variable’s role and identified the bottlenecks limiting the desired phenotype. Ultimately, we compared the performance of our strain with E. coli BL21(DE3). When expressing GFP using the same plasmid, our strain exhibited lower uninduced expression and maximum fluorescence. Using our newly developed system, we expressed the flavin-dependent ene-reductase YqjM from Bacillus subtilis , to measure the strain’s performance towards the production of an enzyme interesting for biocatalytic applications ( Pesic et al., 2017 ). Our best strain ( C. necator T7R2 pT72A) achieved the highest production of FMN-bound enzyme per biomass unit ( Figure 6 , Figure S5 ), demonstrating the success of our strategy in increasing the intracellular amount of YqjM. However, T7-based expression led to a considerable decrease in cell growth compared to plasmid-driven expression ( Figure S4B ). When producing YqjM using the pMVRha plasmid, the final yield of YqjM was higher than that obtained with our T7-based strains due to the higher final OD 600 . A similar result was previously observed in E. coli , where some plasmid-based expression strains reached higher protein titers than usual T7-based expression ( Schuster and Reisch, 2022 ). Both the pMVRha and the T7-based strain produced more total FMN-bound enzyme than E. coli BL21(DE3). With our best C. necator strain, a theoretical yield of 106 mg/L of FMN-bound YqjM was achieved, compared to 46 mg/L in E. coli . Optimizing the media composition and feeding strategy may further increase the final protein production. In conclusion, our study demonstrates that C. necator is a promising industrial chassis for protein production. The T7-based system developed herein resulted in higher FMN-bound YqjM production per unit of biomass, whereas our previously developed plasmid pMVRha resulted in higher total production due to higher cell density achieved at the end of the growth phase. These systems can be used to produce enzymes that are difficult to express in E. coli due to the formation of inclusion bodies ( Srinivasan et al., 2002 ) or a lack of cofactor maturation chaperones ( Ryu et al., 2024 ). Even when producing different enzymes, our system outperformed E. coli in expressing FMN-bound soluble enzyme, further highlighting the potential of C. necator for biocatalysis applications. Furthermore, these optimized expression systems could also be used for lithoautotrophic or formatotrophic enzyme production, ultimately leading to CO 2 -driven enzyme synthesis. Declaration of competing interests The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper. Author contributions: CRediT Matteo Vajente (RUG) – Conceptualization, Investigation, Writing – original draft Hendrik Ballerstendt (RWTH-Aachen) – Supervision, Writing – review & editing Lars M. Blank (RWTH-Aachen) – Resources, Supervision, Writing – review & editing Sandy Schmidt (RUG) – Conceptualization, Supervision, Resources, Writing – review & editing Funding sources This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska Curie grant agreement No 955740 and the Netherlands Organization for Scientific Research (OCENW.XS23.3.002). Supplementary Information Supplementary Tables View this table: View inline View popup Table S1: Plasmids used in this study. View this table: View inline View popup Table S2: Acceptor plasmids, donor plasmids, DNA fragments and oligonucleotides used for assembly of each plasmid. View this table: View inline View popup Table S3: List of all genetic parts and fragments synthesized and used in this study. Restriction enzyme recognition sites are bold, restriction enzyme cutting sites are underlined . View this table: View inline View popup Table S4: Codon usage tables of E. coli BL21 (NCBI: GCF_013166975) and C. necator H16 (NCBI: GCF_004798725) calculated using cusp (EMBOSS). View this table: View inline View popup Download powerpoint Table S5: Table of calculated Codon Adaptation Index values (CAI) for all genes expressed in this study. View this table: View inline View popup Table S6: List of primers used in this study. Supplementary Figures Download figure Open in new tab Figure S1: Schematic representation of the genotype of all strains created in this manuscript. Download figure Open in new tab Figure S2: Design of RBS C for C. necator . A) Zoom-in of the alignment between rRNA sequences of E. coli and C. necator, with the original Epsilon sequence highlighted. B) Alignment of the pET RBS sequence (T7RBS from the Golden Standard library) and the newly designed RBS C. Download figure Open in new tab Figure S3: C. necator T7R and C. necator T7R2 have the same response to different concentrations of rhamnose. Fluorescence values after 22 hours of different C. necator strains expressing GFP under the control of plasmids pT734-Cn and pT7A-Cn. For all figures, arithmetic means and standard deviations of three biological replicates are reported. Fluorescence is reported as GFU (Green Fluorescent Units: fluorescein equivalent units over OD 600 ). Download figure Open in new tab Figure S4: Theoretical yield of FMN-loaded enzyme and OD 600 reached by the strains analyzed in Figure 6 . A) Theoretical yield of FMN-loaded enzyme produced by the strains analyzed in Figure 6 . The calculations were performed assuming that one molecule of FMN is equal to one protein. B) OD 600 reached by the strains at the moment of harvest, measured by a spectrophotometer. T[°C]: incubation temperature after induction; OD i : induction OD 600 ; FMN: in one experiment (+), FMN was supplemented to the culture at a final concentration of 1 μM; YqjM: two sequences with different codon usages were used (Ec, Cn) (see Table S5 for CAI and Table S3 for sequences). Arithmetic means and standard deviations of two biological replicates are reported. Download figure Open in new tab Figure S5: Relative quantification of soluble YqjM produced by C. necator in different conditions, measured from SDS-PAGE. The YqjM band intensity (red square) was divided by another protein band’s intensity (blue square) in order to normalize the data. The assumption is that the intensity of this second band is constants in all conditions tested. Band intensities were quantified using the Gel Analysis tools from Fiji (Schindelin et al., 2012). T[°C]: incubation temperature after induction; OD i : induction OD 600 ; FMN: in one experiment (+), FMN was supplemented to the culture at a final concentration of 1 μM; YqjM: two sequences with different codon usages were used (Ec, Cn) (see Table S5 for CAI and Table S3 for sequences). Arithmetic means and standard deviations of two biological replicates are reported. Acknowledgements We thank Riccardo Clerici, Franziska Meier and all the employees at Formo GmbH for support and discussions, in particular Andrea Annibal and Emma Bassini for their insightful observations and experimental help. Funder Information Declared European Union’s Horizon 2020 research and innovation programme , 955740 Netherlands Organization for Scientific Research , OCENW.XS23.3.002 Bibliography ↵ Alagesan , S. , Hanko , E.K.R. , Malys , N. , Ehsaan , M. , Winzer , K. , Minton , N.P ., 2018 . Functional Genetic Elements for Controlling Gene Expression in Cupriavidus necator H16 . 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Share Optimization of a T7 RNA polymerase expression system for high-yield protein production in Cupriavidus necator H16 Matteo Vajente , Hendrik Ballerstedt , Lars Mathias Blank , Sandy Schmidt bioRxiv 2025.11.17.688765; doi: https://doi.org/10.1101/2025.11.17.688765 Share This Article: Copy Citation Tools Optimization of a T7 RNA polymerase expression system for high-yield protein production in Cupriavidus necator H16 Matteo Vajente , Hendrik Ballerstedt , Lars Mathias Blank , Sandy Schmidt bioRxiv 2025.11.17.688765; doi: https://doi.org/10.1101/2025.11.17.688765 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Synthetic Biology Subject Areas All Articles Animal Behavior and Cognition (7619) Biochemistry (17639) Bioengineering (13865) Bioinformatics (41854) Biophysics (21405) Cancer Biology (18544) Cell Biology (25432) Clinical Trials (138) Developmental Biology (13356) Ecology (19863) Epidemiology (2067) Evolutionary Biology (24287) Genetics (15587) Genomics (22465) Immunology (17701) Microbiology (40300) Molecular Biology (17142) Neuroscience (88440) Paleontology (666) Pathology (2825) Pharmacology and Toxicology (4814) Physiology (7633) Plant Biology (15107) Scientific Communication and Education (2042) Synthetic Biology (4285) Systems Biology (9809) Zoology (2268)