This research was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research Award Number DE-SC0019363, the NSF CAREER Award CBET-1751840, The Pew Charitable Trusts, and the Camille Dreyfus Teacher-Scholar Award.

<ol>
	<li>Figueroa, D., Rojas, V., Romero, A., Larrondo, L. F., Salinas, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+rise+and+shine+of+yeast+optogenetics.">The rise and shine of yeast optogenetics.</a> Yeast. 38 (2), 131-146 (2021).</li><li>Pouzet, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+promise+of+optogenetics+for+bioproduction:+Dynamic+control+strategies+and+scale-up+instruments.">The promise of optogenetics for bioproduction: Dynamic control strategies and scale-up instruments.</a> Bioengineering. 7 (4), 151 (2020).</li><li>Venayak, N., Anesiadis, N., Cluett, W. R., Mahadevan, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineering+metabolism+through+dynamic+control.">Engineering metabolism through dynamic control.</a> Current Opinion in Biotechnology. 34, 142-152 (2015).</li><li>Lalwani, M. A., Zhao, E. M., Avalos, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Current+and+future+modalities+of+dynamic+control+in+metabolic+engineering.">Current and future modalities of dynamic control in metabolic engineering.</a> Current Opinion in Biotechnology. 52, 56-65 (2018).</li><li>Zhao, E. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Design+and+characterization+of+rapid+optogenetic+circuits+for+dynamic+control+in+yeast+metabolic+engineering.">Design and characterization of rapid optogenetic circuits for dynamic control in yeast metabolic engineering.</a> ACS Synthetic Biology. 9 (12), 3254-3266 (2020).</li><li>Lalwani, M. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optogenetic+control+of+the+lac+operon+for+bacterial+chemical+and+protein+production.">Optogenetic control of the lac operon for bacterial chemical and protein production.</a> Nature Chemical Biology. 17 (1), 71-79 (2021).</li><li>Zhao, E. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optogenetic+regulation+of+engineered+cellular+metabolism+for+microbial+chemical+production.">Optogenetic regulation of engineered cellular metabolism for microbial chemical production.</a> Nature. 555 (7698), 683-687 (2018).</li><li>Baumschlager, A., Khammash, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synthetic+biological+approaches+for+optogenetics+and+tools+for+transcriptional+light-control+in+bacteria.">Synthetic biological approaches for optogenetics and tools for transcriptional light-control in bacteria.</a> Advanced Biology. 5 (5), 2000256 (2021).</li><li>Dvorak, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exacerbation+of+substrate+toxicity+by+IPTG+in+Escherichia+coli+BL21(DE3)+carrying+a+synthetic+metabolic+pathway.">Exacerbation of substrate toxicity by IPTG in Escherichia coli BL21(DE3) carrying a synthetic metabolic pathway.</a> Microbial Cell Factories. 14, 201 (2015).</li><li>Hartline, C. J., Schmitz, A. C., Han, Y., Zhang, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamic+control+in+metabolic+engineering:+Theories,+tools,+and+applications.">Dynamic control in metabolic engineering: Theories, tools, and applications.</a> Metabolic Engineering. 63, 126-140 (2021).</li><li>Ni, C., Dinh, C. V., Prather, K. L. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamic+control+of+metabolism.">Dynamic control of metabolism.</a> Annual Review of Chemical and Biomolecular Engineering. 12, 519-560 (2021).</li><li>Zhao, E. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optogenetic+amplification+circuits+for+light-induced+metabolic+control.">Optogenetic amplification circuits for light-induced metabolic control.</a> ACS Synthetic Biology. 10 (5), 1143-1154 (2021).</li><li>Lalwani, M. A., Zhao, E. M., Wegner, S. A., Avalos, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Neurospora+crassa+Inducible+Q+System+Enables+Simultaneous+Optogenetic+Amplification+and+Inversion+in+Saccharomyces+cerevisiae+for+Bidirectional+Control+of+Gene+Expression.">The Neurospora crassa Inducible Q System Enables Simultaneous Optogenetic Amplification and Inversion in Saccharomyces cerevisiae for Bidirectional Control of Gene Expression.</a> ACS Synthetic Biology. 10 (8), 2060-2075 (2021).</li><li>Motta-Mena, L. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+optogenetic+gene+expression+system+with+rapid+activation+and+deactivation+kinetics.">An optogenetic gene expression system with rapid activation and deactivation kinetics.</a> Nature Chemical Biology. 10 (3), 196-202 (2014).</li><li>Gietz, R. D., Woods, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transformation+of+yeast+by+lithium+acetate/single-stranded+carrier+DNA/polyethylene+glycol+method.">Transformation of yeast by lithium acetate/single-stranded carrier DNA/polyethylene glycol method.</a> Methods in Enzymology. 350, 87-96 (2002).</li><li>Marx, H., Mecklenbr&#228;uker, A., Gasser, B., Sauer, M., Mattanovich, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Directed+gene+copy+number+amplification+in+Pichia+pastoris+by+vector+integration+into+the+ribosomal+DNA+locus.">Directed gene copy number amplification in Pichia pastoris by vector integration into the ribosomal DNA locus.</a> FEMS Yeast Research. 9 (8), 1260-1270 (2009).</li><li>Nord&#233;n, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Increasing+gene+dosage+greatly+enhances+recombinant+expression+of+aquaporins+in+Pichia+pastoris.">Increasing gene dosage greatly enhances recombinant expression of aquaporins in Pichia pastoris.</a> BMC Biotechnology. 11, 47 (2011).</li><li>Zhao, E. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Light-based+control+of+metabolic+flux+through+assembly+of+synthetic+organelles.">Light-based control of metabolic flux through assembly of synthetic organelles.</a> Nature Chemical Biology. 15 (6), 589-597 (2019).</li><li>Dowee, W. J., Miller, J. F., Ragsdale, C. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High+efficiency+transformation+of+E.+coli+by+high+voltage+electroporation.">High efficiency transformation of E. coli by high voltage electroporation.</a> Nucleic Acids Research. 16 (13), 6127-6145 (1988).</li><li>Zhou, K., Edgar, S., Stephanopoulos, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineering+microbes+to+synthesize+plant+isoprenoids.">Engineering microbes to synthesize plant isoprenoids.</a> Methods in Enzymology. 575, 225-245 (2016).</li><li>Arfman, N., Worrell, V., Ingram, L. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+the+tac+promoter+and+lacI(q)+for+the+controlled+expression+of+Zymomonas+mobilis+fermentative+genes+in+Escherichia+coli+and+Zymomonas+mobilis.">Use of the tac promoter and lacI(q) for the controlled expression of Zymomonas mobilis fermentative genes in Escherichia coli and Zymomonas mobilis.</a> Journal of Bacteriology. 174 (22), 7370-7378 (1992).</li><li>Steen, E. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metabolic+engineering+of+Saccharomyces+cerevisiae+for+the+production+of+n-butanol.">Metabolic engineering of Saccharomyces cerevisiae for the production of n-butanol.</a> Microbial Cell Factories. 7 (1), 1-8 (2008).</li><li>Tan, S. Z., Manchester, S., Prather, K. L. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Controlling+central+carbon+metabolism+for+improved+pathway+yields+in+Saccharomyces+cerevisiae.">Controlling central carbon metabolism for improved pathway yields in Saccharomyces cerevisiae.</a> ACS Synthetic Biology. 5 (2), 116-124 (2015).</li><li>Jayaraman, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Blue+light-mediated+transcriptional+activation+and+repression+of+gene+expression+in+bacteria.">Blue light-mediated transcriptional activation and repression of gene expression in bacteria.</a> Nucleic Acids Research. 44 (14), 6994 (2016).</li><li>Fernandez-Rodriguez, J., Moser, F., Song, M., Voigt, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineering+RGB+color+vision+into+Escherichia+coli.">Engineering RGB color vision into Escherichia coli.</a> Nature Chemical Biology. 13 (7), 706-708 (2017).</li><li>Ding, Q., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Light-powered+Escherichia+coli+cell+division+for+chemical+production.">Light-powered Escherichia coli cell division for chemical production.</a> Nature Communications. 11 (1), 1-14 (2020).</li><li>Senoo, S., Tandar, S. T., Kitamura, S., Toya, Y., Shimizu, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Light-inducible+flux+control+of+triosephosphate+isomerase+on+glycolysis+in+Escherichia+coli.">Light-inducible flux control of triosephosphate isomerase on glycolysis in Escherichia coli.</a> Biotechnology and Bioengineering. 116 (12), 3292-3300 (2019).</li><li>Ramakrishnan, P., Tabor, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Repurposing+synechocystis+PCC6803+UirS-UirR+as+a+UV-violet/green+photoreversible+transcriptional+regulatory+tool+in+E.+Coli.">Repurposing synechocystis PCC6803 UirS-UirR as a UV-violet/green photoreversible transcriptional regulatory tool in E. Coli.</a> ACS Synthetic Biology. 5 (7), 733-740 (2016).</li><li>Tabor, J. J., Levskaya, A., Voigt, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multichromatic+control+of+gene+expression+in+escherichia+coli.">Multichromatic control of gene expression in escherichia coli.</a> Journal of Molecular Biology. 405 (2), 315-324 (2011).</li><li>Stewart, C. J., McClean, M. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Design+and+implementation+of+an+automated+illuminating,+culturing,+and+sampling+system+for+microbial+optogenetic+applications.">Design and implementation of an automated illuminating, culturing, and sampling system for microbial optogenetic applications.</a> Journal of Visualized Experiments:JoVE. (120), e54894 (2017).</li><li>Gr&#248;dem, E. O. S., Sweeney, K., McClean, M. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+calibration+of+optoPlate+LEDs+to+reduce+light+dose+variation+in+optogenetic+experiments.">Automated calibration of optoPlate LEDs to reduce light dose variation in optogenetic experiments.</a> BioTechniques. 69 (4), 313-316 (2020).</li><li>Gerhardt, K. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+open-hardware+platform+for+optogenetics+and+photobiology.">An open-hardware platform for optogenetics and photobiology.</a> Scientific Reports. 6, (2016).</li><li>Bugaj, L. J., Lim, W. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+multicolor+optogenetics+in+microwell+plates.">High-throughput multicolor optogenetics in microwell plates.</a> Nature Protocols. 14 (7), 2205-2228 (2019).</li><li>Steel, H., Habgood, R., Kelly, C., Papachristodoulou, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+situ+characterisation+and+manipulation+of+biological+systems+with+Chi.Bio.">In situ characterisation and manipulation of biological systems with Chi.Bio.</a> PLoS Biology. 18 (7), (2020).</li><li>Carrasco-L&#243;pez, C., Garc&#237;a-Echauri, S. A., Kichuk, T., Avalos, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optogenetics+and+biosensors+set+the+stage+for+metabolic+cybergenetics.">Optogenetics and biosensors set the stage for metabolic cybergenetics.</a> Current Opinion in Biotechnology. 65, 296-309 (2020).</li><li>Milias-Argeitis, A., Rullan, M., Aoki, S. K., Buchmann, P., Khammash, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+optogenetic+feedback+control+for+precise+and+robust+regulation+of+gene+expression+and+cell+growth.">Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth.</a> Nature Communications. 7 (1), 1-11 (2016).</li><li>Melendez, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+optogenetic+control+of+intracellular+protein+concentration+in+microbial+cell+cultures.">Real-time optogenetic control of intracellular protein concentration in microbial cell cultures.</a> Integrative Biology: Quantitative Biosciences From Nano to Macro. 6 (3), 366-372 (2014).</li><li>Milias-Argeitis, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+silico+feedback+for+in+vivo+regulation+of+a+gene+expression+circuit.">In silico feedback for in vivo regulation of a gene expression circuit.</a> Nature Biotechnology. 29 (12), 1114-1116 (2011).</li><li>Castillo-Hair, S. M., Baerman, E. A., Fujita, M., Igoshin, O. A., Tabor, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optogenetic+control+of+Bacillus+subtilis+gene+expression.">Optogenetic control of Bacillus subtilis gene expression.</a> Nature Communications. 10 (1), 1-11 (2019).</li><li>Xia, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optogenetic+modification+of+pseudomonas+aeruginosa+enables+controllable+twitching+motility+and+host+infection.">Optogenetic modification of pseudomonas aeruginosa enables controllable twitching motility and host infection.</a> ACS Synthetic Biology. 10 (3), 531-541 (2021).</li><li>Pu, L., Yang, S., Xia, A., Jin, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optogenetics+manipulation+enables+prevention+of+biofilm+formation+of+engineered+pseudomonas+aeruginosa+on+surfaces.">Optogenetics manipulation enables prevention of biofilm formation of engineered pseudomonas aeruginosa on surfaces.</a> ACS Synthetic Biology. 7 (1), 200-208 (2018).</li></ol>

The authors have applied for several patents for the optogenetic circuits and methods described in this article.

Dynamic control has long been applied to improve yields for metabolic engineering and recombinant protein production4. Shifts in enzymatic expression are most typically implemented using chemical inducers such as IPTG21, galactose22, and tetracycline23, but have also been mediated using process conditions such as temperature and pH. Optogenetic control of gene expression eliminates the need for changes to fermentation paramete...

Optogenetics, the control of biological processes with light-responsive proteins, offers a new strategy to dynamically control microbial fermentations for chemical and protein production1,2. The burden of engineered metabolic pathways and the toxicity of some intermediates and products often impairs cell growth3. Such stresses can lead to poor biomass accumulation and reduced productivity3. This challenge can be addressed by temporally dividing fermentations into a growth and production phase, which devote metabolic resources to biomass accumulation or product synthesis respectively4. We recently showed that the transition from growth to production in this two-phase fermentation can be induced with changes in illumination conditions5,6,7. The high tunability, reversibility, and orthogonality of light inputs8 offer unique advantages to light-controlled fermentations that are difficult or impossible to replicate with chemical inducers used in dynamical control of conventional two-phase fermentations4,9,10,11.
The blue-light responsive EL222 protein derived from Erythrobacter litoralis has been used to develop several optogenetic circuits for metabolic engineering in Saccharomyces cerevisiae5,7,12,13. EL222 contains a light-oxygen-voltage sensor (LOV) domain that undergoes a conformational shift upon blue light activation (465 nm), which allows it to bind to its cognate DNA sequence (C120)13. Fusing EL222 to the viral VP16 activation domain (VP16-EL222) results in a blue-light responsive transcription factor that can reversibly activate gene expression in S. cerevisiae7 and other organisms14 from the synthetic promoter PC120. Several circuits based on EL222 have been developed and used for chemical production in S. cerevisiae, such as the basic light-activated OptoEXP system7, in which the gene of interest is directly expressed from PC120&#160;(Figure 1A). However, concerns of light penetration at the high cell densities typically encountered in the production phase of fermentations motivated us to develop inverted circuits that are induced in the dark, such as the OptoINVRT and OptoQ-INVRT circuits (Figure 1B)5,7,13. These systems harness the galactose (GAL) or quinic acid (Q) regulons from S. cerevisiae and N. crassa, respectively, controlling their corresponding repressors (GAL80 and QS) with VP16-EL222, to repress gene expression in the light and strongly induce it in the dark. Combining OptoEXP and OptoINVRT circuits results in bidirectional control of gene expression, enabling two-phase fermentations in which the growth phase is induced with blue light, and the production phase with darkness (Figure 2A)5,7.
Using light instead of darkness to induce gene expression during the production phase would greatly expand the capabilities of optogenetic controls but would also require overcoming the light penetration limitations of the high cell densities typically encountered in this phase of fermentation. To this end, we have developed circuits, known as OptoAMP and OptoQ-AMP, that amplify the transcriptional response to blue light stimulation. These circuits use wild-type or hypersensitive mutants of VP16-EL222 to control production of&#160;the transcriptional activators Gal4p or&#160;QF2 of the GAL or Q regulons, respectively, achieving enhanced sensitivity and stronger gene expression with light12,13&#160;(Figure 1C). OptoAMP circuits can achieve complete and homogeneous light induction in 5 L bioreactors at an optical density (measured at 600 nm; OD600) values of at least 40 with only ~0.35% of illumination (5% light dose on only ~7% of the bulk surface). This demonstrates a higher degree of sensitivity compared to OptoEXP, which requires close to 100% illumination12. The ability to effectively induce gene expression with light at high cell densities opens new opportunities for dynamical control of fermentations. This includes operating fermentations in more than two temporal phases, such as three-phase fermentations, in which growth, induction, and production phases are established with unique light schedules to optimize chemical production (Figure 2B)12.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63269/63269fig1v2.jpg" /> 
Figure 1: Optogenetic circuits for dynamic control of S. cerevisiae. The OptoEXP, OptoINVRT, and OptoAMP circuits are based on the light-sensitive VP16-EL222 system. (A) In the OptoEXP circuit, exposure to blue light causes a conformational change and dimerization of VP16-EL222, which exposes a DNA-binding domain and allows for transcription from PC120. The figure has been modified from Zhao et al.7. (B) OptoINVRT circuits harnesses the GAL (shown) or Q regulons to induce expression in the dark. In GAL-based circuits, VP16-EL222 and GAL4 are constitutively expressed, while PC120 drives expression of the GAL80 repressor (in Q-based circuits, GAL4 and GAL80 are replaced by QF2 and QS, respectively, and a synthetic QUAS-containing promoter is used instead of a GAL promoter). In light, Gal80p prevents activation of the gene of interest from PGAL1. In the dark, GAL80 is not expressed and rapidly degraded by fusing it to a constitutive degron domain (small brown domain),&#160;which allows for activation of PGAL1 by Gal4p. The figure has been modified from Zhao et al.5. (C) OptoAMP circuits also use VP16-EL222 to control the GAL (shown) or Q regulons. In these circuits, the GAL80 repressor (or QS) is constitutively expressed and fused to a photo-sensitive degron (small blue domain) ensuring tight repression in the dark. PC120 and a hypersensitive VP16-EL222 mutant control expression of GAL4 (or QF2) with light, which strongly activates PGAL1&#160;(or a QUAS-containing promoter) in the light. GAL-derived circuits can use engineered forms of PGAL1, such as PGAL1-M or PGAL1-S, which have increased activity, as well as wild-type promoters controlled by the GAL regulon (PGAL1, PGAL10, PGAL2, PGAL7). The figure has been modified from Zhao et al.12. <a href="https://www.jove.com/files/ftp_upload/63269/63269fig1v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/63269/63269fig02.jpg" /> 
Figure 2: Two- and three-phase fermentations through time. (A) Two-phase fermentations operated with inverted circuits consist of a light-driven growth phase and a dark production phase. In the growth phase, biomass accumulates as the production pathway stays repressed. Upon reaching the desired OD600, cells are shifted to the dark to metabolically adjust before being resuspended in fresh media for the production phase. (B) In a three-phase process, the growth, incubation, and production phases are defined by unique light schedules, which may consist of a dark growth period, pulsed incubation, and fully illuminated production phase. Figure created with Biorender. <a href="https://www.jove.com/files/ftp_upload/63269/63269fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Optogenetic circuits have also been developed for dynamical control of chemical and protein production in E. coli. OptoLAC circuits control the bacterial LacI repressor using the light-responsive pDawn circuit, which is based on the YF1/FixJ two-component system6 (Figure 3). Similar to OptoINVRT5, OptoLAC circuits are designed to repress gene expression in the light and induce it in the dark. Expression levels using OptoLAC circuits can match or exceed those achieved with standard isopropyl &#946;-d-1-thiogalactopyranoside (IPTG) induction, thus maintaining the strength of chemical induction while offering enhanced tunability and reversibility6. Therefore, OptoLAC circuits enable effective optogenetic control for metabolic engineering in E. coli.
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/63269/63269fig03.jpg" /> 
Figure 3: OptoLAC circuits for dynamic control of E. coli. The OptoLAC circuits adapt the pDawn system and lac operon to achieve activation in the dark and repression in the light. In the dark, YF1 phosphorylates FixJ, which then activates the PFixK2 promoter to express the cI repressor. The cI repressor prevents expression of the lacI repressor&#160;from the PR promoter, which permits transcription of the gene of interest from a lacO-containing promoter. Conversely, blue light reduces YF1 net kinase activity, reversing FixJ phosphorylation and thus cI expression, which derepresses expression of lacI and prevents expression from the lacO-containing promoter. The figure has been modified from Lalwani et al.6. <a href="https://www.jove.com/files/ftp_upload/63269/63269fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
We describe here the basic protocols for light-controlled fermentations of S. cerevisiae and E. coli for chemical or protein production. For both yeast and bacteria, we first focus on fermentations with a light-driven growth phase and a darkness-induced production phase enabled by OptoINVRT and OptoLAC circuits. Subsequently, we describe a protocol for a three-phase (growth, induction, production) light-controlled fermentation enabled by OptoAMP circuits. Furthermore, we describe how to scale up optogenetically controlled fermentations from microplates to lab-scale bioreactors. With this protocol, we aim to provide a complete and easily reproducible guide for performing light-controlled fermentations for chemical or protein production.

<table><tbody><tr><td>&lt;strong&gt;Light-controlled chemical production using &lt;em&gt;S. cerevisiae&lt;/em&gt;&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>24-well culture plate</td><td>USA Scientific</td><td>CC7672-7524</td><td></td></tr><tr><td>Agar powder</td><td>Thermo Fisher Scientific</td><td>303991049</td><td></td></tr><tr><td>Aluminum foil</td><td>Reynolds</td><td>B004NG90YO</td><td></td></tr><tr><td>BioSpectrometer with &amp;mu;cuvette</td><td>Eppendorf</td><td>6135000923</td><td></td></tr><tr><td>Blue LED panel</td><td>HQRP</td><td>884667106091218</td><td></td></tr><tr><td>EZ-L439 OptoINVRT7 Plasmid</td><td>N/A</td><td>N/A</td><td>See Reference 1</td></tr><tr><td>Glucose</td><td>Thermo Fisher Scientific</td><td>501879892 (G8270-5KG)</td><td></td></tr><tr><td>Microcentrifuge</td><td>Thermo Fisher Scientific</td><td>75002403</td><td></td></tr><tr><td>Microcentrifuge tubes</td><td>USA Scientific</td><td>1615-5510</td><td></td></tr><tr><td>Orbital Shaker</td><td>Yamato Scientific America</td><td>SOU-300</td><td></td></tr><tr><td>Petri dish</td><td>Celltreat</td><td>229656</td><td></td></tr><tr><td>PmeI</td><td>New England Biolabs</td><td>R0560L</td><td></td></tr><tr><td>Quantum meter</td><td>Apogee Instruments</td><td>MQ-510</td><td></td></tr><tr><td>Replica-plating device</td><td>Thomas Scientific</td><td>F37848-0000</td><td></td></tr><tr><td>Replica-plating pads</td><td>Sunrise Science Products</td><td>3005-012</td><td></td></tr><tr><td>SC-His powder</td><td>Sunrise Science Products</td><td>1303-030</td><td></td></tr><tr><td>SC Complete powder</td><td>Sunrise Science Products</td><td>1459-100</td><td></td></tr><tr><td>Sterile sealing film</td><td>Excel Scientific</td><td>STR-SEAL-PLT</td><td></td></tr><tr><td>YPD agar plates</td><td>VWR</td><td>100217-054</td><td></td></tr><tr><td>Zeocin</td><td>Thermo Fisher Scientific</td><td>R25005</td><td></td></tr><tr><td>&lt;strong&gt;Light-controlled protein production using &lt;em&gt;E. coli&lt;/em&gt;&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>6X SDS Sample Buffer</td><td>Cepham Life Sciences</td><td>10502</td><td></td></tr><tr><td>12% Acrylamide protein gels</td><td>Thermo Fisher Scientific</td><td>NP0341BOX</td><td></td></tr><tr><td>24-well culture plate</td><td>USA Scientific</td><td>CC7672-7524</td><td></td></tr><tr><td>Aluminum foil</td><td>Reynolds</td><td>B004NG90YO</td><td></td></tr><tr><td>BioSpectrometer with &amp;mu;cuvette</td><td>Eppendorf</td><td>6135000923</td><td></td></tr><tr><td>Blue LED panel</td><td>HQRP</td><td>884667106091218</td><td></td></tr><tr><td>Coomassie Brilliant Blue G-250</td><td>Thermo Fisher Scientific</td><td>20279</td><td></td></tr><tr><td>Electrophoresis cell</td><td>Bio-Rad</td><td>1658004</td><td></td></tr><tr><td>Electrophoresis power supply</td><td>Bio-Rad</td><td>1645050</td><td></td></tr><tr><td>LB broth (Miller)</td><td>Fisher Scientific</td><td>BP97235</td><td></td></tr><tr><td>Microcentrifuge</td><td>Thermo Fisher Scientific</td><td>75002403</td><td></td></tr><tr><td>Microcentrifuge tubes</td><td>USA Scientific</td><td>1615-5510</td><td></td></tr><tr><td>NaCl</td><td>Thomas Scientific</td><td>SX0425-1</td><td></td></tr><tr><td>OptoLAC plasmids</td><td>N/A</td><td>N/A</td><td>See Reference 2</td></tr><tr><td>Orbital Shaker</td><td>Yamato Scientific America</td><td>SOU-300</td><td></td></tr><tr><td>Petri dish</td><td>Celltreat</td><td>229656</td><td></td></tr><tr><td>Quantum meter</td><td>Apogee Instruments</td><td>MQ-510</td><td></td></tr><tr><td>SOC medium</td><td>Thermo Fisher Scientific</td><td>15544034</td><td></td></tr><tr><td>Thermomixer</td><td>Eppendorf</td><td>5382000015</td><td></td></tr><tr><td>Tris base</td><td>Fisher Scientific</td><td>BP1521</td><td></td></tr><tr><td>&lt;strong&gt;Three-phase fermentation using &lt;em&gt;S. cerevisiae&lt;/em&gt;&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Same materials as &quot;Light-controlled chemical production using S. cerevisiae&quot; protocol plus the following:</td><td></td><td></td><td></td></tr><tr><td>EZ-L580 OptoAMP4 Plasmid</td><td>N/A</td><td>N/A</td><td>See Reference 10</td></tr><tr><td>&lt;strong&gt;Chemical production in a light-controlled bioreactor&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Aluminum foil</td><td>Reynolds</td><td>B004NG90YO</td><td></td></tr><tr><td>Antifoam</td><td>Sigma-Aldrich</td><td>A8311</td><td></td></tr><tr><td>Bioreactor with control station</td><td>Eppendorf</td><td>B120110001</td><td></td></tr><tr><td>BioSpectrometer with &amp;mu;cuvette</td><td>Eppendorf</td><td>6135000923</td><td></td></tr><tr><td>Bleach</td><td>VWR Scientific</td><td>89501-620 (CS)</td><td></td></tr><tr><td>Blue LED panel</td><td>HQRP</td><td>884667106091218</td><td></td></tr><tr><td>BPT tubing</td><td>Fisher Scientific</td><td>14-170-15</td><td></td></tr><tr><td>Glucose</td><td>Thermo Fisher Scientific</td><td>501879892 (G8270-5KG)</td><td></td></tr><tr><td>Hydrochloric acid (HCl)</td><td>Fisher Scientific</td><td>7647-01-0</td><td></td></tr><tr><td>M9 Minimal Salts</td><td>Thermo Fisher Scientific</td><td>A1374401</td><td></td></tr><tr><td>Microcentrifuge</td><td>Thermo Fisher Scientific</td><td>75002403</td><td></td></tr><tr><td>Microcentrifuge tubes</td><td>USA Scientific</td><td>1615-5510</td><td></td></tr><tr><td>NH4OH Solution</td><td>Sigma-Aldrich</td><td>I0503-1VL</td><td></td></tr><tr><td>Orbital Shaker</td><td>Yamato Scientific America</td><td>SOU-300</td><td></td></tr><tr><td>Quantum meter</td><td>Apogee Instruments</td><td>MQ-510</td><td></td></tr><tr><td>SC Complete powder</td><td>Sunrise Science Products</td><td>1459-100</td><td></td></tr></tbody></table>

light-controlled fermentations for microbial chemical and protein production

Microbial cell factories offer a sustainable alternative for producing chemicals and recombinant proteins from renewable feedstocks. However, overburdening a microorganism with genetic modifications can reduce host fitness and productivity. This problem can be overcome by using dynamic control: inducible expression of enzymes and pathways, typically using chemical- or nutrient-based additives, to balance cellular growth and production. Optogenetics offers a non-invasive, highly tunable, and reversible method of dynamically regulating gene expression. Here, we describe how to set up light-controlled fermentations of engineered Escherichia coli and Saccharomyces cerevisiae for the production of chemicals or recombinant proteins. We discuss how to apply light at selected times and dosages to decouple microbial growth and production for improved fermentation control and productivity, as well as the key optimization considerations for best results. Additionally, we describe how to implement light controls for lab-scale bioreactor experiments. These protocols facilitate the adoption of optogenetic controls in engineered microorganisms for improved fermentation performance.

Optogenetic regulation of microbial metabolism has been successfully implemented to produce a variety of products, including biofuels, bulk chemicals, proteins, and natural products5,6,7,12,13. Most of these processes are designed for cell growth to occur in the light (when low cell density poses minimal challenges with light penetration), and for production t...

Watch this Scientific Journal Video about Light-Controlled Fermentations for Microbial Chemical and Protein Production at JoVE.com

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Optogenetic control of microbial metabolism offers flexible dynamic control over fermentation processes. The protocol here shows how to set up blue light-regulated fermentations for chemical and protein production at different volumetric scales.

Microbial cell factories offer a sustainable alternative for producing chemicals and recombinant proteins from renewable feedstocks. However, ...

light-controlled-fermentations-for-microbial-chemical-protein

Research

JoVE Journal

Bioengineering

3.9K Views.  Princeton University. Optogenetica is gebruikt om hogere titers van verschillende chemicaliën en eiwitten te bereiken in vergelijking met typische inductoren. Met behulp van dit protocol kunnen anderen hun eigen processen verbeteren met op licht gebaseerde controle. Optogenetica controle is niet-invasief, zeer afstembaar en omkeerbaar.Deze kwaliteiten zorgen voor een gestroomlijnde optimalisatie van microbiële processen en openen zelfs unieke mogelijkheden, zoals driefasige fermentaties en multichromatisc...

Video: Light-Controlled Fermentations for Microbial Chemical and Protein Production

Microfluidic Picoliter Bioreactor for Microbial Single-cell Analysis: Fabrication, System Setup, and Operation

In this protocol the fabrication, experimental setup and basic operation of the recently introduced microfluidic picoliter bioreactor (PLBR) is described in detail. The PLBR can be utilized for the analysis of single bacteria and microcolonies to investigate biotechnological and microbiological related questions concerning, e.g.&#160;cell growth, morphology, stress response, and metabolite or protein production on single-cell level. The device features continuous media flow enabling constant environmental conditions for perturbation studies, but in addition allows fast medium changes as well as oscillating conditions to mimic any desired environmental situation. To fabricate the single use devices, a silicon wafer containing sub micrometer sized SU-8 structures served as the replication mold for rapid polydimethylsiloxane casting. Chips were cut, assembled, connected, and set up onto a high resolution and fully automated microscope suited for time-lapse imaging, a powerful tool for spatio-temporal cell analysis. Here, the biotechnological platform organism Corynebacterium glutamicum&#160;was seeded into the PLBR and cell growth and intracellular fluorescence were followed over several hours unraveling time dependent population heterogeneity on single-cell level, not possible with conventional analysis methods such as flow cytometry. Besides insights into device fabrication, furthermore, the preparation of the preculture, loading, trapping of bacteria, and the PLBR cultivation of single cells and colonies is demonstrated. These devices will add a new dimension in microbiological research to analyze time dependent phenomena of single bacteria under tight environmental control. Due to the simple and relatively short fabrication process the technology can be easily adapted at any microfluidics lab and simply tailored towards specific needs.

In this protocol the fabrication, setup and basic operation of a microfluidic picoliter bioreactor (PLBR) for single-cell analysis of prokaryotic microorganisms is introduced. Industrially relevant microorganisms were analyzed as proof of principle allowing insights into growth rate, morphology, and phenotypic heterogeneity over certain time periods, hardly possible with conventional methods.

In this protocol the fabrication, experimental setup and basic operation of the recently introduced microfluidic picoliter bioreactor (PLBR) is described ...

Microalgae Cultivation and Biomass Quantification in a Bench-Scale Photobioreactor with Corrosive Flue Gases

Photobioreactors are illuminated cultivation systems for experiments on phototrophic microorganisms. These systems provide a sterile environment for microalgal cultivation with temperature, pH, and gas composition and flow rate control. At bench-scale, photobioreactors are advantageous to researchers studying microalgal properties, productivity, and growth optimization. At industrial scales, photobioreactors can maintain product purity and improve production efficiency. The video describes the preparation and use of a bench-scale photobioreactor for microalgal cultivation, including the safe use of corrosive gas inputs, and details relevant biomass measurements and biomass productivity calculations. Specifically, the video illustrates microalgal culture storage and preparation for inoculation, photobioreactor assembly and sterilization, biomass concentration measurements, and a logistic model for microalgal biomass productivity with rate calculations including maximum and overall biomass productivities. Additionally, since there is growing interest in experiments to cultivate microalgae using simulated or real waste gas emissions, the video will cover the photobioreactor equipment adaptations necessary to work with corrosive gases and discuss safe sampling in such scenarios.

Bench-scale, axenic cultivation facilitates microalgal characterization and productivity optimization before subsequent process scale-up. Photobioreactors provide the necessary control for reliable and reproducible microalgal experiments and can be adapted to safely cultivate microalgae with the corrosive gases (CO2, SO2, NO2) from municipal or industrial combustion emissions.

Photobioreactors are illuminated cultivation systems for experiments on phototrophic microorganisms. These systems provide a sterile environment for ...

Environment

Medium Preparation for the Cultivation of Microorganisms under Strictly Anaerobic/Anoxic Conditions

In contrast to aerobic organisms, strictly anaerobic microorganisms require the absence of oxygen and usually a low redox potential to initiate growth. As oxygen is ubiquitous in air, retaining O2-free conditions during all steps of cultivation is challenging but a prerequisite for anaerobic culturing. The protocol presented here demonstrates the successful cultivation of an anaerobic mixed culture derived from a biogas plant using a simple and inexpensive method. A precise description of the entire anoxic culturing process is given including media preparation, filling of cultivation flasks, supplementation with redox indicator and reducing agents to provide low redox potentials as well as exchanging the headspace to keep media free from oxygen. Furthermore, a detailed overview of aseptically inoculating gas tight serum flasks (by using sterile syringes and needles) and suitable incubation conditions is provided. The present protocol further deals with gas and liquid sampling for subsequent analyses regarding gas composition and volatile fatty acid concentrations using gas chromatography (GC) and high performance liquid chromatography (HPLC), respectively, and the calculation of biogas and methane yield considering the ideal gas law.

As obligate anaerobic organisms are unable to grow upon oxygen exposure, the use of anaerobic culturing techniques is indispensable. Here, we demonstrate a simple and effective method to cultivate a mixed culture derived from a biogas plant from media preparation to gas and volatile fatty acid quantification.

In contrast to aerobic organisms, strictly anaerobic microorganisms require the absence of oxygen and usually a low redox potential to initiate growth. As ...

Biochemistry

In Vivo Monitoring of Transcriptional Activity During Metabolic Transition Using a Bioluminescent Reporter in Yeast

Sequential sugar consumption, from a preferred sugar source to a less preferred one, represents a critical metabolic adaptation in yeast, which is particularly relevant for survival in fluctuating environments such as those found in beer fermentation. However, sugar transitions are an environmental variable that is challenging to predict and detect, impacting the outcome of beer fermentations. This protocol describes an in vivo system to monitor transcriptional activation associated with the glucose-to-maltose metabolic shift in Saccharomyces eubayanus that applies to different wild Saccharomyces yeast strains. 
The system employs an episomal bioluminescent transcriptional reporter for maltose metabolism, focusing on MAL32, since it provides a good readout for metabolic shifts, as studied in S. cerevisiae. For this, yeast strains were transformed with plasmids containing the MAL32 regulatory region from S. eubayanus, controlling the expression of a gene encoding for a destabilized version of firefly luciferase1, and a hygromycin resistance gene used exclusively during transformation to ensure plasmid acquisition. Following selection, transformed yeast cells can be cultured under non-selective conditions, as the episomal plasmid remains stable in culture conditions for up to 7 days. 
This system was validated under a complex sugar environment in microfermentation assays, confirming the effectiveness of the luciferase reporter in informing metabolic transitions. Samples were collected regularly and analyzed with a luminometer, providing continuous insights into yeast responses. While broadly applicable, this protocol is particularly valuable for assessing yeast performance under fermentation conditions, where metabolic changes pose a significant challenge. Additionally, this methodology can be adapted by selecting alternative promoters to explore a broader range of responses to environmental changes, allowing characterization as well as optimization of wild yeast strains for diverse industrial applications.

This protocol employs a bioluminescent reporter, allowing measurements of transcriptional activity in Saccharomyces eubayanus to monitor the glucose-to-maltose transition, enabling real-time analysis of metabolic adaptations and supporting strain optimization for industrial fermentation under diverse conditions.

Sequential sugar consumption, from a preferred sugar source to a less preferred one, represents a critical metabolic adaptation in yeast, which is ...

Genetics

Design and Implementation of an Automated Illuminating, Culturing, and Sampling System for Microbial Optogenetic Applications

Optogenetic systems utilize genetically-encoded proteins that change conformation in response to specific wavelengths of light to alter cellular processes. There is a need for culturing and measuring systems that incorporate programmed illumination and stimulation of optogenetic systems. We present a protocol for building and using a continuous culturing apparatus to illuminate microbial cells with programmed doses of light, and automatically acquire and analyze images of cells in the effluent. The operation of this apparatus as a chemostat allows the growth rate and the cellular environment to be tightly controlled. The effluent of the continuous cell culture is regularly sampled and the cells are imaged by multi-channel microscopy. The culturing, sampling, imaging, and image analysis are fully automated so that dynamic responses in the fluorescence intensity and cellular morphology of cells sampled from the culture effluent are measured over multiple days without user input. We demonstrate the utility of this culturing apparatus by dynamically inducing protein production in a strain of Saccharomyces cerevisiae engineered with an optogenetic system that activates transcription.

We designed a continuous culturing apparatus for use with optogenetic systems to illuminate cultures of microbes and regularly image cells in the effluent with an inverted microscope. The culturing, sampling, imaging, and image analysis are fully automated so that dynamic responses to illumination can be measured over several days.

Optogenetic systems utilize genetically-encoded proteins that change conformation in response to specific wavelengths of light to alter cellular ...

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

A core business in industrial biotechnology using microbial production cell factories is the iterative process of strain engineering and optimization of bioprocess conditions. One important aspect is the improvement of cultivation medium to provide an optimal environment for microbial formation of the product of interest. It is well accepted that the media composition can dramatically influence overall bioprocess performance. Nutrition medium optimization is known to improve recombinant protein production with microbial systems and thus, this is a rewarding step in bioprocess development. However, very often standard media recipes are taken from literature, since tailor-made design of the cultivation medium is a tedious task that demands microbioreactor technology for sufficient cultivation throughput, fast product analytics, as well as support by lab robotics to enable reliability in liquid handling steps. Furthermore, advanced mathematical methods are required for rationally analyzing measurement data and efficiently designing parallel experiments such as to achieve optimal information content.
The generic nature of the presented protocol allows for easy adaption to different lab equipment, other expression hosts, and target proteins of interest, as well as further bioprocess parameters. Moreover, other optimization objectives like protein production rate, specific yield, or product quality can be chosen to fit the scope of other optimization studies. The applied Kriging Toolbox (KriKit) is a general tool for Design of Experiments (DOE) that contributes to improved holistic bioprocess optimization. It also supports multi-objective optimization which can be important in optimizing both upstream and downstream processes.

This manuscript describes a generic approach for tailor-made design of microbial cultivation media. This is enabled by an iterative workflow combining Kriging-based experimental design and microbioreactor technology for sufficient cultivation throughput, which is supported by lab robotics to increase reliability and speed in liquid handling media preparation.

A core business in industrial biotechnology using microbial production cell factories is the iterative process of strain engineering and optimization of ...

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Studies in the field of microbiology rely on the implementation of a wide range of methodologies. In particular, the development of appropriate methods substantially contributes to providing extensive knowledge of the metabolism of microorganisms growing in chemically defined media containing unique nitrogen and carbon sources. In contrast, the management through metabolism of multiple nutrient sources, despite their broad presence in natural or industrial environments, remains virtually unexplored. This situation is mainly due to the lack of suitable methodologies, which hinders investigations.
We report an experimental strategy to quantitatively and comprehensively explore how metabolism operates when a nutrient is provided as a mixture of different molecules, i.e., a complex resource. Here, we describe its application for assessing the partitioning of multiple nitrogen sources through the yeast metabolic network. The workflow combines information obtained during stable isotope tracer experiments using selected 13C- or 15N-labeled substrates. It first consists of parallel and reproducible fermentations in the same medium, which includes a mixture of N-containing molecules; however,a selected nitrogen source is labeled each time. A combination of analytical procedures (HPLC, GC-MS) is implemented to assess the labeling patterns of targeted compounds and to quantify the consumption and recovery of substrates in other metabolites. An integrated analysis of the complete dataset provides an overview of the fate of consumed substrates within cells. This approach requires an accurate protocol for the collection of samples&#8211;facilitated by a robot-assisted system for online monitoring of fermentations&#8211;and the achievement of numerous time-consuming analyses. Despite these constraints, it allowed understanding, for the first time, the partitioning of multiple nitrogen sources throughout the yeast metabolic network. We elucidated the redistribution of nitrogen from more abundant sources toward other N-compounds and determined the metabolic origins of volatile molecules and proteinogenic amino acids.

This protocol describes an experimental procedure to quantitatively and comprehensively investigate the metabolism of multiple nutrient sources. This workflow, based on a combination of isotopic tracer experiments and an analytical procedure, allows the fate of consumed nutrients and the metabolic origin of molecules synthetized by microorganisms to be determined.

Studies in the field of microbiology rely on the implementation of a wide range of methodologies. In particular, the development of appropriate methods ...

Use of High-Throughput Automated Microbioreactor System for Production of Model IgG1 in CHO Cells

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of experimental conditions while minimizing potential process variability. Applications of this approach include: clone screening, temperature and pH shifts,&#160;media and supplement optimization. Furthermore, the small reactor volumes are conducive to large Design of Experiments that investigate a wide range of conditions. This allows upstream processes to be significantly optimized before scale-up where experimentation is more limited in scope due to time and economic constraints. Automated microscale bioreactor systems offer various advantages over traditional small scale cell culture units, such as shake flasks or spinner flasks. However, during pilot scale process development&#160;significant care must be taken to ensure that these advantages are realized. When run with care, the system can enable high level automation, can be programmed to run DOE&#39;s with a higher number of variables&#160;and can reduce sampling time when integrated with a nutrient analyzer or cell counter. Integration of the expert-derived heuristics presented here, with current automated microscale bioreactor experiments can minimize common pitfalls that hinder meaningful results. In the extreme, failure to adhere to the principles laid out here can lead to equipment damage that requires expensive repairs. Furthermore, the microbioreactor systems have small culture volumes&#160;making characterization of cell culture conditions difficult. The number and amount of samples taken in-process in batch mode culture is limited as operating volumes cannot fall below 10 mL. This method will discuss the benefits and drawbacks of microscale bioreactor systems.

A detailed protocol for the concurrent operation of 48 parallel cell cultures under varied conditions in a microbioreactor system is presented. Cell culture process, harvest and subsequent antibody titer analysis are described.

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of ...

Methanol Independent Expression by Pichia Pastoris Employing De-repression Technologies

Methanol is a well-established carbon source and inducer for efficient protein production employing Pichia pastoris (P. pastoris) as a host on micro-, lab and industrial scale. However, due to its toxicity and flammability, there is a desire to avoid methanol while maintaining the high productivity of P. pastoris. Small scale bioreactor cultivations (0.5-5 L working volume) are commonly used to evaluate a strain and its protein production characteristics since microscale cultivation in deep well plates can be hardly controlled or relies on expensive equipment. Furthermore, traditional protocols for the cultivation and induction of P. pastoris were established for constitutive expression or methanol induction and so far, no reliable protocols were described to screen P. pastoris expression strains with derepressible promoters in (controlled and monitored) parallel cultivations. To simplify such initial cultivations to characterize and compare new protein production strains, we established a simple shake flask cultivation system for methanol free expression that simulates bioreactor conditions including a constant slow glycerol feed and online monitoring, thereby coming closer to the real conditions in bioreactors compared to mostly applied small scale batch cultivations. To drive recombinant protein expression in P. pastoris, the carbon source repressed promoters PDC and PDF were applied. Polymer discs with embedded carbon source, releasing a constant amount of glycerol, assured a feed rate delivering the necessary energy for maintaining the promoters active while keeping the biomass generation low.

Methanol Independent Expression by Pichia Pastoris Employing De-repression Technologies

This method for the first time describes reliable experimental procedures for efficient inducible methanol-free recombinant protein production in Pichia pastoris (Komagataella phaffii), employing the carbon source regulated promoters PDCand PDF in small scale experiments while cultivation parameters can be monitored online, and a constant glycerol feed is applied.

Methanol is a well-established carbon source and inducer for efficient protein production employing Pichia pastoris (P. pastoris) as a host on micro-, lab ...

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Optimization of bioprocesses to increase the yield of desired products is of importance in the biopharmaceutical industry. This can be achieved by strain selection and by developing bioprocess parameters. Shake flasks have been used for this purpose. They, however, lack the capability to control the process parameters such as pH and dissolved oxygen (DO). This limitation can be overcome with the help of an automated micro-bioreactor. These bioreactors mimic cultivation at a larger scale. One of the major advantages of this system is the integration of the Design of Experiment (DOE) in the software. This integration enables establishing a design where multiple process parameters can be varied simultaneously. The critical process parameters and optimum bioprocess conditions can be analyzed within the software. The focus of the work presented here is to introduce the user to the steps involved in process design in the software and incorporation of the DOE within the cultivation run.

Here, we present a detailed procedure to run a Design of Experiment in an automated micro-bioreactor followed by cell harvest and protein quantification using a Protein A column.

Optimization of bioprocesses to increase the yield of desired products is of importance in the biopharmaceutical industry. This can be achieved by strain ...

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Samenvatting

Meer video's verkennen

Hoofdstukken in deze video