Cycling between growth and production phases increases cyanobacteria bioproduction of lactate
Open accessAbstract
Decoupling growth from product synthesis is a promising strategy to increase carbon partitioning and maximize productivity in cell factories. However, reduction in both substrate uptake rate and metabolic activity in the production phase are an underlying problem for upscaling. Here, we used CRISPR interference to repress growth in lactate-producing Synechocystis sp. PCC 6803. Carbon partitioning to lactate in the production phase exceeded 90%, but CO2 uptake was severely reduced compared to uptake during the growth phase. We characterized strains during the onset of growth arrest using transcriptomics and proteomics. Multiple genes involved in ATP homeostasis were regulated once growth was inhibited, which suggests an alteration of energy charge that may lead to reduced substrate uptake. In order to overcome the reduced metabolic activity and take advantage of increased carbon partitioning, we tested a novel production strategy that involved alternating growth arrest and recovery by periodic addition of an inducer molecule to activate CRISPRi. Using this strategy, we maintained lactate biosynthesis in Synechocystis for 30 days in a constant light turbidostat cultivation. Cumulative lactate titers were also increased by 100% compared to a constant growth-arrest regime, and reached 1 g/L. Further, the cultivation produced lactate for 30 days, compared to 20 days for the non-growth arrest cultivation. Periodic growth arrest could be applicable for other products, and in cyanobacteria, could be linked to internal circadian rhythms that persist in constant light.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Efforts in metabolic engineering within cyanobacteria are often limited by constraints in metabolic flux and the availability of precursors.
“Alongside genetic obstacles, efforts in metabolic engineering within cyanobacteria are often limited by constraints in metabolic flux and the availability of precursors.”
From Cyanobacteria as a Photosynthetic Chassis for Metabolic Pathway Engineering with Heterologous Gene Expression (2026) · cites this paper as [204]
The Introduction (page unavailable) describes reduced metabolic activity and CO₂ fixation as limits on cyanobacterial production, and discusses redirecting flux from competing pathways. It does not establish that limited precursor availability is often a separate constraint on cyanobacterial metabolic engineering. (LLM, conf=0.82)
Experimental — accuracy not yet measuredNumerous heterologous pathways compete with native cellular processes for carbon intermediates, ATP, and reducing agents such as NADPH.
“Numerous heterologous pathways compete with native cellular processes for carbon intermediates, ATP, and reducing agents such as NADPH [204].”
From Cyanobacteria as a Photosynthetic Chassis for Metabolic Pathway Engineering with Heterologous Gene Expression (2026) · cites this paper as [204]
Establishing a suitable balance between native metabolic functions and heterologous pathway activity remains a significant challenge in the engineering of cyanobacterial strains.
“Therefore, establishing a suitable balance between native metabolic functions and heterologous pathway activity remains a significant challenge in the engineering of cyanobacterial strains [204].”
From Cyanobacteria as a Photosynthetic Chassis for Metabolic Pathway Engineering with Heterologous Gene Expression (2026) · cites this paper as [204]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106 · see citing works
A synthetic oscillatory network of transcriptional regulators
Elowitz, M., & Leibler, S. (2000) · Nature · doi:10.1038/35002125 · Cited by 4,812 · see citing works
Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning
Gessulat, S., Schmidt, T., Zolg, D. P., Samaras, P., Schnatbaum, K., Zerweck, J., Knaute, T., Rechenberger, J., Delanghe, B., Hühmer, A. F. R., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0426-7 · Cited by 842 · see citing works
Ho, S., Chen, C., & Chang, J. (2011) · Bioresource Technology · doi:10.1016/j.biortech.2011.11.133 · Cited by 781 · see citing works
Improving lycopene production in Escherichia coli by engineering metabolic control
Farmer, W. R., & Liao, J. C. (2000) · Nature Biotechnology · doi:10.1038/75398 · Cited by 523 · see citing works
Searle, B. C., Pino, L. K., Egertson, J. D., Ting, Y. S., Lawrence, R., MacLean, B., Villén, J., & MacCoss, M. J. (2018) · Nature Communications · doi:10.1038/s41467-018-07454-w · Cited by 508 · see citing works
Ajjawi, I., Verruto, J., Aqui, M., Soriaga, L. B., Coppersmith, J. L., Kwok, K., Peach, L., Orchard, E. D., Kalb, R., Xu, W., et al. (2017) · Nature Biotechnology · doi:10.1038/nbt.3865 · Cited by 472 · see citing works
Mapping photoautotrophic metabolism with isotopically nonstationary 13C flux analysis
Young, J. D., Shastri, A. A., Stephanopoulos, G. N., & Morgan, J. A. (2011) · Metabolic Engineering · doi:10.1016/j.ymben.2011.08.002 · Cited by 347 · see citing works
Cyanobacteria Perceive Nitrogen Status by Sensing Intracellular 2-Oxoglutarate Levels
Muro‐Pastor, M. I., Reyes, J. C., & Florencio, F. J. (2001) · Journal of Biological Chemistry · doi:10.1074/jbc.m105297200 · Cited by 312 · see citing works
Ammonium assimilation in cyanobacteria
Muro-Pastor, M. I., Reyes, J. C., & Florencio, F. J. (2005) · Photosynthesis Research · doi:10.1007/s11120-004-2082-7 · Cited by 287 · see citing works
Wang, H., Postier, B. L., & Burnap, R. L. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m311336200 · Cited by 266 · see citing works
Adams, C., Godfrey, V., Wahlen, B., Seefeldt, L., & Bugbee, B. (2013) · Bioresource Technology · doi:10.1016/j.biortech.2012.12.143 · Cited by 242 · see citing works
Schwarz, R., & Forchhammer, K. (2005) · Microbiology · doi:10.1099/mic.0.27883-0 · Cited by 240 · see citing works
Engineering metabolism through dynamic control
Venayak, N., Anesiadis, N., Cluett, W. R., & Mahadevan, R. (2015) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2014.12.022 · Cited by 211 · see citing works
Soma, Y., Tsuruno, K., Wada, M., Yokota, A., & Hanai, T. (2014) · Metabolic Engineering · doi:10.1016/j.ymben.2014.02.008 · Cited by 198 · see citing works
Dynamic metabolic engineering: New strategies for developing responsive cell factories
Reizman, I., & Prather, K. L. J. (2015) · Biotechnology Journal · doi:10.1002/biot.201400422 · Cited by 187 · see citing works
Engineering a Cyanobacterial Cell Factory for Production of Lactic Acid
Angermayr, S. A., Paszota, M., & Hellingwerf, K. J. (2012) · Applied and Environmental Microbiology · doi:10.1128/aem.01587-12 · Cited by 187 · see citing works
Angermayr, S. A., van der Woude, A. D., Correddu, D., Vreugdenhil, A., Verrone, V., & Hellingwerf, K. J. (2014) · Biotechnology for Biofuels · doi:10.1186/1754-6834-7-99 · Cited by 163 · see citing works
Yao, L., Shabestary, K., Björk, S., Asplund‐Samuelsson, J., Joensson, H. N., Jahn, M., & Hudson, E. P. (2020) · Nature Communications · doi:10.1038/s41467-020-15491-7 · Cited by 158 · see citing works
Self-citationBhaya, D., Watanabe, N., Ogawa, T., & Grossman, A. R. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.6.3188 · Cited by 153 · see citing works
Glycogen Synthesis and Metabolite Overflow Contribute to Energy Balancing in Cyanobacteria
Cano, M., Holland, S. C., Artier, J., Burnap, R. L., Ghirardi, M. L., Morgan, J. A., & Yu, J. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.083 · Cited by 143 · see citing works
Metabolic and Transcriptional Response to Cofactor Perturbations in Escherichia coli
Holm, A. K., Blank, L. M., Oldiges, M., Schmid, A., Solem, C., Jensen, P. R., & Vemuri, G. N. (2010) · Journal of Biological Chemistry · doi:10.1074/jbc.m109.095570 · Cited by 141 · see citing works
PHB is Produced from Glycogen Turn-over during Nitrogen Starvation in Synechocystis sp. PCC 6803
Koch, M., Doello, S., Gutekunst, K., & Forchhammer, K. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20081942 · Cited by 141 · see citing works
A model for improving microbial biofuel production using a synthetic feedback loop
Dunlop, M. J., Keasling, J. D., & Mukhopadhyay, A. (2010) · Systems and Synthetic Biology · doi:10.1007/s11693-010-9052-5 · Cited by 138 · see citing works
Metabolic design for cyanobacterial chemical synthesis
Oliver, J. W. K., & Atsumi, S. (2014) · Photosynthesis Research · doi:10.1007/s11120-014-9997-4 · Cited by 134 · see citing works
Krasikov, V., Aguirre‐von‐Wobeser, E., Dekker, H. L., Huisman, J., & Matthijs, H. C. P. (2012) · Physiologia Plantarum · doi:10.1111/j.1399-3054.2012.01585.x · Cited by 133 · see citing works
Growth of Cyanobacteria Is Constrained by the Abundance of Light and Carbon Assimilation Proteins
Jahn, M., Vialás, V., Karlsen, J. R., Maddalo, G., Edfors, F., Forsström, B., Uhlén, M., Käll, L., & Hudson, E. P. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.09.040 · Cited by 130 · see citing works
Self-citationMarin, K., Kanesaki, Y., Los, D. A., Murata, N., Suzuki, I., & Hagemann, M. (2004) · PLANT PHYSIOLOGY · doi:10.1104/pp.104.045047 · Cited by 129 · see citing works
Environmental Dependence of Stationary-Phase Metabolism in Bacillus subtilis and Escherichia coli
Chubukov, V., & Sauer, U. (2014) · Applied and Environmental Microbiology · doi:10.1128/aem.00061-14 · Cited by 125 · see citing works
RICHAUD, C., Zabulon, G., Joder, A., & Thomas, J. (2001) · Journal of Bacteriology · doi:10.1128/jb.183.10.2989-2994.2001 · Cited by 124 · see citing works
Vavilin, D. V., & Vermaas, W. F. J. (2002) · Physiologia Plantarum · doi:10.1034/j.1399-3054.2002.1150102.x · Cited by 123 · see citing works
Quantitative insights into the cyanobacterial cell economy
Zavřel, T., Faizi, M., Loureiro, C., Poschmann, G., Stühler, K., Sinetova, M. A., Zorina, A. A., Steuer, R., & Červený, J. (2019) · eLife · doi:10.7554/elife.42508 · Cited by 114 · see citing works
Cameron, J. C., & Pakrasi, H. B. (2010) · PLANT PHYSIOLOGY · doi:10.1104/pp.110.162990 · Cited by 113 · see citing works
Fokina, O., Chellamuthu, V.-R., Forchhammer, K., & Zeth, K. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1007653107 · Cited by 112 · see citing works
A dynamic metabolite valve for the control of central carbon metabolism
Solomon, K., Sanders, T. M., & Prather, K. L. J. (2012) · Metabolic Engineering · doi:10.1016/j.ymben.2012.08.006 · Cited by 110 · see citing works
A Two-Layer Gene Circuit for Decoupling Cell Growth from Metabolite Production
Lo, T., Chng, S. H., Teo, W. S., Cho, H.-S., & Chang, M. W. (2016) · Cell Systems · doi:10.1016/j.cels.2016.07.012 · Cited by 110 · see citing works
Genetic Instability in Cyanobacteria – An Elephant in the Room?
Jones, P. R. (2014) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2014.00012 · Cited by 105 · see citing works
NTP-sensing by rRNA promoters in Escherichia coli is direct
Schneider, D. A., Gaál, T., & Gourse, R. L. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.132285199 · Cited by 105 · see citing works
Huckauf, J., Nomura, C. T., Forchhammer, K., & Hagemann, M. (2000) · Microbiology · doi:10.1099/00221287-146-11-2877 · Cited by 97 · see citing works
Enhanced protein and biochemical production using CRISPRi-based growth switches
Li, S., Jendresen, C. B., Grünberger, A., Ronda, C., Jensen, S. I., Noack, S., & Nielsen, A. T. (2016) · Metabolic Engineering · doi:10.1016/j.ymben.2016.09.003 · Cited by 95 · see citing works
Shabestary, K., & Hudson, E. P. (2016) · Metabolic Engineering Communications · doi:10.1016/j.meteno.2016.07.003 · Cited by 90 · see citing works
Self-citationShabestary, K., Anfelt, J., Ljungqvist, E., Jahn, M., Yao, L., & Hudson, E. P. (2018) · ACS Synthetic Biology · doi:10.1021/acssynbio.8b00056 · Cited by 89 · see citing works
Self-citationEstimating optimal profiles of genetic alterations using constraint‐based models
Gadkar, K. G., Doyle, F. J., Edwards, J. S., & Mahadevan, R. (2004) · Biotechnology and Bioengineering · doi:10.1002/bit.20349 · Cited by 88 · see citing works
Erdrich, P., Knoop, H., Steuer, R., & Klamt, S. (2014) · Microbial Cell Factories · doi:10.1186/s12934-014-0128-x · Cited by 85 · see citing works
Koch, M., Berendzen, K. W., & Forchhammer, K. (2020) · Life · doi:10.3390/life10040047 · Cited by 84 · see citing works
Quintero, M., Muro-Pastor, A. M., Herrero, A., & Flores, E. (2000) · Journal of Bacteriology · doi:10.1128/jb.182.4.1008-1015.2000 · Cited by 83 · see citing works
Gene expression patterns of sulfur starvation in Synechocystis sp. PCC 6803
Zhang, Z., Pendse, N. D., Phillips, K. N., Cotner, J. B., & Khodursky, A. B. (2008) · BMC Genomics · doi:10.1186/1471-2164-9-344 · Cited by 82 · see citing works
Zhou, J., Zhang, F., Meng, H., Zhang, Y., & Li, Y. (2016) · Metabolic Engineering · doi:10.1016/j.ymben.2016.08.002 · Cited by 80 · see citing works
Durante‐Rodríguez, G., de Lorenzo, V., & Nikel, P. I. (2018) · ACS Synthetic Biology · doi:10.1021/acssynbio.8b00345 · Cited by 76 · see citing works
Doello, S., Klotz, A., Makowka, A., Gutekunst, K., & Forchhammer, K. (2018) · PLANT PHYSIOLOGY · doi:10.1104/pp.18.00297 · Cited by 73 · see citing works
Labarre, J., Thuriaux, P., & Chauvat, F. (1987) · Journal of Bacteriology · doi:10.1128/jb.169.10.4668-4673.1987 · Cited by 70 · see citing works
Comparative Dose–Response Analysis of Inducible Promoters in Cyanobacteria
Behle, A., Saake, P., Germann, A. T., Dienst, D., & Axmann, I. M. (2020) · ACS Synthetic Biology · doi:10.1021/acssynbio.9b00505 · Cited by 67 · see citing works
Hädicke, O., Bettenbrock, K., & Klamt, S. (2015) · Biotechnology and Bioengineering · doi:10.1002/bit.25623 · Cited by 64 · see citing works
Gopalakrishnan, S., Pakrasi, H. B., & Maranas, C. D. (2018) · Metabolic Engineering · doi:10.1016/j.ymben.2018.03.008 · Cited by 63 · see citing works
Quintero, M., Montesinos, M. L., Antonia Herrero, B., & Flores, E. (2001) · Genome Research · doi:10.1101/gr.196301 · Cited by 59 · see citing works
Tapping the Unused Potential of Photosynthesis with a Heterologous Electron Sink
Berepiki, A., Hitchcock, A., Moore, C. M., & Bibby, T. S. (2016) · ACS Synthetic Biology · doi:10.1021/acssynbio.6b00100 · Cited by 57 · see citing works
Universal Molecular Triggers of Stress Responses in Cyanobacterium Synechocystis
Mironov, K., Sinetova, M., Shumskaya, M., & Los, D. (2019) · Life · doi:10.3390/life9030067 · Cited by 56 · see citing works
The Transcriptional Landscape of the Photosynthetic Model Cyanobacterium Synechocystis sp. PCC6803
Hernández‐Prieto, M. A., Semeniuk, T. A., Giner‐Lamia, J., & Futschik, M. E. (2016) · Scientific Reports · doi:10.1038/srep22168 · Cited by 55 · see citing works
Broadening the Scope of Enforced ATP Wasting as a Tool for Metabolic Engineering in Escherichia coli
Boecker, S., Ahmed, Z., Schramm, T., Link, H., & Klamt, S. (2019) · Biotechnology Journal · doi:10.1002/biot.201800438 · Cited by 55 · see citing works
Engineering an Optogenetic CRISPRi Platform for Improved Chemical Production
Wu, P., Chen, Y., Liu, M., Xiao, G., & Yuan, J. (2020) · ACS Synthetic Biology · doi:10.1021/acssynbio.0c00488 · Cited by 54 · see citing works
Proteomic Dissection of the Cellulolytic Machineries Used by Soil-Dwelling Bacteroidetes
Taillefer, M., Arntzen, M. Ø., Henrissat, B., Pope, P. B., & Larsbrink, J. (2018) · mSystems · doi:10.1128/msystems.00240-18 · Cited by 52 · see citing works
Williams, T. J., Allen, M. A., Ivanova, N., Huntemann, M., Haque, S., Hancock, A. M., Brazendale, S., & Cavicchioli, R. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.674758 · Cited by 52 · see citing works
Beck, C., Hertel, S., Rediger, A., Lehmann, R., Wiegard, A., Kölsch, A., Heilmann, B., Georg, J., Hess, W. R., & Axmann, I. M. I. (2014) · Applied and Environmental Microbiology · doi:10.1128/aem.01086-14 · Cited by 51 · see citing works
Orf, I., Schwarz, D., Kaplan, A., Kopka, J., Hess, W. R., Hagemann, M., & Klähn, S. (2016) · Plant and Cell Physiology · doi:10.1093/pcp/pcw146 · Cited by 49 · see citing works
Uptake of 2-Oxoglutarate in Synechococcus Strains Transformed with the Escherichia coli kgtP Gene
Vázquez-Bermúdez, M. F., Antonia Herrero, B., & Flores, E. (2000) · Journal of Bacteriology · doi:10.1128/jb.182.1.211-215.2000 · Cited by 44 · see citing works
Citrate synthase from Synechocystis is a distinct class of bacterial citrate synthase
Ito, S., Koyama, N., & Osanai, T. (2019) · Scientific Reports · doi:10.1038/s41598-019-42659-z · Cited by 44 · see citing works
Borirak, O., de Koning, L. J., van der Woude, A. D., Hoefsloot, H. C. J., Dekker, H. L., Roseboom, W., de Koster, C. G., & Hellingwerf, K. J. (2015) · Biotechnology for Biofuels · doi:10.1186/s13068-015-0294-z · Cited by 42 · see citing works
Lynch, M. (2016) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2016.01.009 · Cited by 39 · see citing works
Chávez, S., Lucena, J. M., Reyes, J. C., Florencio, F. J., & Candau, P. (1999) · Journal of Bacteriology · doi:10.1128/jb.181.3.808-813.1999 · Cited by 35 · see citing works
Asplund‐Samuelsson, J., Janasch, M., & Hudson, E. P. (2017) · Metabolic Engineering · doi:10.1016/j.ymben.2017.12.011 · Cited by 35 · see citing works
Self-citationRedirecting carbon to bioproduction via a growth arrest switch in a sucrose-secreting cyanobacterium
Abramson, B. W., Lensmire, J., Lin, Y.-T., Jennings, E., & Ducat, D. C. (2018) · Algal Research · doi:10.1016/j.algal.2018.05.013 · Cited by 35 · see citing works
van Alphen, P., & Hellingwerf, K. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0127715 · Cited by 34 · see citing works
Du, W., Angermayr, S., Jongbloets, J., Molenaar, D., Bachmann, H., Hellingwerf, K., & dos Santos, F. B. (2017) · ACS Synthetic Biology · doi:10.1021/acssynbio.6b00235 · Cited by 34 · see citing works
Karlsen, J., Asplund‐Samuelsson, J., Jahn, M., Vitay, D., & Hudson, E. P. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.657379 · Cited by 25 · see citing works
Self-citationRibosome Profiling of Synechocystis Reveals Altered Ribosome Allocation at Carbon Starvation
Karlsen, J., Asplund‐Samuelsson, J., Thomas, Q. A., Jahn, M., & Hudson, E. P. (2018) · mSystems · doi:10.1128/msystems.00126-18 · Cited by 23 · see citing works
Self-citationLandberg, J., Wright, N. R., Wulff, T., Herrgård, M. J., & Nielsen, A. T. (2020) · Biotechnology and Bioengineering · doi:10.1002/bit.27536 · Cited by 21 · see citing works
Schramm, T., Lempp, M., Beuter, D., Sierra, S. G., Glatter, T., & Link, H. (2020) · Metabolic Engineering · doi:10.1016/j.ymben.2020.03.004 · Cited by 19 · see citing works
Du, W., Caicedo-Burbano, P., Hellingwerf, K. J., & dos Santos, F. B. (2018) · Advances in experimental medicine and biology · doi:10.1007/978-981-13-0854-3_1 · Cited by 13 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Fokina, O., Chellamuthu, V.-R., Forchhammer, K., Zeth, K., 2010. Mechanism of 2-oxo- glutarate signaling by the Synechococcus elongatus PII signal transduction protein. Proc. Natl. Acad. Sci. U. S. A. 107, 19760-19765.
Cited by
Sorted by citations
Recent Advances in CRISPR-Cas Technologies for Synthetic Biology
Jeong, S. H., Lee, H. J., & Lee, S. J. (2023) · The Journal of Microbiology · doi:10.1007/s12275-022-00005-5 · Cited by 82 · see citing works
New synthetic biology tools for metabolic control
Lv, X., Hueso‐Gil, Á., Bi, X., Wu, Y., Liu, Y., Liu, L., & Ledesma‐Amaro, R. (2022) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2022.102724 · Cited by 67 · see citing works
Carbon-negative synthetic biology: challenges and emerging trends of cyanobacterial technology
Tan, C., Xu, P., & Tao, F. (2022) · Trends in biotechnology · doi:10.1016/j.tibtech.2022.09.012 · Cited by 55 · see citing works
Cyanobacteria as whole-cell factories: Current status and future prospectives
Toepel, J., Karande, R., Klähn, S., & Bühler, B. (2023) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2023.102892 · Cited by 52 · see citing works
CRISPR-Based Approaches for Gene Regulation in Non-Model Bacteria
Call, S. N., & Andrews, L. B. (2022) · Frontiers in Genome Editing · doi:10.3389/fgeed.2022.892304 · Cited by 48 · see citing works
Cui, J., Sun, H., Chen, R., Sun, J., Mo, G., Luan, G., & Lü, X. (2023) · Green Carbon · doi:10.1016/j.greenca.2023.11.004 · Cited by 48 · see citing works
Nawaz, T., Gu, L., Fahad, S., Saud, S., Harrison, M. T., & Zhou, R. (2024) · Food and Energy Security · doi:10.1002/fes3.536 · Cited by 45 · see citing works
Miao, R., Jahn, M., Shabestary, K., Peltier, G., & Hudson, E. P. (2023) · The Plant Cell · doi:10.1093/plcell/koad208 · Cited by 47 · see citing works
Self-citationJaramillo, A., Satta, A., Pinto, F., Faraloni, C., Zittelli, G. C., Benavides, A. M. S., Torzillo, G., Schumann, C., Méndez, J. F., Berggren, G., et al. (2025) · Energy & Fuels · doi:10.1021/acs.energyfuels.4c04772 · Cited by 40 · see citing works
Base editing for reprogramming cyanobacterium Synechococcus elongatus
Wang, S.-Y., Li, X., Wang, S.-G., & Xia, P.-F. (2023) · Metabolic Engineering · doi:10.1016/j.ymben.2022.11.005 · Cited by 31 · see citing works
CRISPR Tools for Engineering Prokaryotic Systems: Recent Advances and New Applications
Burbano, D. A., Kiattisewee, C., Karanjia, A. V., Cardiff, R. A. L., Faulkner, I., Sugianto, W., & Carothers, J. M. (2024) · Annual Review of Chemical and Biomolecular Engineering · doi:10.1146/annurev-chembioeng-100522-114706 · Cited by 32 · see citing works
Sun, T., Li, Z., Li, S., Chen, L., & Zhang, W. (2022) · Chemical Engineering Journal · doi:10.1016/j.cej.2022.139158 · Cited by 27 · see citing works
Thermodynamic limitations of PHB production from formate and fructose in Cupriavidus necator
Janasch, M., Crang, N., Asplund‐Samuelsson, J., Sporre, E., Bruch, M., Gynnå, A. H., Jahn, M., & Hudson, E. P. (2022) · Metabolic Engineering · doi:10.1016/j.ymben.2022.08.005 · Cited by 28 · see citing works
Self-citationRodrigues, J. S., Kovács, L., Lukeš, M., Höper, R., Steuer, R., Červený, J., Lindberg, P., & Zavřel, T. (2023) · Bioresource Technology · doi:10.1016/j.biortech.2023.129068 · Cited by 29 · see citing works
Engineering highly productive cyanobacteria towards carbon negative emissions technologies
Victoria, A. J., Astbury, M. J., & McCormick, A. J. (2024) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2024.103141 · Cited by 27 · see citing works
Design of microbial catalysts for two-stage processes
Shabestary, K., Klamt, S., Link, H., Mahadevan, R., Steuer, R., & Hudson, E. P. (2024) · Nature Reviews Bioengineering · doi:10.1038/s44222-024-00225-x · Cited by 23 · see citing works
Self-citationMethanol biotransformation for the production of biodegradable plastic monomer L-lactate in yeast
Yu, W., Zhang, C., Li, Y., Chen, Q., Fei, Q., Gao, J., & Zhou, Y. J. (2025) · Nature Communications · doi:10.1038/s41467-025-65793-x · Cited by 21 · see citing works
Phenotypic heterogeneity follows a growth-viability tradeoff in response to amino acid identity
Shabestary, K., Klemm, C., Carling, B., Marshall, J., Savigny, J., Storch, M., & Ledesma‐Amaro, R. (2024) · Nature Communications · doi:10.1038/s41467-024-50602-8 · Cited by 15 · see citing works
Self-citationCRISPR-Cas mediated genome engineering of cyanobacteria
Sengupta, A., Liu, D., & Pakrasi, H. B. (2022) · Methods in Enzymology · doi:10.1016/bs.mie.2022.07.023 · Cited by 13 · see citing works
Sustainable citric acid production from CO2 in an engineered cyanobacterium
Zhang, L., Bryan, S. J., & Selão, T. T. (2022) · Frontiers in Microbiology · doi:10.3389/fmicb.2022.973244 · Cited by 11 · see citing works
Assessing and reducing phenotypic instability in cyanobacteria
Guillaume, M. C., & Branco dos Santos, F. (2023) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2023.102899 · Cited by 11 · see citing works
Reprogramming Microbial CO2-Metabolizing Chassis With CRISPR-Cas Systems
Yu, H., Wang, S., & Xia, P. (2022) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2022.897204 · Cited by 11 · see citing works
Pfennig, T., Kullmann, E., Zavřel, T., Nakielski, A., Ebenhöh, O., Červený, J., Bernát, G., & Matuszyńska, A. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012445 · Cited by 9 · see citing works
Rana, A. K., & Thakur, V. K. (2024) · Bioresource Technology · doi:10.1016/j.biortech.2024.131951 · Cited by 9 · see citing works
Nivedha, R. M., & Prasanna, R. (2025) · Archives of Microbiology · doi:10.1007/s00203-025-04449-2 · Cited by 6 · see citing works
Resource allocation models: theory and applications in microbial biotechnology
Teusink, B., Grigaitis, P., Remeijer, M., Bruggeman, F. J., & Steuer, R. (2025) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2025.103391 · Cited by 6 · see citing works
Nondiazotrophic cyanobacteria metabolic engineering for succinate and lactate production
Yamane, M., & Osanai, T. (2023) · Algal Research · doi:10.1016/j.algal.2023.103088 · Cited by 5 · see citing works
Advances in organic acid production using cyanobacteria: Strategies and applications
Pathania, R., & Srivastava, A. (2025) · Blue Biotechnology · doi:10.1186/s44315-025-00045-7 · Cited by 4 · see citing works
Harnessing engineered cyanobacteria for next-generation therapeutics
Bhardwaj, A., & Mishra, A. K. (2026) · Archives of Microbiology · doi:10.1007/s00203-026-04790-0 · Cited by 2 · see citing works
Walshe, J., & Saha, S. K. (2026) · Current Issues in Molecular Biology · doi:10.3390/cimb48060638 · Cited by 1 · see citing works
Faulkner, M., Andrews, F., & Scrutton, N. S. (2025) · Biotechnology for Biofuels and Bioproducts · doi:10.1186/s13068-025-02718-2 · Cited by 1 · see citing works
Applications and Prospects of CRISPR-Cas system in Cyanobacteria
Jing, Y. (2023) · BIO Web of Conferences · doi:10.1051/bioconf/20236101009 · Cited by 1 · see citing works
Jones, C. M., Innes, S., Holland, S. C., Burch, T. A., Parrish, S., & Nielsen, D. R. (2024) · Biotechnology and Bioengineering · doi:10.1002/bit.28905 · Cited by 1 · see citing works
Jones, C. M., Innes, S., Holland, S. C., Burch, T. A., Parrish, S., & Nielsen, D. R. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.02.597031
Carbon Partitioning and Resource Use Efficiency for Enhancing Biofuel Production
Islam, M. S., Hossain, O., Pramanik, M. H., Aurib, K., Chowdhury, M. K., Hafeez, A. G., Bari, A. K. M. A., Islam, M. R., Akdeniz, H., Ueda, A., et al. (2025) · Springer eBooks · doi:10.1007/978-981-96-2536-9_15
Biofuels: Exploring the Future of Green & Clean Energy
Jabeen, M., Parveen, S., Aslam, N., Zafar, A., Aslam, S., & Elboughdiri, N. A. (2026) · El-Cezeri Fen ve Mühendislik Dergisi · doi:10.31202/ecjse.1680236
Dai, R., Zhan, J., Li, S., Huang, X., Luo, H., Wang, H., Wang, S., & Sun, Y. (2026) · Green Carbon · doi:10.1016/j.greenca.2026.03.007
Over 4 months of ethylene production using solid-state photosynthetic cell factories
Kosourov, S. N., Siitonen, V., Tóth, G. S., Levä, T., Tammelin, T., Kallio, P., & Allahverdiyeva, Y. (2026) · Trends in biotechnology · doi:10.1016/j.tibtech.2026.06.006
Employing Nanotechnology to Enhance Ethanol Production in Two Synechococcus elongatus Strains
Schirmacher, A. M., Russo, D. A., Furch, A. C. U., & Zedler, J. A. Z. (2026) · ChemBioChem · doi:10.1002/cbic.70480
CO2 as a sustainable carbon synthon for advanced chemical manufacturing
Raheja, Y., Gupta, P., Singh, S., Gautam, K., Aishwarya, A., Kumar, A., Chauhan, R., Chadha, B. S., Srivastava, J. K., & Gaur, V. K. (2026) · Frontiers in Chemical Engineering · doi:10.3389/fceng.2026.1896459
Opportunities and Challenges of Overflow Metabolism in Industrial Microorganisms
Xu, M., Liu, S., Sun, D., & Ren, H. (2026) · ACS Synthetic Biology · doi:10.1021/acssynbio.6c00508
- Authors
- Shabestary, K., Hernández, H. P., Miao, R., Ljungqvist, E., Hallman, O., Sporre, E., Branco dos Santos, F., & Hudson, E. P.
- Affiliations
- Science for Life Laboratory (SE)
- University of Amsterdam (NL)
- Corresponding author
- Hudson, Elton P.
- Venue
- Metabolic Engineering
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 68
- Pages
- 131-141
- ISSN
- 1096-7176 (ISSN-L)
- OpenAlex
- W3203850845
- Cited by
- 42
- References
- 77
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 10 · 2023: 8 · 2022: 9
- FWCI
- 2.12
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Metabolic Engineering (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion, cc-by)
- Funders
- Horizon 2020 Framework Programme
- Horizon 2020 (760994)
- Vetenskapsrådet (2020-04329)
- Novo Nordisk Fonden (NNF20OC0061469, NNF20OC0064371)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Photosynthetic Processes and Mechanisms
- Keywords
- cyanobacteria, lactic acid production, Synechocystis sp. PCC 6803, growth arrest, CRISPR interference, carbon allocation, cell factories, CO2 uptake, ATP homeostasis, energy charge, transcriptomics, proteomics
- MeSH terms
- Lactic Acid, Synechocystis, Clustered Regularly Interspaced Short Palindromic Repeats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
