Mixed and membrane-separated culturing of synthetic cyanobacteria-yeast consortia reveals metabolic cross-talk mimicking natural cyanolichens.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
25 Oct 2024
Historique:
received: 20 07 2024
accepted: 30 09 2024
medline: 26 10 2024
pubmed: 26 10 2024
entrez: 25 10 2024
Statut: epublish

Résumé

Metabolite exchange mediates crucial interactions in microbial communities, significantly impacting global carbon and nitrogen cycling. Understanding these chemically-mediated interactions is essential for elucidating natural community functions and developing engineered synthetic communities. This study investigated membrane-separated bioreactors (mBRs) as a novel tool to identify transient metabolites and their producers/consumers in mixed microbial communities. We compared three co-culture methods (direct mixed, 2-chamber mBR, and 3-chamber mBR) to grow a synthetic binary community of the cyanobacterium Synechococcus elongatus PCC 7942 and the fungus Rhodotorula toruloides NBRC 0880, as well as axenic S. elongatus. Despite not being natural lichen constituents, these organisms exhibited interactions resembling those in cyanolichens. S. elongatus fixed CO

Identifiants

pubmed: 39455633
doi: 10.1038/s41598-024-74743-4
pii: 10.1038/s41598-024-74743-4
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

25303

Subventions

Organisme : Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory
ID : Predictive Phenomics Initiative
Organisme : Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory
ID : Predictive Phenomics Initiative
Organisme : Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory
ID : Predictive Phenomics Initiative
Organisme : Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory
ID : Predictive Phenomics Initiative
Organisme : Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory
ID : Predictive Phenomics Initiative
Organisme : U.S. Department of Energy Genomic Science Program
ID : DE-SC0019388
Organisme : U.S. Department of Energy Genomic Science Program
ID : DE-SC0019388
Organisme : U.S. Department of Energy Genomic Science Program
ID : DE-SC0019388
Organisme : U.S. Department of Energy Genomic Science Program
ID : DE-SC0019388

Informations de copyright

© 2024. Battelle Memorial Institute and The Authors 2024.

Références

Flombaum, P. et al. Present and future global distributions of the marine Cyanobacteria Prochlorococcus and Synechococcus. Proceedings of the National Academy of Sciences, 110(24): pp. 9824–9829. (2013).
Field, C. B., Behrenfeld, M. J., Randerson, J. T. & Falkowski, P. Primary production of the Biosphere: integrating Terrestrial and Oceanic Components. Science. 281 (5374), 237–240 (1998).
pubmed: 9657713 doi: 10.1126/science.281.5374.237
Jardillier, L., Zubkov, M. V., Pearman, J. & Scanlan, D. J. Significant CO2 fixation by small prymnesiophytes in the subtropical and tropical northeast Atlantic Ocean. ISME J. 4 (9), 1180–1192 (2010).
pubmed: 20393575 doi: 10.1038/ismej.2010.36
Teiser, M. L. O. Extracellular low Molecular Weight Organic Compounds Produced by Synechococcus sp. and Their Roles in the food web of Alkaline hot Spring Microbial mat Communities, in Department of Biology (University of Oregon, 1993).
Biddanda, B. & Benner, R. Carbon, nitrogen, and carbohydrate fluxes during the production of particulate and dissolved organic matter by marine phytoplankton. Limnol. Oceanogr. 42 (3), 506–518 (1997).
doi: 10.4319/lo.1997.42.3.0506
Bertilsson, S., Berglund, O., Pullin, M. & Chisholm, S. Release of Dissolved Organic Matter by Prochlorococcus55p. 225–231 (Vie et Milieu/Life & Environment, 2005).
Morán, X. A. G., Gasol, J. M., Pedrós-Alió, C. & Estrada, M. Partitioning of phytoplanktonic organic carbon production and bacterial production along a coastal-offshore gradient in the NE Atlantic during different hydrographic regimes. Aquat. Microb. Ecol. 29, 239–252 (2002).
doi: 10.3354/ame029239
Marañón, E., Cermeño, P., Fernández, E., Rodríguez, J. & Zabala, L. Significance and mechanisms of photosynthetic production of dissolved organic carbon in a coastal eutrophic ecosystem. Limnol. Oceanogr. 49 (5), 1652–1666 (2004).
doi: 10.4319/lo.2004.49.5.1652
Teira, E., José Pazó, M., Serret, P. & Fernández, E. Dissolved organic carbon production by microbial populations in the Atlantic Ocean. Limnol. Oceanogr. 46 (6), 1370–1377 (2001).
doi: 10.4319/lo.2001.46.6.1370
Jiao, N. et al. Microbial production of recalcitrant dissolved organic matter: long-term carbon storage in the global ocean. Nat. Rev. Microbiol. 8 (8), 593–599 (2010).
pubmed: 20601964 doi: 10.1038/nrmicro2386
Amon, R. M. W. Ocean dissolved organics matter. Nat. Geosci. 9 (12), 864–865 (2016).
doi: 10.1038/ngeo2841
Moran, M. A. et al. Deciphering ocean carbon in a changing world. Proceedings of the National Academy of Sciences, 113(12): pp. 3143–3151. (2016).
Sexton, P. F. et al. Eocene global warming events driven by ventilation of oceanic dissolved organic carbon. Nature. 471 (7338), 349–352 (2011).
pubmed: 21412336 doi: 10.1038/nature09826
Rothman, D. H., Hayes, J. M. & Summons, R. E. Dynamics of the Neoproterozoic carbon cycle. Proceedings of the National Academy of Sciences, 100(14): pp. 8124–8129. (2003).
Porada, P., Weber, B., Elbert, W., Pöschl, U. & Kleidon, A. Estimating impacts of lichens and bryophytes on global biogeochemical cycles. Glob. Biogeochem. Cycles. 28 (2), 71–85 (2014).
doi: 10.1002/2013GB004705
Elbert, W. et al. Contribution of cryptogamic covers to the global cycles of carbon and nitrogen. Nat. Geosci. 5 (7), 459–462 (2012).
doi: 10.1038/ngeo1486
Honegger, R. Functional aspects of the Lichen Symbiosis. Annu. Rev. Plant Physiol. Plant Mol. Biol. 42 (1), 553–578 (1991).
doi: 10.1146/annurev.pp.42.060191.003005
Morán, X. A. G., Ducklow, H. W. & Erickson, M. Carbon fluxes through estuarine bacteria reflect coupling with phytoplankton. Mar. Ecol. Prog. Ser. 489, 75–85 (2013).
doi: 10.3354/meps10428
Luo, Y. W., Friedrichs, M. A. M., Doney, S. C., Church, M. J. & Ducklow, H. W. Oceanic heterotrophic bacterial nutrition by semilabile DOM as revealed by data assimilative modeling. Aquat. Microb. Ecol. 60 (3), 273–287 (2010).
doi: 10.3354/ame01427
Li, B. et al. Catalytic promiscuity in the biosynthesis of cyclic peptide secondary metabolites in planktonic marine cyanobacteria. Proceedings of the National Academy of Sciences, 107(23): pp. 10430–10435. (2010).
Christie-Oleza, J. A., Armengaud, J., Guerin, P. & Scanlan, D. J. Functional distinctness in the exoproteomes of marineSynechococcus. Environ. Microbiol. 17 (10), 3781–3794 (2015).
pubmed: 25727668 pmcid: 4949707 doi: 10.1111/1462-2920.12822
Landa, M. et al. Phylogenetic and structural response of heterotrophic bacteria to dissolved organic matter of different chemical composition in a continuous culture study. Environ. Microbiol. 16 (6), 1668–1681 (2014).
pubmed: 24020678 doi: 10.1111/1462-2920.12242
Becker, J. W. et al. Closely Relat. Phytoplankton Species Produce Similar Suites Dissolved Org. Matter Front. Microbiol., 5. (2014).
Teeling, H. et al. Substrate-controlled succession of Marine Bacterioplankton populations Induced by a Phytoplankton Bloom. Science. 336 (6081), 608–611 (2012).
pubmed: 22556258 doi: 10.1126/science.1218344
Pontiller, B., Martínez-García, S., Lundin, D. & Pinhassi, J. Labile dissolved Organic Matter compound characteristics select for divergence in Marine bacterial activity and transcription. Front. Microbiol., 11. (2020).
Xu, J. et al. You Exude What You Eat: How Carbon-, Nitrogen-, and Sulfur-Rich Organic Substrates Shape Microbial Community Composition and the Dissolved Organic Matter Pool (Applied and Environmental Microbiology, 2022). 88(23).
Sher, D., Thompson, J. W., Kashtan, N., Croal, L. & Chisholm, S. W. Response of Prochlorococcus ecotypes to co-culture with diverse marine bacteria. ISME J. 5 (7), 1125–1132 (2011).
pubmed: 21326334 pmcid: 3146288 doi: 10.1038/ismej.2011.1
Morris, J. J., Kirkegaard, R., Szul, M. J., Johnson, Z. I. & Zinser, E. R. Facilitation of Robust Growth of Prochlorococcus colonies and dilute liquid cultures by helper heterotrophic Bacteria. Appl. Environ. Microbiol. 74 (14), 4530–4534 (2008).
pubmed: 18502916 pmcid: 2493173 doi: 10.1128/AEM.02479-07
Weissberg, O., Aharonovich, D. & Sher, D. Phototroph-heterotroph interactions during growth and long-term starvation across Prochlorococcus and Alteromonas diversity. ISME J. 17 (2), 227–237 (2022).
pubmed: 36335212 pmcid: 9860064 doi: 10.1038/s41396-022-01330-8
Christie-Oleza, J. A., Sousoni, D., Lloyd, M., Armengaud, J. & Scanlan, D. J. Nutrient recycling facilitates long-term stability of marine microbial phototroph–heterotroph interactions. Nat. Microbiol., (2017). 2(9).
Roth-Rosenberg, D. et al. Prochlorococcus cells rely on microbial interactions rather than on chlorotic resting stages to survive long-term nutrient starvation. mBio, 11(4). (2020).
Coe, A. et al. Survival of Prochlorococcus in extended darkness. Limnol. Oceanogr. 61 (4), 1375–1388 (2016).
doi: 10.1002/lno.10302
Biller, S. J., Coe, A., Roggensack, S. E., Chisholm, S. W. & Mason, O. Heterotroph Interact. Alter. Prochlorococcus Transcriptome Dynamics Dur. Ext. Periods Darkn. mSystems, 3(3). (2018).
Morris, J. J., Johnson, Z. I., Szul, M. J., Keller, M. & Zinser, E. R. Dependence of the Cyanobacterium Prochlorococcus on Hydrogen Peroxide Scavenging Microbes for Growth at the Ocean’s Surface. PLoS ONE, 6(2). (2011).
Bohutskyi, P. et al. Metabolic effects of vitamin B12 on physiology, stress resistance, growth rate and biomass productivity of cyanobacterium stanieri planktonic and biofilm cultures. Algal Res., 42. (2019).
Smith, D., Muscatine, L. & Lewis, D. Carbohydrate movement from autotrophs to heterotrophs in parasitic and mutualistic symbiosis. Biol. Rev. 44 (1), 17–85 (1969).
pubmed: 4890118 doi: 10.1111/j.1469-185X.1969.tb00821.x
Lines, C. E. M., Ratcliffe, R. G., Rees, T. A. V. & Southon, T. E. A 13 C NMR study of photosynthate transport and metabolism in the lichen Xanthoria Calcicola Oxner. New Phytol. 111 (3), 447–456 (1989).
pubmed: 33874007 doi: 10.1111/j.1469-8137.1989.tb00707.x
Honegger, R., Kutasi, V. & Ruffner, H. P. Polyol patterns in eleven species of aposymbiotically cultured lichen mycobionts. Mycol. Res. 97 (1), 35–39 (1993).
doi: 10.1016/S0953-7562(09)81109-X
Fahselt, D. Carbon Metabolism in Lichens. Symbiosis. 17, 127–182 (1994).
Armstrong, R. A. & Smith, S. N. The Levels of Ribitol, Arabitol and Mannitol in Individual Lobes of the Lichen Parmelia Conspersa (Ehrh. ex Ach.) ACH34p. 253–260 (Environmental and Experimental Botany, 1994). 3.
Aubert, S., Juge, C., Boisson, A. M., Gout, E. & Bligny, R. Metabolic processes sustaining the reviviscence of lichen Xanthoria elegans (Link) in high mountain environments. Planta. 226 (5), 1287–1297 (2007).
pubmed: 17574473 pmcid: 2386907 doi: 10.1007/s00425-007-0563-6
Honegger, R. Metabolic Interactions at the Mycobiont-Photobiont Interface in Lichens, in Plant Relationships. pp. 209–221. (1997).
Huneck, S. & Yoshimura, I. Identification of Lichen Substances, in Identification of Lichen Substances. pp. 11–123. (1996).
Stocker-Wörgötter, E. Metabolic diversity of lichen-forming ascomycetous fungi: culturing, polyketide and shikimatemetabolite production, and PKS genes. Nat. Prod. Rep. 25 (1), 188–200 (2008).
pubmed: 18250902 doi: 10.1039/B606983P
Calcott, M. J., Ackerley, D. F., Knight, A., Keyzers, R. A. & Owen, J. G. Secondary metabolism in the lichen symbiosis. Chem. Soc. Rev. 47 (5), 1730–1760 (2018).
pubmed: 29094129 doi: 10.1039/C7CS00431A
Williamson, J. D., Jennings, D. B., Guo, W. W., Pharr, D. M. & Ehrenshaft, M. Sugar Alcohols, Salt stress, and Fungal Resistance: polyols—multifunctional Plant Protection? J. Am. Soc. Hortic. Sci. 127 (4), 467–473 (2002).
doi: 10.21273/JASHS.127.4.467
Kosugi, M. et al. Arabitol provided by Lichenous Fungi Enhances Ability To Dissipate Excess Light Energy in a Symbiotic Green Alga under Desiccation. Plant Cell Physiol. 54 (8), 1316–1325 (2013).
pubmed: 23737501 doi: 10.1093/pcp/pct079
Kranner, I. et al. Antioxidants and photoprotection in a lichen as compared with its isolated symbiotic partners. Proceedings of the National Academy of Sciences, 102(8): pp. 3141–3146. (2005).
Millot, M., Di Meo, F., Tomasi, S., Boustie, J. & Trouillas, P. Photoprotective capacities of lichen metabolites: a joint theoretical and experimental study. J. Photochem. Photobiol., B. 111, 17–26 (2012).
pubmed: 22516892 doi: 10.1016/j.jphotobiol.2012.03.005
Straight, P. D. & Kolter, R. Interspecies Chemical Communication in Bacterial Development. Annu. Rev. Microbiol. 63 (1), 99–118 (2009).
pubmed: 19566421 doi: 10.1146/annurev.micro.091208.073248
Gökalsın, B., Berber, D., Özyiğitoğlu, G. Ç., Yeşilada, E. & Sesal, N. C. Quorum sensing attenuation properties of ethnobotanically valuable lichens againstPseudomonas aeruginosa. Plant. Biosystems - Int. J. Dealing all Aspects Plant. Biology. 154 (6), 792–799 (2019).
doi: 10.1080/11263504.2019.1701117
Nazem-Bokaee, H., Hom, E. F. Y., Warden, A. C., Mathews, S. & Gueidan, C. Towards a Systems Biology Approach to Understanding the Lichen Symbiosis: Opportunities and Challenges of Implementing Network Modelling12 (Frontiers in Microbiology, 2021).
Amin, S. A. et al. Interaction and signalling between a cosmopolitan phytoplankton and associated bacteria. Nature. 522 (7554), 98–101 (2015).
pubmed: 26017307 doi: 10.1038/nature14488
Friedmann, E. I., Hua, M. & Ocampo-Friedmann, R. 3.6 cryptoendolithic lichen and cyanobacterial communities of the Ross Desert, Antarctica. Polarforschung. 58 (2/3), 251–259 (1988).
pubmed: 11538357
Li, H. & Wei, J. C. Functional analysis of thioredoxin from the desert lichen-forming fungus, endocarpon pusillum Hedwig, reveals its role in stress tolerance. Sci. Rep. 6, 27184 (2016).
pubmed: 27251605 pmcid: 4890037 doi: 10.1038/srep27184
Paoli, A., Celussi, M., Del Negro, P., Fonda Umani, S. & Talarico, L. Ecological advantages from light adaptation and heterotrophic-like behavior in Synechococcus harvested from the Gulf of Trieste (Northern Adriatic Sea). FEMS Microbiol. Ecol. 64 (2), 219–229 (2008).
pubmed: 18336557 doi: 10.1111/j.1574-6941.2008.00459.x
Muñoz-Marín, M. C. Mixotrophy in depth. Nat. Microbiol. 7 (12), 1949–1950 (2022).
pubmed: 36329199 doi: 10.1038/s41564-022-01251-4
Wu, Z. et al. Single-cell Measurements Modelling Reveal. Substantial Org. Carbon Acquisition Prochlorococcus Nat. Microbiol., 7(12): 2068–2077. (2022).
pubmed: 36329198
Yelton, A. P. et al. Global genetic capacity for mixotrophy in marine picocyanobacteria. ISME J. 10 (12), 2946–2957 (2016).
pubmed: 27137127 pmcid: 5148188 doi: 10.1038/ismej.2016.64
Muñoz-Marín, M. C. et al. Mixotrophy in Marine picocyanobacteria: use of organic compounds by Prochlorococcus and Synechococcus. ISME J. 14 (5), 1065–1073 (2020).
pubmed: 32034281 pmcid: 7174365 doi: 10.1038/s41396-020-0603-9
Mary, I. et al. Diel rhythmicity in amino acid uptake byProchlorococcus. Environ. Microbiol. 10 (8), 2124–2131 (2008).
pubmed: 18430019 doi: 10.1111/j.1462-2920.2008.01633.x
Michelou, V. K., Cottrell, M. T. & Kirchman, D. L. Light-stimulated bacterial production and amino acid assimilation by Cyanobacteria and other microbes in the North Atlantic Ocean. Appl. Environ. Microbiol. 73 (17), 5539–5546 (2007).
pubmed: 17630296 pmcid: 2042078 doi: 10.1128/AEM.00212-07
Malmstrom, R. R., Kiene, R. P., Vila, M. & Kirchman, D. L. Dimethylsulfoniopropionate (DMSP) assimilation by Synechococcus in the Gulf of Mexico and northwest Atlantic Ocean. Limnol. Oceanogr. 50 (6), 1924–1931 (2005).
doi: 10.4319/lo.2005.50.6.1924
Vila-Costa, M. et al. Dimethylsulfoniopropionate Uptake Mar. Phytoplankton Sci., 314(5799): 652–654. (2006).
Ruiz-González, C., Simó, R., Vila-Costa, M., Sommaruga, R. & Gasol, J. M. Sunlight modulates the relative importance of heterotrophic bacteria and picophytoplankton in DMSP-sulphur uptake. ISME J. 6 (3), 650–659 (2011).
pubmed: 21955992 pmcid: 3280132 doi: 10.1038/ismej.2011.118
Cuhel, R. L. & Waterbury, J. B. Biochemical composition and short term nutrient incorporation patterns in a unicellular marine cyanobacterium, Synechococcus (WH7803)1. Limnology and Oceanography, 29(2): pp. 370–374. (1984).
Martinez, J., Riera, M., Lalucat, J. & Vives-Rego, J. Thymidine incorporation into algal DNA from axenic cultures of Synechococcus, Chlorella and Tetraselmis. Lett. Appl. Microbiol. 8 (4), 135–138 (1989).
doi: 10.1111/j.1472-765X.1989.tb00258.x
Wang, J. et al. Construction of fungi-microalgae Symbiotic System and Adsorption Study of Heavy Metal ions268 (Separation and Purification Technology, 2021).
Li, T. et al. Creating a synthetic lichen: Mutualistic co-culture of fungi and extracellular polysaccharide-secreting cyanobacterium Nostoc PCC 7413. Algal Res., 45. (2020).
Li, T. et al. Mimicking lichens: incorporation of yeast strains together with sucrose-secreting cyanobacteria improves survival, growth, ROS removal, and lipid production in a stable mutualistic co-culture production platform. Biotechnol. Biofuels, 10(1). (2017).
Jiang, L. et al. Evidence for a mutualistic relationship between the cyanobacteria Nostoc and fungi Aspergilli in different environments. Appl. Microbiol. Biotechnol. 104 (14), 6413–6426 (2020).
pubmed: 32472175 doi: 10.1007/s00253-020-10663-3
Weiss, T. L., Young, E. J. & Ducat, D. C. A synthetic, light-driven consortium of cyanobacteria and heterotrophic bacteria enables stable polyhydroxybutyrate production. Metab. Eng. 44, 236–245 (2017).
pubmed: 29061492 doi: 10.1016/j.ymben.2017.10.009
Zuñiga, C. et al. Synthetic microbial communities of heterotrophs and phototrophs facilitate sustainable growth. Nature Communications, 11(1). (2020).
DiMucci, D., Kon, M., Segrè, D. & Typas, N. Machine learning reveals Missing edges and Putative Interaction mechanisms in Microbial Ecosystem Networks. mSystems, 3(5). (2018).
Zhang, Z. et al. Long-term survival of Synechococcus and heterotrophic Bacteria without external nutrient supply after changes in their relationship from antagonism to Mutualism. mBio, 12(4). (2021).
Nair, S. et al. Inherent tendency of Synechococcus and heterotrophic bacteria for mutualism on long-term coexistence despite environmental interference. Sci. Adv., 8(39). (2022).
Zuñiga, C. et al. Environmental stimuli drive a transition from cooperation to competition in synthetic phototrophic communities. Nat. Microbiol. 4 (12), 2184–2191 (2019).
pubmed: 31591554 doi: 10.1038/s41564-019-0567-6
Bohutskyi, P. et al. Production of lipid-containing algal-bacterial polyculture in wastewater and biomethanation of lipid extracted residues: enhancing methane yield through hydrothermal pretreatment and relieving solvent toxicity through co-digestion. Sci. Total Environ. 653, 1377–1394 (2019).
pubmed: 30759577 doi: 10.1016/j.scitotenv.2018.11.026
Bohutskyi, P. et al. Conversion of stranded waste-stream carbon and nutrients into value-added products via metabolically coupled binary heterotroph-photoautotroph system. Bioresour. Technol. 260, 68–75 (2018).
pubmed: 29614453 doi: 10.1016/j.biortech.2018.02.080
Shannon, P. et al. Cytoscape: a Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Res. 13 (11), 2498–2504 (2003).
pubmed: 14597658 pmcid: 403769 doi: 10.1101/gr.1239303
Morris, J. H. et al. clusterMaker: a multi-algorithm clustering plugin for Cytoscape. BMC Bioinform., 12(1). (2011).
De Perez, L., Alseekh, S., Brotman, Y. & Fernie, A. R. Network-based strategies in metabolomics data analysis and interpretation: from molecular networking to biological interpretation. Expert Rev. Proteomics. 17 (4), 243–255 (2020).
doi: 10.1080/14789450.2020.1766975
Jahagirdar, S. & Saccenti, E. On the use of correlation and MI as a measure of Metabolite—Metabolite Association for Network Differential Connectivity Analysis. Metabolites, 10(4). (2020).
Birer-Williams, C. M. C., Chu, R. K., Anderton, C. R., Wright, E. S. & Bernstein, H. C. SubTap, a versatile 3D printed platform for eavesdropping on extracellular interactions. mSystems, 6(4). (2021).
Jo, C. et al. Construction and modeling of a coculture microplate for real-time measurement of Microbial interactions. mSystems, 8(2). (2023).
Lange, O. L., Green, T. G. A. & Heber, U. Hydration-dependent photosynthetic production of lichens: what do laboratory studies tell us about field performance? J. Exp. Bot. 52 (363), 2033–2042 (2001).
pubmed: 11559739 doi: 10.1093/jexbot/52.363.2033
Osyczka, P. & Myśliwa-Kurdziel, B. The pattern of photosynthetic response and adaptation to changing light conditions in lichens is linked to their ecological range. Photosynth. Res. 157 (1), 21–35 (2023).
pubmed: 36976446 pmcid: 10282042 doi: 10.1007/s11120-023-01015-z
Cowan, D. A., Green, T. G. A. & Wilson, A. T. Lichen Metabolism. 2. Aspects of light and dark physiology. New Phytol. 83 (3), 761–769 (2006).
doi: 10.1111/j.1469-8137.1979.tb02307.x
Abramson, B. W., Kachel, B., Kramer, D. M. & Ducat, D. C. Increased photochemical efficiency in Cyanobacteria via an Engineered sucrose Sink. Plant Cell Physiol. 57 (12), 2451–2460 (2016).
pubmed: 27742883 doi: 10.1093/pcp/pcw169
Pomraning, K. R. et al. Integration of Proteomics and Metabolomics Into the Design, Build, Test, Learn Cycle to Improve 3-Hydroxypropionic Acid Production in Aspergillus pseudoterreus. Frontiers in Bioengineering and Biotechnology, 9. (2021).
Hiller, K. et al. MetaboliteDetector: Comprehensive Analysis Tool for targeted and nontargeted GC/MS based Metabolome Analysis. Anal. Chem. 81 (9), 3429–3439 (2009).
pubmed: 19358599 doi: 10.1021/ac802689c
Pang, Z. et al. Using MetaboAnalyst 5.0 for LC–HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data. Nat. Protoc. 17 (8), 1735–1761 (2022).
pubmed: 35715522 doi: 10.1038/s41596-022-00710-w
Xia, J., Psychogios, N., Young, N. & Wishart, D. MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Res. 37 (Web Server), W652–W660 (2009).
pubmed: 19429898 pmcid: 2703878 doi: 10.1093/nar/gkp356
Team, R. C. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL (2022). https://www.R-project.org/
Kassambara, A. & Mundt, F. Factoextra: Extract and Visualize the Results of Multivariate Data Analyses. R Package Version 1.0.7. (2020). https://CRAN.R-project.org/package=factoextra
Blighe, K., Rana, S. & Lewis, M. EnhancedVolcano: Publication-ready volcano plots with enhanced colouring and labeling. R package version 1.16.0. (2022). https://github.com/kevinblighe/EnhancedVolcano.
Chen, T., Zhang, H., Liu, Y., Liu, Y. X. & Huang, L. EVenn: Easy to create repeatable and editable Venn diagrams and Venn networks online. J. Genet. Genomics. 48 (9), 863–866 (2021).
pubmed: 34452851 doi: 10.1016/j.jgg.2021.07.007
Kanehisa, M., Goto, S., Sato, Y., Furumichi, M. & Tanabe, M. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res. 40 (D1), D109–D114 (2011).
pubmed: 22080510 pmcid: 3245020 doi: 10.1093/nar/gkr988

Auteurs

Pavlo Bohutskyi (P)

Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99354, USA. pavlo.bohutskyi@pnnl.gov.
Department of Biological Systems Engineering, Washington State University, Pullman, WA, 99164, USA. pavlo.bohutskyi@pnnl.gov.

Kyle R Pomraning (KR)

Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.

Jackson P Jenkins (JP)

Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.

Young-Mo Kim (YM)

Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.

Brenton C Poirier (BC)

Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.

Michael J Betenbaugh (MJ)

Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.

Jon K Magnuson (JK)

Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA, 99354, USA.

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