The minimum energy required to build a cell.

Biosynthesis Gibbs energy Group Contribution Algorithm (GCA) Virtual cell

Journal

Scientific reports

ISSN: 2045-2322

Titre abrégé: Sci Rep

Pays: England

ID NLM: 101563288

Informations de publication

Date de publication:
04 Mar 2024

Historique:

received: 04 10 2023

accepted: 11 02 2024

medline: 5 3 2024

pubmed: 5 3 2024

entrez: 4 3 2024

Statut: epublish

Résumé

Understanding the energy requirements for cell synthesis accurately and comprehensively has been a longstanding challenge. We introduce a computational model that estimates the minimum energy necessary to build any cell from its constituent parts. This method combines omics and internal cell compositions from various sources to calculate the Gibbs Free Energy of biosynthesis independently of specific metabolic pathways. Our public tool, Synercell, can be used with other models for minumum species-specific energy estimations in any well-sequenced species. The energy for synthesising the genome, transcriptome, proteome, and lipid bilayer of four cell types: Escherichia coli, Saccharomyces cerevisiae, an average mammalian cell and JCVI-syn3A were estimated. Their modelled minimum synthesis energies at 298 K were

Identifiants

DOI: 10.1038/s41598-024-54303-6 PMID: 38438463

pubmed: 38438463

doi: 10.1038/s41598-024-54303-6

pii: 10.1038/s41598-024-54303-6

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Pagination

5267

Subventions

Organisme : Science and Technology Facilities Council

ID : ST/R000875/1

Informations de copyright

Références

Cockell, C. S. et al. Habitability: A review. Astrobiology 16, 89–117 (2016).

doi: 10.1089/ast.2015.1295

Hoehler, T. An energy balance concept for habitability. Astrobiology 7, 824–838 (2007).

doi: 10.1089/ast.2006.0095

Hoehler, T. M., Bains, W., Davila, A., Parenteau, M. N. & Pohorille, A. Life’s requirements, habitability, and biological potential. in (Meadows, V. S., Des Marais, D. J., Arney, G. N. & Schmidt, B. E. Eds.) Planet. Astrobiol. 37–69 (University of Arizona Press, 2020).

Higgins, P. M. & Cockell, C. S. A bioenergetic model to predict habitability, biomass and biosignatures in astrobiology and extreme conditions. J. R. Soc. Interface 17, 20200588 (2020).

doi: 10.1098/rsif.2020.0588

Stouthamer, A. H. A theoretical study on the amount of ATP required for synthesis of microbial cell material. Antonie van Leeuwenhoek 39, 545–565 (1973).

doi: 10.1007/BF02578899

McCollom, T. & Amend, J. A thermodynamic assessment of energy requirements for biomass synthesis by chemolithoautotrophic micro-organisms in oxic and anoxic environments. Geobiology 3, 135–144 (2005).

doi: 10.1111/j.1472-4669.2005.00045.x

Kleerebezem, R. & Van Loosdrecht, M. C. A generalized method for thermodynamic state analysis of environmental systems. Crit. Rev. Environ. Sci. Technol. 40, 1–54 (2010).

doi: 10.1080/10643380802000974

Amend, J., LaRowe, D., McCollom, T. & Shock, E. The energetics of organic synthesis inside and outside the cell. Philos. Trans. R Soc. B Biol. Sci. 368, 20120255 (2013).

doi: 10.1098/rstb.2012.0255

Schrödinger, E. What is Life? The Physical Aspect of the Living Cell (Cambridge University Press, 1944).

Asimov, I. Life and energy (Avon, 1977). OCLC: 898831983.

Schneider, E. & Kay, J. Life as a manifestation of the second law of thermodynamics. Math. Comput. Model 19, 25–48 (1994).

doi: 10.1016/0895-7177(94)90188-0

Krebs, H., Kornberg, H. & Burton, K. A survey of the energy transformations in living matter. Ergeb. Physiol. 49, 212–298 (1957).

doi: 10.1007/BF02269485

LaRowe, D. & Dick, J. Calculation of the standard molal thermodynamic properties of crystalline peptides. Geochim. Cosmochim Acta 80, 70–91 (2012).

doi: 10.1016/j.gca.2011.11.041

Greinert, T., Vogel, K., Maskow, T. & Held, C. New thermodynamic activity-based approach allows predicting the feasibility of glycolysis. Sci. Rep. 11, 1–9 (2021).

doi: 10.1038/s41598-021-85594-8

Stettner, A. I. & Segrè, D. The cost of efficiency in energy metabolism. Proc. Natl. Acad. Sci. 110, 9629–9630 (2013).

doi: 10.1073/pnas.1307485110

Mavrovouniotis, M. L. Group contributions for estimating standard gibbs energies of formation of biochemical compounds in aqueous solution. Biotechnol. Bioeng. 36, 1070–1082 (1990).

doi: 10.1002/bit.260361013

Dick, J., LaRowe, D. & Helgeson, H. Group additivity calculation of the standard molal thermodynamic properties of aqueous amino acids, polypeptides and unfolded proteins as a function of temperature, pressure and ionization state. Biogeosci. Discuss 2, 1515–1615 (2005).

Noor, E., Haraldsdóttir, H., Milo, R. & Fleming, R. Consistent estimation of gibbs energy using component contributions. PLOS Comput. Biol. 9, e1003098 (2013).

doi: 10.1371/journal.pcbi.1003098

Amend, J. & Helgeson, H. Calculation of the standard molal thermodynamic properties of aqueous biomolecules at elevated temperatures and pressures II. Unfolded proteins. Biophys. Chem. 84, 105–136 (2000).

doi: 10.1016/S0301-4622(00)00116-2

Higgins, P. M. “Modelling extraterrestrial habitability, biomass and biosignatures through the bioenergetic lens”. Ph.D. thesis, University of Edinburgh, Edinburgh, UK (2022).

Higgins, P. M., Glein, C. R. & Cockell, C. S. Instantaneous habitable windows in the parameter space of Enceladus’ Ocean. J. Geophys. Res. Planets. 126, e2021JE006951 (2021).

LaRowe, D. & Amend, J. The energetics of anabolism in natural settings. ISME J. 10, 1285–1295 (2016).

doi: 10.1038/ismej.2015.227

Hutchison, C. A. et al. Design and synthesis of a minimal bacterial genome. Science 351, aad6253. https://doi.org/10.1126/science.aad6253 (2024). Publisher: American Association for the Advancement of Science.

Breuer, M. et al. Essential metabolism for a minimal cell. eLife 8, e36842. https://doi.org/10.7554/eLife.36842 (2019). Publisher: eLife Sciences Publications, Ltd.

Hoehler, T. M. et al. The metabolic rate of the biosphere and its components. Proc. Natl. Acad. Sci. 120, e2303764120 (2023).

doi: 10.1073/pnas.2303764120

Bennett, B. et al. Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli. Nat. Chem. Biol. 5, 593–599 (2009).

doi: 10.1038/nchembio.186

Park, J., Rubin, S., Xu, Y.-F., Amador-Noguez, D. & Shlomi, F. Metabolite concentrations, fluxes, and free energies imply efficient enzyme usage. Nat. Chem. Biol. 12, 482–489 (2016).

doi: 10.1038/nchembio.2077

Takai, K. et al. Cell proliferation at 122 C and isotopically heavy CH4 production by a hyperthermophilic methanogen under high-pressure cultivation. Proc. Natl. Acad. Sci. 105, 10949–10954 (2008).

doi: 10.1073/pnas.0712334105

Battley, E. H. Calculation of the heat of growth of Escherichia coli k-12 on succinic acid. Biotechnol. Bioeng. 37, 334–343 (1991).

doi: 10.1002/bit.260370407

Amend, J. & Helgeson, H. Calculation of the standard molal thermodynamic properties of aqueous biomolecules at elevated temperatures and pressures part1l-α-amino acids. J. Chem. Soc. Faraday Trans. 93, 1927–1941 (1997).

doi: 10.1039/a608126f

Dickson, K., Burns, C. & Richardson, J. Determination of the free-energy change for repair of a dna phosphodiester bond. J. Biol. Chem. 275, 15828–15831 (2000).

doi: 10.1074/jbc.M910044199

Petrache, H. I. 5.2 lipid bilayer structure. In Egelman, E. H. (ed.) Comprehensive Biophys. 3–15 (2012).

Lynch, M. & Marinov, G. K. The bioenergetic costs of a gene. Proc. Natl. Acad. Sci. USA 112, 15690–15695 (2015).

doi: 10.1073/pnas.1514974112

Lynch, M. & Marinov, G. K. Membranes, energetics, and evolution across the prokaryote-eukaryote divide. eLife. 6, e20437 (2017).

doi: 10.7554/eLife.20437

Engelbrecht, K. C., Putonti, C., Koenig, D. W. & Wolfe, A. J. Draft genome sequence of Escherichia coli k-12 (ATCC 29425). Genome Announc. 5, e00574-17 (2017).

doi: 10.1128/genomeA.00574-17

Jones, B., Stekel, D., Rowe, J. & Fernando, C. Is there a liquid state machine in the bacterium Escherichia coli? in 2007 IEEE Symposium on Artificial Life, 187–191 (IEEE, 2007).

Tiessen, A., Pérez-Rodríguez, P. & Delaye-Arredondo, L. J. Mathematical modeling and comparison of protein size distribution in different plant, animal, fungal and microbial species reveals a negative correlation between protein size and protein number, thus providing insight into the evolution of proteomes. BMC Res. Notes 5, 85 (2012).

doi: 10.1186/1756-0500-5-85

Akashi, H. & Gojobori, T. Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis. Proc. Natl. Acad. Sci. USA 99, 3695–3700 (2002).

doi: 10.1073/pnas.062526999

Prats, R. & de Pedro, M. A. Normal growth and division of Escherichia coli with a reduced amount of murein. J. Bacteriol. 171, 3740–3745 (1989).

doi: 10.1128/jb.171.7.3740-3745.1989

Niebel, B., Leupold, S. & Heinemann, M. An upper limit on gibbs energy dissipation governs cellular metabolism. Nat. Metab. 1, 125–132 (2019).

doi: 10.1038/s42255-018-0006-7

Feist, A. M. & Palsson, B. O. The biomass objective function. Curr. Opin. Microbiol. 13, 344–349 (2010).

doi: 10.1016/j.mib.2010.03.003

Yuan, H., Cheung, C. Y. M., Hilbers, P. A. J. & van Riel, N. A. W. Flux balance analysis of plant metabolism: The effect of biomass composition and model structure on model predictions. Front. Plant Sci. 7, 1–13 (2016).

doi: 10.3389/fpls.2016.00537

von Kamp, A. & Klamt, S. Balancing biomass reaction stoichiometry and measured fluxes in flux balance analysis. Bioinformatics 39, btad600 (2023).

Varma, A., Boesch, B. & Palsson, B. Stoichiometric interpretation of Escherichia coli glucose catabolism under various oxygenation rates. Appl. Environ. Microbiol. 59, 2465–2473 (1993).

doi: 10.1128/aem.59.8.2465-2473.1993

Orth, J. D., Thiele, I. & Palsson, B. O. What is flux balance analysis?. Nat. Biotechnol. 28, 245–248 (2010).

doi: 10.1038/nbt.1614

Monk, J. M. et al. iML1515, a knowledgebase that computes escherichia coli traits. Nat. Biotechnol. 35, 904–908 (2017). Number: 10 Publisher: Nature Publishing Group.

Doerr, A. Sequencing for carbohydrates. Nat. Methods 14, 1126–1126 (2017).

doi: 10.1038/nmeth.4528

Kalwarczyk, T., Tabaka, M. & Holyst, R. Biologistics-diffusion coefficients for complete proteome of Escherichia coli. Bioinformatics 28, 2971–2978 (2012).

doi: 10.1093/bioinformatics/bts537

Capolupo, L. Single-cell lipidomics reveals the organizing principle of cell fate decision. Nat. Rev. Mol. Cell Biol. 24, 377–377 (2023).

doi: 10.1038/s41580-023-00595-x

Johnson, J. W., Oelkers, E. H. & Helgeson, H. C. SUPCRT92: A software package for calculating the standard molal thermodynamic properties of minerals, gases, aqueous species, and reactions from 1 to 5000 bar and 0 to 1000[Formula: see text]c. Comput. Geosci. 18, 899–947 (1992).

doi: 10.1016/0098-3004(92)90029-Q

Booth, I. The regulation of intracellular pH in bacteria. Novartis Foundation Symp. 221, 19–37 (1999).

Boron, W. Regulation of intracellular pH. Adv. Physiol. Educ. 28, 160–179 (2004).

doi: 10.1152/advan.00045.2004

Cockell, C. S. et al. Sustained and comparative habitability beyond earth. Nat. Astron. 1–9 (2023).

Rouphael, Y. et al. Reducing energy requirements in future bioregenerative life support systems (BLSSs): Performance and bioactive composition of diverse lettuce genotypes grown under optimal and suboptimal light conditions. Front. Plant Sci. 10 (2019).

Ra, K., Shiotsu, F., Abe, J. & Morita, S. Biomass yield and nitrogen use efficiency of cellulosic energy crops for ethanol production. Biomass Bioenergy 37, 330–334 (2012).

doi: 10.1016/j.biombioe.2011.12.047

Wallace, D. C. Bioenergetics, the origins of complexity, and the ascent of man. Proc. Natl. Acad. Sci. 107, 8947–8953 (2010).

doi: 10.1073/pnas.0914635107

Xu, C., Hu, S. & Chen, X. Artificial cells: From basic science to applications. Mater. Today (Kidlington) 19, 516–532 (2016).

doi: 10.1016/j.mattod.2016.02.020

Robinson, K. J. et al. Quantifying the extent of amide and peptide bond synthesis across conditions relevant to geologic and planetary environments. Geochimica et Cosmochimica Acta 300, 318–332 (2021).

doi: 10.1016/j.gca.2021.01.038

Lever, M. et al. Life under extreme energy limitation: A synthesis of laboratory-and field-based investigations. FEMS Microbiol. Rev. 39, 688–728 (2015).

doi: 10.1093/femsre/fuv020

Tijhuis, L., Van Loosdrecht, M. & Heijnen, J. A thermodynamically based correlation for maintenance gibbs energy requirements in aerobic and anaerobic chemotrophic growth. Biotechnol. Bioeng. 42, 509–519 (1993).

doi: 10.1002/bit.260420415

Mavrovouniotis, M. L. Estimation of standard gibbs energy changes of biotransformations. J. Biol. Chem. 266, 14440–14445 (1991).

doi: 10.1016/S0021-9258(18)98705-3

Leal, A. Reaktoro, a unified open-source framework for modeling chemically reactive systems. https://reaktoro.org (2015).

Shock, E., Oelkers, E., Johnson, J., Sverjensky, D. & Helgeson, H. Calculation of the thermodynamic properties of aqueous species at high pressures and temperatures. effective electrostatic radii, dissociation constants and standard partial molal properties to 1000 [Formula: see text]c and 5 kbar. J. Chem. Soc. Faraday Trans. 88, 803–826 (1992).

Van Meer, G., Voelker, D. & Feigenson, G. Membrane lipids: where they are and how they behave 60. Nat. Rev. Mol. Cell Biol. 9, 112–124 (2008).

doi: 10.1038/nrm2330

Sohlenkamp, C., López-Lara, I. & Geiger, O. Biosynthesis of phosphatidylcholine in bacteria. Prog. Lipid Res. 42, 115–162 (2003).

doi: 10.1016/S0163-7827(02)00050-4

Conde-Alvarez, R. et al. Synthesis of phosphatidylcholine, a typical eukaryotic phospholipid, is necessary for full virulence of the intracellular bacterial parasite brucella abortus. Cell Microbiol. 8, 1322–1335 (2006).

doi: 10.1111/j.1462-5822.2006.00712.x

Henry, C. S., Jankowski, M. D., Broadbelt, L. J. & Hatzimanikatis, V. Genome-scale thermodynamic analysis of Escherichia coli metabolism. Biophys. J. 90, 1453–1461 (2006).

doi: 10.1529/biophysj.105.071720

Jankowski, M. D., Henry, C. S., Broadbelt, L. J. & Hatzimanikatis, V. Group contribution method for thermodynamic analysis of complex metabolic networks. Biophys. J. 95, 1487–1499 (2008).

doi: 10.1529/biophysj.107.124784

Geopig slop files [slop07]. Zenodo, v1. https://doi.org/10.5281/zenodo.2630820 (2019).