#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Hydrogenotrophic methanogens of the mammalian gut: Functionally similar, thermodynamically different—A modelling approach


Autoři: Rafael Muñoz-Tamayo aff001;  Milka Popova aff002;  Maxence Tillier aff002;  Diego P. Morgavi aff002;  Jean-Pierre Morel aff003;  Gérard Fonty aff003;  Nicole Morel-Desrosiers aff003
Působiště autorů: UMR Modélisation Systémique Appliquée aux Ruminants, INRA, AgroParisTech, Université Paris-Saclay, Paris, France aff001;  Institute National de la Recherche Agronomique, UMR1213 Herbivores, Clermont Université, VetAgro Sup, UMR Herbivores, Clermont-Ferrand, France aff002;  Université Clermont Auvergne, CNRS, LMGE, Clermont-Ferrand, France aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0226243

Souhrn

Methanogenic archaea occupy a functionally important niche in the gut microbial ecosystem of mammals. Our purpose was to quantitatively characterize the dynamics of methanogenesis by integrating microbiology, thermodynamics and mathematical modelling. For that, in vitro growth experiments were performed with pure cultures of key methanogens from the human and ruminant gut, namely Methanobrevibacter smithii, Methanobrevibacter ruminantium and Methanobacterium formicium. Microcalorimetric experiments were performed to quantify the methanogenesis heat flux. We constructed an energetic-based mathematical model of methanogenesis. Our model captured efficiently the dynamics of methanogenesis with average concordance correlation coefficients of 0.95 for CO2, 0.98 for H2 and 0.97 for CH4. Together, experimental data and model enabled us to quantify metabolism kinetics and energetic patterns that were specific and distinct for each species despite their use of analogous methane-producing pathways. Then, we tested in silico the interactions between these methanogens under an in vivo simulation scenario using a theoretical modelling exercise. In silico simulations suggest that the classical competitive exclusion principle is inapplicable to gut ecosystems and that kinetic information alone cannot explain gut ecological aspects such as microbial coexistence. We suggest that ecological models of gut ecosystems require the integration of microbial kinetics with nonlinear behaviours related to spatial and temporal variations taking place in mammalian guts. Our work provides novel information on the thermodynamics and dynamics of methanogens. This understanding will be useful to construct new gut models with enhanced prediction capabilities and could have practical applications for promoting gut health in mammals and mitigating ruminant methane emissions.

Klíčová slova:

Carbon dioxide – Fermentation – Hydrogen – Mathematical models – Methane – Methanogens – Ribosomal RNA – Thermodynamics


Zdroje

1. Miller TL, Wolin MJ, Hongxue Z, Bryant MP. Characteristics of methanogens isolated from bovine rumen. Appl Environ Microbiol. 1986;51: 201–202. 3954338

2. Dridi B, Fardeau ML, Ollivier B, Raoult D, Drancourt M. Methanomassiliicoccus luminyensis gen. nov., sp. nov., a methanogenic archaeon isolated from human faeces. Int J Syst Evol Microbiol. 2012;62: 1902–1907. doi: 10.1099/ijs.0.033712-0 22859731

3. Paul K, Nonoh JO, Mikulski L, Brune A. “Methanoplasmatales,” thermoplasmatales-related archaea in termite guts and other environments, are the seventh order of methanogens. Appl Environ Microbiol. 2012;78: 8245–8253. doi: 10.1128/AEM.02193-12 23001661

4. Dridi B, Raoult D, Drancourt M. Archaea as emerging organisms in complex human microbiomes. Anaerobe. 2011;17: 56–63. doi: 10.1016/j.anaerobe.2011.03.001 21420503

5. Carberry CA, Waters SM, Kenny DA, Creevey CJ. Rumen methanogenic genotypes differ in abundance according to host residual feed intake phenotype and diet type. Appl Env Microbiol. 2014;80: 586–594.

6. Borrel G, McCann A, Deane J, Neto MC, Lynch DB, Brugère JF, et al. Genomics and metagenomics of trimethylamine-utilizing Archaea in the human gut microbiome. ISME J. 2017;11: 2059–2074. doi: 10.1038/ismej.2017.72 28585938

7. Bang C, Weidenbach K, Gutsmann T, Heine H, Schmitz RA. The intestinal archaea Methanosphaera stadtmanae and Methanobrevibacter smithii activate human dendritic cells. PLoS One. 2014;9: e99411. doi: 10.1371/journal.pone.0099411 24915454

8. Ghavami SB, Rostami E, Sephay AA, Shahrokh S, Balaii H, Aghdaei HA, et al. Alterations of the human gut Methanobrevibacter smithii as a biomarker for inflammatory bowel diseases. Microb Pathog. 2018;117: 285–289. doi: 10.1016/j.micpath.2018.01.029 29477743

9. Mathur R, Barlow GM. Obesity and the microbiome. Expert Review of Gastroenterology and Hepatology. 2015. pp. 1087–1099. doi: 10.1586/17474124.2015.1051029 26082274

10. Hook SE, Wright A-DG, McBride BW. Methanogens: methane producers of the rumen and mitigation strategies. Archaea. 2010; 945785. doi: 10.1155/2010/945785 21253540

11. Poulsen M, Schwab C, Jensen BB, Engberg RM, Spang A, Canibe N, et al. Methylotrophic methanogenic Thermoplasmata implicated in reduced methane emissions from bovine rumen. Nat Commun. 2013;4: 1428. doi: 10.1038/ncomms2432 23385573

12. Jarvis GN, Strömpl C, Burgess DM, Skillman LC, Moore ERB, Joblin KN. Isolation and identification of ruminal methanogens from grazing cattle. Curr Microbiol. 2000;40: 327–332. doi: 10.1007/s002849910065 10706664

13. Friedman N, Jami E, Mizrahi I. Compositional and functional dynamics of the bovine rumen methanogenic community across different developmental stages. Environ Microbiol. 2017;19: 3365–3373. doi: 10.1111/1462-2920.13846 28654196

14. Hansen EE, Lozupone CA, Rey FE, Wu M, Guruge JL, Narra A, et al. Pan-genome of the dominant human gut-associated archaeon, Methanobrevibacter smithii, studied in twins. Proc Natl Acad Sci. 2011;108: 4599–4606. doi: 10.1073/pnas.1000071108 21317366

15. Thauer RK, Kaster AK, Seedorf H, Buckel W, Hedderich R. Methanogenic archaea: Ecologically relevant differences in energy conservation. Nat Rev Microbiol. 2008;6: 579–591. doi: 10.1038/nrmicro1931 18587410

16. Morgavi DP, Forano E, Martin C, Newbold CJ. Microbial ecosystem and methanogenesis in ruminants. Animal. 2010;4: 1024–1036. doi: 10.1017/S1751731110000546 22444607

17. Jackson BE, McInerney MJ. Anaerobic microbial metabolism can proceed close to thermodynamic limits. Nature. 2002;415: 454–456. doi: 10.1038/415454a 11807560

18. Gonzalez-Cabaleiro R, Lema JM, Rodriguez J, Kleerebezem R. Linking thermodynamics and kinetics to assess pathway reversibility in anaerobic bioprocesses. Energy Environ Sci. 2013;6: 3780–3789.

19. Muñoz-Tamayo R, Laroche B, Walter E, Doré J, Leclerc M. Mathematical modelling of carbohydrate degradation by human colonic microbiota. J Theor Biol. 2010;266: 189–201. doi: 10.1016/j.jtbi.2010.05.040 20561534

20. Van Wey AS, Lovatt SJ, Roy NC, Shorten PR. Determination of potential metabolic pathways of human intestinal bacteria by modeling growth kinetics from cross-feeding dynamics. Food Res Int. 2016;88: 207–216.

21. Shoaie S, Ghaffari P, Kovatcheva-Datchary P, Mardinoglu A, Sen P, Pujos-Guillot E, et al. Quantifying Diet-Induced Metabolic Changes of the Human Gut Microbiome. Cell Metab. 2015;22: 320–331. doi: 10.1016/j.cmet.2015.07.001 26244934

22. Kettle H, Louis P, Holtrop G, Duncan SH, Flint HJ. Modelling the emergent dynamics and major metabolites of the human colonic microbiota. Environ Microbiol. 2015;17: 1615–1630. doi: 10.1111/1462-2920.12599 25142831

23. Heijnen JJ, Dijken JP. In search of a thermodynamic description of biomass yields for the chemotrophic growth of microorgansims. Biotechnol Bioengeneering. 1992;39: 833–852.

24. Kleerebezem R, Van Loosdrecht MCM. A Generalized Method for Thermodynamic State Analysis of Environmental Systems. Crit Rev Environ Sci Technol. 2010;40: 1–54.

25. Hoh CY, Cord-Ruwisch R. A practical kinetic model that considers endproduct inhibition in anaerobic digestion processes by including the equilibrium constant. Biotechnol Bioeng. 1996;51: 597–604. doi: 10.1002/(SICI)1097-0290(19960905)51:5<597::AID-BIT12>3.0.CO;2-F 18629824

26. Desmond-Le Quemener E, Bouchez T. A thermodynamic theory of microbial growth. Isme J. 2014;8: 1747–1751. doi: 10.1038/ismej.2014.7 24522260

27. Großkopf T, Soyer OS. Microbial diversity arising from thermodynamic constraints. ISME J. 2016;10: 2725–2733. doi: 10.1038/ismej.2016.49 27035705

28. Kohn R a, Boston RC. The Role of Thermodynamics in Controlling Rumen Metabolism. Model Nutr Util Farm Anim. 2000; 11–24.

29. Ungerfeld EM. A theoretical comparison between two ruminal electron sinks. Front Microbiol. 2013;4.

30. Janssen PH. Influence of hydrogen on rumen methane formation and fermentation balances through microbial growth kinetics and fermentation thermodynamics. Anim Feed Sci Technol. 2010;160: 1–22.

31. Van Lingen HJ, Plugge CM, Fadel JG, Kebreab E, Bannink A, Dijkstra J. Thermodynamic driving force of hydrogen on rumen microbial metabolism: A theoretical investigation. PLoS One. 2016;11: e0161362. doi: 10.1371/journal.pone.0161362 27783615

32. Offner A, Sauvant D. Thermodynamic modeling of ruminal fermentations. 2006;55: 343–365.

33. Ghimire S, Gregorini P, Hanigan MD. Evaluation of predictions of volatile fatty acid production rates by the Molly cow model. J Dairy Sci. 2014;97: 354–362. doi: 10.3168/jds.2012-6199 24268399

34. Wolfe RS. Techniques for cultivating methanogens. Methods Enzymol. 2011;494: 1–22. doi: 10.1016/B978-0-12-385112-3.00001-9 21402207

35. Ohene-Adjei S, Teather RM, Ivan M, Forster RJ. Postinoculation protozoan establishment and association patterns of methanogenic archaea in the ovine rumen. Appl Environ Microbiol. 2007;73: 4609–4618. doi: 10.1128/AEM.02687-06 17513586

36. Popova M, Martin C, Eugene M, Mialon MM, Doreau M, Morgavi DP. Effect of fibre- and starch-rich finishing diets on methanogenic Archaea diversity and activity in the rumen of feedlot bulls. Anim Feed Sci Technol. 2011;166–67: 113–121.

37. Bricheux G, Bonnet JL, Bohatier J, Morel JP, Morel-Desrosiers N. Microcalorimetry: a powerful and original tool for tracking the toxicity of a xenobiotic on Tetrahymena pyriformis. Ecotoxicol Env Saf. 2013;98: 88–94.

38. Braissant O, Bonkat G, Wirz D, Bachmann A. Microbial growth and isothermal microcalorimetry: Growth models and their application to microcalorimetric data. Thermochim Acta. 2013;555: 64–71.

39. Muñoz-Tamayo R, Giger-Reverdin S, Sauvant D. Mechanistic modelling of in vitro fermentation and methane production by rumen microbiota. Anim Feed Sci Technol. 2016;220: 1–21.

40. Batstone DJ, Keller J, Angelidaki I, Kalyuzhnyi S V, Pavlostathis SG, Rozzi A, et al. Anaerobic Digestion Model No.1 (ADM1). IWA Task Group for Mathematical Modelling of Anaerobic Digestion Processes. IWA Publishing, London; 2002.

41. Pavlostathis SG, Miller TL, Wolin MJ. Cellulose Fermentation by Continuous Cultures of Ruminococcus-Albus and Methanobrevibacter-Smithii. Appl Microbiol Biotechnol. 1990;33: 109–116.

42. Schauer NL, Ferry JG. Metabolism of formate in Methanobacterium formicicum. J Bacteriol. 1980;142: 800–807. 6769911

43. Haydock AK, Porat I, Whitman WB, Leigh JA. Continuous culture of Methanococcus maripaludis under defined nutrient conditions. FEMS Microbiol Lett. 2004.

44. Walter E, Pronzato L. Identification of Parametric Models from Experimental Data. Springer, London; 1997.

45. Muñoz-Tamayo R, Puillet L, Daniel JB, Sauvant D, Martin O, Taghipoor M, et al. Review: To be or not to be an identifiable model. Is this a relevant question in animal science modelling? Animal. 2018;12: 701–712. doi: 10.1017/S1751731117002774 29096725

46. Bellu G, Saccomani MP, Audoly S, D’Angio L. DAISY: A new software tool to test global identifiability of biological and physiological systems. Comput Methods Programs Biomed. 2007;88: 52–61. doi: 10.1016/j.cmpb.2007.07.002 17707944

47. Vanrolleghem PA, Vandaele M, Dochain D. Practical identifiability of a biokinetic model of activated-sludge respiration. Water Res. 1995;29: 2561–2570.

48. Muñoz-Tamayo R, Laroche B, Leclerc M, Walter E. IDEAS: A parameter identification toolbox with symbolic analysis of uncertainty and its application to biological modelling. IFAC Proceedings Volumes. 2009. pp. 1271–1276.

49. Lin LI. A concordance correlation-coefficient to evaluate reproducibility. Biometrics. 1989;45: 255–268. 2720055

50. Schill NA, Liu JS, von Stockar U. Thermodynamic analysis of growth of Methanobacterium thermoautotrophicum. Biotechnol Bioeng. 1999;64: 74–81. doi: 10.1002/(sici)1097-0290(19990705)64:1<74::aid-bit8>3.0.co;2-3 10397841

51. Liu JS, Marison IW, von Stockar U. Microbial growth by a net heat up-take: A calorimetric and thermodynamic study on acetotrophic methanogenesis by Methanosarcina barkeri. Biotechnol Bioeng. 2001;75: 170–180. doi: 10.1002/bit.1176 11536139

52. Ruiz T, Bec A, Danger M, Koussoroplis A, Aguer J, Morel J, et al. A microcalorimetric approach for investigating stoichiometric constraints on the standard metabolic rate of a small invertebrate. Ecol Lett. 2018;21: 1714–1722. doi: 10.1111/ele.13137 30151853

53. Janssen PH, Kirs M. Structure of the archaeal community of the rumen. Appl Environ Microbiol. 2008;74: 3619–3625. doi: 10.1128/AEM.02812-07 18424540

54. von Stockar U, Larsson C, Marison IW. Calorimetry and energetic efficiencies in aerobic and anaerobic microbial growth. Pure Appl Chem. 1993;65: 1889–1892.

55. Von Stockar U, Liu JS. Does microbial life always feed on negative entropy? Thermodynamic analysis of microbial growth. Biochim Biophys Acta—Bioenerg. 1999;1412: 191–211.

56. Hardin G. The competitive exclusion principle. Science (80-). 1960;131: 1292–1297.

57. Lynch TA, Wang Y, van Brunt B, Pacheco D, Janssen PH. Modelling thermodynamic feedback on the metabolism of hydrogenotrophic methanogens. J Theor Biol. 2019;477: 14–23. doi: 10.1016/j.jtbi.2019.05.018 31150665

58. Udén P, Rounsaville TR, Wiggans GR, Van Soest PJ. The measurement of liquid and solid digesta retention in ruminants, equines and rabbits given timothy (Phleum pratense) hay. Br J Nutr. 1982;48: 329–339. doi: 10.1079/bjn19820117 6810917

59. Ng F, Kittelmann S, Patchett ML, Attwood GT, Janssen PH, Rakonjac J, et al. An adhesin from hydrogen-utilizing rumen methanogen Methanobrevibacter ruminantium M1 binds a broad range of hydrogen-producing microorganisms. Env Microbiol. 2016;18: 3010–3021.

60. Samuel BS, Hansen EE, Manchester JK, Coutinho PM, Henrissat B, Fulton R, et al. Genomic and metabolic adaptations of Methanobrevibacter smithii to the human gut. Proc Natl Acad Sci. 2007;104: 10643–10648. doi: 10.1073/pnas.0704189104 17563350

61. Kelly WJ, Leahy SC, Li D, Perry R, Lambie SC, Attwood GT, et al. The complete genome sequence of the rumen methanogen Methanobacterium formicicum BRM9. Stand Genomic Sci. 2014;9: 15. doi: 10.1186/1944-3277-9-15 25780506

62. Hutchinson GE. The paradox of the plankton. Am Nat. 1961;95: 137–145.

63. Bernalier A, Lelait M, Rochet V, Grivet JP, Gibson GR, Durand M. Acetogenesis from H2 and CO2 by methane- and non-methane-producing human colonic bacterial communities. FEMS Microbiol Ecol. 1996;19: 193–202.

64. Nava GM, Carbonero F, Croix JA, Greenberg E, Gaskins HR. Abundance and diversity of mucosa-associated hydrogenotrophic microbes in the healthy human colon. ISME J. 2012;6: 57–70.

65. Flint HJ, Duncan SH, Scott KP. Interactions and competition within the microbial community of the human colon : links between diet and health. Environ Microbiol. 2007;9: 1101–1111. doi: 10.1111/j.1462-2920.2007.01281.x 17472627

66. Huws SA, Creevey CJ, Oyama LB, Mizrahi I, Denman SE, Popova M, et al. Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future. Front Microbiol. 2018;9: 2161. doi: 10.3389/fmicb.2018.02161 30319557

67. Pfeiffer T, Schuster S, Bonhoeffer S. Cooperation and competition in the evolution of ATP-producing Pathways. Science (80-). 2001;292: 50–507.

68. Vandermeer J, Evans MA, Foster P, Höök T, Reiskind M, Wund M. Increased competition may promote species coexistence. Proc Natl Acad Sci. 2002;99: 8731–8736. doi: 10.1073/pnas.142073599 12070354

69. MacLean RC, Gudelj I. Resource competition and social conflict in experimental populations of yeast. Nature. 2006;441: 498–501. doi: 10.1038/nature04624 16724064

70. Rapaport A, Dochain D, Harmand J. Long run coexistence in the chemostat with multiple species. J Theor Biol. 2009;257: 252–259. doi: 10.1016/j.jtbi.2008.11.015 19111560

71. Grognard F, Masci P, Benoît E, Bernard O. Competition between phytoplankton and bacteria: exclusion and coexistence. J Math Biol. 2015;70: 959–1006. doi: 10.1007/s00285-014-0783-x 24748458

72. Hsu SB, Hubbell S, Waltman P. A mathematical theory for single-nutrient competition in continuous cultures of micro-organisms. SIAM J Appl Math. 1977;32: 366–383.

73. Widder S, Allen RJ, Pfeiffer T, Curtis TP, Wiuf C, Sloan WT, et al. Challenges in microbial ecology: Building predictive understanding of community function and dynamics. ISME J. 2016;10: 2557–2568. doi: 10.1038/ismej.2016.45 27022995

74. Muñoz-Tamayo R, Ramirez Agudelo JF, Dewhurst RJ, Miller G, Vernon T, Kettle H. A parsimonious software sensor for estimating the individual dynamic pattern of methane emissions from cattle. Animal. 2019;13: 1180–1187. doi: 10.1017/S1751731118002550 30333069

75. Ou JZ, Yao CK, Rotbart A, Muir JG, Gibson PR, Kalantar-zadeh K. Human intestinal gas measurement systems: In vitro fermentation and gas capsules. Trends Biotechnol. 2015;33: 208–213. doi: 10.1016/j.tibtech.2015.02.002 25772639


Článek vyšel v časopise

PLOS One


2019 Číslo 12
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

KOST
Koncepce osteologické péče pro gynekology a praktické lékaře
nový kurz
Autoři: MUDr. František Šenk

Sekvenční léčba schizofrenie
Autoři: MUDr. Jana Hořínková

Hypertenze a hypercholesterolémie – synergický efekt léčby
Autoři: prof. MUDr. Hana Rosolová, DrSc.

Svět praktické medicíny 5/2023 (znalostní test z časopisu)

Imunopatologie? … a co my s tím???
Autoři: doc. MUDr. Helena Lahoda Brodská, Ph.D.

Všechny kurzy
Kurzy Podcasty Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#