Inference of Network Dynamics and Metabolic Interactions in the Gut Microbiome

PLoS Computational Biology

Volumn 11, Issue 6, 2015, Pages

  Steinway, Steven N ^a,b   Biggs, Matthew B ^c   Loughran, Thomas P ^b   Papin, Jason A ^c   Albert, Reka ^d  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF VIRGINIA   (United States)

^c University of Virginia   (United States)

^d PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIBIOTICS; GENES; METABOLISM; REPAIR;

ANTIBIOTIC TREATMENT; CLINDAMYCIN; DYNAMIC INTERACTION; GENOME-SCALE METABOLIC NETWORK; METABOLIC INTERACTIONS; METABOLIC NETWORK RECONSTRUCTION; MICROBIAL INTERACTIONS; MICROBIOME; NETWORK DYNAMICS; NOVEL METHODOLOGY;

PROBIOTICS;

CLINDAMYCIN; ANTIINFECTIVE AGENT;

ARTICLE; BACTERIAL GENOME; BACTERIUM IDENTIFICATION; CLOSTRIDIUM DIFFICILE INFECTION; DATA ANALYSIS; DYNAMIC NETWORK MODEL; GENOME ANALYSIS; GROWTH RATE; HUMAN; IN VITRO STUDY; INTESTINE FLORA; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; METAGENOMICS; MICROBIAL COMMUNITY; MICROBIAL INTERACTION NETWORK; ORGANISMAL INTERACTION; PEPTOCLOSTRIDIUM DIFFICILE; POPULATION ABUNDANCE; PREDICTION; PROCESS DEVELOPMENT; VALIDATION PROCESS; ALGORITHM; ANIMAL; CHEMISTRY; CLOSTRIDIUM INFECTION; COCULTURE; COMPUTER SIMULATION; GASTROINTESTINAL TRACT; METABOLISM; MICROBIOLOGY; MICROFLORA; MOUSE; PHYSIOLOGY;

ALGORITHMS; ANIMALS; ANTI-BACTERIAL AGENTS; CLINDAMYCIN; CLOSTRIDIUM DIFFICILE; CLOSTRIDIUM INFECTIONS; COCULTURE TECHNIQUES; COMPUTER SIMULATION; GASTROINTESTINAL MICROBIOME; GASTROINTESTINAL TRACT; METABOLIC NETWORKS AND PATHWAYS; MICE; MICROBIOTA;

EID: 84953319558     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1004338     Document Type: Article

References (69)

1. Gordon JI, (2012) Honor thy gut symbionts redux. Science 336: 1251–1253. doi: 10.1126/science.1224686 22674326
2. Bergman EN, (1990) Energy contributions of volatile fatty acids from the gastrointestinal tract in various species. Physiol Rev 70: 567–590. 2181501
3. Rosenberg E, Sharon G, Atad I, Zilber-Rosenberg I, (2010) The evolution of animals and plants via symbiosis with microorganisms. Environ Microbiol Rep 2: 500–506. doi: 10.1111/j.1758-2229.2010.00177.x 23766221
4. Kau AL, Ahern PP, Griffin NW, Goodman AL, Gordon JI, (2011) Human nutrition, the gut microbiome and the immune system. Nature 474: 327–336. doi: 10.1038/nature10213 21677749
5. Faith JJ, Guruge JL, Charbonneau M, Subramanian S, Seedorf H, et al. (2013) The long-term stability of the human gut microbiota. Science 341: 1237439. doi: 10.1126/science.1237439 23828941
6. Reeves AE, Theriot CM, Bergin IL, Huffnagle GB, Schloss PD, et al. (2011) The interplay between microbiome dynamics and pathogen dynamics in a murine model of Clostridium difficile Infection. Gut Microbes 2: 145–158. 21804357
7. Bartlett JG, Moon N, Chang TW, Taylor N, Onderdonk AB, (1978) Role of Clostridium difficile in antibiotic-associated pseudomembranous colitis. Gastroenterology 75: 778–782. 700321
8. George WL, Rolfe RD, Finegold SM, (1982) Clostridium difficile and its cytotoxin in feces of patients with antimicrobial agent-associated diarrhea and miscellaneous conditions. J Clin Microbiol 15: 1049–1053. 7107838
9. Meyers S, Mayer L, Bottone E, Desmond E, Janowitz HD, (1981) Occurrence of Clostridium difficile toxin during the course of inflammatory bowel disease. Gastroenterology 80: 697–670. 7202942
10. Chang JY, Antonopoulos DA, Kalra A, Tonelli A, Khalife WT, et al. (2008) Decreased diversity of the fecal Microbiome in recurrent Clostridium difficile-associated diarrhea. J Infect Dis 197: 435–438. doi: 10.1086/525047 18199029
11. Aroniadis OC, Brandt LJ, (2013) Fecal microbiota transplantation: past, present and future. Curr Opin Gastroenterol 29: 79–84. doi: 10.1097/MOG.0b013e32835a4b3e 23041678
12. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, et al. (2006) An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444: 1027–1031. 17183312
13. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, et al. (2009) A core gut microbiome in obese and lean twins. Nature 457: 480–484. doi: 10.1038/nature07540 19043404
14. Qin J, Li Y, Cai Z, Li S, Zhu J, et al. (2012) A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490: 55–60. doi: 10.1038/nature11450 23023125
15. Hsiao EY, McBride SW, Hsien S, Sharon G, Hyde ER, et al. (2013) Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders. Cell 155: 1451–1463. doi: 10.1016/j.cell.2013.11.024 24315484
16. Dapito DH, Mencin A, Gwak GY, Pradere JP, Jang MK, et al. (2012) Promotion of hepatocellular carcinoma by the intestinal microbiota and TLR4. Cancer Cell 21: 504–516. doi: 10.1016/j.ccr.2012.02.007 22516259
17. Reddy BS, Watanabe K, (1978) Effect of intestinal microflora on 2,2'-dimethyl-4-aminobiphenyl-induced carcinogenesis in F344 rats. J Natl Cancer Inst 61: 1269–1271. 280712
18. Bonneau R, Facciotti MT, Reiss DJ, Schmid AK, Pan M, et al. (2007) A predictive model for transcriptional control of physiology in a free living cell. Cell 131: 1354–1365. 18160043
19. Schmid AK, Reiss DJ, Kaur A, Pan M, King N, et al. (2007) The anatomy of microbial cell state transitions in response to oxygen. Genome Res 17: 1399–1413. 17785531
20. Thakar J, Pilione M, Kirimanjeswara G, Harvill ET, Albert R, (2007) Modeling systems-level regulation of host immune responses. PLoS Comput Biol 3: e109. 17559300
21. Saez-Rodriguez J, Alexopoulos LG, Epperlein J, Samaga R, Lauffenburger DA, et al. (2009) Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction. Mol Syst Biol 5: 331. doi: 10.1038/msb.2009.87 19953085
22. Zhang R, Shah MV, Yang J, Nyland SB, Liu X, et al. (2008) Network model of survival signaling in large granular lymphocyte leukemia. Proc Natl Acad Sci U S A 105: 16308–16313. doi: 10.1073/pnas.0806447105 18852469
23. Saadatpour A, Wang RS, Liao A, Liu X, Loughran TP, et al. (2011) Dynamical and structural analysis of a T cell survival network identifies novel candidate therapeutic targets for large granular lymphocyte leukemia. PLoS Comput Biol 7: e1002267. doi: 10.1371/journal.pcbi.1002267 22102804
24. Stein RR, Bucci V, Toussaint NC, Buffie CG, Ratsch G, et al. (2013) Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota. PLoS Comput Biol 9: e1003388. doi: 10.1371/journal.pcbi.1003388 24348232
25. Marino S, Baxter NT, Huffnagle GB, Petrosino JF, Schloss PD, (2014) Mathematical modeling of primary succession of murine intestinal microbiota. Proc Natl Acad Sci U S A 111: 439–444. doi: 10.1073/pnas.1311322111 24367073
26. Davidich MI, Bornholdt S, (2013) Boolean network model predicts knockout mutant phenotypes of fission yeast. PLoS One 8: e71786. doi: 10.1371/journal.pone.0071786 24069138
27. Bornholdt S, (2005) Systems biology. Less is more in modeling large genetic networks. Science 310: 449–451. 16239464
28. Steinway SN, Zanudo JG, Ding W, Rountree CB, Feith DJ, et al. (2014) Network modeling of TGFbeta signaling in hepatocellular carcinoma epithelial-to-mesenchymal transition reveals joint sonic hedgehog and Wnt pathway activation. Cancer Res 74: 5963–5977. doi: 10.1158/0008-5472.CAN-14-0225 25189528
29. Naldi A, Monteiro PT, Mussel C, the Consortium for Logical M, Tools, et al. (2015) Cooperative development of logical modelling standards and tools with CoLoMoTo. Bioinformatics.
30. Campbell C, Yang S, Albert R, Shea K, (2011) A network model for plant-pollinator community assembly. Proc Natl Acad Sci U S A 108: 197–202. doi: 10.1073/pnas.1008204108 21173234
31. Oberhardt MA, Palsson BO, Papin JA, (2009) Applications of genome-scale metabolic reconstructions. Mol Syst Biol 5: 320. doi: 10.1038/msb.2009.77 19888215
32. Buffie CG, Jarchum I, Equinda M, Lipuma L, Gobourne A, et al. (2012) Profound alterations of intestinal microbiota following a single dose of clindamycin results in sustained susceptibility to Clostridium difficile-induced colitis. Infect Immun 80: 62–73. doi: 10.1128/IAI.05496-11 22006564
33. Bartels RH, Beatty J.C., Barskey B.A, . (1998) Hermite and Cubic Spline Interpolation. An Introduction to Splines for Use in Computer Graphics and Geometric Modelling: Morgan Kaufmann. pp. 9–17.
34. Saadatpour A, Albert R, (2013) Boolean modeling of biological regulatory networks: a methodology tutorial. Methods 62: 3–12. doi: 10.1016/j.ymeth.2012.10.012 23142247
35. Berestovsky N, Nakhleh L, (2013) An Evaluation of Methods for Inferring Boolean Networks from Time-Series Data. PLoS One 8: e66031. 23805196
36. Lähdesmäki H, SI Yli-Harja O, (2003) On learning gene regulatory networks under the Boolean network model. Machine Learning 52: 147–167.
37. Mussel C, Hopfensitz M, Kestler HA, (2010) BoolNet—an R package for generation, reconstruction and analysis of Boolean networks. Bioinformatics 26: 1378–1380. doi: 10.1093/bioinformatics/btq124 20378558
38. Chaves M, Albert R, Sontag ED, (2005) Robustness and fragility of Boolean models for genetic regulatory networks. J Theor Biol 235: 431–449. 15882705
39. Albert I, Thakar J, Li S, Zhang R, Albert R, (2008) Boolean network simulations for life scientists. Source Code Biol Med 3: 16. doi: 10.1186/1751-0473-3-16 19014577
40. Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, et al. (2008) The RAST Server: rapid annotations using subsystems technology. BMC Genomics 9: 75. doi: 10.1186/1471-2164-9-75 18261238
41. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, et al. (2014) The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res 42: D206–214. doi: 10.1093/nar/gkt1226 24293654
42. Taffs R, Aston JE, Brileya K, Jay Z, Klatt CG, et al. (2009) In silico approaches to study mass and energy flows in microbial consortia: a syntrophic case study. BMC Syst Biol 3: 114. doi: 10.1186/1752-0509-3-114 20003240
43. Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, et al. (2014) Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res 42: D199–205. doi: 10.1093/nar/gkt1076 24214961
44. Kanehisa M, Goto S, (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28: 27–30. 10592173
45. The MathWorks I (2012) MATLAB and Statistics Toolbox Release 2012b. Natick, Massachusetts, United States.
46. Levy R, Borenstein E, (2013) Metabolic modeling of species interaction in the human microbiome elucidates community-level assembly rules. Proc Natl Acad Sci U S A 110: 12804–12809. doi: 10.1073/pnas.1300926110 23858463
47. Borenstein E, Kupiec M, Feldman MW, Ruppin E, (2008) Large-scale reconstruction and phylogenetic analysis of metabolic environments. Proc Natl Acad Sci U S A 105: 14482–14487. doi: 10.1073/pnas.0806162105 18787117
48. Faust K, Raes J, (2012) Microbial interactions: from networks to models. Nat Rev Microbiol 10: 538–550. doi: 10.1038/nrmicro2832 22796884
49. Team RC (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. doi: 10.3758/s13428-013-0330-5 23519455
50. Jensen PA, Dougherty BV, Moutinho TJ, Jr.Papin JA, (2015) Miniaturized plate readers for low-cost, high-throughput phenotypic screening. J Lab Autom 20: 51–55. doi: 10.1177/2211068214555414 25366331
51. Deatherage Kaiser BL, Li J, Sanford JA, Kim YM, Kronewitter SR, et al. (2013) A Multi-Omic View of Host-Pathogen-Commensal Interplay in-Mediated Intestinal Infection. PLoS One 8: e67155. 23840608
52. Jump RL, Polinkovsky A, Hurless K, Sitzlar B, Eckart K, et al. (2014) Metabolomics analysis identifies intestinal microbiota-derived biomarkers of colonization resistance in clindamycin-treated mice. PLoS One 9: e101267. doi: 10.1371/journal.pone.0101267 24988418
53. Lawley TD, Clare S, Walker AW, Goulding D, Stabler RA, et al. (2009) Antibiotic treatment of clostridium difficile carrier mice triggers a supershedder state, spore-mediated transmission, and severe disease in immunocompromised hosts. Infect Immun 77: 3661–3669. doi: 10.1128/IAI.00558-09 19564382
54. Buffie CG, Bucci V, Stein RR, McKenney PT, Ling L, et al. (2015) Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile. Nature 517: 205–208. doi: 10.1038/nature13828 25337874
55. Ubeda C, Bucci V, Caballero S, Djukovic A, Toussaint NC, et al. (2013) Intestinal microbiota containing Barnesiella species cures vancomycin-resistant Enterococcus faecium colonization. Infect Immun 81: 965–973. doi: 10.1128/IAI.01197-12 23319552
56. Lawley TD, Clare S, Walker AW, Stares MD, Connor TR, et al. (2012) Targeted restoration of the intestinal microbiota with a simple, defined bacteriotherapy resolves relapsing Clostridium difficile disease in mice. PLoS Pathog 8: e1002995. doi: 10.1371/journal.ppat.1002995 23133377
57. Reeves AE, Koenigsknecht MJ, Bergin IL, Young VB, (2012) Suppression of Clostridium difficile in the gastrointestinal tracts of germfree mice inoculated with a murine isolate from the family Lachnospiraceae. Infect Immun 80: 3786–3794. doi: 10.1128/IAI.00647-12 22890996
58. Klitgord N, Segre D, (2010) Environments that induce synthetic microbial ecosystems. PLoS Comput Biol 6: e1001002. doi: 10.1371/journal.pcbi.1001002 21124952
59. Sam Ma Z, Guan Q, Ye C, Zhang C, Foster JA, et al. (2015) Network analysis suggests a potentially 'evil' alliance of opportunistic pathogens inhibited by a cooperative network in human milk bacterial communities. Sci Rep 5: 8275. doi: 10.1038/srep08275 25651890
60. Shankar V, Agans R, Holmes B, Raymer M, Paliy O, (2013) Do gut microbial communities differ in pediatric IBS and health? Gut Microbes 4: 347–352. doi: 10.4161/gmic.24827 23674073
61. Rigsbee L, Agans R, Shankar V, Kenche H, Khamis HJ, et al. (2012) Quantitative profiling of gut microbiota of children with diarrhea-predominant irritable bowel syndrome. Am J Gastroenterol 107: 1740–1751. 22986438
62. Trosvik P, de Muinck EJ, Stenseth NC (2014) Biotic interactions and temporal dynamics of the human gastrointestinal microbiota. ISME J.
63. Feist AM, Herrgard MJ, Thiele I, Reed JL, Palsson BO, (2009) Reconstruction of biochemical networks in microorganisms. Nat Rev Microbiol 7: 129–143. doi: 10.1038/nrmicro1949 19116616
64. Zomorrodi AR, Maranas CD, (2012) OptCom: a multi-level optimization framework for the metabolic modeling and analysis of microbial communities. PLoS Comput Biol 8: e1002363. doi: 10.1371/journal.pcbi.1002363 22319433
65. Foster KR, Bell T, (2012) Competition, not cooperation, dominates interactions among culturable microbial species. Curr Biol 22: 1845–1850. doi: 10.1016/j.cub.2012.08.005 22959348
66. Pultz NJ, Stiefel U, Subramanyan S, Helfand MS, Donskey CJ, (2005) Mechanisms by which anaerobic microbiota inhibit the establishment in mice of intestinal colonization by vancomycin-resistant Enterococcus. J Infect Dis 191: 949–956. 15717271
67. Buffie CG, Pamer EG, (2013) Microbiota-mediated colonization resistance against intestinal pathogens. Nat Rev Immunol 13: 790–801. doi: 10.1038/nri3535 24096337
68. Brandl K, Plitas G, Mihu CN, Ubeda C, Jia T, et al. (2008) Vancomycin-resistant enterococci exploit antibiotic-induced innate immune deficits. Nature 455: 804–807. doi: 10.1038/nature07250 18724361
69. Kinnebrew MA, Ubeda C, Zenewicz LA, Smith N, Flavell RA, et al. (2010) Bacterial flagellin stimulates Toll-like receptor 5-dependent defense against vancomycin-resistant Enterococcus infection. J Infect Dis 201: 534–543. doi: 10.1086/650203 20064069