This repository contains the current genome-scale metabolic models for 58 gut bacterial species, which are selected from gut microbiota of healthy and malnourished children.
- General Concepts:
Annotated genomes based on Rapid Annotation using Subsystem Technology (RAST) sever were used for reconstructing the GEMs at Kbase platform (The U.S. Department of Energy Systems Biology Knowledgebase, https://kbase.us/).
- Abstract:
Malnutrition is a severe noncommunicable disease, which is prevalent in children of low-income countries. Recently, a number of metagenomics studies have illustrated associations between an altered gut microbiota and child malnutrition. However, these studies did not examine metabolic functions and interactions between individual species in the gut microbiota during health and malnutrition. Here, we applied genome-scale metabolic modeling to model the gut microbial species, which were selected from healthy and malnourished children from three countries (Malawi, Bangladesh, and Sweden). Our analysis showed reduced metabolite production capabilities in children from Bangladesh and Malawi compared with Swedish children. Additionally, the models were also used to predict the community-level metabolic potentials of gut microbes and the patterns of pairwise interactions among species. Hereby we found that due to bacterial interactions there may be reduced production of certain amino acids in malnourish children compared with healthy children from the same communities. To gain insight into alterations in metabolism of malnourished (stunted) children, we also performed targeted plasma metabolic profiling in the first 2 years of life of 25 healthy and 25 stunted children from Bangladesh. Plasma metabolic profiling further revealed that stunted children had reduced plasma levels of essential amino acids compared to healthy controls. Our analyses provide a framework for future efforts towards further characterization of gut microbial metabolic capabilities and their contribution to malnutrition.
- Main Model Descriptors:
| Bacterial species | Model ID | Reactions | Metabolites | Genes |
|---|---|---|---|---|
| Bacteroides caccae | 'kbg1379.xml' | 1029 | 976 | 3753 |
| Bacteroides fragilis | 'kbg1616.xml' | 1038 | 1003 | 4862 |
| Bacteroides intestinalis | 'kbg1697.xml' | 1022 | 981 | 4796 |
| Bacteroides ovatus | 'kbg28919.xml' | 1040 | 993 | 6680 |
| Bacteroides stercoris | 'kbg1552.xml' | 1027 | 983 | 3481 |
| Bacteroides thetaiotaomicron | 'kbg31348.xml' | 1046 | 995 | 4981 |
| Bacteroides uniformis | 'kbg1370.xml' | 1033 | 1004 | 4178 |
| Bacteroides vulgatus | 'kbg31349.xml' | 1075 | 1014 | 4574 |
| Bifidobacterium adolescentis | 'kbg1371.xml' | 934 | 901 | 2108 |
| Bifidobacterium bifidum | 'kbg25501.xml' | 915 | 899 | 2028 |
| Bifidobacterium breve | 'kbg31087.xml' | 950 | 901 | 2244 |
| Bifidobacterium longum | 'kbg26583.xml' | 966 | 929 | 2664 |
| Bifidobacterium pseudocatenulatum | 'kbg26897.xml' | 939 | 917 | 1981 |
| Bifidobacterium pseudolongum | 'kbg239964.xml' | 893 | 857 | 1645 |
| Catenibacterium mitsuokai | 'kbg1558.xml' | 985 | 944 | 2341 |
| Clostridium bartlettii | 'kbg1525.xml' | 1046 | 978 | 2805 |
| Clostridium paraputrificum | 'kbg208693.xml' | 1163 | 1053 | 3544 |
| Clostridium ramosum | 'kbg1526.xml' | 1048 | 973 | 3123 |
| Clostridium sp SS2 1 | 'kbg1373.xml' | 1088 | 1018 | 3048 |
| Collinsella aerofaciens | 'kbg1381.xml' | 913 | 868 | 2173 |
| Dialister succinatiphilus | 'kbg27482.xml' | 987 | 949 | 2214 |
| Dorea formicigenerans | 'kbg1356.xml' | 1091 | 1026 | 3085 |
| Dorea longicatena | 'kbg1357.xml' | 977 | 943 | 2839 |
| Enterobacter aerogenes | 'kbg_MK4.xml' | 1547 | 1289 | 5016 |
| Enterococcus faecalis | 'kbg435.xml' | 1104 | 1005 | 3323 |
| Escherichia coli | 'kbg1870.xml' | 1526 | 1255 | 4655 |
| Eubacterium biforme | 'kbg1911.xml' | 936 | 907 | 2359 |
| Eubacterium eligens | 'kbg1895.xml' | 963 | 943 | 2690 |
| Eubacterium rectale | 'kbg2826.xml' | 1057 | 1001 | 3480 |
| Faecalibacterium cf | 'kbg3160.xml' | 1051 | 981 | 2840 |
| Faecalibacterium prausnitzii | 'kbg3105.xml' | 1028 | 964 | 3291 |
| Fusobacterium mortiferum | 'kbg1673.xml' | 1108 | 1025 | 2635 |
| Haemophilus parainfluenzae | 'kbg24173.xml' | 1150 | 1023 | 2052 |
| Lactobacillus mucosae | 'kbg24465.xml' | 951 | 893 | 2074 |
| Lactobacillus rhamnosus | 'kbg209856.xml' | 1108 | 1025 | 3022 |
| Lactobacillus ruminis | 'kbg84.xml' | 1004 | 957 | 2317 |
| Lactobacillus salivarius | 'kbg3076.xml' | 958 | 905 | 2269 |
| Megasphaera elsdenii | 'kbg241889.xml' | 1064 | 1017 | 2322 |
| Parabacteroides distasonis | 'kbg242180.xml' | 1160 | 1080 | 4889 |
| Parabacteroides johnsonii | 'kbg2144.xml' | 1071 | 1035 | 3958 |
| Prevotella copri | 'kbg2146.xml' | 925 | 904 | 5637 |
| Roseburia intestinalis | 'kbg2141.xml' | 1086 | 1017 | 4125 |
| Roseburia inulinivorans | 'kbg2642.xml' | 1058 | 1011 | 4055 |
| Ruminococcus bromii | 'kbg2829.xml' | 818 | 805 | 2209 |
| Ruminococcus gnavus | 'kbg210975.xml' | 1129 | 1041 | 3973 |
| Ruminococcus lactaris | 'kbg206793.xml' | 997 | 966 | 2965 |
| Ruminococcus obeum | 'kbg2823.xml' | 1080 | 1014 | 3614 |
| Ruminococcus sp 5 1 39BFAA | 'kbg1613.xml' | 1108 | 1022 | 3527 |
| Ruminococcus torques | 'kbg2822.xml' | 1091 | 1025 | 3176 |
| Staphylococcus warneri | 'kbg31042.xml' | 1252 | 1098 | 2507 |
| Streptococcus parasanguinis | 'kbg206790.xml' | 981 | 896 | 2168 |
| Streptococcus thermophilus | 'kbg23407.xml' | 921 | 857 | 2259 |
| Streptococcus vestibularis | 'kbg3655.xml' | 976 | 900 | 2052 |
| Subdoligranulum variabile | 'kbg1366.xml' | 1055 | 990 | 6038 |
| Succinivibrio dextrinosolvens | 'kbg244674.xml' | 1046 | 994 | 2343 |
| Veillonella atypica | 'kbg3465.xml' | 977 | 930 | 1932 |
| Veillonella dispar | 'kbg212687.xml' | 1039 | 979 | 2115 |
| Weissella cibaria | 'kbg28337.xml' | 999 | 937 | 2151 |
This repository is administered by Manish Kumar @manishku and Dimitra Lappa @demilappa, Division of Systems and Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology
Last update: 2018-06-25
- PROGRAMMING LANGUAGE/Version (e.g.):
- libSBML MATLAB API (version 5.13.0 is recommended).
- Gurobi Optimizer for MATLAB (version 6.5.2 is recommended).
- Clone ChildrenGutMicrobialGEMs branch from SysBioChalmers GitHub
- Add the directory to your Matlab path, instructions here
- Manish Kumar, Chalmers University of Technology, Gothenburg Sweden
- Dimitra Lappa, Chalmers University of Technology, Gothenburg Sweden
The MIT License (MIT)
Copyright (c) 2017 Systems and Synthetic Biology
Chalmers University of Technology Gothenburg, Sweden
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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