References
Fung, T. C., Olson, C. A. & Hsiao, E. Y. Interactions between the microbiota, immune and nervous systems in health and disease. Nat. Neurosci. 20, 145–155 (2017).
Browne, H. P. et al. Culturing of ‘unculturable’ human microbiota reveals novel taxa and extensive sporulation. Nature 533, 543–546 (2016).
Lagier, J. C. et al. The rebirth of culture in microbiology through the example of culturomics to study human gut microbiota. Clin. Microbiol. Rev. 28, 237–264 (2015).
Lagkouvardos, I., Overmann, J. & Clavel, T. Cultured microbes represent a substantial fraction of the human and mouse gut microbiota. Gut Microbes 8, 493–503 (2017).
D’Onofrio, A. et al. Siderophores from neighboring organisms promote the growth of uncultured bacteria. Chem. Biol. 17, 254–264 (2010).
Fenn, K. et al. Quinones are growth factors for the human gut microbiota. Microbiome 5, 161 (2017).
Carlier, J. P., Bedora-Faure, M., K’Ouas, G., Alauzet, C. & Mory, F. Proposal to unify Clostridium orbiscindens Winter et al. 1991 and Eubacterium plautii (Seguin 1928) Hofstad and Aasjord 1982, with description of Flavonifractor plautii gen. nov., comb. nov., and reassignment of Bacteroides capillosus to Pseudoflavonifractor capillosus gen. nov., comb. nov. Int. J. Syst. Evol. Microbiol. 60, 585–590 (2010).
Klaring, K. et al. Intestinimonas butyriciproducens gen. nov., sp. nov., a butyrate-producing bacterium from the mouse intestine. Int. J. Syst. Evol. Microbiol. 63, 4606–4612 (2013).
Yarza, P. et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat. Rev. Microbiol. 12, 635–645 (2014).
Fodor, A. A. et al. The “most wanted” taxa from the human microbiome for whole genome sequencing. PLoS ONE 7, e41294 (2012).
Lagkouvardos, I. et al. IMNGS: a comprehensive open resource of processed 16S rRNA microbial profiles for ecology and diversity studies. Sci. Rep. 6, 33721 (2016).
Goodman, A. L. et al. Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice. Proc. Natl Acad. Sci. USA 108, 6252–6257 (2011).
Deutscher, J., Francke, C. & Postma, P. W. How phosphotransferase system-related protein phosphorylation regulates carbohydrate metabolism in bacteria. Microbiol. Mol. Biol. Rev. 70, 939–1031 (2006).
Feehily, C. & Karatzas, K. A. Role of glutamate metabolism in bacterial responses towards acid and other stresses. J. Appl. Microbiol. 114, 11–24 (2013).
Hardman, J. K. & Stadtman, T. C. Metabolism of omega-amino acids. I. Fermentation of gamma-aminobutyric acid by Clostridium aminobutyricum n. sp. J. Bacteriol. 79, 544–548 (1960).
Fallingborg, J. Intraluminal pH of the human gastrointestinal tract. Dan. Med. Bull. 46, 183–196 (1999).
CAS PubMed Google Scholar
Aziz, R. K. et al. The RAST Server: rapid annotations using subsystems technology. BMC Genomics 9, 75 (2008).
Bateman, A. et al. UniProt: a hub for protein information. Nucleic Acids Res. 43, D204–D212 (2015).
McDonald, D. et al. American gut: an open platform for citizen science microbiome research. mSystems 3, e00031–18 (2018).
Sneath, P. H. Principles of bacterial taxonomy. Proc. R. Soc. Med. 65, 851–852 (1972).
Arkin, A. P. et al. The United States Department of Energy Systems Biology Knowledgebase. Nat. Biotechnol. 36, 566–569 (2018).
Ni, Y., Li, J. & Panagiotou, G. A molecular-level landscape of diet–gut microbiome interactions: toward dietary interventions targeting bacterial genes. mBio 6, e01263-15 (2015).
Haas, B. J. et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat. Protoc. 8, 1494–1512 (2013).
Matsumoto, M. et al. Colonic absorption of low-molecular-weight metabolites influenced by the intestinal microbiome: a pilot study. PLoS ONE 12, e0169207 (2017).
van Berlo, C. L. et al. Gamma-aminobutyric acid production in small and large intestine of normal and germ-free Wistar rats. Influence of food intake and intestinal flora. Gastroenterology 93, 472–479 (1987).
Fujisaka, S. et al. Diet, genetics, and the gut microbiome drive dynamic changes in plasma metabolites. Cell Rep. 22, 3072–3086 (2018).
Luscher, B., Shen, Q. & Sahir, N. The GABAergic deficit hypothesis of major depressive disorder. Mol. Psychiatry 16, 383–406 (2011).
Davidson, R. J., Pizzagalli, D., Nitschke, J. B. & Putnam, K. Depression: perspectives from affective neuroscience. Annu. Rev. Psychol. 53, 545–574 (2002).
Greicius, M. D., Krasnow, B., Reiss, A. L. & Menon, V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc. Natl Acad. Sci. USA 100, 253–258 (2003).
Greicius, M. D. et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol. Psychiatry 62, 429–437 (2007).
Sheline, Y. I. et al. The default mode network and self-referential processes in depression. Proc. Natl Acad. Sci. USA 106, 1942–1947 (2009).
Liston, C. et al. Default mode network mechanisms of transcranial magnetic stimulation in depression. Biol. Psychiatry 76, 517–526 (2014).
Koechlin, E. & Hyafil, A. Anterior prefrontal function and the limits of human decision-making. Science 318, 594–598 (2007).
Wager, T. D., Davidson, M. L., Hughes, B. L., Lindquist, M. A. & Ochsner, K. N. Prefrontal–subcortical pathways mediating successful emotion regulation. Neuron 59, 1037–1050 (2008).
Tillisch, K. et al. Brain structure and response to emotional stimuli as related to gut microbial profiles in healthy women. Psychosom. Med. 79, 905–913 (2017).
Hassan, A. M. et al. High-fat diet induces depression-like behaviour in mice associated with changes in microbiome, neuropeptide Y, and brain metabolome. Nutr. Neurosci. https://doi.org/10.1080/1028415X.2018.1465713 (2018).
Bravo, J. A. et al. Ingestion of Lactobacillus strain regulates emotional behavior and central GABA receptor expression in a mouse via the vagus nerve. Proc. Natl Acad. Sci. USA 108, 16050–16055 (2011).
Janik, R. et al. Magnetic resonance spectroscopy reveals oral Lactobacillus promotion of increases in brain GABA, N-acetyl aspartate and glutamate. Neuroimage 125, 988–995 (2016).
Lin, Q. Submerged fermentation of Lactobacillus rhamnosus YS9 for gamma-aminobutyric acid (GABA) production. Braz. J. Microbiol. 44, 183–187 (2013).
Barrett, E., Ross, R. P., O’Toole, P. W., Fitzgerald, G. F. & Stanton, C. Gamma-aminobutyric acid production by culturable bacteria from the human intestine. J. Appl. Microbiol. 113, 411–417 (2012).
Pokusaeva, K. et al. GABA-producing Bifidobacterium dentium modulates visceral sensitivity in the intestine. Neurogastroenterol. Motil. 29, e12904 (2017).
Kootte, R. S. et al. Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition. Cell. Metab. 26, 611–619 (2017).
Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).
Wattam, A. R. et al. Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center. Nucleic Acids Res. 45, D535–D542 (2017).
Wixon, J. & Kell, D. The Kyoto encyclopedia of genes and genomes—KEGG. Yeast 17, 48–55 (2000).
Kitagawa, M. et al. Complete set of ORF clones of Escherichia coli ASKA library (a complete set of E. coli K-12 ORF archive): unique resources for biological research. DNA Res. 12, 291–299 (2005).
Hyatt, D. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11, 119 (2010).
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).
Amir, A. et al. Deblur rapidly resolves single-nucleotide community sequence patterns. mSystems 2, e00191–16 (2017).
Amir, A. et al. Correcting for microbial blooms in faecal samples during room-temperature shipping. mSystems 2, e00199–16 (2017).
Chang, C. & Glover, G. H. Effects of model-based physiological noise correction on default mode network anti-correlations and correlations. Neuroimage 47, 1448–1459 (2009).
Shirer, W. R., Ryali, S., Rykhlevskaia, E., Menon, V. & Greicius, M. D. Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cereb. Cortex 22, 158–165 (2012).
