Interrogation of the mammalian gut–brain axis using LC–MS/MS-based targeted metabolomics with in vitro bacterial and organoid cultures and in vivo gnotobiotic mouse models

Thomas D. Horvath, Sigmund J. Haidacher, Melinda A. Engevik, Berkley Luck, Wenly Ruan, Faith Ihekweazu, Meghna Bajaj, Kathleen M. Hoch, Numan Oezguen, Jennifer K. Spinler, James Versalovic, Anthony M. Haag

Published: 2022-11-08 DOI: 10.1038/s41596-022-00767-7

organoid cultures

metabolomics

gut-brain axis

LC-MS/MS

gnotobiotic mouse models

AI 解读

Author Correction: Full-length sequencing of circular DNA viruses and extrachromosomal circular DNA using CIDER-Seq

Generation of heart-forming organoids from human pluripotent stem cells

Design and fabrication of wearable electronic textiles using twisted fiber-based threads

Activation of mechanoluminescent nanotransducers by focused ultrasound enables light delivery to deep-seated tissue in vivo

Chromatin accessibility profiling by ATAC-seq

Deoxyfluorination of phenols for chemoselective18F-labeling of peptides

Author Correction: cfSNV: a software tool for the sensitive detection of somatic mutations from cell-free DNA

Human primordial germ cell-like cells specified from resetting precursors develop in human hindgut organoids

An inexpensive semi-automated sample processing pipeline for cell-free RNA extraction

Application of CHyMErA Cas9-Cas12a combinatorial genome-editing platform for genetic interaction mapping and gene fragment deletion screening

查看全部

Sections

Figures

References

Interest in the communication between the gastrointestinal tract and central nervous system, known as the gut–nobreakbrain axis, has prompted the development of quantitative analytical platforms to analyze microbe- and host-derived signals. This p
Introduction
Materials
- Biological materials
Reagents
Equipment
Reagent setup
Equipment setup
Procedure
Troubleshooting
Timing
- Equipment setup
- Procedure
Anticipated results
- References
References
ACKNOWLEDGMENTS

Yatsunenko, T. et al. Human gut microbiome viewed across age and geography. Nature 486, 222–227 (2012).
The Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).
Nagpal, R. et al. Gut microbiome and aging: physiological and mechanistic insights. Nutr. Healthy Aging 4, 267–285 (2018).
Luck, B. et al. Bifidobacteria shape host neural circuits during postnatal development by promoting synapse formation and microglial function. Sci. Rep. 10, 7737 (2020).
Desbonnet, L., Clarke, G., Shanahan, F., Dinan, T. G. & Cryan, J. F. Microbiota is essential for social development in the mouse. Mol. Psychiatry 19, 146–148 (2014).
Desbonnet, L. et al. Effects of the probiotic Bifidobacterium infantis in the maternal separation model of depression. Neuroscience 170, 1179–1188 (2010).
Mayer, E. A., Knight, R., Mazmanian, S. K., Cryan, J. F. & Tillisch, K. Gut microbes and the brain: paradigm shift in neuroscience. J. Neurosci. 34, 15490–15496 (2014).
Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012).
Johnson, C. L. & Versalovic, J. The human microbiome and its potential importance to pediatrics. Pediatrics 129, 950–960 (2012).
Hollister, E. B. et al. Structure and function of the healthy pre-adolescent pediatric gut microbiome. Microbiome 3, 36 (2015).
Martin, R. et al. Role of commensal and probiotic bacteria in human health: a focus on inflammatory bowel disease. Microb. Cell Fact. 12, 71 (2013).
Engevik, M. A. et al. Human-derived Bifidobacterium dentium modulates the mammalian serotonergic system and gut–brain axis. Cell Mol. Gastroenterol. Hepatol. https://doi.org/10.1016/j.jcmgh.2020.08.002 (2020).
Luk, B. et al. Postnatal colonization with human “infant-type” Bifidobacterium species alters behavior of adult gnotobiotic mice. PLoS ONE 13, e0196510 (2018).
Yano, J. M. et al. Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell 161, 264–276 (2015).
Chang-Graham, A. L. et al. Human intestinal enteroids with inducible neurogenin-3 expression as a novel model of gut hormone secretion. Cell Mol. Gastroenterol. Hepatol. 8, 209–229 (2019).
Luczynski, P. et al. Growing up in a bubble: using germ-free animals to assess the influence of the gut microbiota on brain and behavior. Int. J. Neuropsychopharmacol. https://doi.org/10.1093/ijnp/pyw020 (2016).
Desbonnet, L. et al. Gut microbiota depletion from early adolescence in mice: implications for brain and behaviour. Brain Behav. Immun. 48, 165–173 (2015).
Desbonnet, L., Garrett, L., Clarke, G., Bienenstock, J. & Dinan, T. G. The probiotic Bifidobacteria infantis: an assessment of potential antidepressant properties in the rat. J. Psychiatr. Res. 43, 164–174 (2008).
Engevik, M. A. & Versalovic, J. Biochemical features of beneficial microbes: foundations for therapeutic microbiology. Microbiol. Spectr. https://doi.org/10.1128/microbiolspec.BAD-0012-2016 (2017).
Ma, Q. et al. Impact of microbiota on central nervous system and neurological diseases: the gut–brain axis. J. Neuroinflammation 16, 53 (2019).
Horvath, T. D. et al. Bacteroides ovatus colonization influences the abundance of intestinal short chain fatty acids and neurotransmitters. iScience 25, 104158 (2022).
Luck, B. et al. Neurotransmitter profiles are altered in the gut and brain of mice mono-associated with Bifidobacterium dentium. Biomolecules https://doi.org/10.3390/biom11081091 (2021).
Engevik, M. A. et al. Bifidobacterium dentium fortifies the intestinal mucus layer via autophagy and calcium signaling pathways. mBio https://doi.org/10.1128/mBio.01087-19 (2019).
Pokusaeva, K. et al. GABA-producing Bifidobacterium dentium modulates visceral sensitivity in the intestine. Neurogastroenterol. Motil. https://doi.org/10.1111/nmo.12904 (2017).
Ihekweazu, F. D. et al. Bacteroides ovatus promotes IL-22 production and reduces trinitrobenzene sulfonic acid-driven colonic inflammation. Am. J. Pathol. 191, 704–719 (2021).
Ihekweazu, F. D. et al. Bacteroides ovatus ATCC 8483 monotherapy is superior to traditional fecal transplant and multi-strain bacteriotherapy in a murine colitis model. Gut Microbes 10, 504–520 (2019).
Tareke, E., Bowyer, J. F. & Doerge, D. R. Quantification of rat brain neurotransmitters and metabolites using liquid chromatography/electrospray tandem mass spectrometry and comparison with liquid chromatography/electrochemical detection. Rapid Commun. Mass Spectrom. 21, 3898–3904 (2007).
Zhang, M. Y. & Beyer, C. E. Measurement of neurotransmitters from extracellular fluid in brain by in vivo microdialysis and chromatography-mass spectrometry. J. Pharm. Biomed. Anal. 40, 492–499 (2006).
Donaldson, G. P. et al. Spatially distinct physiology of Bacteroides fragilis within the proximal colon of gnotobiotic mice. Nat. Microbiol. 5, 746–756 (2020).
Kovac, A., Somikova, Z., Zilka, N. & Novak, M. Liquid chromatography–tandem mass spectrometry method for determination of panel of neurotransmitters in cerebrospinal fluid from the rat model for tauopathy. Talanta 119, 284–290 (2014).
Sato, T. et al. Single Lgr5 stem cells build crypt–villus structures in vitro without a mesenchymal niche. Nature 459, 262–265 (2009).
Ruan, W. et al. Enhancing responsiveness of human jejunal enteroids to host and microbial stimuli. J. Physiol. 598, 3085–3105 (2020).
Begou, O., Gika, H. G., Wilson, I. D. & Theodoridis, G. Hyphenated MS-based targeted approaches in metabolomics. Analyst 142, 3079–3100 (2017).
Jang, C., Chen, L. & Rabinowitz, J. D. Metabolomics and isotope tracing. Cell 173, 822–837 (2018).
Rinschen, M. M., Ivanisevic, J., Giera, M. & Siuzdak, G. Identification of bioactive metabolites using activity metabolomics. Nat. Rev. Mol. Cell Biol. 20, 353–367 (2019).
Cajka, T. & Fiehn, O. Toward merging untargeted and targeted methods in mass spectrometry-based metabolomics and lipidomics. Anal. Chem. 88, 524–545 (2016).
Mahmud, I. & Garrett, T. J. Mass spectrometry techniques in emerging pathogens studies: COVID-19 perspectives. J. Am. Soc. Mass Spectrom. 31, 2013–2024 (2020).
Anderson, B. G., Raskind, A., Habra, H., Kennedy, R. T. & Evans, C. R. Modifying chromatography conditions for improved unknown feature identification in untargeted metabolomics. Anal. Chem. 93, 15840–15849 (2021).
Horvath, T. D., Dagan, S. & Scaraffia, P. Y. Unraveling mosquito metabolism with mass spectrometry-based metabolomics. Trends Parasitol. 37, 747–761 (2021).
Lee, S. M. et al. Adaptation in a mouse colony monoassociated with Escherichia coli K-12 for more than 1,000 days. Appl. Environ. Microbiol. 76, 4655–4663 (2010).
Hoffmann, T. W. et al. Microorganisms linked to inflammatory bowel disease-associated dysbiosis differentially impact host physiology in gnotobiotic mice. ISME J. 10, 460–477 (2016).
Stehlikova, Z. et al. Crucial role of microbiota in experimental psoriasis revealed by a gnotobiotic mouse model. Front. Microbiol. https://doi.org/10.3389/fmicb.2019.00236 (2019).
Klaasen, H. L. B. M., Koopman, J. P., Van den Brink, M. E., Van Wezel, H. P. N. & Beynen, A. C. Mono-association of mice with non-cultivable, intestinal, segmented, filamentous bacteria. Arch. Microbiol. 156, 148–151 (1991).
Kim, J. et al. Lactobacillus rhamnosus GG modifies the metabolome of pathobionts in gnotobiotic mice. BMC Microbiol. 21, 165 (2021).
Mao, J.-H. et al. Genetic and metabolic links between the murine microbiome and memory. Microbiome 8, 53 (2020).
Engevik, M. A. et al. Bifidobacterium dentium-derived y-glutamylcysteine suppresses ER-mediated goblet cell stress and reduces TNBS-driven colonic inflammation. Gut Microbes 13, 1–21 (2021).
Chen, Y. P. & Chen, M. J. Effects of Lactobacillus kefiranofaciens M1 isolated from kefir grains on germ-free mice. PLoS ONE 8, e78789 (2013).
Chiu, C. C. et al. Monocolonization of germ-free mice with Bacteroides fragilis protects against dextran sulfate sodium-induced acute colitis. Biomed. Res. Int. 2014, 675786 (2014).
Lee, Y. P. et al. The germ-free mice monocolonization with Bacteroides fragilis improves azoxymethane/dextran sulfate sodium induced colitis-associated colorectal cancer. Immunopharmacol. Immunotoxicol. 41, 207–213 (2019).
Anesi, A. et al. Metabolic profiling of human plasma and urine, targeting tryptophan, tyrosine and branched chain amino acid pathways. Metabolites https://doi.org/10.3390/metabo9110261 (2019).
Peterson, D. A. et al. Characterizing the interactions between a naturally primed immunoglobulin A and its conserved Bacteroides thetaiotaomicron species-specific epitope in gnotobiotic mice. J. Biol. Chem. 290, 12630–12649 (2015).
Aktar, R. et al. Human resident gut microbe Bacteroides thetaiotaomicron regulates colonic neuronal innervation and neurogenic function. Gut Microbes 11, 1745–1757 (2020).
Soavelomandroso, A. P. et al. Biofilm structures in a mono-associated mouse model of Clostridium difficile infection. Front. Microbiol. 8, 2086–2086 (2017).
Tamura, M., Hirayama, K. & Itoh, K. Comparison of colonic bacterial enzymes in gnotobiotic mice monoassociated with different intestinal bacteria. Microb. Ecol. Health Dis. 9, 287–294 (1996).
Liu, W.-H. et al. Alteration of behavior and monoamine levels attributable to Lactobacillus plantarum PS128 in germ-free mice. Behav. Brain Res. 298, 202–209 (2016).
Kozakova, H. et al. Colonization of germ-free mice with a mixture of three lactobacillus strains enhances the integrity of gut mucosa and ameliorates allergic sensitization. Cell Mol. Immunol. 13, 251–262 (2016).
Eberl, C. et al. Reproducible colonization of germ-free mice with the oligo-mouse-microbiota in different animal facilities. Front. Microbiol. https://doi.org/10.3389/fmicb.2019.02999 (2020).
Darnaud, M. et al. A standardized gnotobiotic mouse model harboring a minimal 15-member mouse gut microbiota recapitulates SOPF/SPF phenotypes. Nat. Commun. 12, 6686 (2021).
Mark Welch, J. L., Hasegawa, Y., McNulty, N. P., Gordon, J. I. & Borisy, G. G. Spatial organization of a model 15-member human gut microbiota established in gnotobiotic mice. Proc. Natl Acad. Sci. USA 114, E9105–e9114 (2017).
Zhang, G., Mills, D. A. & Block, D. E. Development of chemically defined media supporting high-cell-density growth of lactococci, enterococci, and streptococci. Appl. Environ. Microbiol. 75, 1080–1087 (2009).
Sidhaye, J. & Knoblich, J. A. Brain organoids: an ensemble of bioassays to investigate human neurodevelopment and disease. Cell Death Differ. https://doi.org/10.1038/s41418-020-0566-4 (2020).
Manousiouthakis, E. et al. Bioengineered in vitro enteric nervous system. J. Tissue Eng. Regen. Med. 13, 1712–1723 (2019).
Noel, G. et al. A primary human macrophage-enteroid co-culture model to investigate mucosal gut physiology and host-pathogen interactions. Sci. Rep. 7, 45270 (2017).
Kennedy, E. A., King, K. Y. & Baldridge, M. T. Mouse microbiota models: comparing germ-free mice and antibiotics treatment as tools for modifying gut bacteria. Front. Physiol. 9, 1534 (2018).
Luk, B. et al. in Figshare (2018).
Zhang, S., Wang, H. & Zhu, M. J. A sensitive GC/MS detection method for analyzing microbial metabolites short chain fatty acids in fecal and serum samples. Talanta 196, 249–254 (2019).
Mulat, D. G. & Feilberg, A. GC/MS method for determining carbon isotope enrichment and concentration of underivatized short-chain fatty acids by direct aqueous solution injection of biogas digester samples. Talanta 143, 56–63 (2015).
Hsu, Y.-L. et al. Evaluation and optimization of sample handling methods for quantification of short-chain fatty acids in human fecal samples by GC–MS. J. Proteome Res. 18, 1948–1957 (2019).
Furuhashi, T., Sugitate, K., Nakai, T., Jikumaru, Y. & Ishihara, G. Rapid profiling method for mammalian feces short chain fatty acids by GC–MS. Anal. Biochem. 543, 51–54 (2018).
Marcos, J. et al. Targeting tryptophan and tyrosine metabolism by liquid chromatography tandem mass spectrometry. J. Chromatogr. A 1434, 91–101 (2016).
Whiley, L. et al. Ultrahigh-performance liquid chromatography tandem mass spectrometry with electrospray ionization quantification of tryptophan metabolites and markers of gut health in serum and plasma—application to clinical and epidemiology cohorts. Anal. Chem. 91, 5207–5216 (2019).
Hook, V. et al. Metabolomics analyses of 14 classical neurotransmitters by GC–TOF with LC–MS illustrates secretion of 9 cell-cell signaling molecules from sympathoadrenal chromaffin cells in the presence of lithium. ACS Chem. Neurosci. 10, 1369–1379 (2019).
Pan, J. X. et al. Diagnosis of major depressive disorder based on changes in multiple plasma neurotransmitters: a targeted metabolomics study. Transl. Psychiatry 8, 130 (2018).
Yuan, M., Breitkopf, S. B., Yang, X. & Asara, J. M. A positive/negative ion-switching, targeted mass spectrometry-based metabolomics platform for bodily fluids, cells, and fresh and fixed tissue. Nat. Protoc. 7, 872–881 (2012).
Zheng, F. et al. Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography–mass spectrometry. Nat. Protoc. 15, 2519–2537 (2020).
Han, S. et al. A metabolomics pipeline for the mechanistic interrogation of the gut microbiome. Nature 595, 415–420 (2021).
Engevik, M. A. et al. Microbial metabolic capacity for intestinal folate production and modulation of host folate receptors. Front. Microbiol. 10, 2305 (2019).
Engevik, M. A. et al. Loss of NHE3 alters gut microbiota composition and influences Bacteroides thetaiotaomicron growth. Am. J. Physiol. Gastrointest. Liver Physiol. 305, G697–G711 (2013).
Williamson, I. A. et al. A high-throughput organoid microinjection platform to study gastrointestinal microbiota and luminal physiology. Cell Mol. Gastroenterol. Hepatol. 6, 301–319 (2018).
Dutta, D., Heo, I. & Clevers, H. Disease modeling in stem cell-derived 3D organoid systems. Trends Mol. Med. 23, 393–410 (2017).
Zhang, Y. G. & Sun, J. Study bacteria–host interactions using intestinal organoids. Methods Mol. Biol. 1576, 249–254 (2019).
Lukovac, S. et al. Differential modulation by Akkermansia muciniphila and Faecalibacterium prausnitzii of host peripheral lipid metabolism and histone acetylation in mouse gut organoids. mBio https://doi.org/10.1128/mBio.01438-14 (2014).
Co, J. Y. et al. Controlling epithelial polarity: a human enteroid model for host-pathogen interactions. Cell Rep. 26, 2509–2520 e2504 (2019).
Engevik, M. A. et al. Human intestinal enteroids as a model of Clostridioides difficile-induced enteritis. Am. J. Physiol. Gastrointest. Liver Physiol. 318, G870–G888 (2020).
Wilke, G. et al. A stem-cell-derived platform enables complete Cryptosporidium development in vitro and genetic tractability. Cell Host Microbe 26, 123–134.e128 (2019).
Engevik, M. A. et al. Human-derived Bifidobacterium dentium modulates the mammalian serotonergic system and gut–brain axis. Cell Mol. Gastroenterol. Hepatol. 11, 221–248 (2021).
Fultz, R. et al. Unraveling the metabolic requirements of the gut commensal Bacteroides ovatus. Front. Microbiol. 12, 745469 (2021).
Engevik, M. A. et al. The metabolic profile of Bifidobacterium dentium reflects its status as a human gut commensal. BMC Microbiol. 21, 154 (2021).
Engevik, M. A. et al. Fusobacterium nucleatum adheres to Clostridioides difficile via the RadD adhesin to enhance biofilm formation in intestinal mucus. Gastroenterology 160, 1301–1314 e1308 (2021).
Engevik, M. A. et al. Mucin-degrading microbes release monosaccharides that chemoattract Clostridioides difficile and facilitate colonization of the human intestinal mucus layer. ACS Infect. Dis. 7, 1126–1142 (2021).
Fultz, R., Ticer, T., Glover, J., Stripe, L. & Engevik, M. A. Select streptococci can degrade Candida mannan to facilitate growth. Appl. Environ. Microbiol., aem0223721 (2021).
Siddiquee, S. in Practical Handbook of the Biology and Molecular Diversity of Trichoderma Species from Tropical Regions (eds Gupta, V. K. & Tuohy, M. G.) 1–15 (Springer, 2017).
Strobel, H. J. Basic laboratory culture methods for anaerobic bacteria. Methods Mol. Biol. 581, 247–261 (2009).
Kilkenny, C., Browne, W. J., Cuthi, I., Emerson, M. & Altman, D. G. Improving bioscience research reporting: the ARRIVE guidelines for reporting animal research. Vet. Clin. Pathol. 41, 27–31 (2012).
Chan, J. C., Kioh, D. Y., Yap, G. C., Lee, B. W. & Chan, E. C. A novel LCMSMS method for quantitative measurement of short-chain fatty acids in human stool derivatized with (12)C- and (13)C-labelled aniline. J. Pharm. Biomed. Anal. 138, 43–53 (2017).
Horvath, T. D., Dagan, S., Lorenzi, P. L., Hawke, D. H. & Scaraffia, P. Y. Positional stable isotope tracer analysis reveals carbon routes during ammonia metabolism of Aedes aegypti mosquitoes. FASEB J. 32, 466–477 (2018).
Engevik, K. A., Matthis, A. L., Montrose, M. H. & Aihara, E. Organoids as a model to study infectious disease. Methods Mol. Biol. 1734, 71–81 (2018).
Hill, D. R., Huang, S., Tsai, Y. H., Spence, J. R. & Young, V. B. Real-time measurement of epithelial barrier permeability in human intestinal organoids. J. Vis. Exp. https://doi.org/10.3791/56960 (2017).
Mazzoli, R. & Pessione, E. The neuro-endocrinological role of microbial glutamate and GABA signaling. Front. Microbiol. 7, 1934 (2016).
Julio-Pieper, M., O’Connor, R. M., Dinan, T. G. & Cryan, J. F. Regulation of the brain–gut axis by group III metabotropic glutamate receptors. Eur. J. Pharmacol. 698, 19–30 (2013).
Soeiro-de-Souza, M. G. et al. Anterior cingulate glutamate–glutamine cycle metabolites are altered in euthymic bipolar I disorder. Eur. Neuropsychopharmacol. 25, 2221–2229 (2015).

Interrogation of the mammalian gut–brain axis using LC–MS/MS-based targeted metabolomics with in vitro bacterial and organoid cultures and in vivo gnotobiotic mouse models

Supplementary information

推荐阅读