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Key Event Title
Gut microbiota, alteration
Key Event Components
Key Event Overview
AOPs Including This Key Event
|AOP Name||Role of event in AOP||Point of Contact||Author Status||OECD Status|
|ACE2 dysregulation leads to gut dysbiosis||KeyEvent||Laure-Alix Clerbaux (send email)||Under development: Not open for comment. Do not cite|
|Enteric SARS-CoV-2 infection leads to gastrointestinal disorders||KeyEvent||Laure-Alix Clerbaux (send email)||Under development: Not open for comment. Do not cite|
|All life stages||High|
Key Event Description
Gut dysbiosis features one or more of the following non-mutually exclusive characteristics 1,2:
Bloom of pathobionts (members of the commensal microbiota that have the potential to cause pathology). Such bacteria are typically present at low relative abundances but proliferate when aberrations occur in the intestinal ecosystem
Loss of commensals, the reduction or complete loss of normally residing members of the microbiota, which can be the consequence of microbial killing or diminished bacterial proliferation
Loss of diversity, characteristic of disease-associated dysbiosis
How It Is Measured or Detected
Among the culture independent methods, nucleic acids (amplicon sequencing, WGS, metatranscriptomics), proteins (metaproteomics) and metabolites (metabolomics) based methodologies are used to obtain the taxonomical and/or the functional profiles of the gut microbiome 12.
The comparative analysis between meta-data obtained from the profiling of different groups (e.g. healthy vs diseased subjects) is used to detect dysbiosis.
Comparative analysis of TAXONOMIC SIGNATURES - Gut microbiome diversity measurements include alpha diversity (among the commonly used estimators there are: Shannon index, Chao1 index, Operational Taxonomic Unit (OTU) richness, Simpson index, Faith’s Phylogenetic diversity, and Abundance-based Coverage Estimators (ACE) index); beta diversity (e.g. UniFrac, Bray-Curtis dissimilarity).
To qualify the term dysbiosis, several indexes have been defined and applied (Table 1, references in the table are detailed in 13) 13. Such indexes, interpreted in the context of the clinical findings, may help to characterize diseases and adverse conditions, predict treatment outcomes, and provide information other than the commonly used alpha and beta diversity assessments.
The Firmicutes/Bacteroidetes (F/B) ratio is widely accepted to have an important influence in maintaining normal intestinal homeostasis. Increased or decreased F/B ratio is used as an indicator of dysbiosis 14. However, other compositional changes at family, genus, or species level, might be more relevant than the Firmicutes/Bacteroidetes ratio.
Comparative analysis of FUNCTIONAL SIGNATURES - It has been noted by several groups that function seems more highly conserved across samples than across taxa, suggesting that function is more resilient across communities than the individual strains that come and go 15. In contrast to the indexes described above, evidence of functional dysbiosis are obtained by comparing e.g. metagenomic functional compositions predicted from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database 16, proportions of Clusters of Orthologous Groups (COG) encoding proteins, functional states based on peptides and/or proteins identified by MS 17, metabolomic profiles 18.
Domain of Applicability
nonhuman primate model (Rhesus macaques and cynomolgus macaques)9
Hooks and O’Malley. Dysbiosis and Its Discontents. mBio 8 (2017).
Levy, M., Kolodziejczyk, A., Thaiss, C. et al. Dysbiosis and the immune system. Nat Rev Immunol 17, 219–232 (2017).
Zuo T, Zhang F, Lui GCY, Yeoh YK, Li AYL, Zhan H, et al. Alterations in Gut Microbiota of Patients With COVID-19 During Time of Hospitalization. Gastroenterology. 159:944–55 e8. (2020).
Gu S, Chen Y, Wu Z, Chen Y, Gao H, Lv L, et al. Alterations of the Gut Microbiota in Patients With Coronavirus Disease 2019 or H1N1 Influenza. Clin Infect Dis. 71:2669–78 (2020).
Petrillo M, Brogna C, Cristoni S et al. Increase of SARS-CoV-2 RNA load in faecal samples prompts for rethinking of SARS-CoV-2 biology and COVID-19 epidemiology. F1000Research, 10:370 (2021).
Gubernatorova EO, Gorshkova EA, Polinova AI, Drutskaya MS. IL-6: Relevance for immunopathology of SARS-CoV-2. Cytokine Growth Factor Rev. 53:13–24 (2020).
Yeoh YK, Zuo T, Lui GC, Zhang F, Liu Q, Li AY, et al. Gut microbiota composition reflects disease severity and dysfunctional immune responses in patients with COVID-19. Gut. 70:698–706 (2021).
Forslund, S.K., Chakaroun, R., Zimmermann-Kogadeeva, M. et al. Combinatorial, additive and dose-dependent drug–microbiome associations. Nature (2021).
Sokol H, Contreras V, Maisonnasse P, et al. SARS-CoV-2 infection in nonhuman primates alters the composition and functional activity of the gut microbiota. Gut Microbes. 13(1):1-19 (2021).
Saraswati S and Sitaraman R. Aging and the human gut microbiota—from correlation to causality. Front. Microbiol. 5:764 (2015).
O’Toole P W and Jeffery I B. Gut microbiota and aging. Science 350, 1214-1215 (2015)
Ursell LK, Metcalf JL, Parfrey LW, Knight R. Defining the human microbiome. Nutr Rev. 70 Suppl 1(Suppl 1):S38-S44. (2012).
Wei S, Bahl MI, Baunwall SMD, Hvas CL, Licht TR. Determining Gut Microbial Dysbiosis: a Review of Applied Indexes for Assessment of Intestinal Microbiota Imbalances. Appl Environ Microbiol. 87(11):e00395-21. (2021).
Stojanov, S.; Berlec, A.; Štrukelj, B. The Influence of Probiotics on the Firmicutes/Bacteroidetes Ratio in the Treatment of Obesity and Inflammatory Bowel disease. Microorganisms 8, 1715. (2020).
Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486:207–214. (2012).
Wang WL, Xu SY, Ren ZG, Tao L, Jiang JW, Zheng SS. Application of metagenomics in the human gut microbiome. World J Gastroenterol 21(3):803-814 (2015).
Sajulga R, Easterly C, Riffle M, Mesuere B, Muth T, Mehta S, et al. Survey of metaproteomics software tools for functional microbiome analysis. PLoS ONE 15(11): e0241503. (2020).
Peter E. Larsen, Yang Dai, Metabolome of human gut microbiome is predictive of host dysbiosis, GigaScience, 4, s13742–015–0084–3. (2015).