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Event: 1954

Key Event Title

A descriptive phrase which defines a discrete biological change that can be measured. More help

Gut microbiota, alteration

Short name
The KE short name should be a reasonable abbreviation of the KE title and is used in labelling this object throughout the AOP-Wiki. More help
Gut dysbiosis
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Biological Context

Structured terms, selected from a drop-down menu, are used to identify the level of biological organization for each KE. More help
Level of Biological Organization

Organ term

The location/biological environment in which the event takes place.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable.  Further information on Event Components and Biological Context may be viewed on the attached pdf. More help

Key Event Components

The KE, as defined by a set structured ontology terms consisting of a biological process, object, and action with each term originating from one of 14 biological ontologies (Ives, et al., 2017; Biological process describes dynamics of the underlying biological system (e.g., receptor signalling).Biological process describes dynamics of the underlying biological system (e.g., receptor signaling).  The biological object is the subject of the perturbation (e.g., a specific biological receptor that is activated or inhibited). Action represents the direction of perturbation of this system (generally increased or decreased; e.g., ‘decreased’ in the case of a receptor that is inhibited to indicate a decrease in the signaling by that receptor).  Note that when editing Event Components, clicking an existing Event Component from the Suggestions menu will autopopulate these fields, along with their source ID and description.  To clear any fields before submitting the event component, use the 'Clear process,' 'Clear object,' or 'Clear action' buttons.  If a desired term does not exist, a new term request may be made via Term Requests.  Event components may not be edited; to edit an event component, remove the existing event component and create a new one using the terms that you wish to add.  Further information on Event Components and Biological Context may be viewed on the attached pdf. More help

Key Event Overview

AOPs Including This Key Event

All of the AOPs that are linked to this KE will automatically be listed in this subsection. This table can be particularly useful for derivation of AOP networks including the KE. Clicking on the name of the AOP will bring you to the individual page for that AOP. More help
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 Under Development

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KE.In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available in relation to this KE. More help
Term Scientific Term Evidence Link
Homo sapiens Homo sapiens High NCBI
rhesus macaques Macaca mulatta High NCBI
cynomolgus monkeys Macaca fascicularis Moderate NCBI
Mus musculus Mus musculus High NCBI

Life Stages

An indication of the the relevant life stage(s) for this KE. More help
Life stage Evidence
All life stages High

Sex Applicability

An indication of the the relevant sex for this KE. More help
Term Evidence
Male High
Female High

Key Event Description

A description of the biological state being observed or measured, the biological compartment in which it is measured, and its general role in the biology should be provided. More help

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

A description of the type(s) of measurements that can be employed to evaluate the KE and the relative level of scientific confidence in those measurements.These can range from citation of specific validated test guidelines, citation of specific methods published in the peer reviewed literature, or outlines of a general protocol or approach (e.g., a protein may be measured by ELISA). Do not provide detailed protocols. More help

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

A description of the scientific basis for the indicated domains of applicability and the WoE calls (if provided).  More help

Homo sapiens

nonhuman primate model (Rhesus macaques and cynomolgus macaques)9


List of the literature that was cited for this KE description. More help


  1. Hooks and O’Malley. Dysbiosis and Its Discontents. mBio 8 (2017).

  1. Levy, M., Kolodziejczyk, A., Thaiss, C. et al. Dysbiosis and the immune system. Nat Rev Immunol 17, 219–232 (2017).

  1. 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). 

  2. 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). 

  3. 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).

  4. 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).

  5. 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). 

  6. Forslund, S.K., Chakaroun, R., Zimmermann-Kogadeeva, M. et al. Combinatorial, additive and dose-dependent drug–microbiome associations. Nature (2021).

  7. 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).

  8. Saraswati S and Sitaraman R. Aging and the human gut microbiota—from correlation to causality. Front. Microbiol. 5:764 (2015). 

  9.  O’Toole P W  and Jeffery I B. Gut microbiota and aging. Science 350, 1214-1215 (2015)

  10. Ursell LK, Metcalf JL, Parfrey LW, Knight R. Defining the human microbiome. Nutr Rev. 70 Suppl 1(Suppl 1):S38-S44. (2012).

  11. 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).

  12. 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). 

  13. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486:207–214. (2012). 

  14. 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).

  15. 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).

  16. Peter E. Larsen, Yang Dai, Metabolome of human gut microbiome is predictive of host dysbiosis, GigaScience, 4, s13742–015–0084–3. (2015).