ArticleBMC bioinformatics2019
AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 53 citations in OpenAlex.
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- Microbiome, Metabolism, and Immunoregulation of Asthma: An American Thoracic Society and National Institute of Allergy and Infectious Diseases Workshop Report.American journal of respiratory cell and molecular biology · 2022Article
- Mass spectrometry-based metabolomics in microbiome investigations.Nature reviews. Microbiology · 2022Review
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- It takes guts to learn: machine learning techniques for disease detection from the gut microbiome.Emerging topics in life sciences · 2021Review
- Overview of Metabolomic Analysis and the Integration with Multi-Omics for Economic Traits in Cattle.Metabolites · 2021Review
- Systems Analysis of Gut Microbiome Influence on Metabolic Disease in HIV-Positive and High-Risk Populations.mSystems · 2021Article
- A Literature Review and Framework Proposal for Halitosis Assessment in Cigarette Smokers and Alternative Nicotine-Delivery Products Users.Frontiers in oral health · 2021Review
- Seeing the forest for the trees: Retrieving plant secondary biochemical pathways from metabolome networks.Computational and structural biotechnology journal · 2021Review
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundUntargeted metabolomics of host-associated samples has yielded insights into mechanisms by which microbes modulate health. However, data interpretation is challenged by the complexity of origins of the small molecules measured, which can come from the host, microbes that live within the host, or from other exposures such as diet or the environment.
resultsWe address this challenge through development of AMON: Annotation of Metabolite Origins via Networks. AMON is an open-source bioinformatics application that can be used to annotate which compounds in the metabolome could have been produced by bacteria present or the host, to evaluate pathway enrichment of host verses microbial metabolites, and to visualize which compounds may have been produced by host versus microbial enzymes in KEGG pathway maps.
conclusionsAMON empowers researchers to predict origins of metabolites via genomic information and to visualize potential host:microbe interplay. Additionally, the evaluation of enrichment of pathway metabolites of host versus microbial origin gives insight into the metabolic functionality that a microbial community adds to a host:microbe system. Through integrated analysis of microbiome and metabolome data, mechanistic relationships between microbial communities and host phenotypes can be better understood.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.