AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data
Abstract Background Untargeted 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 wit...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-11-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-019-3176-8 |
| _version_ | 1818427003584380928 |
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| author | M. Shaffer K. Thurimella K. Quinn K. Doenges X. Zhang S. Bokatzian N. Reisdorph C. A. Lozupone |
| author_facet | M. Shaffer K. Thurimella K. Quinn K. Doenges X. Zhang S. Bokatzian N. Reisdorph C. A. Lozupone |
| author_sort | M. Shaffer |
| collection | DOAJ |
| description | Abstract Background Untargeted 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. Results We 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. Conclusions AMON 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. |
| first_indexed | 2024-12-14T14:38:49Z |
| format | Article |
| id | doaj.art-18f008e554d34004ba8c9d16f5cefe77 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-14T14:38:49Z |
| publishDate | 2019-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-18f008e554d34004ba8c9d16f5cefe772022-12-21T22:57:29ZengBMCBMC Bioinformatics1471-21052019-11-0120111110.1186/s12859-019-3176-8AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome dataM. Shaffer0K. Thurimella1K. Quinn2K. Doenges3X. Zhang4S. Bokatzian5N. Reisdorph6C. A. Lozupone7Department of Medicine, University of Colorado Anschutz Medical CampusDepartment of Medicine, University of Colorado Anschutz Medical CampusSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical CampusSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical CampusSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical CampusSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical CampusSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical CampusDepartment of Medicine, University of Colorado Anschutz Medical CampusAbstract Background Untargeted 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. Results We 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. Conclusions AMON 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.https://doi.org/10.1186/s12859-019-3176-8MicrobiomeMetabolomeData-integration |
| spellingShingle | M. Shaffer K. Thurimella K. Quinn K. Doenges X. Zhang S. Bokatzian N. Reisdorph C. A. Lozupone AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data BMC Bioinformatics Microbiome Metabolome Data-integration |
| title | AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data |
| title_full | AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data |
| title_fullStr | AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data |
| title_full_unstemmed | AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data |
| title_short | AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data |
| title_sort | amon annotation of metabolite origins via networks to integrate microbiome and metabolome data |
| topic | Microbiome Metabolome Data-integration |
| url | https://doi.org/10.1186/s12859-019-3176-8 |
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