The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes

Animal Microbiome

Software

Tamara Tal¹  Peter F. Stadler²  Ulisses Rocha³  João Pedro Saraiva³  Muhammad Kabiru Nata’ala⁴  Jonas Coelho Kasmanas⁵  Stephanie D. Jurburg⁶  Anderson Paulo Avila Santos⁷  Danilo Sipoli Sanches⁸  Alexander Bartholomäus⁹  Amélia Camarinha-Silva^1,10  Tina Keller-Costa^1,11  André Carlos Ponce de Leon Ferreira de Carvalho^1,12 

[1] Department of Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany;Department of Computer Science and Interdisciplinary Centre of Bioinformatics, University of Leipzig, Härtelstraße 16-18, 04107, Leipzig, Saxony, Germany;Max Planck Institute for Mathematics in the Sciences, Inselstraße, 04103, Leipzig, Germany;Institute for Theoretical Chemistry, Universität Wien, Währingerstraße 17, A-1090, Vienna, Austria;Center for Scalable Data Analytics and Artificial Intelligence Dresden-Leipzig, Leipzig University, Leipzig, Germany;Faculdad de Ciencias, Universidad Nacional de Colombia, Sede Bogotá, Bogotá, Colombia;Center for non-coding RNA in Technology and Health, University of Copenhagen, Frederiksberg, Denmark;The Santa Fe Institute, 1399 Hyde Park Rd., 87501, Santa Fe, NM, USA;Department of Environmental Microbiology, Helmholtz Centre for Environmental Research - UFZ GmbH, 04318, Leipzig, Germany;Department of Environmental Microbiology, Helmholtz Centre for Environmental Research - UFZ GmbH, 04318, Leipzig, Germany;Department of Computer Science and Interdisciplinary Centre of Bioinformatics, University of Leipzig, Härtelstraße 16-18, 04107, Leipzig, Saxony, Germany;Department of Environmental Microbiology, Helmholtz Centre for Environmental Research - UFZ GmbH, 04318, Leipzig, Germany;Department of Computer Science and Interdisciplinary Centre of Bioinformatics, University of Leipzig, Härtelstraße 16-18, 04107, Leipzig, Saxony, Germany;Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil;Department of Environmental Microbiology, Helmholtz Centre for Environmental Research - UFZ GmbH, 04318, Leipzig, Germany;German Centre of Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstraße 4, 04103, Leipzig, Germany;Department of Environmental Microbiology, Helmholtz Centre for Environmental Research - UFZ GmbH, 04318, Leipzig, Germany;Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil;Federal Univ. of Technology - Paraná (UTFPR), Cornélio Procópio, Brazil;GFZ German Research Centre for Geosciences, Section 3.7 Geomicrobiology, 14473, Telegrafenberg, Potsdam, Germany;Hohenheim Center for Livestock Microbiome Research (HoLMiR), University of Hohenheim, Stuttgart, Germany;Institute of Animal Science, University of Hohenheim, Stuttgart, Germany;Institute for Bioengineering and Biosciences (iBB) and Institute for Health and Bioeconomy (i4HB), Instituto Superior Tecnico (IST), Universidade de Lisboa, 1049-001, Lisbon, Portugal;Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil;

关键词: Metagenome;    Animal-Associated Microbiomes;    Microbial Ecology;    Metadata;    Database;    FAIR principles;   

DOI  :  10.1186/s42523-023-00267-3

 received in 2022-11-09, accepted in 2023-09-18,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundMetagenomic data can shed light on animal-microbiome relationships and the functional potential of these communities. Over the past years, the generation of metagenomics data has increased exponentially, and so has the availability and reusability of data present in public repositories. However, identifying which datasets and associated metadata are available is not straightforward. We created the Animal-Associated Metagenome Metadata Database (AnimalAssociatedMetagenomeDB - AAMDB) to facilitate the identification and reuse of publicly available non-human, animal-associated metagenomic data, and metadata. Further, we used the AAMDB to (i) annotate common and scientific names of the species; (ii) determine the fraction of vertebrates and invertebrates; (iii) study their biogeography; and (iv) specify whether the animals were wild, pets, livestock or used for medical research.ResultsWe manually selected metagenomes associated with non-human animals from SRA and MG-RAST.  Next, we standardized and curated 51 metadata attributes (e.g., host, compartment, geographic coordinates, and country). The AAMDB version 1.0 contains 10,885 metagenomes associated with 165 different species from 65 different countries. From the collected metagenomes, 51.1% were recovered from animals associated with medical research or grown for human consumption (i.e., mice, rats, cattle, pigs, and poultry). Further, we observed an over-representation of animals collected in temperate regions (89.2%) and a lower representation of samples from the polar zones, with only 11 samples in total. The most common genus among invertebrate animals was Trichocerca (rotifers).ConclusionOur work may guide host species selection in novel animal-associated metagenome research, especially in biodiversity and conservation studies. The data available in our database will allow scientists to perform meta-analyses and test new hypotheses (e.g., host-specificity, strain heterogeneity, and biogeography of animal-associated metagenomes), leveraging existing data. The AAMDB WebApp is a user-friendly interface that is publicly available at https://webapp.ufz.de/aamdb/.

【 授权许可】

CC BY   
© BioMed Central Ltd. 2023

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