{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T13:20:28Z","timestamp":1780320028019,"version":"3.54.1"},"reference-count":65,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T00:00:00Z","timestamp":1652227200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100009092","name":"Universidad de Alicante","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009092","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:p>\n                    A comprehensive characterization of the human body resistome [sets of antibiotic resistance genes (ARGs)] is yet to be done and paramount for addressing the antibiotic microbial resistance threat. Here, we study the resistome of 771 samples from five major body parts (skin, nares, vagina, gut, and oral cavity) of healthy subjects from the Human Microbiome Project (HMP) and addressed the potential dispersion of ARGs in pristine environments. A total of 28,714 ARGs belonging to 235 different ARG types were found in the HMP proteome dataset (\n                    <jats:italic>n<\/jats:italic>\n                    = 9.1 \u00d7 10\n                    <jats:sup>7<\/jats:sup>\n                    proteins analyzed). Our study reveals a distinct resistome profile (ARG type and abundance) between body sites and high interindividual variability. Nares had the highest ARG load (\u22485.4 genes\/genome) followed by the oral cavity, whereas the gut showed one of the highest ARG richness (shared with nares) but the lowest abundance (\u22481.3 genes\/genome). The fluroquinolone resistance genes were the most abundant in the human body, followed by macrolide\u2013lincosamide\u2013streptogramin (MLS) or tetracycline. Most ARGs belonged to common bacterial commensals and multidrug resistance trait were predominant in the nares and vagina. Many ARGs detected here were considered as low risk for human health, whereas only a few of them, such as\n                    <jats:italic>BlaZ<\/jats:italic>\n                    ,\n                    <jats:italic>dfrA<\/jats:italic>\n                    14,\n                    <jats:italic>dfrA<\/jats:italic>\n                    17, or\n                    <jats:italic>tetM<\/jats:italic>\n                    , were classified as high-risk ARG. Our data also provide hope, since the spread of common ARG from the human body to pristine environments (\n                    <jats:italic>n<\/jats:italic>\n                    = 271 samples; 77 Gb of sequencing data and 2.1 \u00d7 10\n                    <jats:sup>8<\/jats:sup>\n                    proteins analyzed) thus far remains very unlikely (only one case found in an autochthonous bacterium from a pristine environment). These findings broaden our understanding of ARG in the context of the human microbiome and the One-Health Initiative of WHO uniting human host\u2013microbes and environments as a whole.\n                  <\/jats:p>","DOI":"10.3389\/fmicb.2022.858831","type":"journal-article","created":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T10:40:21Z","timestamp":1652265621000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":22,"title":["A Resistome Roadmap: From the Human Body to Pristine Environments"],"prefix":"10.3389","volume":"13","author":[{"given":"Lucia","family":"Maestre-Carballa","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vicente","family":"Navarro-L\u00f3pez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manuel","family":"Martinez-Garcia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2022,5,11]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1186\/s40168-018-0401-z","article-title":"DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.","volume":"6","author":"Arango-Argoty","year":"2018","journal-title":"Microbiome"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/82_2012_223","article-title":"One Health: Its Origins and Future.","volume":"365","author":"Atlas","year":"2012","journal-title":"Curr. 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