<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY accession="ERP138831" alias="f79e5ece-d210-43a9-976b-dcf55fc770bc" center_name="Key Laboratory of Environmental and Applied Microbiology, CAS">
    <IDENTIFIERS>
      <PRIMARY_ID>ERP138831</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject">PRJEB54009</EXTERNAL_ID>
      <SUBMITTER_ID namespace="Key Laboratory of Environmental and Applied Microbiology, CAS">f79e5ece-d210-43a9-976b-dcf55fc770bc</SUBMITTER_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>Wildlife carcass and antibiotic resistome</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Other"/>
      <STUDY_ABSTRACT>Animal carcass decomposition may bring serious harm to the environment, including pathogenic viruses, toxic gases and metabolites, and antibiotic resistance genes (ARGs). However, there are few studies on the succession patterns and driving mechanism of ARG profiles during decomposition process of wild mammal corpses. Through metagenomics, 16S rRNA gene sequencing, and physicochemical analysis, this study explored the succession patterns, influencing factors, and assembly process of ARGs and mobile genetic elements (MGEs) in gravesoil during long-term corpse decomposition of wild mammals. Our results indicate that the ARG and MGE communities related to wildlife corpses exhibited a pattern of differentiation first and then convergence. The decomposition of wildlife corpses increased the temporal turnover of ARGs and MGEs. Different from the farmed animals, the decomposition of wildlife corpses first reduced the diversity of ARGs and MGEs, and then recovered to a level similar to that of the control group. ARGs and MGEs of the gravesoil are mainly affected by deterministic processes in different stages. MGEs and bacterial community are the two most important factors affecting ARGs in gravesoil. It is worth noting that the decomposition of wild animal carcasses enriched different opportunistic pathogens at different stages, which have co-occurrence patterns with high-risk ARGs, thereby posing a great threat to public health. These results are of great significance for wildlife corpse management and ecological safety.</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>Metagenomics on pika</CENTER_PROJECT_NAME>
      <STUDY_DESCRIPTION>Animal carcass decomposition may bring serious harm to the environment, including pathogenic viruses, toxic gases and metabolites, and antibiotic resistance genes (ARGs). However, there are few studies on the succession patterns and driving mechanism of ARG profiles during decomposition process of wild mammal corpses. Through metagenomics, 16S rRNA gene sequencing, and physicochemical analysis, this study explored the succession patterns, influencing factors, and assembly process of ARGs and mobile genetic elements (MGEs) in gravesoil during long-term corpse decomposition of wild mammals. Our results indicate that the ARG and MGE communities related to wildlife corpses exhibited a pattern of differentiation first and then convergence. The decomposition of wildlife corpses increased the temporal turnover of ARGs and MGEs. Different from the farmed animals, the decomposition of wildlife corpses first reduced the diversity of ARGs and MGEs, and then recovered to a level similar to that of the control group. ARGs and MGEs of the gravesoil are mainly affected by deterministic processes in different stages. MGEs and bacterial community are the two most important factors affecting ARGs in gravesoil. It is worth noting that the decomposition of wild animal carcasses enriched different opportunistic pathogens at different stages, which have co-occurrence patterns with high-risk ARGs, thereby posing a great threat to public health. These results are of great significance for wildlife corpse management and ecological safety.</STUDY_DESCRIPTION>
    </DESCRIPTOR>
    <STUDY_ATTRIBUTES>
      <STUDY_ATTRIBUTE>
        <TAG>ENA-FIRST-PUBLIC</TAG>
        <VALUE>2024-02-01</VALUE>
      </STUDY_ATTRIBUTE>
      <STUDY_ATTRIBUTE>
        <TAG>ENA-LAST-UPDATE</TAG>
        <VALUE>2024-02-01</VALUE>
      </STUDY_ATTRIBUTE>
    </STUDY_ATTRIBUTES>
  </STUDY>
</STUDY_SET>
