{"title":"来自 Kermadec 和 Diamantina Trenches 沉积物的元基因组测序和 982 个微生物基因组。","authors":"Yingdong Li, Hao Liu, Yao Xiao, Hongmei Jing","doi":"10.1038/s41597-024-03902-z","DOIUrl":null,"url":null,"abstract":"<p><p>Deep-sea trenches representing an intriguing ecosystem for exploring the survival and evolutionary strategies of microbial communities in the highly specialized deep-sea environments. Here, 29 metagenomes were obtained from sediment samples collected from Kermadec and Diamantina trenches. Notably, those samples covered a varying sampling depths (from 5321 m to 9415 m) and distinct layers within the sediment itself (from 0~40 cm in Kermadec trench and 0~24 cm in Diamantina trench). Through metagenomic binning process, we reconstructed 982 metagenome assembled genomes (MAGs) with completeness >60% and contamination <5%. Within them, completeness of 351 MAGs were >90%, while an additional 331 were >80%. Phylogenomic analysis for the MAGs revealed nearly all of them were distantly related to known cultivated isolates. The abundant bacterial MAGs affiliated to phyla of Proteobacteria, Planctomycetota, Nitrospirota, Acidobacteriota, Actinobacteriota, and Chlorofexota, while the abundant archaeal phyla affiliated with Nanoarchaeota and Thermoproteota. These results provide a dataset available for further interrogation of diversity, distribution and ecological function of deep-sea microbes existed in the trenches.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":null,"pages":null},"PeriodicalIF":5.8000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11445380/pdf/","citationCount":"0","resultStr":"{\"title\":\"Metagenome sequencing and 982 microbial genomes from Kermadec and Diamantina Trenches sediments.\",\"authors\":\"Yingdong Li, Hao Liu, Yao Xiao, Hongmei Jing\",\"doi\":\"10.1038/s41597-024-03902-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Deep-sea trenches representing an intriguing ecosystem for exploring the survival and evolutionary strategies of microbial communities in the highly specialized deep-sea environments. Here, 29 metagenomes were obtained from sediment samples collected from Kermadec and Diamantina trenches. Notably, those samples covered a varying sampling depths (from 5321 m to 9415 m) and distinct layers within the sediment itself (from 0~40 cm in Kermadec trench and 0~24 cm in Diamantina trench). Through metagenomic binning process, we reconstructed 982 metagenome assembled genomes (MAGs) with completeness >60% and contamination <5%. Within them, completeness of 351 MAGs were >90%, while an additional 331 were >80%. Phylogenomic analysis for the MAGs revealed nearly all of them were distantly related to known cultivated isolates. The abundant bacterial MAGs affiliated to phyla of Proteobacteria, Planctomycetota, Nitrospirota, Acidobacteriota, Actinobacteriota, and Chlorofexota, while the abundant archaeal phyla affiliated with Nanoarchaeota and Thermoproteota. These results provide a dataset available for further interrogation of diversity, distribution and ecological function of deep-sea microbes existed in the trenches.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11445380/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-024-03902-z\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-024-03902-z","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Metagenome sequencing and 982 microbial genomes from Kermadec and Diamantina Trenches sediments.
Deep-sea trenches representing an intriguing ecosystem for exploring the survival and evolutionary strategies of microbial communities in the highly specialized deep-sea environments. Here, 29 metagenomes were obtained from sediment samples collected from Kermadec and Diamantina trenches. Notably, those samples covered a varying sampling depths (from 5321 m to 9415 m) and distinct layers within the sediment itself (from 0~40 cm in Kermadec trench and 0~24 cm in Diamantina trench). Through metagenomic binning process, we reconstructed 982 metagenome assembled genomes (MAGs) with completeness >60% and contamination <5%. Within them, completeness of 351 MAGs were >90%, while an additional 331 were >80%. Phylogenomic analysis for the MAGs revealed nearly all of them were distantly related to known cultivated isolates. The abundant bacterial MAGs affiliated to phyla of Proteobacteria, Planctomycetota, Nitrospirota, Acidobacteriota, Actinobacteriota, and Chlorofexota, while the abundant archaeal phyla affiliated with Nanoarchaeota and Thermoproteota. These results provide a dataset available for further interrogation of diversity, distribution and ecological function of deep-sea microbes existed in the trenches.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.