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Geochemical-Compositional-Functional Changes in Arctic Soil Microbiomes Post Land Submergence Revealed by Metagenomics.

Microbes and environments | 2019

Lakes of meltwater in the Artic have become one of the transforming landscape changes under global warming. We herein compared microbial communities between sediments and bank soils at an arctic lake post land submergence using geochemistry, 16S rRNA amplicons, and metagenomes. The results obtained showed that each sample had approximately 2,609 OTUs on average and shared 1,716 OTUs based on the 16S rRNA gene V3-V4 region. Dominant phyla in sediments and soils included Proteobacteria, Acidobacteria, Actinobacteria, Gemmatimonadetes, and Nitrospirae; sediments contained a unique phylum, Euryarchaeota, with the phylum Thaumarchaeota being primarily present in bank soils. Among the top 35 genera across all sites, 17 were more abundant in sediments, while the remaining 18 were more abundant in bank soils; seven out of the top ten genera across all sites were only from sediments. A redundancy analysis separated sediment samples from soil samples based on the components of nitrite and ammonium. Metagenome results supported the role of nitrite because most of the genes for denitrification and methane metabolic genes were more abundant in sediments than in soils, while the abundance of phosphorus-utilizing genes was similar and, thus, was not a significant explanatory factor. We identified several modules from the global networks of OTUs that were closely related to some geochemical factors, such as pH and nitrite. Collectively, the present results showing consistent changes in geochemistry, microbiome compositions, and functional genes suggest an ecological mechanism across molecular and community levels that structures microbiomes post land submergence.

Pubmed ID: 31178526 RIS Download

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This is a list of tools and resources that we have found mentioned in this publication.


Cytoscape (tool)

RRID:SCR_003032

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

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UPARSE (tool)

RRID:SCR_005020

An Operational Taxonomic Unit (OTU) clustering software for 16S and other marker genes. Highly accurate OTU sequences and improved diversity measures.

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CD-HIT (tool)

RRID:SCR_007105

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software program for clustering biological sequences with many applications in various fields such as making non-redundant databases, finding duplicates, identifying protein families, filtering sequence errors and improving sequence assembly etc. It is very fast and can handle extremely large databases. CD-HIT helps to significantly reduce the computational and manual efforts in many sequence analysis tasks and aids in understanding the data structure and correct the bias within a dataset. The CD-HIT package has CD-HIT, CD-HIT-2D, CD-HIT-EST, CD-HIT-EST-2D, CD-HIT-454, CD-HIT-PARA, PSI-CD-HIT, CD-HIT-OTU and over a dozen scripts. * CD-HIT (CD-HIT-EST) clusters similar proteins (DNAs) into clusters that meet a user-defined similarity threshold. * CD-HIT-2D (CD-HIT-EST-2D) compares 2 datasets and identifies the sequences in db2 that are similar to db1 above a threshold. * CD-HIT-454 identifies natural and artificial duplicates from pyrosequencing reads. * CD-HIT-OTU cluster rRNA tags into OTUs The usage of other programs and scripts can be found in CD-HIT user''s guide. CD-HIT was originally developed by Dr. Weizhong Li at Dr. Adam Godzik''s Lab at the Burnham Institute (now Sanford-Burnham Medical Research Institute).

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RRID:SCR_008249

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.

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DIAMOND (tool)

RRID:SCR_009457

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KEGG (tool)

RRID:SCR_012773

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

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New England Biolabs (tool)

RRID:SCR_013517

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