2019
DOI: 10.1101/599233
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Transcriptomic responses to warming and cooling of an Arctic tundra soil microbiome

Abstract: 6Background: Arctic surface soils experience pronounced seasonal changes in temperature

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Cited by 3 publications
(6 citation statements)
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“…A pronounced shift during the incubation period was noticed by Schostag et al. [14] that was not replicated by the assembly-free approach. However, using CoMW, we identified an increase of genes in the subsystem “[P] Inorganic ion transport and metabolism.” During cooling, CoMW also captured the upregulation and downregulation of genes related to “[J] Translation, ribosomal structure, and biogenesis” and “[C] Energy production and conversion,” respectively (Fig.…”
Section: Resultsmentioning
confidence: 89%
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“…A pronounced shift during the incubation period was noticed by Schostag et al. [14] that was not replicated by the assembly-free approach. However, using CoMW, we identified an increase of genes in the subsystem “[P] Inorganic ion transport and metabolism.” During cooling, CoMW also captured the upregulation and downregulation of genes related to “[J] Translation, ribosomal structure, and biogenesis” and “[C] Energy production and conversion,” respectively (Fig.…”
Section: Resultsmentioning
confidence: 89%
“…Three different protein databases were selected for this benchmarking in order to include a representative selection of 3 different degrees of specialization, on a range from a more inclusive database with wide coverage (universality) and low degree of expert curation to a smaller, highly curated database, with more narrow coverage: (i) M5nr [11], an inclusive and comprehensive non-redundant protein database in combination with Evolutionary Genealogy of Genes: Non-supervised Orthologous Groups (eggNOG) hierarchical annotation; (ii) Carbohydrate-Active Enzymes (CAZy) [12], a database dedicated to describing the families of structurally related catalytic and carbohydrate-binding modules of enzymes; and (iii) Nitrogen Cycling Database (NCycDB) [13], a specialized and manually curated database covering only nitrogen cycle genes. Finally, to estimate the consistency and variance in the results caused by the choice of approach, we then applied them to real-world metatranscriptomes from microbial communities in (i) active-layer permafrost soil from Svalbard, Norway [14], and (ii) ash-impacted Danish forest soil [15].…”
Section: Introductionmentioning
confidence: 99%
“…The recycling of cell wall components such as peptidoglycan from microbial necromass by microbes has been recognized as an important C and N source in soil (Basler et al, 2015;Guenet et al, 2011;Hu et al, 2017;Kindler et al, 2006). In addition, various studies have previously stressed the importance of C and nutrient release from vulnerable cells as energy and nutrient sources upon stressful stimuli like heat, radiation and freezethaw transitions (Mooshammer et al, 2017;Perez-Mon et al, 2020;Schostag, Anwar, et al, 2019;. Similar to the general functional annotation with eggNOG, genes within each CAZy family reacted very inconsistently, and highly increased genes were affiliated with a few abundant genera (Phenylobacterium, Caulobacter, Ralstonia and Dyella) that have previously been found to respond positively to high temperature (Donhauser et al, 2020;Jurburg, Nunes, Brejnrod, et al, 2017;Jurburg, Nunes, Stegen, et al, 2017).…”
Section: Changes In the Microbial C-cycling Potentialmentioning
confidence: 85%
“…The aim of the study was to understand taxonomic and functional shifts in microbial communities caused by climate change in the Arctic. A pronounced shift during the incubation period was noticed by Schostag et al [14] which was not replicated by the assembly-free approach. However, using CoMW, we identified an increase of genes in the subsystem “[P] Inorganic ion transport and metabolism”.…”
Section: Resultsmentioning
confidence: 87%
“…Three different protein databases were selected for this benchmarking in order to include a representative selection of three different degrees of specialization, on a range from a more inclusive database with wide coverage (universality) and low degree of expert curation, to a smaller, highly curated database, with more narrow coverage: 1) M5nr [11] an inclusive and comprehensive non-redundant protein database in combination with eggNOG hierarchical annotation 2) Carbohydrate-Active Enzymes (CAZymes) [12] a database dedicated to describing the families of structurally-related catalytic and carbohydrate-binding modules of enzymes and 3) Nitrogen Cycling Database (NCycDB) [13] a specialized and manually curated database covering only N cycle genes. Finally, in order to estimate the consistency and variance in the results caused by the choice of approach we then applied them to real world metatranscriptomes from microbial communities in 1) active-layer permafrost soil from Svalbard [14] and 2) Ash impacted Danish Forest soil [15].…”
Section: Introductionmentioning
confidence: 99%