期刊
PLOS ONE
卷 5, 期 11, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0015545
关键词
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资金
- Natural Environmental Research Council [NE/F00138X/1]
- NERC [pml010004, NE/F00138X/1, pml010009] Funding Source: UKRI
- Natural Environment Research Council [pml010004, NE/F00138X/1, pml010009, CEH010021] Funding Source: researchfish
How microbial communities change over time in response to the environment is poorly understood. Previously a six-year time series of 16S rRNA V6 data from the Western English Channel demonstrated robust seasonal structure within the bacterial community, with diversity negatively correlated with day-length. Here we determine whether metagenomes and metatranscriptomes follow similar patterns. We generated 16S rRNA datasets, metagenomes (1.2 GB) and metatranscriptomes (157 MB) for eight additional time points sampled in 2008, representing three seasons (Winter, Spring, Summer) and including day and night samples. This is the first microbial 'multi-omic' study to combine 16S rRNA amplicon sequencing with metagenomic and metatranscriptomic profiling. Five main conclusions can be drawn from analysis of these data: 1) Archaea follow the same seasonal patterns as Bacteria, but show lower relative diversity; 2) Higher 16S rRNA diversity also reflects a higher diversity of transcripts; 3) Diversity is highest in winter and at night; 4) Community-level changes in 16S-based diversity and metagenomic profiles are better explained by seasonal patterns (with samples closest in time being most similar), while metatranscriptomic profiles are better explained by diel patterns and shifts in particular categories (i.e., functional groups) of genes; 5) Changes in key genes occur among seasons and between day and night (i.e., photosynthesis); but these samples contain large numbers of orphan genes without known homologues and it is these unknown gene sets that appear to contribute most towards defining the differences observed between times. Despite the huge diversity of these microbial communities, there are clear signs of predictable patterns and detectable stability over time. Renewed and intensified efforts are required to reveal fundamental deterministic patterns in the most complex microbial communities. Further, the presence of a substantial proportion of orphan sequences underscores the need to determine the gene products of sequences with currently unknown function.
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