Comparing Community Measures in Lake Microbial Ecology: Metagenomes and Metatranscriptomes and Amplicons, oh my!
Lake ecosystems are hotspots on Earth for biogeochemical cycling yet linking their microbiome to physicochemical parameters remains a challenge. Here, we assess the quality of 16S rRNA gene-based metatranscriptomics, assembled metagenomics and 16S rRNA gene amplicon sequencing for 21 lake ecosystems across Europe. We identified method-dependent, massive differences between community composition and proportional activity for key taxa like Alphaproteobacteria suggesting different ecological conclusions for the same lake ecosystems. In redundancy analysis (RDA), environmental parameters explained the greatest amount of the variance in metatranscriptomes suggesting that the active community is heavily influenced by environmental parameters. While amplicon data recruited the least amount of environmental variables in RDA (pH and temperature), four additional parameters explained the sequenced metagenomes. These results suggest that metagenomes and metatranscriptomes are currently the best methods for linking lake microbiomes to physicochemical parameters and can be used as proxies for designing future ecological surveys.
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Posted 19 May, 2020
Comparing Community Measures in Lake Microbial Ecology: Metagenomes and Metatranscriptomes and Amplicons, oh my!
Posted 19 May, 2020
Lake ecosystems are hotspots on Earth for biogeochemical cycling yet linking their microbiome to physicochemical parameters remains a challenge. Here, we assess the quality of 16S rRNA gene-based metatranscriptomics, assembled metagenomics and 16S rRNA gene amplicon sequencing for 21 lake ecosystems across Europe. We identified method-dependent, massive differences between community composition and proportional activity for key taxa like Alphaproteobacteria suggesting different ecological conclusions for the same lake ecosystems. In redundancy analysis (RDA), environmental parameters explained the greatest amount of the variance in metatranscriptomes suggesting that the active community is heavily influenced by environmental parameters. While amplicon data recruited the least amount of environmental variables in RDA (pH and temperature), four additional parameters explained the sequenced metagenomes. These results suggest that metagenomes and metatranscriptomes are currently the best methods for linking lake microbiomes to physicochemical parameters and can be used as proxies for designing future ecological surveys.
Figure 1
Figure 2