Dick Jeffrey M, Tan Jingqiang
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha, 410083, China.
State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640, China.
Microb Ecol. 2023 May;85(4):1338-1355. doi: 10.1007/s00248-022-01988-9. Epub 2022 May 3.
Environmental influences on community structure are often assessed through multivariate analyses in order to relate microbial abundances to separately measured physicochemical variables. However, genes and proteins are themselves chemical entities; in combination with genome databases, differences in microbial abundances directly encode for chemical variability. We predicted that the carbon oxidation state of estimated community proteomes, obtained by combining taxonomic abundances from published 16S rRNA gene sequencing datasets with reference microbial proteomes from the NCBI Reference Sequence (RefSeq) database, would reflect environmental oxidation-reduction conditions. Analysis of multiple datasets confirms the geobiochemical predictions for environmental redox gradients in hydrothermal systems, stratified lakes and marine environments, and shale gas wells. The geobiochemical signal is largest for the steep redox gradients associated with hydrothermal systems and between injected water and produced fluids from shale gas wells, demonstrating that microbial community composition can be a chemical proxy for environmental redox gradients. Although estimates of oxidation state from 16S amplicon and metagenomic sequences are correlated, the 16S-based estimates show stronger associations with redox gradients in some environments.
环境对群落结构的影响通常通过多变量分析来评估，以便将微生物丰度与单独测量的物理化学变量联系起来。然而，基因和蛋白质本身就是化学实体；结合基因组数据库，微生物丰度的差异直接编码了化学变异性。我们预测，通过将已发表的16S rRNA基因测序数据集的分类丰度与NCBI参考序列（RefSeq）数据库中的参考微生物蛋白质组相结合而获得的估计群落蛋白质组的碳氧化态，将反映环境的氧化还原条件。对多个数据集的分析证实了对热液系统、分层湖泊和海洋环境以及页岩气井中的环境氧化还原梯度的地球生物化学预测。地球生物化学信号在与热液系统相关的陡峭氧化还原梯度以及页岩气井注入水和产出液之间最大，这表明微生物群落组成可以作为环境氧化还原梯度的化学替代指标。尽管基于16S扩增子和宏基因组序列的氧化态估计值是相关的，但在某些环境中，基于16S的估计值与氧化还原梯度的关联更强。
