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Updated: Jan 6, 2026

An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis
Published on: September 15, 2015
Bulk metagenomics and machine learning unravels nitrogen metabolism patterns in extreme-temperature marine
Zheng Guo1, Yong-Guang Li1, Xiao-Lin Liu2
1School of Environmental Science and Engineering, Shandong University, Qingdao, Shandong 266237, China.
Abstract:
The nitrogen metabolism genes and associated microorganisms in polar oceans and hydrothermal vents remain insufficiently studied. In this study, metagenomic data were analyzed to characterize the geographical and biological features of 16 key nitrogen-cycling genes. NasA/B, narG, and nxrB were consistently abundant in both environments. Polar oceans were dominated by common nitrogen-cycling taxa, whereas hydrothermal vents hosted species linked to sulfur and methane metabolism. Environmental extremes exerted a stronger influence on nitrogen cycling than depth. Distinct co-occurrence networks (centralized vs. redundant) and accurate habitat classification (>95 %) highlighted strong environmental shaping. Differences in amino acid preferences and enzyme thermal stability reflected evolutionary divergence and adaptation to extreme temperatures. Overall, depth and environmental conditions structured community networks, while genetic variation supported ecological adaptation. These findings reveal contrasting nitrogen-cycling strategies and adaptations, with potential implications for biotechnological applications.
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