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Lignin, as an abundant organic carbon, plays a vital role in the global carbon cycle. However, our understanding of the global lignin-degrading microbiome remains elusive. The greatest barrier has been absence of a comprehensive and accurate functional gene database. Here, we first developed a curated functional gene database (LCdb) for metagenomic profiling of lignin degrading microbial consortia. Via the LCdb, we draw a clear picture describing the global biogeography of communities with lignin-degrading potential. They exhibit clear niche differentiation at the levels of taxonomy and functional traits. The terrestrial microbiomes showed the highest diversity, yet the lowest correlations. In particular, there were few correlations between genes involved in aerobic and anaerobic degradation pathways, showing a clear functional redundancy property. In contrast, enhanced correlations, especially closer inter-connections between anaerobic and aerobic groups, were observed in aquatic consortia in response to the lower diversity. Specifically, dypB and dypA, are widespread on Earth, indicating their essential roles in lignin depolymerization. Estuarine and marine consortia featured the laccase and mnsod genes, respectively. Notably, the roles of archaea in lignin degradation were revealed in marine ecosystems. Environmental factors strongly influenced functional traits, but weakly shaped taxonomic groups. Null mode analysis further verified that composition of functional traits was deterministic, while taxonomic composition was highly stochastic, demonstrating that the environment selects functional genes rather than taxonomic groups. Our study not only develops a useful tool to study lignin degrading microbial communities via metagenome sequencing but also advances our understanding of ecological traits of these global microbiomes., (© 2024 John Wiley & Sons Ltd.)

High-throughput profiling of microbial functional traits involved in various biogeochemical cycling pathways using shotgun metagenomic sequencing has been routinely applied in microbial ecology and environmental science. Multiple bioinformatics data processing approaches are available, including assembly-based (single-sample assembly and multi-sample assembly) and read-based (merged reads and raw data). However, it remains not clear how these different approaches may differ in data analyses and affect result interpretation. In this study, using two typical shotgun metagenome datasets recovered from geographically distant coastal sediments, the performance of different data processing approaches was comparatively investigated from both technical and biological/ecological perspectives. Microbially mediated biogeochemical cycling pathways, including nitrogen cycling, sulfur cycling and B12 biosynthesis, were analyzed. As a result, multi-sample assembly provided the most amount of usable information for targeted functional traits, at a high cost of computational resources and running time. Single-sample assembly and read-based analysis were comparable in obtaining usable information, but the former was much more time- and resource-consuming. Critically, different approaches introduced much stronger variations in microbial profiles than biological differences. However, community-level differences between the two sampling sites could be consistently observed despite the approaches being used. In choosing an appropriate approach, researchers shall balance the trade-offs between multiple factors, including the scientific question, the amount of usable information, computational resources and time cost. This study is expected to provide valuable technical insights and guidelines for the various approaches used for metagenomic data analysis., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Microorganisms play important roles in the biogeochemical cycling of sulphur (S), an essential element in the Earth's biosphere. Shotgun metagenome sequencing has opened a new avenue to advance our understanding of S cycling microbial communities. However, accurate metagenomic profiling of S cycling microbial communities remains technically challenging, mainly due to low coverage and inaccurate definition of S cycling gene families in public orthology databases. Here we developed a manually curated S cycling database (SCycDB) to profile S cycling functional genes and taxonomic groups for shotgun metagenomes. The developed SCycDB contains 207 gene families and 585,055 representative sequences affiliated with 52 phyla and 2684 genera of bacteria/archaea, and 20,761 homologous orthology groups were also included to reduce false positive sequence assignments. SCycDB was applied for functional and taxonomic analysis of S cycling microbial communities from four habitats (freshwater, hot spring, marine sediment and soil). Gene families and microorganisms involved in S reduction were abundant in the marine sediment, while those of S oxidation and dimethylsulphoniopropionate transformation were abundant in the soil. SCycDB is expected to be a useful tool for fast and accurate metagenomic analysis of S cycling microbial communities in the environment. [ABSTRACT FROM AUTHOR]