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Biology subjects

Liu, W.-T.

Publications and source records attributed to Liu, W.-T..

2 recordsLinked to original sources

Ecology and molecular targets of hypermutation in the global microbiome.

Changes in the sequence of an organisms genome, i.e. mutations, are the raw material of evolution1. The frequency and location of mutations can be constrained by specific molecular mechanisms, such as Diversity-generating retroelements (DGRs)2-4. DGRs introduce mutations in specific target genes, and were characterized from several cultivated bacteria and bacteriophages2. Whilst a larger diversity of DGR loci has been identified in genomic data from environmental samples, i.e. metagenomes, the ecological role of these DGRs and their associated evolutionary drivers remain poorly understood5-7. Here we built and analyzed an extensive dataset of >30,000 metagenome-derived DGRs, and determine that DGRs have a single evolutionary origin and a universal bias towards adenine mutations. We further identified six major lineages of DGRs, each associated with a specific ecological niche defined as a genome type, i.e. whether the DGR is encoded on a viral or cellular genome, a limited set of taxa and environments, and a distinct type of target. Finally, we leverage read mapping and metagenomic time series to demonstrate that DGRs are consistently and broadly active, and responsible for >10% of all amino acid changes in some organisms at a conservative estimate. Overall, these results highlight the strong constraints under which DGRs diversify and expand, and elucidate several distinct roles these elements play in natural communities and in shaping microbial community structure and function in our environment.

microbiology↗

Machine learning aided analyses of thousands of draft genomes reveal plant- and environment-specific features of activated sludge process

Microorganisms in activated sludge (AS) play key roles in the wastewater treatment process. However, the ecological behavior of microorganisms in AS and their differences with microorganisms in other environments have mainly been studied using 16S rRNA gene that may not truly represent their in-situ functions. Here, we present 2045 bacterial and archaeal metagenome-assembled genomes (MAGs) recovered from 1.35 Tb of metagenomic sequencing data generated from 114 AS samples of 23 full-scale wastewater treatment plants (WWTPs). The average completeness and contamination of the MAGs are 82.0% and 2.0%, respectively. We find that the AS MAGs have obviously plant-specific features and few proteins are shared by different WWTPs, especially for WWTPs located in geographically distant areas. Despite the differences, specific functional traits (e.g. functions related to aerobic metabolism, nutrient sensing/acquisition, biofilm formation, etc.) of AS MAGs could be identified by a machine learning approach, and based on these traits, AS MAGs could be differentiated from MAGs of other environments with an accuracy of 96.6%. Our work provides valuable genome resources for future investigation of the AS microbiome and also introduces a novel approach to understand the microbial ecology in different ecosystems.

microbiology↗