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Aroney, S. T. N.

Publications and source records attributed to Aroney, S. T. N..

3 recordsLinked to original sources

Stable states in an unstable landscape: microbial resistance at the front line of climate change

Microbiome responses to warming may amplify or ameliorate terrestrial carbon loss and thus are a critical unknown in predicting climate outcomes. Because the rapid thaw of permafrost peatlands makes a very large store of soil carbon available to microbial metabolism, understanding microbiome dynamics in these systems is particularly urgent. We quantified microbial warming response over seven years across three habitats in a thawing permafrost peatland, using large-scale multi-omics data. We integrated analyses of organisms (via taxonomy), functions (via metabolic pathways and proteins), and community organization (via network structure and ecological assembly) to deeply characterize response mechanisms. We consistently found a pattern of within-habitat microbiome stability, with virtually no signal of gradual change in the warming period studied. The resistance to change appeared bolstered by habitat-specific dispersal processes and community-level functional redundancy, particularly via versatile carbon generalists. Our findings also reveal key genome-inferred metabolic processes that underlie microbiome stability. Together, our results highlight the importance of understanding the limits of these stabilizing processes and suggest that future research should reorient towards critical habitat transitions.

microbiology↗

Bin Chicken: targeted metagenomic coassembly for the efficient recovery of novel genomes

Recovery of microbial genomes from metagenomic datasets has provided genomic representation for hundreds of thousands of species from diverse biomes. However, low abundance microorganisms are often missed due to insufficient genomic coverage. Here we present Bin Chicken, an algorithm which substantially improves genome recovery through automated, targeted selection of metagenomes for coassembly based on shared marker gene sequences derived from raw reads. Marker gene sequences that are divergent from known reference genomes can be further prioritised, providing an efficient means of recovering highly novel genomes. Applying Bin Chicken to public metagenomes and coassembling 800 sample-groups recovered 77,562 microbial genomes, including the first genomic representatives of 6 phyla, 41 classes, and 24,028 species. These genomes expand the genomic tree of life and uncover a wealth of novel microbial lineages for further research.

microbiology↗

SingleM and Sandpiper: Robust microbial taxonomic profiles from metagenomic data

Determining the taxonomy and relative abundance of microorganisms in metagenomic data is a foundational problem in microbial ecology. To address the limitations of existing approaches, we developed SingleM, which estimates community composition using conserved regions within universal marker genes. SingleM accurately profiles complex communities of known microbial species, and is the only tool that detects species without genomic representation, even those representing novel phyla. Given SingleMs computational efficiency, we applied it to 248,559 publicly available metagenomes and show that the vast majority of samples from marine, freshwater, sediment and soil environments are dominated by novel species lacking genomic representation (median relative abundance 75.0%). SingleM also provides a way to identify metagenomes for the recovery of novel metagenome-assembled genomes from lineages of interest, and can incorporate user-recovered genomes into its reference database to improve profiling resolution. Quantifying the full diversity of Bacteria and Archaea in metagenomic data shows that microbial genome databases are far from saturated.

microbiology↗