Ruscheweyh, H.-J. | Search bioRxiv

bioRxiv2021

Critical Assessment of Metagenome Interpretation - the second round of challenges

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the community-driven initiative for the Critical Assessment of Metagenome Interpretation (CAMI). In its second challenge, CAMI engaged the community to assess their methods on realistic and complex metagenomic datasets with long and short reads, created from [~]1,700 novel and known microbial genomes, as well as [~]600 novel plasmids and viruses. Altogether 5,002 results by 76 program versions were analyzed, representing a 22x increase in results. Substantial improvements were seen in metagenome assembly, some due to using long-read data. The presence of related strains still was challenging for assembly and genome binning, as was assembly quality for the latter. Taxon profilers demonstrated a marked maturation, with taxon profilers and binners excelling at higher bacterial taxonomic ranks, but underperforming for viruses and archaea. Assessment of clinical pathogen detection techniques revealed a need to improve reproducibility. Analysis of program runtimes and memory usage identified highly efficient programs, including some top performers with other metrics. The CAMI II results identify current challenges, but also guide researchers in selecting methods for specific analyses.

bioinformatics↗

bioRxiv2021

Extended taxonomic profiling of diverse environments with mOTUs 2.6

BackgroundTaxonomic profiling is a fundamental task in microbiome research that aims to detect and quantify the relative abundance of microorganisms in biological samples. Available methods using shotgun metagenomic data generally depend on the availability of sequenced and taxonomically annotated reference genomes. However, the majority of microorganisms have not been cultured yet and lack such reference genomes. Thus, a substantial fraction of microbial community members remains unaccounted for during taxonomic profiling of metagenomes, particularly in samples from underexplored environments. To address this issue, we have developed the mOTU profiler, a tool that enables reference genome-independent species-level profiling of metagenomes. As such, it supports the identification and quantification of both "known" and "unknown" species based on a set of select marker genes. ResultsHere, we present mOTUs3, a command line tool that enables the profiling of metagenomes for >33,000 species-level operational taxonomic units. To achieve this, we leveraged the reconstruction and analysis of >600,000 draft genomes, most of which are metagenome assembled genomes (MAGs), from diverse microbiomes, including soil, freshwater systems, and the gastrointestinal tract of ruminants and other animals, which we found to be greatly underrepresented by reference genomes. Overall, two-thirds of all species-level taxa lacked a reference genome. The cumulative relative abundance of these newly included taxa was low in well-studied microbiomes, such as the human body sites (6-11%). By contrast, they accounted for substantial proportions (ocean, freshwater, soil: 43-63%) or even the vast majority (pig, fish, cattle: 60-80%) of the relative abundance across diverse non-human-associated microbiomes. Using community-developed benchmarks and datasets, we found mOTUs3 to be more accurate than other methods and to be more congruent with 16S rRNA gene-based methods for taxonomic profiling. Furthermore, we demonstrate that mOTUs3 greatly increases the resolution of well-known microbial groups into species-level taxa and helps identify new differentially abundant taxa in comparative metagenomic studies. ConclusionsWe developed mOTUs3 to enable accurate species-level profiling of metagenomes. Compared to other methods, it provides a more comprehensive view of prokaryotic community diversity, in particular for currently underexplored microbiomes. To facilitate comparative analyses by the research community, it is released with >11,000 precomputed profiles for publicly available metagenomes and is freely available at: https://github.com/motu-tool/mOTUs.

bioinformatics↗

bioRxiv2021

Uncharted biosynthetic potential of the ocean microbiome

Microbes are phylogenetically and metabolically diverse. Yet capturing this diversity, assigning functions to host organisms and exploring the biosynthetic potential in natural environments remains challenging. We reconstructed >25,000 draft genomes, including from >2,500 uncharacterized species, from globally-distributed ocean microbial communities, and combined them with [~]10,000 genomes from cultivated and single cells. Mining this resource revealed [~]40,000 putative biosynthetic gene clusters (BGCs), many from unknown phylogenetic groups. Among these, we discovered Candidatus Eudoremicrobiaceae as one of the most biosynthetically diverse microbes detected to date. Discrete transcriptional states structuring natural populations were associated with a potentially niche-partitioning role for BGC products. Together with the characterization of the first Eudoremicrobiaceae natural product, this study demonstrates how microbiomics enables prospecting for candidate bioactive compounds in underexplored microbes and environments.

microbiology↗