The ATCC Genome Portal: Microbial Genome Reference Standards with Data Provenance

Lack of data provenance negatively impacts scientific reproducibility and the reliability of genomic data. The ATCC Genome Portal ( https://genomes.atcc.org ) addresses this by providing data provenance information for microbial whole-genome assemblies originating from authenticated biological materials. To date, we have sequenced 1,579 complete genomes, including 466 type strains and 1,156 novel genomes.

Comparative evaluation of Nanopore polishing tools for microbial genome assembly and polishing strategies for downstream analysis

Assembling high-quality microbial genomes using only cost-effective Nanopore long-read systems such as Flongle is important to accelerate research on the microbial genome and the most critical point for this is the polishing process. In this study, we performed an evaluation based on BUSCO and Prokka gene prediction in terms of microbial genome assembly for eight state-of-the-art Nanopore polishing tools and combinations available. In the evaluation of individual tools, Homopolish, PEPPER, and Medaka demonstrated better results than others. In combination polishing, the second round Homopolish, and the PEPPER × medaka combination also showed better results than others. However, individual tools and combinations have specific limitations on usage and results. Depending on the target organism and the purpose of the downstream research, it is confirmed that there remain some difficulties in perfectly replacing the hybrid polishing carried out by the addition of a short-read. Nevertheless, through continuous improvement of the protein pores, related base-calling algorithms, and polishing tools based on improved error models, a high-quality microbial genome can be achieved using only Nanopore reads without the production of additional short-read data. The polishing strategy proposed in this study is expected to provide useful information for assembling the microbial genome using only Nanopore reads depending on the target microorganism and the purpose of the research.

Embracing Metagenomic Complexity with a Genome-Free Approach

A central paradigm in microbiome data analysis, which we term the genome-centric paradigm, is that a linear (nonbranching) DNA sequence is the ideal representation of a microbial genome. This representation is natural, as microbes indeed have nonbranching genomes.

Microbial Genome-Resolved Metaproteomic Analyses Frame Intertwined Carbon and Nitrogen Cycles in River Hyporheic Sediments

Background:Rivers serve as a nexus for nutrient transfer between terrestrial and marine ecosystems and as such, have a significant impact on global carbon and nitrogen cycles. In river ecosystems, the sediments found within the hyporheic zone are microbial hotspots that can account for a significant portion of ecosystem respiration and have profound impacts on system biogeochemistry. Despite this, studies using genome-resolved analyses linking microbial and viral communities to nitrogen and carbon biogeochemistry are limited.Results:Here, we characterized the microbial and viral communities of Columbia River hyporheic zone sediments to reveal the metabolisms that actively cycle carbon and nitrogen. Using genome-resolved metagenomics, we created the Hyporheic Uncultured Microbial and Viral (HUM-V) database, containing a dereplicated database of 55 microbial Metagenome-Assembled Genomes (MAGs), representing 12 distinct phyla. We also sampled 111 viral Metagenome Assembled Genomes (vMAGs) from 26 distinct and novel genera. The HUM-V recruited metaproteomes from these same samples, providing the first inventory of microbial gene expression in hyporheic zone sediments. Combining this data with metabolite data, we generated a conceptual model where heterotrophic and autotrophic metabolisms co-occur to drive an integrated carbon and nitrogen cycle, revealing microbial sources and sinks for carbon dioxide and ammonium in these sediments. We uncovered the metabolic handoffs underpinning these processes including mutualistic nitrification by Thermoproteota (formerly Thaumarchaeota) and Nitrospirota, as well as identified possible cooperative and cheating behavior impacting nitrogen mineralization. Finally, by linking vMAGs to microbial genome hosts, we reveal possible viral controls on microbial nitrification and organic carbon degradation.Conclusions:Our multi-omics analyses provide new mechanistic insight into coupled carbon-nitrogen cycling in the hyporheic zone. This is a key step in developing predictive hydrobiogeochemical models that account for microbial cross-feeding and viral influences over potential and expressed microbial metabolisms. Furthermore, the publicly available HUM-V genome resource can be queried and expanded by researchers working in other ecosystems to assess the transferability of our results to other parts of the globe.

A non-adaptive demographic mechanism for genome expansion in Streptomyces

The evolution of microbial genome size is driven by gene acquisition and loss events that occur at scales from individual genomes to entire pangenomes. The equilibrium between gene gain and loss is shaped by evolutionary forces, including selection and drift, which are in turn influenced by population demographics. There is a well-known bias towards deletion in microbial genomes, which promotes genome streamlining. Less well described are mechanisms that promote genome expansion, giving rise to the many microbes, such as Streptomyces, that have unusually large genomes. We find evidence of genome expansion in Streptomyces sister-taxa, and we hypothesize that a recent demographic range expansion drove increases in genome size through a non-adaptive mechanism. These Streptomyces sister-taxa, NDR (northern-derived) and SDR (southern-derived), represent recently diverged lineages that occupy distinct geographic ranges. Relative to SDR genomes, NDR genomes are larger, have more genes, and their genomes are enriched in intermediate frequency genes. We also find evidence of relaxed selection in NDR genomes relative to SDR genomes. We hypothesize that geographic range expansion, coupled with relaxed selection, facilitated the introgression of non-adaptive horizontally acquired genes, which accumulated at intermediate frequencies through a mechanism known as genome surfing. We show that similar patterns of pangenome structure and genome expansion occur in a simulation that models the effects of population expansion on genome dynamics. We show that non-adaptive evolutionary phenomena can explain expansion of microbial genome size, and suggest that this mechanism might explain why some bacteria with large genomes can be found in soil.

Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences

Novel antibiotics are urgently needed to address the looming global crisis of antibiotic resistance. Historically, the primary source of clinically used antibiotics has been microbial secondary metabolism. Microbial genome sequencing has revealed a plethora of uncharacterized natural antibiotics that remain to be discovered. However, the isolation of these molecules is hindered by the challenge of linking sequence information to the chemical structures of the encoded molecules. Here, we present PRISM 4, a comprehensive platform for prediction of the chemical structures of genomically encoded antibiotics, including all classes of bacterial antibiotics currently in clinical use. The accuracy of chemical structure prediction enables the development of machine-learning methods to predict the likely biological activity of encoded molecules. We apply PRISM 4 to chart secondary metabolite biosynthesis in a collection of over 10,000 bacterial genomes from both cultured isolates and metagenomic datasets, revealing thousands of encoded antibiotics. PRISM 4 is freely available as an interactive web application at http://prism.adapsyn.com.