Phylogenomics and genetic analysis of solvent-producing Clostridium species.

The genus Clostridium is a large and diverse group within the Bacillota (formerly Firmicutes), whose members can encode useful complex traits such as solvent production, gas-fermentation, and lignocellulose breakdown. We describe 270 genome sequences of solventogenic clostridia from a comprehensive industrial strain collection assembled by Professor David Jones that includes 194 C. beijerinckii, 57 C. saccharobutylicum, 4 C. saccharoperbutylacetonicum, 5 C. butyricum, 7 C. acetobutylicum, and 3 C. tetanomorphum genomes. We report methods, analyses and characterization for phylogeny, key attributes, core biosynthetic genes, secondary metabolites, plasmids, prophage/CRISPR diversity, cellulosomes and quorum sensing for the 6 species. The expanded genomic data described here will facilitate engineering of solvent-producing clostridia as well as non-model microorganisms with innately desirable traits. Sequences could be applied in conventional platform biocatalysts such as yeast or Escherichia coli for enhanced chemical production. Recently, gene sequences from this collection were used to engineer Clostridium autoethanogenum, a gas-fermenting autotrophic acetogen, for continuous acetone or isopropanol production, as well as butanol, butanoic acid, hexanol and hexanoic acid production.

Compendium of Metabolomic and Genomic Datasets for Cyanobacteria: Mined the Gap.

Cyanobacterial blooms, producing toxic secondary metabolites, are becoming increasingly common phenomena in the face of rising global temperatures. They are the world's most abundant photosynthetic organisms, largely owing their success to a range of highly diverse and complex natural products possessing a broad spectrum of different bioactivities. Over 2600 compounds have been isolated from cyanobacteria thus far, and their characterisation has revealed unusual and useful chemistries and motifs including alkynes, halogens, and non-canonical amino acids. Genome sequencing of cyanobacteria lags behind natural product isolation, with only 19% of cyanobacterial natural products associated with a sequenced organism. Recent advances in meta(genomics) provide promise to narrow this gap and has also facilitated the uprise of combined genomic and metabolomic approaches, heralding a new era of discovery of novel compounds. Analyses of the datasets described within this manuscript reveal the asynchrony of current genomic and metabolomic data, highlight the chemical diversity of cyanobacterial natural products. Linked to this manuscript, we make these manually curated datasets freely accessible for the public to facilitate further research in this important area.

Cytochromes P450 involved in bacterial RiPP biosyntheses.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a large class of secondary metabolites that have garnered scientific attention due to their complex scaffolds with potential roles in medicine, agriculture, and chemical ecology. RiPPs derive from the cleavage of ribosomally synthesized proteins and additional modifications, catalyzed by various enzymes to alter the peptide backbone or side chains. Of these enzymes, cytochromes P450 (P450s) are a superfamily of heme-thiolate proteins involved in many metabolic pathways, including RiPP biosyntheses. In this review, we focus our discussion on P450 involved in RiPP pathways and the unique chemical transformations they mediate. Previous studies have revealed a wealth of P450s distributed across all domains of life. While the number of characterized P450s involved in RiPP biosyntheses is relatively small, they catalyze various enzymatic reactions such as C-C or C-N bond formation. Formation of some RiPPs is catalyzed by more than one P450, enabling structural diversity. With the continuous improvement of the bioinformatic tools for RiPP prediction and advancement in synthetic biology techniques, it is expected that further cytochrome P450-mediated RiPP biosynthetic pathways will be discovered. SUMMARY: The presence of genes encoding P450s in gene clusters for ribosomally synthesized and post-translationally modified peptides expand structural and functional diversity of these secondary metabolites, and here, we review the current state of this knowledge.

Comparative and pangenomic analysis of the genus Streptomyces.

Streptomycetes are highly metabolically gifted bacteria with the abilities to produce bioproducts that have profound economic and societal importance. These bioproducts are produced by metabolic pathways including those for the biosynthesis of secondary metabolites and catabolism of plant biomass constituents. Advancements in genome sequencing technologies have revealed a wealth of untapped metabolic potential from Streptomyces genomes. Here, we report the largest Streptomyces pangenome generated by using 205 complete genomes. Metabolic potentials of the pangenome and individual genomes were analyzed, revealing degrees of conservation of individual metabolic pathways and strains potentially suitable for metabolic engineering. Of them, Streptomyces bingchenggensis was identified as a potent degrader of plant biomass. Polyketide, non-ribosomal peptide, and gamma-butyrolactone biosynthetic enzymes are primarily strain specific while ectoine and some terpene biosynthetic pathways are highly conserved. A large number of transcription factors associated with secondary metabolism are strain-specific while those controlling basic biological processes are highly conserved. Although the majority of genes involved in morphological development are highly conserved, there are strain-specific varieties which may contribute to fine tuning the timing of cellular differentiation. Overall, these results provide insights into the metabolic potential, regulation and physiology of streptomycetes, which will facilitate further exploitation of these important bacteria.

A centimeter-long bacterium with DNA contained in metabolically active, membrane-bound organelles.

Cells of most bacterial species are around 2 micrometers in length, with some of the largest specimens reaching 750 micrometers. Using fluorescence, x-ray, and electron microscopy in conjunction with genome sequencing, we characterized Candidatus (Ca.) Thiomargarita magnifica, a bacterium that has an average cell length greater than 9000 micrometers and is visible to the naked eye. These cells grow orders of magnitude over theoretical limits for bacterial cell size, display unprecedented polyploidy of more than half a million copies of a very large genome, and undergo a dimorphic life cycle with asymmetric segregation of chromosomes into daughter cells. These features, along with compartmentalization of genomic material and ribosomes in translationally active organelles bound by bioenergetic membranes, indicate gain of complexity in the Thiomargarita lineage and challenge traditional concepts of bacterial cells.

RIViT-seq enables systematic identification of regulons of transcriptional machineries.

Transcriptional regulation is a critical process to ensure expression of genes necessary for growth and survival in diverse environments. Transcription is mediated by multiple transcription factors including activators, repressors and sigma factors. Accurate computational prediction of the regulon of target genes for transcription factors is difficult and experimental identification is laborious and not scalable. Here, we demonstrate regulon identification by in vitro transcription-sequencing (RIViT-seq) that enables systematic identification of regulons of transcription factors by combining an in vitro transcription assay and RNA-sequencing. Using this technology, target genes of 11 sigma factors were identified in Streptomyces coelicolor A3(2). The RIViT-seq data expands the transcriptional regulatory network in this bacterium, discovering regulatory cascades and crosstalk between sigma factors. Implementation of RIViT-seq with other transcription factors and in other organisms will improve our understanding of transcriptional regulatory networks across biology.

Development of platforms for functional characterization and production of phenazines using a multi-chassis approach via CRAGE.

Phenazines (Phzs), a family of chemicals with a phenazine backbone, are secondary metabolites with diverse properties such as antibacterial, anti-fungal, or anticancer activity. The core derivatives of phenazine, phenazine-1-carboxylic acid (PCA) and phenazine-1,6-dicarboxylic acid (PDC), are themselves precursors for various other derivatives. Recent advances in genome mining tools have enabled researchers to identify many biosynthetic gene clusters (BGCs) that might produce novel Phzs. To characterize the function of these BGCs efficiently, we performed modular construct assembly and subsequent multi-chassis heterologous expression using chassis-independent recombinase-assisted genome engineering (CRAGE). CRAGE allowed rapid integration of a PCA BGC into 23 diverse γ-proteobacteria species and allowed us to identify top PCA producers. We then used the top five chassis hosts to express four partially refactored PDC BGCs. A few of these platforms produced high levels of PDC. Specifically, Xenorhabdus doucetiae and Pseudomonas simiae produced PDC at a titer of 293 mg/L and 373 mg/L, respectively, in minimal media. These titers are significantly higher than those previously reported. Furthermore, selectivity toward PDC production over PCA production was improved by up to 9-fold. The results show that these strains are promising chassis for production of PCA, PDC, and their derivatives, as well as for function characterization of Phz BGCs identified via bioinformatics mining.

Expanding the genomic encyclopedia of Actinobacteria with 824 isolate reference genomes.

The phylum Actinobacteria includes important human pathogens like Mycobacterium tuberculosis and Corynebacterium diphtheriae and renowned producers of secondary metabolites of commercial interest, yet only a small part of its diversity is represented by sequenced genomes. Here, we present 824 actinobacterial isolate genomes in the context of a phylum-wide analysis of 6,700 genomes including public isolates and metagenome-assembled genomes (MAGs). We estimate that only 30%-50% of projected actinobacterial phylogenetic diversity possesses genomic representation via isolates and MAGs. A comparison of gene functions reveals novel determinants of host-microbe interaction as well as environment-specific adaptations such as potential antimicrobial peptides. We identify plasmids and prophages across isolates and uncover extensive prophage diversity structured mainly by host taxonomy. Analysis of >80,000 biosynthetic gene clusters reveals that horizontal gene transfer and gene loss shape secondary metabolite repertoire across taxa. Our observations illustrate the essential role of and need for high-quality isolate genome sequences.

Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative's Workshop and Follow-On Activities.

Microbiome samples are inherently defined by the environment in which they are found. Therefore, data that provide context and enable interpretation of measurements produced from biological samples, often referred to as metadata, are critical. Important contributions have been made in the development of community-driven metadata standards; however, these standards have not been uniformly embraced by the microbiome research community. To understand how these standards are being adopted, or the barriers to adoption, across research domains, institutions, and funding agencies, the National Microbiome Data Collaborative (NMDC) hosted a workshop in October 2019. This report provides a summary of discussions that took place throughout the workshop, as well as outcomes of the working groups initiated at the workshop.

Tiny Earth: A Big Idea for STEM Education and Antibiotic Discovery.

The world faces two seemingly unrelated challenges-a shortfall in the STEM workforce and increasing antibiotic resistance among bacterial pathogens. We address these two challenges with Tiny Earth, an undergraduate research course that excites students about science and creates a pipeline for antibiotic discovery.

Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale.

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.

A genomic catalog of Earth's microbiomes.

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth's continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

IMG-ABC v.5.0: an update to the IMG/Atlas of Biosynthetic Gene Clusters Knowledgebase.

Microbial secondary metabolism is a reservoir of bioactive compounds of immense biotechnological and biomedical potential. The biosynthetic machinery responsible for the production of these secondary metabolites (SMs) (also called natural products) is often encoded by collocated groups of genes called biosynthetic gene clusters (BGCs). High-throughput genome sequencing of both isolates and metagenomic samples combined with the development of specialized computational workflows is enabling systematic identification of BGCs and the discovery of novel SMs. In order to advance exploration of microbial secondary metabolism and its diversity, we developed the largest publicly available database of predicted BGCs combined with experimentally verified BGCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc-public). Here we describe the first major content update of the IMG-ABC knowledgebase, since its initial release in 2015, refreshing the BGC prediction pipeline with the latest version of antiSMASH (v5) as well as presenting the data in the context of underlying environmental metadata sourced from GOLD (https://gold.jgi.doe.gov/). This update has greatly improved the quality and expanded the types of predicted BGCs compared to the previous version.

CRAGE enables rapid activation of biosynthetic gene clusters in undomesticated bacteria.

It is generally believed that exchange of secondary metabolite biosynthetic gene clusters (BGCs) among closely related bacteria is an important driver of BGC evolution and diversification. Applying this idea may help researchers efficiently connect many BGCs to their products and characterize the products' roles in various environments. However, existing genetic tools support only a small fraction of these efforts. Here, we present the development of chassis-independent recombinase-assisted genome engineering (CRAGE), which enables single-step integration of large, complex BGC constructs directly into the chromosomes of diverse bacteria with high accuracy and efficiency. To demonstrate the efficacy of CRAGE, we expressed three known and six previously identified but experimentally elusive non-ribosomal peptide synthetase (NRPS) and NRPS-polyketide synthase (PKS) hybrid BGCs from Photorhabdus luminescens in 25 diverse γ-Proteobacteria species. Successful activation of six BGCs identified 22 products for which diversity and yield were greater when the BGCs were expressed in strains closely related to the native strain than when they were expressed in either native or more distantly related strains. Activation of these BGCs demonstrates the feasibility of exploiting their underlying catalytic activity and plasticity, and provides evidence that systematic approaches based on CRAGE will be useful for discovering and identifying previously uncharacterized metabolites.