April 21, 2020  |  

Global-level population genomics reveals differential effects of geography and phylogeny on horizontal gene transfer in soil bacteria.

Although microorganisms are known to dominate Earth’s biospheres and drive biogeochemical cycling, little is known about the geographic distributions of microbial populations or the environmental factors that pattern those distributions. We used a global-level hierarchical sampling scheme to comprehensively characterize the evolutionary relationships and distributional limitations of the nitrogen-fixing bacterial symbionts of the crop chickpea, generating 1,027 draft whole-genome sequences at the level of bacterial populations, including 14 high-quality PacBio genomes from a phylogenetically representative subset. We find that diverse Mesorhizobium taxa perform symbiosis with chickpea and have largely overlapping global distributions. However, sampled locations cluster based on the phylogenetic diversity of Mesorhizobium populations, and diversity clusters correspond to edaphic and environmental factors, primarily soil type and latitude. Despite long-standing evolutionary divergence and geographic isolation, the diverse taxa observed to nodulate chickpea share a set of integrative conjugative elements (ICEs) that encode the major functions of the symbiosis. This symbiosis ICE takes 2 forms in the bacterial chromosome-tripartite and monopartite-with tripartite ICEs confined to a broadly distributed superspecies clade. The pairwise evolutionary relatedness of these elements is controlled as much by geographic distance as by the evolutionary relatedness of the background genome. In contrast, diversity in the broader gene content of Mesorhizobium genomes follows a tight linear relationship with core genome phylogenetic distance, with little detectable effect of geography. These results illustrate how geography and demography can operate differentially on the evolution of bacterial genomes and offer useful insights for the development of improved technologies for sustainable agriculture.


April 21, 2020  |  

PacBio sequencing reveals bacterial community diversity in cheeses collected from different regions.

Cheese is a fermented dairy product that is popular for its unique flavor and nutritional value. Recent studies have shown that microorganisms in cheese play an important role in the fermentation process and determine the quality of the cheese. We collected 12 cheese samples from different regions and studied the composition of their bacterial communities using PacBio small-molecule real-time sequencing (Pacific Biosciences, Menlo Park, CA). Our data revealed 144 bacterial genera (including Lactobacillus, Streptococcus, Lactococcus, and Staphylococcus) and 217 bacterial species (including Lactococcus lactis, Streptococcus thermophilus, Staphylococcus equorum, and Streptococcus uberis). We investigated the flavor quality of the cheese samples using an electronic nose system and we found differences in flavor-quality indices among samples from different regions. We found a clustering tendency based on flavor quality using principal component analysis. We found correlations between lactic acid bacteria and the flavor quality of the cheese samples. Biodegradation and metabolism of xenobiotics, and lipid-metabolism-related pathways, were predicted to contribute to differences in cheese flavor using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). This preliminary study explored the bacterial communities in cheeses collected from different regions and their potential genome functions from the perspective of flavor quality.Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.


April 21, 2020  |  

Metagenomic assembly through the lens of validation: recent advances in assessing and improving the quality of genomes assembled from metagenomes.

Metagenomic samples are snapshots of complex ecosystems at work. They comprise hundreds of known and unknown species, contain multiple strain variants and vary greatly within and across environments. Many microbes found in microbial communities are not easily grown in culture making their DNA sequence our only clue into their evolutionary history and biological function. Metagenomic assembly is a computational process aimed at reconstructing genes and genomes from metagenomic mixtures. Current methods have made significant strides in reconstructing DNA segments comprising operons, tandem gene arrays and syntenic blocks. Shorter, higher-throughput sequencing technologies have become the de facto standard in the field. Sequencers are now able to generate billions of short reads in only a few days. Multiple metagenomic assembly strategies, pipelines and assemblers have appeared in recent years. Owing to the inherent complexity of metagenome assembly, regardless of the assembly algorithm and sequencing method, metagenome assemblies contain errors. Recent developments in assembly validation tools have played a pivotal role in improving metagenomics assemblers. Here, we survey recent progress in the field of metagenomic assembly, provide an overview of key approaches for genomic and metagenomic assembly validation and demonstrate the insights that can be derived from assemblies through the use of assembly validation strategies. We also discuss the potential for impact of long-read technologies in metagenomics. We conclude with a discussion of future challenges and opportunities in the field of metagenomic assembly and validation. © The Author 2017. Published by Oxford University Press.


April 21, 2020  |  

Metatranscriptomic evidence for classical and RuBisCO-mediated CO2 reduction to methane facilitated by direct interspecies electron transfer in a methanogenic system.

In a staged anaerobic fluidized-bed ceramic membrane bioreactor, metagenomic and metatranscriptomic analyses were performed to decipher the microbial interactions on the granular activated carbon. Metagenome bins, representing the predominating microbes in the bioreactor: syntrophic propionate-oxidizing bacteria (SPOB), acetoclastic Methanothrix concilii, and exoelectrogenic Geobacter lovleyi, were successfully recovered for the reconstruction and analysis of metabolic pathways involved in the transformation of fatty acids to methane. In particular, SPOB degraded propionate into acetate, which was further converted into methane and CO2 by M. concilii via the acetoclastic methanogenesis. Concurrently, G. lovleyi oxidized acetate into CO2, releasing electrons into the extracellular environment. By accepting these electrons through direct interspecies electron transfer (DIET), M. concilii was capable of performing CO2 reduction for further methane formation. Most notably, an alternative RuBisCO-mediated CO2 reduction (the reductive hexulose-phosphate (RHP) pathway) is transcriptionally-active in M. concilii. This RHP pathway enables M. concilii dominance and energy gain by carbon fixation and methanogenesis, respectively via a methyl-H4MPT intermediate, constituting the third methanogenesis route. The complete acetate reduction (2 mole methane formation/1 mole acetate consumption), coupling of acetoclastic methanogenesis and two CO2 reduction pathways, are thermodynamically favorable even under very low substrate condition (down to to 10-5?M level). Such tight interactions via both mediated and direct interspecies electron transfer (MIET and DIET), induced by the conductive GAC promote the overall efficiency of bioenergy processes.


April 21, 2020  |  

Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences.

Sequencing of DNA extracted from environmental samples can provide key insights into the biosynthetic potential of uncultured bacteria. However, the high complexity of soil metagenomes, which can contain thousands of bacterial species per gram of soil, imposes significant challenges to explore secondary metabolites potentially produced by rare members of the soil microbiome. Here, we develop a targeted sequencing workflow termed CONKAT-seq (co-occurrence network analysis of targeted sequences) that detects physically clustered biosynthetic domains, a hallmark of bacterial secondary metabolism. Following targeted amplification of conserved biosynthetic domains in a highly partitioned metagenomic library, CONKAT-seq evaluates amplicon co-occurrence patterns across library subpools to identify chromosomally clustered domains. We show that a single soil sample can contain more than a thousand uncharacterized biosynthetic gene clusters, most of which originate from low frequency genomes which are practically inaccessible through untargeted sequencing. CONKAT-seq allows scalable exploration of largely untapped biosynthetic diversity across multiple soils, and can guide the discovery of novel secondary metabolites from rare members of the soil microbiome.


April 21, 2020  |  

Strain-level metagenomic assignment and compositional estimation for long reads with MetaMaps.

Metagenomic sequence classification should be fast, accurate and information-rich. Emerging long-read sequencing technologies promise to improve the balance between these factors but most existing methods were designed for short reads. MetaMaps is a new method, specifically developed for long reads, capable of mapping a long-read metagenome to a comprehensive RefSeq database with >12,000 genomes in <16?GB or RAM on a laptop computer. Integrating approximate mapping with probabilistic scoring and EM-based estimation of sample composition, MetaMaps achieves >94% accuracy for species-level read assignment and r2?>?0.97 for the estimation of sample composition on both simulated and real data when the sample genomes or close relatives are present in the classification database. To address novel species and genera, which are comparatively harder to predict, MetaMaps outputs mapping locations and qualities for all classified reads, enabling functional studies (e.g. gene presence/absence) and detection of incongruities between sample and reference genomes.


April 21, 2020  |  

A Pathovar of Xanthomonas oryzae Infecting Wild Grasses Provides Insight Into the Evolution of Pathogenicity in Rice Agroecosystems

Xanthomonas oryzae (Xo) are critical rice pathogens. Virulent lineages from Africa and Asia and less virulent strains from the US have been well characterized. X. campestris pv. leersiae (Xcl), first described in 1957, causes bacterial streak on the perennial grass, Leersia hexandra, and is a close relative of Xo. L. hexandra, a member of the Poaceae, is highly similar to rice phylogenetically, is globally ubiquitous around rice paddies, and is a reservoir of pathogenic Xo. We used long read, single molecule, real time (SMRT) genome sequences of five strains of Xcl from Burkina Faso, China, Mali and Uganda to determine the genetic relatedness of this organism with Xo. Novel Transcription Activator-Like Effectors (TALEs) were discovered in all five strains of Xcl. Predicted TALE target sequences were identified in the L. perrieri genome and compared to rice susceptibility gene homologs. Pathogenicity screening on L. hexandra and diverse rice cultivars confirmed that Xcl are able to colonize rice and produce weak but not progressive symptoms. Overall, based on average nucleotide identity, type III effector repertoires and disease phenotype, we propose to rename Xcl to X. oryzae pv. leersiae (Xol) and use this parallel system to improve understanding of the evolution of bacterial pathogenicity in rice agroecosystems.


April 21, 2020  |  

Metaepigenomic analysis reveals the unexplored diversity of DNA methylation in an environmental prokaryotic community.

DNA methylation plays important roles in prokaryotes, and their genomic landscapes-prokaryotic epigenomes-have recently begun to be disclosed. However, our knowledge of prokaryotic methylation systems is focused on those of culturable microbes, which are rare in nature. Here, we used single-molecule real-time and circular consensus sequencing techniques to reveal the ‘metaepigenomes’ of a microbial community in the largest lake in Japan, Lake Biwa. We reconstructed 19 draft genomes from diverse bacterial and archaeal groups, most of which are yet to be cultured. The analysis of DNA chemical modifications in those genomes revealed 22 methylated motifs, nine of which were novel. We identified methyltransferase genes likely responsible for methylation of the novel motifs, and confirmed the catalytic specificities of four of them via transformation experiments using synthetic genes. Our study highlights metaepigenomics as a powerful approach for identification of the vast unexplored variety of prokaryotic DNA methylation systems in nature.


April 21, 2020  |  

Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation.

We describe a method that adds long-read sequencing to a mix of technologies used to assemble a highly complex cattle rumen microbial community, and provide a comparison to short read-based methods. Long-read alignments and Hi-C linkage between contigs support the identification of 188 novel virus-host associations and the determination of phage life cycle states in the rumen microbial community. The long-read assembly also identifies 94 antimicrobial resistance genes, compared to only seven alleles in the short-read assembly. We demonstrate novel techniques that work synergistically to improve characterization of biological features in a highly complex rumen microbial community.


April 21, 2020  |  

Long-read based de novo assembly of low-complexity metagenome samples results in finished genomes and reveals insights into strain diversity and an active phage system.

Complete and contiguous genome assemblies greatly improve the quality of subsequent systems-wide functional profiling studies and the ability to gain novel biological insights. While a de novo genome assembly of an isolated bacterial strain is in most cases straightforward, more informative data about co-existing bacteria as well as synergistic and antagonistic effects can be obtained from a direct analysis of microbial communities. However, the complexity of metagenomic samples represents a major challenge. While third generation sequencing technologies have been suggested to enable finished metagenome-assembled genomes, to our knowledge, the complete genome assembly of all dominant strains in a microbiome sample has not been demonstrated. Natural whey starter cultures (NWCs) are used in cheese production and represent low-complexity microbiomes. Previous studies of Swiss Gruyère and selected Italian hard cheeses, mostly based on amplicon metagenomics, concurred that three species generally pre-dominate: Streptococcus thermophilus, Lactobacillus helveticus and Lactobacillus delbrueckii.Two NWCs from Swiss Gruyère producers were subjected to whole metagenome shotgun sequencing using the Pacific Biosciences Sequel and Illumina MiSeq platforms. In addition, longer Oxford Nanopore Technologies MinION reads had to be generated for one to resolve repeat regions. Thereby, we achieved the complete assembly of all dominant bacterial genomes from these low-complexity NWCs, which was corroborated by a 16S rRNA amplicon survey. Moreover, two distinct L. helveticus strains were successfully co-assembled from the same sample. Besides bacterial chromosomes, we could also assemble several bacterial plasmids and phages and a corresponding prophage. Biologically relevant insights were uncovered by linking the plasmids and phages to their respective host genomes using DNA methylation motifs on the plasmids and by matching prokaryotic CRISPR spacers with the corresponding protospacers on the phages. These results could only be achieved by employing long-read sequencing data able to span intragenomic as well as intergenomic repeats.Here, we demonstrate the feasibility of complete de novo genome assembly of all dominant strains from low-complexity NWCs based on whole metagenomics shotgun sequencing data. This allowed to gain novel biological insights and is a fundamental basis for subsequent systems-wide omics analyses, functional profiling and phenotype to genotype analysis of specific microbial communities.


April 21, 2020  |  

Comparative Genomic Analyses Reveal Core-Genome-Wide Genes Under Positive Selection and Major Regulatory Hubs in Outlier Strains of Pseudomonas aeruginosa.

Genomic information for outlier strains of Pseudomonas aeruginosa is exiguous when compared with classical strains. We sequenced and constructed the complete genome of an environmental strain CR1 of P. aeruginosa and performed the comparative genomic analysis. It clustered with the outlier group, hence we scaled up the analyses to understand the differences in environmental and clinical outlier strains. We identified eight new regions of genomic plasticity and a plasmid pCR1 with a VirB/D4 complex followed by trimeric auto-transporter that can induce virulence phenotype in the genome of strain CR1. Virulence genotype analysis revealed that strain CR1 lacked hemolytic phospholipase C and D, three genes for LPS biosynthesis and had reduced antibiotic resistance genes when compared with clinical strains. Genes belonging to proteases, bacterial exporters and DNA stabilization were found to be under strong positive selection, thus facilitating pathogenicity and survival of the outliers. The outliers had the complete operon for the production of vibrioferrin, a siderophore present in plant growth promoting bacteria. The competence to acquire multidrug resistance and new virulence factors makes these strains a potential threat. However, we identified major regulatory hubs that can be used as drug targets against both the classical and outlier groups.


April 21, 2020  |  

CAMISIM: simulating metagenomes and microbial communities.

Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required.We describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series, and differential abundance studies, includes real and simulated strain-level diversity, and generates second- and third-generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes, we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT, and metaSPAdes, on several thousand small data sets generated with CAMISIM.CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with standards of truth for method evaluation. All data sets and the software are freely available at https://github.com/CAMI-challenge/CAMISIM.


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