June 1, 2021  |  

An interactive workflow for the analysis of contigs from the metagenomic shotgun assembly of SMRT Sequencing data.

The data throughput of next-generation sequencing allows whole microbial communities to be analyzed using a shotgun sequencing approach. Because a key task in taking advantage of these data is the ability to cluster reads that belong to the same member in a community, single-molecule long reads of up to 30 kb from SMRT Sequencing provide a unique capability in identifying those relationships and pave the way towards finished assemblies of community members. Long reads become even more valuable as samples get more complex with lower intra-species variation, a larger number of closely related species, or high intra-species variation. Here we present a collection of tools tailored for PacBio data for the analysis of these fragmented metagenomic assembles, allowing improvements in the assembly results, and greater insight into the communities themselves. Supervised classification is applied to a large set of sequence characteristics, e.g., GC content, raw-read coverage, k-mer frequency, and gene prediction information, allowing the clustering of contigs from single or highly related species. A unique feature of SMRT Sequencing data is the availability of base modification / methylation information, which can be used to further analyze clustered contigs expected to be comprised of single or very closely related species. Here we show base modification information can be used to further study variation, based on differences in the methylated DNA motifs involved in the restriction modification system. Application of these techniques is demonstrated on a monkey intestinal microbiome sample and an in silico mix of real sequencing data from distinct bacterial samples.


June 1, 2021  |  

A workflow for the analysis of contigs from the metagenomic shotgun assembly of SMRT Sequencing data

The throughput of SMRT Sequencing and long reads allows microbial communities to be analyzed using a shotgun sequencing approach. Key to leveraging this data is the ability to cluster sequences belonging to the same member of a community. Long reads of up to 40 kb provide a unique capability in identifying those relationships, and pave the way towards finished assemblies of community members. Long reads are highly valuable when samples are more complex and containing lower intra-species variation, such as a larger number of closely related species, or high intra-species variation. Here, we present a collection of tools tailored for the analysis of PacBio metagenomic assemblies. These tools allow for improvements in the assembly results, and greater insight into the complexity of the study communities. Supervised classification is applied to a large set of sequence characteristics (e.g. GC content, raw read coverage, k-mer frequency, and gene prediction information) and to cluster contigs from single or highly related species. Assembly in isolation of the raw data associated with these contigs is shown to improve assembly statistics. A unique feature of SMRT Sequencing is the availability to leverage simultaneously collected base modification / methylation data to aid the clustering of contigs expected to comprise a single or very closely related species. We demonstrate the added value of base modification information to distinguish and study variation within metagenomic samples based on differences in the methylated DNA motifs involved in the restriction modification system. Application of these techniques is demonstrated on a mock community and monkey intestinal microbiome sample.


April 21, 2020  |  

A comparison of immunoglobulin IGHV, IGHD and IGHJ genes in wild-derived and classical inbred mouse strains.

The genomes of classical inbred mouse strains include genes derived from all three major subspecies of the house mouse, Mus musculus. We recently posited that genetic diversity in the immunoglobulin heavy chain (IGH) gene loci of C57BL/6 and BALB/c mice reflect differences in subspecies origin. To investigate this hypothesis, we conducted high-throughput sequencing of IGH gene rearrangements to document IGH variable (IGHV), joining (IGHJ), and diversity (IGHD) genes in four inbred wild-derived mouse strains (CAST/EiJ, LEWES/EiJ, MSM/MsJ, and PWD/PhJ), and a single disease model strain (NOD/ShiLtJ), collectively representing genetic backgrounds of several major mouse subspecies. A total of 341 germline IGHV sequences were inferred in the wild-derived strains, including 247 not curated in the International Immunogenetics Information System. In contrast, 83/84 inferred NOD IGHV genes had previously been observed in C57BL/6 mice. Variability among the strains examined was observed for only a single IGHJ gene, involving a description of a novel allele. In contrast, unexpected variation was found in the IGHD gene loci, with four previously unreported IGHD gene sequences being documented. Very few IGHV sequences of C57BL/6 and BALB/c mice were shared with strains representing major subspecies, suggesting that their IGH loci may be complex mosaics of genes of disparate origins. This suggests a similar level of diversity is likely present in the IGH loci of other classical inbred strains. This must now be documented if we are to properly understand inter-strain variation in models of antibody-mediated disease. This article is protected by copyright. All rights reserved.This article is protected by copyright. All rights reserved.


April 21, 2020  |  

How Genomics Is Changing What We Know About the Evolution and Genome of Bordetella pertussis.

The evolution of Bordetella pertussis from a common ancestor similar to Bordetella bronchiseptica has occurred through large-scale gene loss, inactivation and rearrangements, largely driven by the spread of insertion sequence element repeats throughout the genome. B. pertussis is widely considered to be monomorphic, and recent evolution of the B. pertussis genome appears to, at least in part, be driven by vaccine-based selection. Given the recent global resurgence of whooping cough despite the wide-spread use of vaccination, a more thorough understanding of B. pertussis genomics could be highly informative. In this chapter we discuss the evolution of B. pertussis, including how vaccination is changing the circulating B. pertussis population at the gene-level, and how new sequencing technologies are revealing previously unknown levels of inter- and intra-strain variation at the genome-level.


April 21, 2020  |  

Heterochromatin-enriched assemblies reveal the sequence and organization of the Drosophila melanogaster Y chromosome.

Heterochromatic regions of the genome are repeat-rich and poor in protein coding genes, and are therefore underrepresented in even the best genome assemblies. One of the most difficult regions of the genome to assemble are sex-limited chromosomes. The Drosophila melanogaster Y chromosome is entirely heterochromatic, yet has wide-ranging effects on male fertility, fitness, and genome-wide gene expression. The genetic basis of this phenotypic variation is difficult to study, in part because we do not know the detailed organization of the Y chromosome. To study Y chromosome organization in D. melanogaster, we develop an assembly strategy involving the in silico enrichment of heterochromatic long single-molecule reads and use these reads to create targeted de novo assemblies of heterochromatic sequences. We assigned contigs to the Y chromosome using Illumina reads to identify male-specific sequences. Our pipeline extends the D. melanogaster reference genome by 11.9 Mb, closes 43.8% of the gaps, and improves overall contiguity. The addition of 10.6 MB of Y-linked sequence permitted us to study the organization of repeats and genes along the Y chromosome. We detected a high rate of duplication to the pericentric regions of the Y chromosome from other regions in the genome. Most of these duplicated genes exist in multiple copies. We detail the evolutionary history of one sex-linked gene family, crystal-Stellate While the Y chromosome does not undergo crossing over, we observed high gene conversion rates within and between members of the crystal-Stellate gene family, Su(Ste), and PCKR, compared to genome-wide estimates. Our results suggest that gene conversion and gene duplication play an important role in the evolution of Y-linked genes. Copyright © 2019 Chang and Larracuente.


April 21, 2020  |  

MSC: a metagenomic sequence classification algorithm.

Metagenomics is the study of genetic materials directly sampled from natural habitats. It has the potential to reveal previously hidden diversity of microscopic life largely due to the existence of highly parallel and low-cost next-generation sequencing technology. Conventional approaches align metagenomic reads onto known reference genomes to identify microbes in the sample. Since such a collection of reference genomes is very large, the approach often needs high-end computing machines with large memory which is not often available to researchers. Alternative approaches follow an alignment-free methodology where the presence of a microbe is predicted using the information about the unique k-mers present in the microbial genomes. However, such approaches suffer from high false positives due to trading off the value of k with the computational resources. In this article, we propose a highly efficient metagenomic sequence classification (MSC) algorithm that is a hybrid of both approaches. Instead of aligning reads to the full genomes, MSC aligns reads onto a set of carefully chosen, shorter and highly discriminating model sequences built from the unique k-mers of each of the reference sequences.Microbiome researchers are generally interested in two objectives of a taxonomic classifier: (i) to detect prevalence, i.e. the taxa present in a sample, and (ii) to estimate their relative abundances. MSC is primarily designed to detect prevalence and experimental results show that MSC is indeed a more effective and efficient algorithm compared to the other state-of-the-art algorithms in terms of accuracy, memory and runtime. Moreover, MSC outputs an approximate estimate of the abundances.The implementations are freely available for non-commercial purposes. They can be downloaded from https://drive.google.com/open?id=1XirkAamkQ3ltWvI1W1igYQFusp9DHtVl. © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.


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  |  

Extended insight into the Mycobacterium chelonae-abscessus complex through whole genome sequencing of Mycobacterium salmoniphilum outbreak and Mycobacterium salmoniphilum-like strains.

Members of the Mycobacterium chelonae-abscessus complex (MCAC) are close to the mycobacterial ancestor and includes both human, animal and fish pathogens. We present the genomes of 14 members of this complex: the complete genomes of Mycobacterium salmoniphilum and Mycobacterium chelonae type strains, seven M. salmoniphilum isolates, and five M. salmoniphilum-like strains including strains isolated during an outbreak in an animal facility at Uppsala University. Average nucleotide identity (ANI) analysis and core gene phylogeny revealed that the M. salmoniphilum-like strains are variants of the human pathogen Mycobacterium franklinii and phylogenetically close to Mycobacterium abscessus. Our data further suggested that M. salmoniphilum separates into three branches named group I, II and III with the M. salmoniphilum type strain belonging to group II. Among predicted virulence factors, the presence of phospholipase C (plcC), which is a major virulence factor that makes M. abscessus highly cytotoxic to mouse macrophages, and that M. franklinii originally was isolated from infected humans make it plausible that the outbreak in the animal facility was caused by a M. salmoniphilum-like strain. Interestingly, M. salmoniphilum-like was isolated from tap water suggesting that it can be present in the environment. Moreover, we predicted the presence of mutational hotspots in the M. salmoniphilum isolates and 26% of these hotspots overlap with genes categorized as having roles in virulence, disease and defense. We also provide data about key genes involved in transcription and translation such as sigma factor, ribosomal protein and tRNA genes.


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  |  

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  |  

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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