Deconvoluting simulated metagenomes: The performance of hard- and softclustering algorithms applied to metagenomic chromosome conformation capture (3C)

© 2016 DeMaere and Darling. Background. Chromosome conformation capture, coupled with high throughputDNA sequencing in protocols like Hi-C and 3C-seq, has been proposed as a viable means of generating data to resolve the genomes of microorganisms living in naturally occuring environments. Metagenomic Hi-C and 3C-seq datasets have begun to emerge, but the feasibility of resolving genomes when closely related organisms (strain-level diversity) are present in the sample has not yet been systematically characterised. Methods. We developed a computational simulation pipeline for metagenomic 3C and Hi-C sequencing to evaluate the accuracy of genomic reconstructions at, above, and below an operationally defined species boundary. We simulated datasets and measured accuracy over a wide range of parameters. Five clustering algorithms were evaluated (2 hard, 3 soft) using an adaptation of the extended B-cubed validation measure. Results. When all genomes in a sample are below 95% sequence identity, all of the tested clustering algorithms performed well. When sequence data contains genomes above 95% identity (our operational definition of strain-level diversity), a naive soft- clustering extension of the Louvain method achieves the highest performance. Discussion. Previously, only hard-clustering algorithms have been applied to metage- nomic 3C and Hi-C data, yet none of these perform well when strain-level diversity exists in a metagenomic sample. Our simple extension of the Louvain method performed the best in these scenarios, however, accuracy remained well below the levels observed for samples without strain-level diversity. Strain resolution is also highly dependent on the amount of available 3C sequence data, suggesting that depth of sequencing must be carefully considered during experimental design. Finally, there appears to be great scope to improve the accuracy of strain resolution through further algorithm development

Bin3C: Exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes

© 2019 The Author(s). Most microbes cannot be easily cultured, and metagenomics provides a means to study them. Current techniques aim to resolve individual genomes from metagenomes, so-called metagenome-assembled genomes (MAGs). Leading approaches depend upon time series or transect studies, the efficacy of which is a function of community complexity, target abundance, and sequencing depth. We describe an unsupervised method that exploits the hierarchical nature of Hi-C interaction rates to resolve MAGs using a single time point. We validate the method and directly compare against a recently announced proprietary service, ProxiMeta. bin3C is an open-source pipeline and makes use of the Infomap clustering algorithm (https://github.com/cerebis/bin3C)

High contiguity genome sequence of a multidrug-resistant hospital isolate of Enterobacter hormaechei

© 2019 The Author(s). Background: Enterobacter hormaechei is an important emerging pathogen and a key member of the highly diverse Enterobacter cloacae complex. E. hormaechei strains can persist and spread in nosocomial environments, and often exhibit resistance to multiple clinically important antibiotics. However, the genomic regions that harbour resistance determinants are typically highly repetitive and impossible to resolve with standard short-read sequencing technologies. Results: Here we used both short- and long-read methods to sequence the genome of a multidrug-resistant hospital isolate (C15117), which we identified as E. hormaechei. Hybrid assembly generated a complete circular chromosome of 4,739,272 bp and a fully resolved plasmid of 339,920 bp containing several antibiotic resistance genes. The strain also harboured a 34,857 bp repeat encoding copper resistance, which was present in both the chromosome and plasmid. Long reads that unambiguously spanned this repeat were required to resolve the chromosome and plasmid into separate replicons. Conclusion: This study provides important insights into the evolution and potential spread of antimicrobial resistance in a nosocomial E. hormaechei strain. More broadly, it further exemplifies the power of long-read sequencing technologies, particularly the Oxford Nanopore platform, for the characterisation of bacteria with complex resistance loci and large repeat elements

Complete Sequences of Multiple-Drug Resistant IncHI2 ST3 Plasmids in Escherichia coli of Porcine Origin in Australia

© Copyright © 2019 Wyrsch, Reid, DeMaere, Liu, Chapman, Roy Chowdhury and Djordjevic. IncHI2 ST3 plasmids are known carriers of multiple antimicrobial resistance genes. Complete plasmid sequences from multiple drug resistant Escherichia coli circulating in Australian swine is however limited. Here we sequenced two related IncHI2 ST3 plasmids, pSDE-SvHI2, and pSDC-F2_12BHI2, from phylogenetically unrelated multiple-drug resistant Escherichia coli strains SvETEC (CC23:O157:H19) and F2_12B (ST93:O7:H4) from geographically disparate pig production operations in New South Wales, Australia. Unicycler was used to co-assemble short read (Illumina) and long read (PacBio SMRT) nucleotide sequence data. The plasmids encoded three drug-resistance loci, two of which carried class 1 integrons. One integron, hosting drfA12-orfF-aadA2, was within a hybrid Tn1721/Tn21, with the second residing within a copper/silver resistance transposon, comprising part of an atypical sul3-associated structure. The third resistance locus was flanked by IS15DI and encoded neomycin resistance (neoR). An oqx-encoding transposon (quinolone resistance), similar in structure to Tn6010, was identified only in pSDC-F2_12BHI2. Both plasmids showed high sequence identity to plasmid pSTM6-275, recently described in Salmonella enterica serotype 1,4,[5],12:i:- that has risen to prominence and become endemic in Australia. IncHI2 ST3 plasmids circulating in commensal and pathogenic E. coli from Australian swine belong to a lineage of plasmids often in association with sul3 and host multiple complex antibiotic and metal resistance structures, formed in part by IS26

A large-scale metagenomic survey dataset of the post-weaning piglet gut lumen

BackgroundEarly weaning and intensive farming practices predispose piglets to the development of infectious and often lethal diseases, against which antibiotics are used. Besides contributing to the build-up of antimicrobial resistance, antibiotics are known to modulate the gut microbial composition. As an alternative to antibiotic treatment, studies have previously investigated the potential of probiotics for the prevention of postweaning diarrhea. In order to describe the post-weaning gut microbiota, and to study the effects of two probiotics formulations and of intramuscular antibiotic treatment on the gut microbiota, we sampled and processed over 800 faecal time-series samples from 126 piglets and 42 sows.ResultsHere we report on the largest shotgun metagenomic dataset of the pig gut lumen microbiome to date, consisting of >8 Tbp of shotgun metagenomic sequencing data. The animal trial, the workflow from sample collection to sample processing, and the preparation of libraries for sequencing, are described in detail. We provide a preliminary analysis of the dataset, centered on a taxonomic profiling of the samples, and a 16S-based beta diversity analysis of the mothers and the piglets in the first 5 weeks after weaning.ConclusionsThis study was conducted to generate a publicly available databank of the faecal metagenome of weaner piglets aged between 3 and 9 weeks old, treated with different probiotic formulations and intramuscular antibiotic treatment. Besides investigating the effects of the probiotic and intramuscular antibiotic treatment, the dataset can be explored to assess a wide range of ecological questions with regards to antimicrobial resistance, host-associated microbial and phage communities, and their dynamics during the aging of the host

Metagenomic Hi-C of a Healthy Human Fecal Microbiome Transplant Donor.

We report the availability of a high-quality metagenomic Hi-C data set generated from a fecal sample taken from a healthy fecal microbiome transplant donor subject. We report on basic features of the data to evaluate their quality

Genomic variation and biogeography of Antarctic haloarchaea

© 2018 The Author(s). Background: The genomes of halophilic archaea (haloarchaea) often comprise multiple replicons. Genomic variation in haloarchaea has been linked to viral infection pressure and, in the case of Antarctic communities, can be caused by intergenera gene exchange. To expand understanding of genome variation and biogeography of Antarctic haloarchaea, here we assessed genomic variation between two strains of Halorubrum lacusprofundi that were isolated from Antarctic hypersaline lakes from different regions (Vestfold Hills and Rauer Islands). To assess variation in haloarchaeal populations, including the presence of genomic islands, metagenomes from six hypersaline Antarctic lakes were characterised. Results: The sequence of the largest replicon of each Hrr. lacusprofundi strain (primary replicon) was highly conserved, while each of the strains' two smaller replicons (secondary replicons) were highly variable. Intergenera gene exchange was identified, including the sharing of a type I-B CRISPR system. Evaluation of infectivity of an Antarctic halovirus provided experimental evidence for the differential susceptibility of the strains, bolstering inferences that strain variation is important for modulating interactions with viruses. A relationship was found between genomic structuring and the location of variation within replicons and genomic islands, demonstrating that the way in which haloarchaea accommodate genomic variability relates to replicon structuring. Metagenome read and contig mapping and clustering and scaling analyses demonstrated biogeographical patterning of variation consistent with environment and distance effects. The metagenome data also demonstrated that specific haloarchaeal species dominated the hypersaline systems indicating they are endemic to Antarctica. Conclusion: The study describes how genomic variation manifests in Antarctic-lake haloarchaeal communities and provides the basis for future assessments of Antarctic regional and global biogeography of haloarchaea

CAMISIM: Simulating metagenomes and microbial communities

© 2019 The Author(s). Background: 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. Results: 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. Conclusions: CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with standards of truth for method evaluation

qc3C: Reference-free quality control for Hi-C sequencing data.

Hi-C is a sample preparation method that enables high-throughput sequencing to capture genome-wide spatial interactions between DNA molecules. The technique has been successfully applied to solve challenging problems such as 3D structural analysis of chromatin, scaffolding of large genome assemblies and more recently the accurate resolution of metagenome-assembled genomes (MAGs). Despite continued refinements, however, preparing a Hi-C library remains a complex laboratory protocol. To avoid costly failures and maximise the odds of successful outcomes, diligent quality management is recommended. Current wet-lab methods provide only a crude assay of Hi-C library quality, while key post-sequencing quality indicators used have-thus far-relied upon reference-based read-mapping. When a reference is accessible, this reliance introduces a concern for quality, where an incomplete or inexact reference skews the resulting quality indicators. We propose a new, reference-free approach that infers the total fraction of read-pairs that are a product of proximity ligation. This quantification of Hi-C library quality requires only a modest amount of sequencing data and is independent of other application-specific criteria. The algorithm builds upon the observation that proximity ligation events are likely to create k-mers that would not naturally occur in the sample. Our software tool (qc3C) is to our knowledge the first to implement a reference-free Hi-C QC tool, and also provides reference-based QC, enabling Hi-C to be more easily applied to non-model organisms and environmental samples. We characterise the accuracy of the new algorithm on simulated and real datasets and compare it to reference-based methods

Simple high-throughput annotation pipeline (SHAP)

SHAP (simple high-throughput annotation pipeline) is a lightweight and scalable sequence annotation pipeline capable of supporting research efforts that generate or utilize large volumes of DNA sequence data. The software provides Grid capable analysis, relational storage and Web-based full-text searching of annotation results. Implemented in Java, SHAP recognizes the limited resources of many smaller research groups. © The Author 2011. Published by Oxford University Press. All rights reserved