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Intensive farming practices can increase exposure of animals to infectious agents against which antibiotics are used. Orally administered antibiotics are well known to cause dysbiosis. To counteract dysbiotic effects, numerous studies in the past two decades sought to understand whether probiotics are a valid tool to help re-establish a healthy gut microbial community after antibiotic treatment. Although dysbiotic effects of antibiotics are well investigated, little is known about the effects of intramuscular antibiotic treatment on the gut microbiome and a few studies attempted to study treatment effects using phylogenetic diversity analysis techniques. In this study we sought to determine the effects of two probiotic- and one intramuscularly administered antibiotic treatment on the developing gut microbiome of post-weaning piglets between their 3rd and 9th week of life. Shotgun metagenomic sequences from over 800 faecal time-series samples derived from 126 post-weaning piglets and 42 sows were analysed in a phylogenetic framework. Differences between individual hosts such as breed, litter, and age, were found to be important contributors to variation in the community composition. Host age was the dominant factor in shaping the gut microbiota of piglets after weaning. The post-weaning pig gut microbiome appeared to follow a highly structured developmental program with characteristic post-weaning changes that can distinguish hosts that were born as little as two days apart in the second month of life. Treatment effects of the antibiotic and probiotic treatments were found but were subtle and included a higher representation of Mollicutes associated with intramuscular antibiotic treatment, and an increase of Lactobacillus associated with probiotic treatment. The discovery of correlations between experimental factors and microbial community composition is more commonly addressed with OTU-based methods and rarely analysed via phylogenetic diversity measures. The latter method, although less intuitive than the former, suffers less from library size normalization biases, and it proved to be instrumental in this study for the discovery of correlations between microbiome composition and host-, and treatment factors.

Prokaryotic evolution is influenced by the exchange of genetic information between species through a process referred to as recombination. The rate of recombination is a useful measure for the adaptive capacity of a prokaryotic population. We introduce Rhometa (https://github.com/sid-krish/Rhometa), a new software package to determine recombination rates from shotgun sequencing reads of metagenomes. It extends the composite likelihood approach for population recombination rate estimation and enables the analysis of modern short-read datasets. We evaluated Rhometa over a broad range of sequencing depths and complexities, using simulated and real experimental short-read data aligned to external reference genomes. Rhometa offers a comprehensive solution for determining population recombination rates from contemporary metagenomic read datasets. Rhometa extends the capabilities of conventional sequence-based composite likelihood population recombination rate estimators to include modern aligned metagenomic read datasets with diverse sequencing depths, thereby enabling the effective application of these techniques and their high accuracy rates to the field of metagenomics. Using simulated datasets, we show that our method performs well, with its accuracy improving with increasing numbers of genomes. Rhometa was validated on a real S. pneumoniae transformation experiment, where we show that it obtains plausible estimates of the rate of recombination. Finally, the program was also run on ocean surface water metagenomic datasets, through which we demonstrate that the program works on uncultured metagenomic datasets.

Using a previously described metagenomics dataset of 27 billion reads, we reconstructed over 50 000 metagenome-assembled genomes (MAGs) of organisms resident in the porcine gut, 46.5 % of which were classified as >70 % complete with a

Background Early 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. Results Here 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. Conclusions This 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.

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., Author summary The Hi-C sequencing technique offers the potential for significant scientific insight about the spatial arrangement of DNA, however achieving such outcomes is highly dependent on the quality of the resulting sequencing library. Unlike conventional next-gen sequencing, only a fraction of a given Hi-C library contains this useful spatial information (the signal) with the remainder being effectively noise. As Hi-C remains a challenging laboratory technique, signal strength of resulting libraries can vary greatly. As a quality metric, the quantification a library’s signal content is an essential asset in any quality mitigation strategy. Quality assessment of Hi-C data has until now relied on access to a (ideally refined) reference sequence, by which indirect indicators of quality are determined. Here we describe qc3C, a software tool capable of the direct, reference-free estimation of the signal content of a Hi-C library. In doing so, not only can researchers make informed decisions on how to progress based on library information content, but eliminating the reference also enables Hi-C quality management for non-model organism and metagenomics researchers.

Using a previously described metagenomics dataset of 27 billion reads, we reconstructed over 50,000 metagenome-assembled genomes (MAGs) of organisms resident in the porcine gut, 46.5% of which were classified as >70% complete with a

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. Studies have previously investigated the effects of probiotics as alternatives to antibiotic treatment for the prevention of post-weaning diarrhea. In order to describe the post-weaning gut microbiota, and the effects of two probiotics formulations and of intramuscular antibiotic treatment on the gut microbiota, we processed over 800 faecal time-series samples from 126 piglets and 42 sows, generating over 8Tbp of metagenomic shotgun sequence data. Here we describe the animal trial procedures, the generation of our metagenomic dataset and the analysis of the microbial community composition using a phylogenetic framework.ResultsFactors such as age, litter effects, and breed, by significantly correlating with gut microbial community shifts, can be major confounding factors in the assessment of treatment effects. Intramuscular antibiotic treatment and probiotic treatments were found to correlate with alpha and beta diversity, as well as with a transient establishment of Mollicutes and Lactobacillales, respectively. We found the abundance of certain taxa to correlate with weight gain.ConclusionsOur findings demonstrate that breed, litter, and age, are important contributors to variation in the community composition, and that treatment effects of the antibiotic and probiotic treatments were subtle, while host age was the dominant factor in shaping the gut microbiota of piglets after weaning. The current study shows, by means of a phylogenetic diversity framework, that the post-weaning pig gut microbiome appears to follow a highly structured developmental program with characteristic post-weaning changes that can distinguish hosts that were born as little as two days apart in the second month of life.

BackgroundIntensive farming practices can increase exposure of animals to infectious agents against which antibiotics are used. Besides leading to antimicrobial resistance (AMR), orally administered antibiotics are well known to cause dysbiosis. To counteract dysbiotic effects, numerous studies in the past two decades sought to understand whether probiotics are a valid tool to help re-establish a healthy gut microbial community after antibiotic treatment. However, although dysbiotic effects of antibiotics are well investigated, little is known about the effects of intramuscular antibiotic treatment on the gut microbiome and a few studies attempted to study treatment effects using phylogenetic diversity analysis techniques. In this study we sought to determine the effects of two probiotic- and one intramuscularly administered antibiotic treatment on the developing gut microbiome of post-weaning piglets between their 3rd and 9th week of life.MethodsShotgun metagenomic sequences from over 800 faecal time-series samples derived from 126 piglets and 42 sows were analysed in a phylogenetic framework to characterise the developing gut microbial community composition of post-weaning piglets. We assessed the effects of intramuscular antibiotic treatment and probiotic oral treatment on the diversity of these gut microbial communities using alpha and beta diversity measures.ResultsDifferences between individual hosts such as breed, litter, and age, were found to be important contributors to variation in the community composition. Host age was the dominant factor in shaping the gut microbiota of piglets after weaning. The post-weaning pig gut microbiome appeared to follow a highly structured developmental program with characteristic post-weaning changes that can distinguish hosts that were born as little as two days apart in the second month of life. Treatment effects of the antibiotic and probiotic treatments were found but were subtle and included a higher representation of Mollicutes associated with intramuscular antibiotic treatment, and an increase of Lactobacillus associated with probiotic treatment.DiscussionThe discovery of correlations between experimental factors and microbial community composition is more commonly addressed with OTU-based methods and rarely analysed via phylogenetic diversity measures. The latter method, although less intuitive than the former, suffers less from library size normalization biases, and it proved to be instrumental in this study for the discovery of correlations between microbiome composition and host-, and treatment factors.

© 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.

IncHI2-ST1 plasmids play an important role in co-mobilizing genes conferring resistance to critically important antibiotics and heavy metals. Here we present the identification and analysis of IncHI2-ST1 plasmid pSPRC-Echo1, isolated from an Enterobacter hormaechei strain from a Sydney hospital, which predates other multi-drug resistant IncHI2-ST1 plasmids reported from Australia. Our time-resolved phylogeny analysis indicates pSPRC-Echo1 represents a new lineage of IncHI2-ST1 plasmids and show how their diversification relates to the era of antibiotics.

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. Electronic supplementary material The online version of this article (10.1186/s40168-018-0495-3) contains supplementary material, which is available to authorized users.

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. All data sets and the software are freely available at https://github.com/CAMI-challenge/CAMISIM Electronic supplementary material The online version of this article (10.1186/s40168-019-0633-6) contains supplementary material, which is available to authorized users.

In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions.

BackgroundProfiling of microbial communities via metagenomic shotgun sequencing has enabled researches to gain unprecedented insight into microbial community structure and the functional roles of community members. This study describes a method and basic analysis for a metagenomic adaptation of the double digest restriction site associated DNA sequencing (ddRADseq) protocol for reduced representation metagenome profiling.MethodsThis technique takes advantage of the sequence specificity of restriction endonucleases to construct an Illumina-compatible sequencing library containing DNA fragments that are between a pair of restriction sites located within close proximity. This results in a reduced sequencing library with coverage breadth that can be tuned by size selection. We assessed the performance of the metagenomic ddRADseq approach by applying the full method to human stool samples and generating sequence data.ResultsThe ddRADseq data yields a similar estimate of community taxonomic profile as obtained from shotgun metagenome sequencing of the same human stool samples. No obvious bias with respect to genomic G + C content and the estimated relative species abundance was detected.DiscussionAlthough ddRADseq does introduce some bias in taxonomic representation, the bias is likely to be small relative to DNA extraction bias. ddRADseq appears feasible and could have value as a tool for metagenome-wide association studies.

© The Author(s) 2017. Background: Chromosome conformation capture (3C) and Hi-C DNA sequencing methods have rapidly advanced our understanding of the spatial organization of genomes and metagenomes. Many variants of these protocols have been developed, each with their own strengths. Currently there is no systematic means for simulating sequence data from this family of sequencing protocols, potentially hindering the advancement of algorithms to exploit this new datatype. Findings: We describe a computational simulator that, given simple parameters and reference genome sequences, will simulate Hi-C sequencing on those sequences. The simulator models the basic spatial structure in genomes that is commonly observed in Hi-C and 3C datasets, including the distance-decay relationship in proximity ligation, differences in the frequency of interaction within and across chromosomes, and the structure imposed by cells. A means to model the 3D structure of randomly generated topologically associating domains is provided. The simulator considers several sources of error common to 3C and Hi-C library preparation and sequencing methods, including spurious proximity ligation events and sequencing error. Conclusions: We have introduced the first comprehensive simulator for 3C and Hi-C sequencing protocols. We expect the simulator to have use in testing of Hi-C data analysis algorithms, as well as more general value for experimental design, where questions such as the required depth of sequencing, enzyme choice, and other decisions can be made in advance in order to ensure adequate statistical power with respect to experimental hypothesis testing.

BackgroundChromosome conformation capture (3C) and HiC DNA sequencing methods have rapidly advanced our understanding of the spatial organization of genomes and metagenomes. Many variants of these protocols have been developed, each with their own strengths. Currently there is no systematic means for simulating sequence data from this family of sequencing protocols.FindingsWe describe a computational simulator that, given reference genome sequences and some basic parameters, will simulate HiC sequencing on those sequences. The simulator models the basic spatial structure in genomes that is commonly observed in HiC and 3C datasets, including the distance-decay relationship in proximity ligation, differences in the frequency of interaction within and across chromosomes, and the structure imposed by cells. A means to model the 3D structure of topologically associating domains (TADs) is provided. The simulator also models several sources of error common to 3C and HiC library preparation and sequencing methods, including spurious proximity ligation events and sequencing error.ConclusionsWe have introduced the first comprehensive simulator for 3C and HiC sequencing protocols. We expect the simulator to have use in testing of HiC data analysis algorithms, as well as more general value for experimental design, where questions such as the required depth of sequencing, enzyme choice, and other decisions must be made in advance in order to ensure adequate statistical power to test the relevant hypotheses.

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions., Nature Methods, 14 (11), ISSN:1548-7105, ISSN:1548-7091

Deep Lake in Antarctica is a globally isolated, hypersaline system that remains liquid at temperatures down to -20 °C. By analyzing metagenome data and genomes of four isolates we assessed genome variation and patterns of gene exchange to learn how the lake community evolved. The lake is completely and uniformly dominated by haloarchaea, comprising a hierarchically structured, low-complexity community that differs greatly to temperate and tropical hypersaline environments. The four Deep Lake isolates represent distinct genera (~85% 16S rRNA gene similarity and ~73% genome average nucleotide identity) with genomic characteristics indicative of niche adaptation, and collectively account for ~72% of the cellular community. Network analysis revealed a remarkable level of intergenera gene exchange, including the sharing of long contiguous regions (up to 35 kb) of high identity (~100%). Although the genomes of closely related Halobacterium, Haloquadratum, and Haloarcula (>90% average nucleotide identity) shared regions of high identity between species or strains, the four Deep Lake isolates were the only distantly related haloarchaea to share long high-identity regions. Moreover, the Deep Lake high-identity regions did not match to any other hypersaline environment metagenome data. The most abundant species, tADL, appears to play a central role in the exchange of insertion sequences, but not the exchange of high-identity regions. The genomic characteristics of the four haloarchaea are consistent with a lake ecosystem that sustains a high level of intergenera gene exchange while selecting for ecotypes that maintain sympatric speciation. The peculiarities of this polar system restrict which species can grow and provide a tempo and mode for accentuating gene exchange.

Antarctica is arguably the world's most important continent for influencing the Earth's climate and ocean ecosystem function. The unique physico-chemical properties of the Southern Ocean enable high levels of microbial primary production to occur. This not only forms the base of a significant fraction of the global oceanic food web, but leads to the sequestration of anthropogenic CO2 and its transport to marine sediments, thereby removing it from the atmosphere; the Southern Ocean accounts for ~ 30% of global ocean uptake of CO2 despite representing ~ 10% of the total surface area of the global ocean. The Antarctic continent itself harbors some liquid water, including a remarkably diverse range of surface and subglacial lakes. Being one of the remaining natural frontiers, Antarctica delivers the paradox of needing to be protected from disturbance while requiring scientific endeavor to discover what is indigenous and learn how best to protect it. Moreover, like many natural environments on Earth, in Antarctica, microorganisms dominate the genetic pool and biomass of the colonizable niches and play the key roles in maintaining proper ecosystem function. This review puts into perspective insight that has been and can be gained about Antarctica's aquatic microbiota using molecular biology, and in particular, metagenomic approaches. Antarctica is arguably the world's most important continent for influencing the Earth's climate and ocean ecosystem function, and this review puts into perspective the insight that has been and can be gained about Antarctica's aquatic microbiota by using molecular biology, and in particular, metagenomic approaches. © 2012 Federation of European Microbiological Societies.

BackgroundChromosome conformation capture, coupled with high throughput DNA 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.MethodsWe 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.ResultsWhen 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.DiscussionPreviously, only hard-clustering algorithms have been applied to metagenomic 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.

Background Clostridium difficile infections (CDI) are a significant health problem to humans and food animals. Clostridial toxins ToxA and ToxB encoded by genes tcdA and tcdB are located on a pathogenicity locus known as the PaLoc and are the major virulence factors of C. difficile. While toxin-negative strains of C. difficile are often isolated from faeces of animals and patients suffering from CDI, they are not considered to play a role in disease. Toxin-negative strains of C. difficile have been used successfully to treat recurring CDI but their propensity to acquire the PaLoc via lateral gene transfer and express clinically relevant levels of toxins has reinforced the need to characterise them genetically. In addition, further studies that examine the pathogenic potential of toxin-negative strains of C. difficile and the frequency by which toxin-negative strains may acquire the PaLoc are needed. Results We undertook a comparative genomic analysis of five Australian toxin-negative isolates of C. difficile that lack tcdA, tcdB and both binary toxin genes cdtA and cdtB that were recovered from humans and farm animals with symptoms of gastrointestinal disease. Our analyses show that the five C. difficile isolates cluster closely with virulent toxigenic strains of C. difficile belonging to the same sequence type (ST) and have virulence gene profiles akin to those in toxigenic strains. Furthermore, phage acquisition appears to have played a key role in the evolution of C. difficile. Conclusions Our results are consistent with the C. difficile global population structure comprising six clades each containing both toxin-positive and toxin-negative strains. Our data also suggests that toxin-negative strains of C. difficile encode a repertoire of putative virulence factors that are similar to those found in toxigenic strains of C. difficile, raising the possibility that acquisition of PaLoc by toxin-negative strains poses a threat to human health. Studies in appropriate animal models are needed to examine the pathogenic potential of toxin-negative strains of C. difficile and to determine the frequency by which toxin-negative strains may acquire the PaLoc. Electronic supplementary material The online version of this article (doi:10.1186/s12866-016-0653-3) contains supplementary material, which is available to authorized users.

We performed a metagenomic survey (6.6 Gbp of 454 sequence data) of Southern Ocean (SO) microorganisms during the austral summer of 2007–2008, examining the genomic signatures of communities across a latitudinal transect from Hobart (44°S) to the Mertz Glacier, Antarctica (67°S). Operational taxonomic units (OTUs) of the SAR11 and SAR116 clades and the cyanobacterial genera Prochlorococcus and Synechococcus were strongly overrepresented north of the Polar Front (PF). Conversely, OTUs of the Gammaproteobacterial Sulfur Oxidizer-EOSA-1 (GSO-EOSA-1) complex, the phyla Bacteroidetes and Verrucomicrobia and order Rhodobacterales were characteristic of waters south of the PF. Functions enriched south of the PF included a range of transporters, sulfur reduction and histidine degradation to glutamate, while branched-chain amino acid transport, nucleic acid biosynthesis and methionine salvage were overrepresented north of the PF. The taxonomic and functional characteristics suggested a shift of primary production from cyanobacteria in the north to eukaryotic phytoplankton in the south, and reflected the different trophic statuses of the two regions. The study provides a new level of understanding about SO microbial communities, describing the contrasting taxonomic and functional characteristics of microbial assemblages either side of the PF.

Most proteins adopt a well defined three-dimensional structure; however, it is increasingly recognized that some proteins can exist with at least two stable conformations. Recently, a class of intracellular chloride ion channel proteins (CLICs) has been shown to exist in both soluble and integral membrane forms. The structure of the soluble form of CLIC1 is typical of a soluble glutathione S-transferase superfamily protein but contains a glutaredoxin-like active site. In this study we show that on oxidation CLIC1 undergoes a reversible transition from a monomeric to a non-covalent dimeric state due to the formation of an intramolecular disulfide bond (Cys-24-Cys-59). We have determined the crystal structure of this oxidized state and show that a major structural transition has occurred, exposing a large hydrophobic surface, which forms the dimer interface. The oxidized CLIC1 dimer maintains its ability to form chloride ion channels in artificial bilayers and vesicles, whereas a reducing environment prevents the formation of ion channels by CLIC1. Mutational studies show that both Cys-24 and Cys-59 are required for channel activity.

Deep Lake in Antarctica is a cold, hypersaline system where four types of haloarchaea representing distinct genera comprise >70% of the lake community: strain tADL ∼44%, strain DL31 ∼18%, Halorubrum lacusprofundi ∼10% and strain DL1 ∼0.3%. By performing comparative genomics, growth substrate assays, and analyses of distribution by lake depth, size partitioning and lake nutrient composition, we were able to infer important metabolic traits and ecophysiological characteristics of the four Antarctic haloarchaea that contribute to their hierarchical persistence and coexistence in Deep Lake. tADL is characterized by a capacity for motility via flagella (archaella) and gas vesicles, a highly saccharolytic metabolism, a preference for glycerol, and photoheterotrophic growth. In contrast, DL31 has a metabolism specialized in processing proteins and peptides, and appears to prefer an association with particulate organic matter, while lacking the genomic potential for motility. H. lacusprofundi is the least specialized, displaying a genomic potential for the utilization of diverse organic substrates. The least abundant species, DL1, is characterized by a preference for catabolism of amino acids, and is the only one species that lacks genes needed for glycerol degradation. Despite the four haloarchaea being distributed throughout the water column, our analyses describe a range of distinctive features, including preferences for substrates that are indicative of ecological niche partitioning. The individual characteristics could be responsible for shaping the composition of the haloarchaeal community throughout the lake by enabling selection of ecotypes and maintaining sympatric speciation. © 2014 International Society for Microbial Ecology All rights reserved.

CLIC1 (NCC27) is a member of the highly conserved class of chloride ion channels that exists in both soluble and integral membrane forms. Purified CLIC1 can integrate into synthetic lipid bilayers forming a chloride channel with similar properties to those observed in vivo. The structure of the soluble form of CLIC1 has been determined at 1.4-A resolution. The protein is monomeric and structurally homologous to the glutathioneS-transferase superfamily, and it has a redox-active site resembling glutaredoxin. The structure of the complex of CLIC1 with glutathione shows that glutathione occupies the redox-active site, which is adjacent to an open, elongated slot lined by basic residues. Integration of CLIC1 into the membrane is likely to require a major structural rearrangement, probably of the N-domain (residues 1–90), with the putative transmembrane helix arising from residues in the vicinity of the redox-active site. The structure indicates that CLIC1 is likely to be controlled by redox-dependent processes.

Organic Lake is a shallow, marine-derived hypersaline lake in the Vestfold Hills, Antarctica that has the highest reported concentration of dimethylsulfide (DMS) in a natural body of water. To determine the composition and functional potential of the microbial community and learn about the unusual sulfur chemistry in Organic Lake, shotgun metagenomics was performed on size-fractionated samples collected along a depth profile. Eucaryal phytoflagellates were the main photosynthetic organisms. Bacteria were dominated by the globally distributed heterotrophic taxa Marinobacter, Roseovarius and Psychroflexus. The dominance of heterotrophic degradation, coupled with low fixation potential, indicates possible net carbon loss. However, abundant marker genes for aerobic anoxygenic phototrophy, sulfur oxidation, rhodopsins and CO oxidation were also linked to the dominant heterotrophic bacteria, and indicate the use of photo- and lithoheterotrophy as mechanisms for conserving organic carbon. Similarly, a high genetic potential for the recycling of nitrogen compounds likely functions to retain fixed nitrogen in the lake. Dimethylsulfoniopropionate (DMSP) lyase genes were abundant, indicating that DMSP is a significant carbon and energy source. Unlike marine environments, DMSP demethylases were less abundant, indicating that DMSP cleavage is the likely source of high DMS concentration. DMSP cleavage, carbon mixotrophy (photoheterotrophy and lithoheterotrophy) and nitrogen remineralization by dominant Organic Lake bacteria are potentially important adaptations to nutrient constraints. In particular, carbon mixotrophy relieves the extent of carbon oxidation for energy production, allowing more carbon to be used for biosynthetic processes. The study sheds light on how the microbial community has adapted to this unique Antarctic lake environment. © 2013 International Society for Microbial Ecology.

The ubiquitous SAR11 bacterial clade is the most abundant type of organism in the world’s oceans, but the reasons for its success are not fully elucidated. We analysed 128 surface marine metagenomes, including 37 new Antarctic metagenomes. The large size of the data set enabled internal transcribed spacer (ITS) regions to be obtained from the Southern polar region, enabling the first global characterization of the distribution of SAR11, from waters spanning temperatures � 2t o 301C. Our data show a stable co-occurrence of phylotypes within both ‘tropical’ (4201C) and ‘polar’ (o101C) biomes, highlighting ecological niche differentiation between major SAR11 subgroups. All phylotypes display transitions in abundance that are strongly correlated with temperature and latitude. By assembling SAR11 genomes from Antarctic metagenome data, we identified specific genes, biases in gene functions and signatures of positive selection in the genomes of the polar SAR11—genomic signatures of adaptive radiation. Our data demonstrate the importance of adaptive radiation in the organism’s ability to proliferate throughout the world’s oceans, and describe genomic traits characteristic of different phylotypes in specific marine biomes. Molecular Systems Biology 8: 595; published online 17 July 2012; doi:10.1038/msb.2012.28

In nature, the complexity and structure of microbial communities varies widely, ranging from a few species to thousands of species, and from highly structured to highly unstructured communities. Here, we describe the identity and functional capacity of microbial populations within distinct layers of a pristine, marine-derived, meromictic (stratified) lake (Ace Lake) in Antarctica. Nine million open reading frames were analyzed, representing microbial samples taken from six depths of the lake size fractionated on sequential 3.0, 0.8 and 0.1 m filters, and including metaproteome data from matching 0.1 m filters. We determine how the interactions of members of this highly structured and moderately complex community define the biogeochemical fluxes throughout the entire lake. Our view is that the health of this delicate ecosystem is dictated by the effects of the polar light cycle on the dominant role of green sulfur bacteria in primary production and nutrient cycling, and the influence of viruses/phage and phage resistance on the cooperation between members of the microbial community right throughout the lake. To test our assertions, and develop a framework applicable to other microbially driven ecosystems, we developed a mathematical model that describes how cooperation within a microbial system is impacted by periodic fluctuations in environmental parameters on key populations of microorganisms. Our study reveals a mutualistic structure within the microbial community throughout the lake that has arisen as the result of mechanistic interactions between the physico-chemical parameters and the selection of individual members of the community. By exhaustively describing and modelling interactions in Ace Lake, we have developed an approach that may be applicable to learning how environmental perturbations affect the microbial dynamics in more complex aquatic systems. © 2011 International Society for Microbial Ecology All rights reserved.

Sponges form close relationships with bacteria, and a remarkable phylogenetic diversity of yet-uncultured bacteria has been identified from sponges using molecular methods. In this study, we use a comparative metagenomic analysis of the bacterial community in the model sponge Cymbastela concentrica and in the surrounding seawater to identify previously unrecognized genomic signatures and functions for sponge bacteria. We observed a surprisingly large number of transposable insertion elements, a feature also observed in other symbiotic bacteria, as well as a set of predicted mechanisms that may defend the sponge community against the introduction of foreign DNA and hence contribute to its genetic resilience. Moreover, several shared metabolic interactions between bacteria and host include vitamin production, nutrient transport and utilization, and redox sensing and response. Finally, an abundance of protein–protein interactions mediated through ankyrin and tetratricopeptide repeat proteins could represent a mechanism for the sponge to discriminate between food and resident bacteria. These data provide new insight into the evolution of symbiotic diversity, microbial metabolism and host–microbe interactions in sponges.

Green sulfur bacteria (GSB) (Chlorobiaceae) are primary producers that are important in global carbon and sulfur cycling in natural environments. An almost complete genome sequence for a single, dominant GSB species ('C-Ace') was assembled from shotgun sequence data of an environmental sample taken from the O(2)-H(2)S interface of the water column of Ace Lake, Antarctica. Approximately 34 Mb of DNA sequence data were assembled into nine scaffolds totaling 1.79 Mb, representing approximately 19-fold coverage for the C-Ace composite genome. A high level ( approximately 31%) of metaproteomic coverage was achieved using matched biomass. The metaproteogenomic approach provided unique insight into the protein complement required for dominating the microbial community under cold, nutrient-limited, oxygen-limited and extremely varied annual light conditions. C-Ace shows physiological traits that promote its ability to compete very effectively with other GSB and gain dominance (for example, specific bacteriochlorophylls, mechanisms of cold adaptation) as well as a syntrophic relationship with sulfate-reducing bacteria that provides a mechanism for the exchange of sulfur compounds. As a result we are able to propose an explanation of the active biological processes promoted by cold-adapted GSB and the adaptive strategies they use to thrive under the severe physiochemical conditions prevailing in polar environments.

Many marine bacteria have evolved to grow optimally at either high (copiotrophic) or low (oligotrophic) nutrient concentrations, enabling different species to colonize distinct trophic habitats in the oceans. Here, we compare the genome sequences of two bacteria, Photobacterium angustum S14 and Sphingopyxis alaskensis RB2256, that serve as useful model organisms for copiotrophic and oligotrophic modes of life and specifically relate the genomic features to trophic strategy for these organisms and define their molecular mechanisms of adaptation. We developed a model for predicting trophic lifestyle from genome sequence data and tested >400,000 proteins representing >500 million nucleotides of sequence data from 126 genome sequences with metagenome data of whole environmental samples. When applied to available oceanic metagenome data (e.g., the Global Ocean Survey data) the model demonstrated that oligotrophs, and not the more readily isolatable copiotrophs, dominate the ocean's free-living microbial populations. Using our model, it is now possible to define the types of bacteria that specific ocean niches are capable of sustaining.

Microbial genome sequencing has entered a new phase, where DNA sequence information is gathered from entire microbial communities (metagenomics or environmental genomics) rather than from individual microorganisms. By providing access to the genetic material of vast numbers of organisms, most of which are organisms that have never been isolated or cultivated, a new level of insight is being gained into the diversity and extent of the microbial processes that are presently occuring in environmental communities. By extending metagenomic-based approaches to the study of very complex and methodologically recalcitrant soil environments, a recent study has found that ammonia-oxidizing archaea are more abundant in many soils than bacteria.1 These findings not only highlight the undoubtedly critical yet unknown roles that archaea play in global nutrient cycles but illustrate the importance of genomic studies for informing us about the functional capacity of life on Earth. BioEssays 29: 11–14, 2007. © 2006 Wiley Periodicals, Inc.

Summary: 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. Availability: Source code is freely available under GPLv3 at https://sourceforge.net/projects/shap. Contact: matt.demaere@unsw.edu.au; r.cavicchioli@unsw.edu.au