Ambarish Biswas

CRISPRTarget: Bioinformatic prediction and analysis of crRNA targets

The bacterial and archaeal CRISPR/Cas adaptive immune system targets specific protospacer nucleotide sequences in invading organisms. This requires base pairing between processed CRISPR RNA and the target protospacer. For type I and II CRISPR/Cas systems, protospacer adjacent motifs (PAM) are essential for target recognition, and for type III, mismatches in the flanking sequences are important in the antiviral response. In this study, we examine the properties of each class of CRISPR. We use this information to provide a tool (CRISPRTarget) that predicts the most likely targets of CRISPR RNAs (http://bioanalysis.otago.ac.nz/CRISPRTarget). This can be used to discover targets in newly sequenced genomic or metagenomic data. To test its utility, we discover features and targets of well-characterized Streptococcus thermophilus and Sulfolobus solfataricus type II and III CRISPR/Cas systems. Finally, in Pectobacterium species, we identify new CRISPR targets and propose a model of temperate phage exposure and subsequent inhibition by the type I CRISPR/Cas systems.

Genomic and metagenomic surveys of hydrogenase distribution indicate H2 is a widely utilised energy source for microbial growth and survival

Recent physiological and ecological studies have challenged the long-held belief that microbial metabolism of molecular hydrogen (H2) is a niche process. To gain a broader insight into the importance of microbial H2 metabolism, we comprehensively surveyed the genomic and metagenomic distribution of hydrogenases, the reversible enzymes that catalyse the oxidation and evolution of H2. The protein sequences of 3286 non-redundant putative hydrogenases were curated from publicly available databases. These metalloenzymes were classified into multiple groups based on (1) amino acid sequence phylogeny, (2) metal-binding motifs, (3) predicted genetic organisation and (4) reported biochemical characteristics. Four groups (22 subgroups) of [NiFe]-hydrogenase, three groups (6 subtypes) of [FeFe]-hydrogenases and a small group of [Fe]-hydrogenases were identified. We predict that this hydrogenase diversity supports H2-based respiration, fermentation and carbon fixation processes in both oxic and anoxic environments, in addition to various H2-sensing, electron-bifurcation and energy-conversion mechanisms. Hydrogenase-encoding genes were identified in 51 bacterial and archaeal phyla, suggesting strong pressure for both vertical and lateral acquisition. Furthermore, hydrogenase genes could be recovered from diverse terrestrial, aquatic and host-associated metagenomes in varying proportions, indicating a broad ecological distribution and utilisation. Oxygen content (pO2) appears to be a central factor driving the phylum- and ecosystem-level distribution of these genes. In addition to compounding evidence that H2 was the first electron donor for life, our analysis suggests that the great diversification of hydrogenases has enabled H2 metabolism to sustain the growth or survival of microorganisms in a wide range of ecosystems to the present day. This work also provides a comprehensive expanded system for classifying hydrogenases and identifies new prospects for investigating H2 metabolism.

MetDAT: a modular and workflow-based free online pipeline for mass spectrometry data processing, analysis and interpretation

SUMMARY Analysis of high throughput metabolomics experiments is a resource-intensive process that includes pre-processing, pre-treatment and post-processing at each level of experimental hierarchy. We developed an interactive user-friendly online software called Metabolite Data Analysis Tool (MetDAT) for mass spectrometry data. It offers a pipeline of tools for file handling, data pre-processing, univariate and multivariate statistical analyses, database searching and pathway mapping. Outputs are produced in the form of text and high-quality images in real-time. MetDAT allows users to combine data management and experiment-centric workflows for optimization of metabolomics methods and metabolite analysis. AVAILABILITY MetDAT is available free for academic use from http://smbl.nus.edu.sg/METDAT2/. CONTACT sanjay@nus.edu.sg

H2 metabolism is widespread and diverse among human colonic microbes

ABSTRACT Microbial molecular hydrogen (H2) cycling is central to metabolic homeostasis and microbial composition in the human gastrointestinal tract. Molecular H2 is produced as an endproduct of carbohydrate fermentation and is reoxidised primarily by sulfate-reduction, acetogenesis, and methanogenesis. However, the enzymatic basis for these processes is incompletely understood and the hydrogenases responsible have not been investigated. In this work, we surveyed the genomic and metagenomic distribution of hydrogenase-encoding genes in the human colon to infer dominant mechanisms of H2 cycling. The data demonstrate that 70% of gastrointestinal microbial species listed in the Human Microbiome Project encode the genetic capacity to metabolise H2. A wide variety of anaerobically-adapted hydrogenases were present, with [FeFe]-hydrogenases predominant. We subsequently analyzed the hydrogenase gene content of stools from 20 healthy human subjects. The hydrogenase gene content of all samples was overwhelmingly dominated by fermentative and electron-bifurcating [FeFe]-hydrogenases emerging from the Bacteroidetes and Firmicutes. This study supports that H2 metabolism in the human gut is driven by fermentative H2 production and interspecies H2 transfer. However, it suggests that electron-bifurcation rather than respiration is the dominant mechanism of H2 reoxidation in the human colon, generating reduced ferredoxin to sustain carbon-fixation (e.g. acetogenesis) and respiration (via the Rnf complex). This work provides the first comprehensive bioinformatic insight into the mechanisms of H2 metabolism in the human colon.

Phylogenetic and functional potential links pH and N2O emissions in pasture soils

Denitrification is mediated by microbial, and physicochemical, processes leading to nitrogen loss via N2O and N2 emissions. Soil pH regulates the reduction of N2O to N2, however, it can also affect microbial community composition and functional potential. Here we simultaneously test the link between pH, community composition, and the N2O emission ratio (N2O/(NO + N2O + N2)) in 13 temperate pasture soils. Physicochemical analysis, gas kinetics, 16S rRNA amplicon sequencing, metagenomic and quantitative PCR (of denitrifier genes: nirS, nirK, nosZI and nosZII) analysis were carried out to characterize each soil. We found strong evidence linking pH to both N2O emission ratio and community changes. Soil pH was negatively associated with N2O emission ratio, while being positively associated with both community diversity and total denitrification gene (nir & nos) abundance. Abundance of nosZII was positively linked to pH, and negatively linked to N2O emissions. Our results confirm that pH imposes a general selective pressure on the entire community and that this results in changes in emission potential. Our data also support the general model that with increased microbial diversity efficiency increases, demonstrated in this study with lowered N2O emission ratio through more efficient conversion of N2O to N2.

Accurate computational prediction of the transcribed strand of CRISPR non-coding RNAs

MOTIVATION CRISPR RNAs (crRNAs) are a type of small non-coding RNA that form a key part of an acquired immune system in prokaryotes. Specific prediction methods find crRNA-encoding loci in nearly half of sequenced bacterial, and three quarters of archaeal, species. These Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) arrays consist of repeat elements alternating with specific spacers. Generally one strand is transcribed, producing long pre-crRNAs, which are processed to short crRNAs that base pair with invading nucleic acids to facilitate their destruction. No current software for the discovery of CRISPR loci predicts the direction of crRNA transcription. RESULTS We have developed an algorithm that accurately predicts the strand of the resulting crRNAs. The method uses as input CRISPR repeat predictions. CRISPRDirection uses parameters that are calculated from the CRISPR repeat predictions and flanking sequences, which are combined by weighted voting. The prediction may use prior coding sequence annotation but this is not required. CRISPRDirection correctly predicted the orientation of 94% of a reference set of arrays. AVAILABILITY AND IMPLEMENTATION The Perl source code is freely available from http://bioanalysis.otago.ac.nz/CRISPRDirection.

The methanogenic redox cofactor F420 is widely synthesized by aerobic soil bacteria

F420 is a low-potential redox cofactor that mediates the transformations of a wide range of complex organic compounds. Considered one of the rarest cofactors in biology, F420 is best known for its role in methanogenesis and has only been chemically identified in two phyla to date, the Euryarchaeota and Actinobacteria. In this work, we show that this cofactor is more widely distributed than previously reported. We detected the genes encoding all five known F420 biosynthesis enzymes (cofC, cofD, cofE, cofG and cofH) in at least 653 bacterial and 173 archaeal species, including members of the dominant soil phyla Proteobacteria, Chloroflexi and Firmicutes. Metagenome datamining validated that these genes were disproportionately abundant in aerated soils compared with other ecosystems. We confirmed through high-performance liquid chromatography analysis that aerobically grown stationary-phase cultures of three bacterial species, Paracoccus denitrificans, Oligotropha carboxidovorans and Thermomicrobium roseum, synthesized F420, with oligoglutamate sidechains of different lengths. To understand the evolution of F420 biosynthesis, we also analyzed the distribution, phylogeny and genetic organization of the cof genes. Our data suggest that although the Fo precursor to F420 originated in methanogens, F420 itself was first synthesized in an ancestral actinobacterium. F420 biosynthesis genes were then disseminated horizontally to archaea and other bacteria. Together, our findings suggest that the cofactor is more significant in aerobic bacterial metabolism and soil ecosystem composition than previously thought. The cofactor may confer several competitive advantages for aerobic soil bacteria by mediating their central metabolic processes and broadening the range of organic compounds they can synthesize, detoxify and mineralize.

Scan for Motifs: a webserver for the analysis of post-transcriptional regulatory elements in the 3′ untranslated regions (3′ UTRs) of mRNAs

BackgroundGene expression in vertebrate cells may be controlled post-transcriptionally through regulatory elements in mRNAs. These are usually located in the untranslated regions (UTRs) of mRNA sequences, particularly the 3′UTRs.ResultsScan for Motifs (SFM) simplifies the process of identifying a wide range of regulatory elements on alignments of vertebrate 3′UTRs. SFM includes identification of both RNA Binding Protein (RBP) sites and targets of miRNAs. In addition to searching pre-computed alignments, the tool provides users the flexibility to search their own sequences or alignments. The regulatory elements may be filtered by expected value cutoffs and are cross-referenced back to their respective sources and literature. The output is an interactive graphical representation, highlighting potential regulatory elements and overlaps between them. The output also provides simple statistics and links to related resources for complementary analyses. The overall process is intuitive and fast. As SFM is a free web-application, the user does not need to install any software or databases.ConclusionsVisualisation of the binding sites of different classes of effectors that bind to 3′UTRs will facilitate the study of regulatory elements in 3′ UTRs.

datPAV—an online processing, analysis and visualization tool for exploratory investigation of experimental data

SUMMARY Data processing, analysis and visualization (datPAV) is an exploratory tool that allows experimentalist to quickly assess the general characteristics of the data. This platform-independent software is designed as a generic tool to process and visualize data matrices. This tool explores organization of the data, detect errors and support basic statistical analyses. Processed data can be reused whereby different step-by-step data processing/analysis workflows can be created to carry out detailed investigation. The visualization option provides publication-ready graphics. Applications of this tool are demonstrated at the web site for three cases of metabolomics, environmental and hydrodynamic data analysis. AVAILABILITY datPAV is available free for academic use at http://www.sdwa.nus.edu.sg/datPAV/.

Erratum: Erratum: Phylogenetic and functional potential links pH and N2O emissions in pasture soils

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