Metagenome mining to explore novel regions of natural products chemical space

Genomics has accelerated discovery in biology in an unprecedented way. Still, we are far from solving grand challenges facing humanity. The challenge to combat antimicrobial resistance requires us to accelerate natural product discovery by several orders of magnitude. We are already running out of our existing arsenal of antibiotics and novel approaches are needed to accelerate the pace of their discovery and development. Quick screening of natural product biosynthesis potential via metagenome mining holds new hope to revive the antibiotic discovery pipeline. Thanks to recent advancements in next generation sequencing technologies and big data mining, now we can hope to rationally survey the diverse ecosystem metagenomes to discover novel secondary metabolites. In this thesis we have presented our developed metagenome data mining pipeline and approaches to explore novel regions of natural products chemical space. We present our results and insights from multiple ecosystem metagenome surveys. Novel biosynthesis genes, domains, cluster sequences and comparative patterns from the surveyed ecosystem are highlighted in separate chapters. Metagenome mining patterns from following diverse ecosystems were studied: 1) Different horizons of soil sampled from three sites in close vicinity from the Schoenbuch forest; 2) Lake Huron sediments; 3) human gut microbiome and 4) the Tuebingen actinomycetes strain collection. The insights gained from this thesis will be helpful to the natural products research community to accelerate metagenome based novel natural products discovery and revive the antibiotics discovery pipeline

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions

BACKGROUND: The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. RESULTS: Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study identified several quality related key genes including many other genes, their interactions (quality x development) and temporal and spatial distributions. CONCLUSIONS: The candidate genes identified for processing quality and information on temporal and spatial distributions of their expressions would be useful for designing wheat improvement programs for processing quality either by changing their expression or development of single nucleotide polymorphisms (SNPs) markers

Genome wide expression profiling of two accession of G. herbaceum L. in response to drought

<p>Abstract</p> <p>Background</p> <p>Genome-wide gene expression profiling and detailed physiological investigation were used for understanding the molecular mechanism and physiological response of <it>Gossypium herbaceum</it>, which governs the adaptability of plants in drought conditions. Recently, microarray-based gene expression analysis is commonly used to decipher genes and genetic networks controlling the traits of interest. However, the results of such an analysis are often plagued due to a limited number of genes (probe sets) on microarrays. On the other hand, pyrosequencing of a transcriptome has the potential to detect rare as well as a large number of transcripts in the samples quantitatively. We used Affymetrix microarray as well as Roche's GS-FLX transcriptome sequencing for a comparative analysis of cotton transcriptome in leaf tissues under drought conditions.</p> <p>Results</p> <p>Fourteen accessions of <it>Gossypium herbaceum </it>were subjected to mannitol stress for preliminary screening; two accessions, namely Vagad and RAHS-14, were selected as being the most tolerant and most sensitive to osmotic stress, respectively. Affymetrix cotton arrays containing 24,045 probe sets and Roche's GS-FLX transcriptome sequencing of leaf tissue were used to analyze the gene expression profiling of Vagad and RAHS-14 under drought conditions. The analysis of physiological measurements and gene expression profiling showed that Vagad has the inherent ability to sense drought at a much earlier stage and to respond to it in a much more efficient manner than does RAHS-14. Gene Ontology (GO) studies showed that the phenyl propanoid pathway, pigment biosynthesis, polyketide biosynthesis, and other secondary metabolite pathways were enriched in Vagad under control and drought conditions as compared with RAHS-14. Similarly, GO analysis of transcriptome sequencing showed that the GO terms <it>responses to various abiotic stresses </it>were significantly higher in Vagad. Among the classes of transcription factors (TFs) uniquely expressed in both accessions, RAHS-14 showed the expression of ERF and WRKY families. The unique expression of ERFs in response to drought conditions reveals that RAHS-14 responds to drought by inducing senescence. This was further supported by transcriptome analysis which revealed that RAHS-14 responds to drought by inducing many transcripts related to senescence and cell death.</p> <p>Conclusion</p> <p>The comparative genome-wide gene expression profiling study of two accessions of <it>G.herbaceum </it>under drought stress deciphers the differential patterns of gene expression, including TFs and physiologically relevant processes. Our results indicate that drought tolerance observed in Vagad is not because of a single molecular reason but is rather due to several unique mechanisms which Vagad has developed as an adaptation strategy.</p

Transcriptomic and metabolomic shifts in rice roots in response to Cr (VI) stress

<p>Abstract</p> <p>Background</p> <p>Widespread use of chromium (Cr) contaminated fields due to careless and inappropriate management practices of effluent discharge, mostly from industries related to metallurgy, electroplating, production of paints and pigments, tanning, and wood preservation elevates its concentration in surface soil and eventually into rice plants and grains. In spite of many previous studies having been conducted on the effects of chromium stress, the precise molecular mechanisms related to both the effects of chromium phytotoxicity, the defense reactions of plants against chromium exposure as well as translocation and accumulation in rice remain poorly understood.</p> <p>Results</p> <p>Detailed analysis of genome-wide transcriptome profiling in rice root is reported here, following Cr-plant interaction. Such studies are important for the identification of genes responsible for tolerance, accumulation and defense response in plants with respect to Cr stress. Rice root metabolome analysis was also carried out to relate differential transcriptome data to biological processes affected by Cr (VI) stress in rice. To check whether the Cr-specific motifs were indeed significantly over represented in the promoter regions of Cr-responsive genes, occurrence of these motifs in whole genome sequence was carried out. In the background of whole genome, the lift value for these 14 and 13 motifs was significantly high in the test dataset. Though no functional role has been assigned to any of the motifs, but all of these are present as promoter motifs in the Database of orthologus promoters.</p> <p>Conclusion</p> <p>These findings clearly suggest that a complex network of regulatory pathways modulates Cr-response of rice. The integrated matrix of both transcriptome and metabolome data after suitable normalization and initial calculations provided us a visual picture of the correlations between components. Predominance of different motifs in the subsets of genes suggests the involvement of motif-specific transcription modulating proteins in Cr stress response of rice.</p

WImpiBLAST: Web Interface for mpiBLAST to Help Biologists Perform Large-Scale Annotation Using High Performance Computing

<div><p>The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design decisions, describe workflows and provide a detailed analysis.</p></div

Snapshot of Job reporting module.

<p>Snapshot of Job reporting module.</p