MOSGA 2: Comparative genomics and validation tools

Metagenomic analysis of pristine oil sheds new light on the global distribution of microbial genetic repertoire in hydrocarbon-associated ecosystems

Oil reservoirs are society's primary source of hydrocarbons. While microbial communities in industrially exploited oil reservoirs have been investigated in the past, pristine microbial communities in untapped oil reservoirs are little explored, as are distribution patterns of respective genetic signatures. Here, we show that a pristine oil sample contains a complex community consisting of bacteria and fungi for the degradation of hydrocarbons. We identified microorganisms and their pathways for the degradation of methane, n-alkanes, mono-aromatic, and polycyclic aromatic compounds in a metagenome retrieved from biodegraded petroleum encountered in a subsurface reservoir in the Barents Sea. Capitalizing on marker genes from metagenomes and public data mining, we compared the prokaryotes, putative viruses, and putative plasmids of the sampled site to those from 10 other hydrocarbon-associated sites, revealing a shared network of species and genetic elements across the globe. To test for the potential dispersal of the microbes and predicted elements via seawater, we compared our findings to the Tara Ocean dataset, resulting in a broad distribution of prokaryotic and viral signatures. Although frequently shared between hydrocarbon-associated sites, putative plasmids, however, showed little coverage in the Tara Oceans dataset, suggesting an undiscovered mode of transfer between hydrocarbon-affected ecosystems. Based on our analyses, genetic information is globally shared between oil reservoirs and hydrocarbon-associated sites, and we propose that currents and other physical occurrences within the ocean along with deep aquifers are major distributors of prokaryotes and viruses into these subsurface ecosystems.

Virulence perspective genomic research unlocks the secrets of Rhizoctonia solani associated with banded sheath blight in Barnyard Millet (Echinochloa frumentacea)

Introduction

Banded sheath blight (Bsb) disease, caused by Rhizoctonia solani, is an emerging problem in barnyard millet cultivation. One of the significant goals of pathogenomic research is to identify genes responsible for pathogenicity in the fungus.

Methods

A virulence profiling-based approach was employed and six R. solani isolates were collected from various ecological zones of India. The morphological parameters and virulence of all of the six R. solani isolates were investigated. The most virulent strain was designated as RAP2 and its genome has been sequenced, assembled, and annotated.

Results

The RAP2 genome is 43.63 megabases in size and comprises 10.95% repetitive DNA, within which 46% are retroelements, 8% are DNA transposons, and 46% are unidentified DNA. The Gene Ontology (GO) annotation of RAP2 proteins revealed that "phosphorylation", "membrane", and "ATP binding" have the highest gene enrichment in the "biological process", "cellular component" and "molecular function" domains, respectively. The genome comprises a majority of secretory proteins in the pectin lyase fold/virulence factor superfamily, which break down plant cell wall polymers to extract saccharides. The RAP2 genome is comparable to R. solani, which infects maize and rice, but it diverges further from soybean in terms of nucleotide-level genetic similarity. Orthologous clustering of RAP2 protein sequences with R. solani infecting maize, rice, and soybean yields 5606 proteins shared across all genomes. GO analysis of 25 proteins specific to the RAP2 genome found enrichment in the ethylene response, which can cause spore germination and infection in host plants.

Discussion

Interestingly, a 28-bp deletion in the RAP2 strain's cutinase domain was discovered in the cutinase protein, which might be important in the infection process, perhaps rendering the enzyme inactive or allowing the pathogen to infect barnyard millet while avoiding host defense. This study sheds light on the genetic makeup of R. solani, allowing researchers to discover critical genes related with pathogenicity as well as potential targets for fungicide development.

Going through phages: a computational approach to revealing the role of prophage in Staphylococcus aureus

Prophages have important roles in virulence, antibiotic resistance, and genome evolution in Staphylococcus aureus . Rapid growth in the number of sequenced S. aureus genomes allows for an investigation of prophage sequences at an unprecedented scale. We developed a novel computational pipeline for phage discovery and annotation. We combined PhiSpy, a phage discovery tool, with VGAS and PROKKA, genome annotation tools to detect and analyse prophage sequences in nearly 10 011  S . aureus genomes, discovering thousands of putative prophage sequences with genes encoding virulence factors and antibiotic resistance. To our knowledge, this is the first large-scale application of PhiSpy on a large-scale set of genomes (10 011  S . aureus ). Determining the presence of virulence and resistance encoding genes in prophage has implications for the potential transfer of these genes/functions to other bacteria via transduction and thus can provide insight into the evolution and spread of these genes/functions between bacterial strains. While the phage we have identified may be known, these phages were not necessarily known or characterized in S. aureus and the clustering and comparison we did for phage based on their gene content is novel. Moreover, the reporting of these genes with the S. aureus genomes is novel.

Bioinformatics in bioscience and bioengineering: Recent advances, applications, and perspectives

Recent advances have led to the emergence of highly comprehensive and analytical approaches, such as omics analysis and high-resolution, time-resolved bioimaging analysis. These technologies have made it possible to obtain vast data from a single measurement. Subsequently, large datasets have pioneered the data-driven approach, an alternative to the traditional hypothesis-testing system, for researchers. However, processing, interpreting, and elucidating enormous datasets is no longer possible without computation. Bioinformatics is a field that has developed over long periods, intending to understand biological phenomena using methods collected from information science and statistics, thus solving this proposed research challenge. This review presents the latest methodologies and applications in sequencing, imaging, and mass spectrometry that were developed using bioinformatics. We presented the features of individual techniques and outlines in each part, avoiding the use of complex algorithms and formulas to allow beginning researchers to understand an overview. In the section on sequencing, we focused on comparative genomic, transcriptomic, and bacterial microbiome analyses, which are frequently used as applications of next-generation sequencing. Bioinformatic methods for handling sequence data and case studies were described. In the section on imaging, we introduced the analytical methods and microscopy imaging informatics techniques used in animal cell biology and plant physiology. We introduce informatics technologies for maximizing the value of measured data, including predicting the structure of unknown molecules and untargeted analysis in the section on mass spectrometry. Finally, we discuss the future outlook of this field. We anticipate that this review will assist biologists in using bioinformatics more effectively.