Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
Project description:Sulfoquinovose (SQ) is a major organosulfonate in nature, and thus plays an important role in the biogeochemical sulfur and carbon cycles. We identified a bacterial anaerobic consortium, enriched from lake Konstanz, which degraded SQ to isethionate as intermediate and further into acetate and sulfide. By a metagenomic analysis we identified Faecalicatena sp. DSM22707 as major SQ-degrader in the consortium. Strain DSM22707 degraded SQ in pure culture into isethionate and small amounts of sulfolactate.
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
Project description:Epigenetic variation has the potential to control environmentally dependent development and contribute to phenotypic responses to local environments. Environmental epigenetic studies of sexual organisms confirm the responsiveness of epigenetic variation, which should be even more important when genetic variation is lacking. A previous study of an asexual snail, Potamopyrgus antipodarum, demonstrated that different populations derived from a single clonal lineage differed in both shell phenotype and methylation signature when comparing lake versus river populations. Here, we examine methylation variation among lakes that differ in environmental disturbance and pollution histories. The differential DNA methylation regions (DMRs) identified among the different lake comparisons suggested a higher number of DMRs and variation between rural Lake 1 and one urban Lake 2 and between the two urban Lakes 2 and 3, but limited variation between the rural Lake 1 and urban Lake 3. DMR genomic characteristics and gene associations were investigated. Observations suggest there is no effect of geographic distance or any consistent pattern of DMRs between urban and rural lakes. Environmental factors may influence epigenetic response.