SKPDB: a structural database of shikimate pathway enzymes

Background  

The functional and structural characterisation of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design. The main interest in studying shikimate pathway enzymes involves the fact that they are essential for bacteria but do not occur in humans, making them selective targets for design of drugs that do not directly impact humans.     

Role of the daily food ration of perch fry (Perca fluvialis) in infestation with Bunodera luciopercae (Trematoda, Allocreadiidae)

The list of intermediate hosts of Bunodera luciopercae is given. In Lake Syamozero they are represented by crustaceans Heterocope, Ophryoxus. Data on their role in the ration of juvenile perch are given. Diurnal dynamics of the ratio between infected and noninfected plankton in feeding and the process of the formation of fish infection have been studied.     

Role of dietary fiber in the recovery of the human gut microbiome and its metabolome

1. Download : Download high-res image (229KB)
2. Download : Download full-size image

     

A Model-Based Approach for Species Abundance Quantification Based on Shotgun Metagenomic Data

The human microbiome, which includes the collective microbes residing in or on the human body, has a profound influence on the human health. DNA sequencing technology has made the large-scale human microbiome studies possible by using shotgun metagenomic sequencing. One important aspect of data analysis of such metagenomic data is to quantify the bacterial abundances based on the metagenomic sequencing data. Existing methods almost always quantify such abundances one sample at a time, which ignore certain systematic differences in read coverage along the genomes due to GC contents, copy number variation and the bacterial origin of replication. In order to account for such differences in read counts, we propose a multi-sample Poisson model to quantify microbial abundances based on read counts that are assigned to species-specific taxonomic markers. Our model takes into account the marker-specific effects when normalizing the sequencing count data in order to obtain more accurate quantification of the species abundances. Compared to currently available methods on simulated data and real data sets, our method has demonstrated an improved accuracy in bacterial abundance quantification, which leads to more biologically interesting results from downstream data analysis.