Coupled integration of human immunodeficiency virus type 1 cDNA ends by purified integrase in vitro: stimulation by the viral nucleocapsid protein.

Integration of retroviral cDNA involves coupled joining of the two ends of the viral genome at precisely spaced positions in the host cell DNA. Correct coupled joining is essential for viral replication, as shown, for example, by the finding that viral mutants defective in coupled joining are defective in integration and replication. To date, reactions with purified human immunodeficiency virus type 1 (HIV-1) integrase protein in vitro have supported mainly uncoupled joining of single cDNA ends. We have analyzed an activity stimulating coupled joining present in HIV-1 virions, which led to the finding that the HIV-1 nucleocapsid (NC) protein can stimulate coupled joining more than 1,000-fold under some conditions. The requirements for stimulating coupled joining were investigated in assays with mutant NC proteins, revealing that mutations in the zinc finger domains can influence stimulation of integration. These findings (i) provide a means for assembling more authentic integrase complexes for mechanistic studies, (ii) reveal a new activity of NC protein in vitro, (iii) indicate a possible role for NC in vivo, and (iv) provide a possible method for identifying a new class of inhibitors that disrupt coupled joining.     

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

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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.