jpHMM: Improving the reliability of recombination prediction in HIV-1

Previously, we developed jumping profile hidden Markov model (jpHMM), a new method to detect recombinations in HIV-1 genomes. The jpHMM predicts recombination breakpoints in a query sequence and assigns to each position of the sequence one of the major HIV-1 subtypes. Since incorrect subtype assignment or recombination prediction may lead to wrong conclusions in epidemiological or vaccine research, information about the reliability of the predicted parental subtypes and breakpoint positions is valuable. For this reason, we extended the output of jpHMM to include such information in terms of ‘uncertainty’ regions in the recombination prediction and an interval estimate of the breakpoint. Both types of information are computed based on the posterior probabilities of the subtypes at each query sequence position. Our results show that this extension strongly improves the reliability of the jpHMM recombination prediction. The jpHMM is available online at http://jphmm.gobics.de/

Genital Tract Sequestration of SIV following Acute Infection

We characterized the evolution of simian immunodeficiency virus (SIV) in the male genital tract by examining blood- and semen-associated virus from experimentally and sham vaccinated rhesus monkeys during primary infection. At the time of peak virus replication, SIV sequences were intermixed between the blood and semen supporting a scenario of high-level virus "spillover" into the male genital tract. However, at the time of virus set point, compartmentalization was apparent in 4 of 7 evaluated monkeys, likely as a consequence of restricted virus gene flow between anatomic compartments after the resolution of primary viremia. These findings suggest that SIV replication in the male genital tract evolves to compartmentalization after peak viremia resolves

HIV Types, Groups, Subtypes and Recombinant Forms: Errors in Replication, Selection Pressure and Quasispecies

HIV-1 is a chimpanzee virus which was transmitted to humans by several zoonotic events resulting in infection with HIV-1 groups M P, and in parallel transmission events from sooty mangabey monkey viruses leading to infections with HIV-2 groups A H. Both viruses have circulated in the human population for about 80 years. In the infected patient, HIV mutates, and by elimination of some of the viruses by the action of the immune system individual quasispecies are formed. Along with the selection of the fittest viruses, mutation and recombination after superinfection with HIV from different groups or subtypes have resulted in the diversity of their patterns of geographic distribution. Despite the high variability observed, some essential parts of the HIV genome are highly conserved. Viral diversity is further facilitated in some parts of the HIV genome by drug selection pressure and may also be enhanced by different genetic factors, including HLA in patients from different regions of the world. Viral and human genetic factors influence pathogenesis. Viral genetic factors are proteins such as Tat, Vif and Rev. Human genetic factors associated with a better clinical outcome are proteins such as APOBEC, langerin, tetherin and chemokine receptor 5 (CCR5) and HLA B27, B57, DRB1{*}1303, KIR and PARD3B. Copyright (C) 2012 S. Karger AG, Base

Selection at a single locus leads to widespread expansion of toxoplasma gondii lineages that are virulent in mice

The determinants of virulence are rarely defined for eukaryotic parasites such as T. gondii, a widespread parasite of mammals that also infects humans, sometimes with serious consequences. Recent laboratory studies have established that variation in a single secreted protein, a serine/threonine kinase known as ROPO18, controls whether or not mice survive infection. Here, we establish the extent and nature of variation in ROP18among a collection of parasite strains from geographically diverse regions. Compared to other genes, ROP18 showed extremely high levels of diversification and changes in expression level, which correlated with severity of infection in mice. Comparison with an out-group demonstrated that changes in the upstream region that regulates expression of ROP18 led to an historical increase in the expression and exposed the protein to diversifying selective pressure. Surprisingly, only three atypically distinct protein variants exist despite marked genetic divergence elsewhere in the genome. These three forms of ROP18 are likely adaptations for different niches in nature, and they confer markedly different virulence to mice. The widespread distribution of a single mouse-virulent allele among geographically and genetically disparate parasites may have consequences for transmission and disease in other hosts, including humans

Validation of an NSP-based (negative selection pattern) gene family identification strategy

<p>Abstract</p> <p>Background</p> <p>Gene family identification from ESTs can be a valuable resource for analysis of genome evolution but presents unique challenges in organisms for which the entire genome is not yet sequenced. We have developed a novel gene family identification method based on negative selection patterns (NSP) between family members to screen EST-generated contigs. This strategy was tested on five known gene families in Arabidopsis to see if individual paralogs could be identified with accuracy from EST data alone when compared to the actual gene sequences in this fully sequenced genome.</p> <p>Results</p> <p>The NSP method uniquely identified family members in all the gene families tested. Two members of the FtsH gene family, three members each of the PAL, RF1, and ribosomal L6 gene families, and four members of the CAD gene family were correctly identified. Additionally all ESTs from the representative contigs when checked against MapViewer data successfully identify the gene locus predicted.</p> <p>Conclusion</p> <p>We demonstrate the effectiveness of the NSP strategy in identifying specific gene family members in Arabidopsis using only EST data and we describe how this strategy can be used to identify many gene families in agronomically important crop species where they are as yet undiscovered.</p

T-Cell Epitope Prediction: Rescaling Can Mask Biological Variation between MHC Molecules

Theoretical methods for predicting CD8+ T-cell epitopes are an important tool in vaccine design and for enhancing our understanding of the cellular immune system. The most popular methods currently available produce binding affinity predictions across a range of MHC molecules. In comparing results between these MHC molecules, it is common practice to apply a normalization procedure known as rescaling, to correct for possible discrepancies between the allelic predictors. Using two of the most popular prediction software packages, NetCTL and NetMHC, we tested the hypothesis that rescaling removes genuine biological variation from the predicted affinities when comparing predictions across a number of MHC molecules. We found that removing the condition of rescaling improved the prediction software's performance both qualitatively, in terms of ranking epitopes, and quantitatively, in the accuracy of their binding affinity predictions. We suggest that there is biologically significant variation among class 1 MHC molecules and find that retention of this variation leads to significantly more accurate epitope prediction