Foxp3 and IL-10 expression correlates with parasite burden in lesional tissues of post kala azar dermal leishmaniasis (PKDL) patients

Background

Post kala-azar dermal leishmaniasis (PKDL), a sequel to visceral leishamaniasis (VL) in 5–15% cases, constitutes a parasite reservoir important in disease transmission. The precise immunological cause of PKDL outcome remains obscure. However, overlapping counter regulatory responses with elevated IFN-γ and IL-10 are reported.

Methodology/Principal Findings

Present study deals with ex-vivo mRNA and protein analysis of natural regulatory T cells (nTreg) markers (Foxp3, CD25 and CTLA-4) and IL-10 levels in lesion tissues of PKDL patients at pre and post treatment stages. In addition, correlation of nTreg markers and IL-10 with parasite load in tissue lesions was investigated. mRNA levels of nTreg markers and IL-10 were found significantly elevated in pre-treatment PKDL cases compared to controls (Foxp3, P = 0.0009; CD25 & CTLA-4, P<0.0001; IL-10, P<0.0001), and were restored after treatment. Analysis of nTreg cell markers and IL-10 in different clinical manifestations of disease revealed elevated levels in nodular lesions compared to macules/papules. Further, Foxp3, CD25 and IL-10 mRNA levels directly correlated with parasite load in lesions tissues.

Conclusion/Significance

Data demonstrated accumulation of nTreg cells in infected tissue and a correlation of both IL-10 and nTreg levels with parasite burden suggesting their role in disease severity in PKDL.     

Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein

Background  

A large number of papers have been published on analysis of microarray data with particular emphasis on normalization of data, detection of differentially expressed genes, clustering of genes and regulatory network. On other hand there are only few studies on relation between expression level and composition of nucleotide/protein sequence, using expression data. There is a need to understand why particular genes/proteins express more in particular conditions. In this study, we analyze 3468 genes of Saccharomyces cerevisiae obtained from Holstege et al., (1998) to understand the relationship between expression level and amino acid composition.     

Genes Involved in Degradation of para-Nitrophenol Are Differentially Arranged in Form of Non-Contiguous Gene Clusters in Burkholderia sp. strain SJ98

Biodegradation of para-Nitrophenol (PNP) proceeds via two distinct pathways, having 1,2,3-benzenetriol (BT) and hydroquinone (HQ) as their respective terminal aromatic intermediates. Genes involved in these pathways have already been studied in different PNP degrading bacteria. Burkholderia sp. strain SJ98 degrades PNP via both the pathways. Earlier, we have sequenced and analyzed a ~41 kb fragment from the genomic library of strain SJ98. This DNA fragment was found to harbor all the lower pathway genes; however, genes responsible for the initial transformation of PNP could not be identified within this fragment. Now, we have sequenced and annotated the whole genome of strain SJ98 and found two ORFs (viz., pnpA and pnpB) showing maximum identity at amino acid level with p-nitrophenol 4-monooxygenase (PnpM) and p-benzoquinone reductase (BqR). Unlike the other PNP gene clusters reported earlier in different bacteria, these two ORFs in SJ98 genome are physically separated from the other genes of PNP degradation pathway. In order to ascertain the identity of ORFs pnpA and pnpB, we have performed in-vitro assays using recombinant proteins heterologously expressed and purified to homogeneity. Purified PnpA was found to be a functional PnpM and transformed PNP into benzoquinone (BQ), while PnpB was found to be a functional BqR which catalyzed the transformation of BQ into hydroquinone (HQ). Noticeably, PnpM from strain SJ98 could also transform a number of PNP analogues. Based on the above observations, we propose that the genes for PNP degradation in strain SJ98 are arranged differentially in form of non-contiguous gene clusters. This is the first report for such arrangement for gene clusters involved in PNP degradation. Therefore, we propose that PNP degradation in strain SJ98 could be an important model system for further studies on differential evolution of PNP degradation functions.     

Identification of ATP binding residues of a protein from its primary sequence

Background  

One of the major challenges in post-genomic era is to provide functional annotations for large number of proteins arising from genome sequencing projects. The function of many proteins depends on their interaction with small molecules or ligands. ATP is one such important ligand that plays critical role as a coenzyme in the functionality of many proteins. There is a need to develop method for identifying ATP interacting residues in a ATP binding proteins (ABPs), in order to understand mechanism of protein-ligands interaction.     

Ebselen,a promising antioxidant drug: mechanisms of action and targets of biological pathways

Ebselen, an organoselenium compound, mimics glutathione peroxidase activity. It is a multifunctional compound, which catalyzes several essential reactions for the protection of cellular components from oxidative and free radical damage. Based on a number of in vitro and in vivo studies, various mechanisms are proposed to understand the biomedical actions of ebselen in health and diseases. It modulates metallo-proteins, enzymatic cofactors, gene expression, epigenetics, antioxidant defenses and immune systems. Owing to these properties, ebselen is currently under clinical trials for the prevention and treatment of various disorders such as cardiovascular diseases, arthritis, stroke, atherosclerosis, and cancer. A few ebselen-based pharmaceutical agents are under extensive investigation. As ebselen has been shown to have significant cellular toxicity, appropriate studies are needed to redesign the ebselen-based therapy for clinical trials. This review summarizes current understanding of the biochemical and molecular properties, and pharmacological applications of ebselen and future directions in this area of research.     

Identification of Proteins Secreted by Malaria Parasite into Erythrocyte using SVM and PSSM profiles

Background  

Malaria parasite secretes various proteins in infected RBC for its growth and survival. Thus identification of these secretory proteins is important for developing vaccine/drug against malaria. The existing motif-based methods have got limited success due to lack of universal motif in all secretory proteins of malaria parasite.     

Integrative analyses reveal signaling pathways underlying familial breast cancer susceptibility

The signaling events that drive familial breast cancer (FBC) risk remain poorly understood. While the majority of genomic studies have focused on genetic risk variants, known risk variants account for at most 30% of FBC cases. Considering that multiple genes may influence FBC risk, we hypothesized that a pathway‐based strategy examining different data types from multiple tissues could elucidate the biological basis for FBC. In this study, we performed integrated analyses of gene expression and exome‐sequencing data from peripheral blood mononuclear cells and showed that cell adhesion pathways are significantly and consistently dysregulated in women who develop FBC. The dysregulation of cell adhesion pathways in high‐risk women was also identified by pathway‐based profiling applied to normal breast tissue data from two independent cohorts. The results of our genomic analyses were validated in normal primary mammary epithelial cells from high‐risk and control women, using cell‐based functional assays, drug‐response assays, fluorescence microscopy, and Western blotting assays. Both genomic and cell‐based experiments indicate that cell–cell and cell–extracellular matrix adhesion processes seem to be disrupted in non‐malignant cells of women at high risk for FBC and suggest a potential role for these processes in FBC development.     

BTXpred: prediction of bacterial toxins

This paper describes a method developed for predicting bacterial toxins from their amino acid sequences. All the modules, developed in this study, were trained and tested on a non-redundant dataset of 150 bacterial toxins that included 77 exotoxins and 73 endotoxins. Firstly, support vector machines (SVM) based modules were developed for predicting the bacterial toxins using amino acids and dipeptides composition and achieved an accuracy of 96.07% and 92.50%, respectively. Secondly, SVM based modules were developed for discriminating entotoxins and exotoxins, using amino acids and dipeptides composition and achieved an accuracy of 95.71% and 92.86%, respectively. In addition, modules have been developed for classifying the exotoxins (e.g. activate adenylate cyclase, activate guanylate cyclase, neurotoxins) using hidden Markov models (HMM), PSI-BLAST and a combination of the two and achieved overall accuracy of 95.75%, 97.87% and 100%, respectively. Based on the above study, a web server called 'BTXpred' has been developed, which is available at http://www.imtech.res.in/raghava/btxpred/. Supplementary information is available at http://www.imtech.res.in/raghava/btxpred/supplementary.html.