Identification of immuno-dominant antigens of Trypanosoma evansi for detection of chronic trypanosomosis using experimentally infected equines

Trypanosoma evansi is the most extensively distributed trypanosome responsible for disease called surra in livestock in many countries including frequent outbreaks in India. The prevalence of this disease is most commonly reported by standard parasitological detection methods (SPDM); however, antibody ELISA is being in practice by locally produced whole cell lysate (WCL) antigens in many countries. In the present investigation, we attempted to identify and purify immuno dominant, infection specific trypanosome antigens from T. evansi proteome using experimentally infected equine serum by immuno blot. Three immuno dominant clusters of proteins i.e. 62-66 kDa, 52-55 kDa and 41-43 kDa were identified based on their consistent reactivity with donkey sequential serum experimentally infected T. evansi up to 280 days post infection (dpi). The protein cluster of 62-66 kDa was purified in bulk in native form and comparatively evaluated with whole cell lysate antigen (WCL). ELISA and immuno blot showed that polypeptide of this cluster is 100% sensitive in detection of early and chronic infection. Further, this protein cluster was also found immuno reactive against hyper immune serum raised against predominantly 66 kDa exo antigen, revealed that this is a common immunodominant moieties in proteome and secretome of T. evansi.

Identification and characterization of starvation induced msdgc-1 promoter involved in the c-di-GMP turnover

C-di-GMP Bis-(3'-5')-cyclic-dimeric-guanosine monophosphate], a second messenger is involved in intracellular communication in the bacterial species. As a result several multi-cellular behaviors in both Gram-positive and Gram-negative bacteria are directly linked to the intracellular level of c-di-GMP. The cellular concentration of c-di-GMP is maintained by two opposing activities, diguanylate cyclase (DGC) and phosphodiesterase (PDE-A). In Mycobacterium smegmatis, a single bifunctional protein MSDGC-1 is responsible for the cellular concentration of c-di-GMP. A better understanding of the regulation of c-di-GMP at the genetic level is necessary to control the function of above two activities. In this work, we have characterized the promoter element present in msdgc-1 along with the + 1 transcription start site and identified the sigma factors that regulate the transcription of msdgc-1. Interestingly, msdgc-1 utilizes SigA during the initial phase of growth, whereas near the stationary phase SigB containing RNA polymerase takes over the expression of msdgc-1. We report here that the promoter activity of msdgc-1 increases during starvation or depletion of carbon source like glucose or glycerol. When msdgc-1 is deleted, the numbers of viable cells are similar to 10 times higher in the stationary phase in comparison to that of the wild type. We propose here that msdgc-1 is involved in the regulation of cell population density. (C) 2013 Elsevier B.V. All rights reserved.

Examining the Effectiveness of Discriminant Function Analysis and Cluster Analysis in Species Identification of Male Field Crickets Based on Their Calling Songs

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.

Support vector clustering-based direct coherency identification of generators in a multi-machine power system

This study investigates the application of support vector clustering (SVC) for the direct identification of coherent synchronous generators in large interconnected multi-machine power systems. The clustering is based on coherency measure, which indicates the degree of coherency between any pair of generators. The proposed SVC algorithm processes the coherency measure matrix that is formulated using the generator rotor measurements to cluster the coherent generators. The proposed approach is demonstrated on IEEE 10 generator 39-bus system and an equivalent 35 generators, 246-bus system of practical Indian southern grid. The effect of number of data samples and fault locations are also examined for determining the accuracy of the proposed approach. An extended comparison with other clustering techniques is also included, to show the effectiveness of the proposed approach in grouping the data into coherent groups of generators. This effectiveness of the coherent clusters obtained with the proposed approach is compared in terms of a set of clustering validity indicators and in terms of statistical assessment that is based on the coherency degree of a generator pair.

Identification of key amino acid residues in the catalytic mechanism of diaminopropionate ammonialyase from Salmonella typhimurium

Diaminopropionate ammonialyase (DAPAL), a fold-typeII pyridoxal 5-phosphate-dependent enzyme, catalyzes the ,-elimination of diaminopropionate (DAP) to pyruvate and ammonia. DAPAL was able to utilize both d- and l-DAP as substrates with almost equal efficiency. Mutational analysis of functionally important residues such as Thr385, Asp125 and Asp194 was carried out to understand the mechanism by which the isomers are hydrolyzed. Further, the putative residues involved in the formation of disulfide bond Cys271 and Cys299 were also mutated. T385S, T385D sDAPAL were as active with dl-DAP as substrate as sDAPAL, whereas the later exhibited a threefold increase in catalytic efficiency with d-Ser as substrate. Further analysis of these mutants suggested that DAPAL might follow an anti-E-2 mechanism of catalysis that does not involve the formation of a quinonoid intermediate. Of the two mutants of Asp125, D125E showed complete loss of activity with d-DAP as substrate, whereas the reaction with l-DAP was not affected significantly, demonstrating that Asp125 was essential for abstraction of protons from the d-isomer. By contrast, mutational analysis of Asp194 showed that the residue may not be directly involved in proton abstraction from l-DAP. sDAPAL does not form a disulfide bond in solution, although the position of Cys299 and Cys271 in the modeled structure of sDAPAL favored the formation of a disulfide bond. Further, unlike eDAPAL, sDAPAL could be activated by monovalent cations. Mutation of the cysteine residues showed that Cys271 may be involved in coordinating the monovalent cation, as observed in the case of other fold-typeII enzymes.

A DNA methylation prognostic signature of glioblastoma: identification of NPTX2-PTEN-NF-kappa B nexus

Glioblastoma (GBM) is the most common, malignant adult primary tumor with dismal patient survival, yet the molecular determinants of patient survival are poorly characterized. Global methylation profile of GBM samples (our cohort; n = 44) using high-resolution methylation microarrays was carried out. Cox regression analysis identified a 9-gene methylation signature that predicted survival in GBM patients. A risk-score derived from methylation signature predicted survival in univariate analysis in our and The Cancer Genome Atlas (TCGA) cohort. Multivariate analysis identified methylation risk score as an independent survival predictor in TCGA cohort. Methylation risk score stratified the patients into low-risk and high-risk groups with significant survival difference. Network analysis revealed an activated NF-kappa B pathway association with high-risk group. NF-kappa B inhibition reversed glioma chemoresistance, and RNA interference studies identified interleukin-6 and intercellular adhesion molecule-1 as key NF-kappa B targets in imparting chemoresistance. Promoter hypermethylation of neuronal pentraxin II (NPTX2), a risky methylated gene, was confirmed by bisulfite sequencing in GBMs. GBMs and glioma cell lines had low levels of NPTX2 transcripts, which could be reversed upon methylation inhibitor treatment. NPTX2 overexpression induced apoptosis, inhibited proliferation and anchorage-independent growth, and rendered glioma cells chemosensitive. Furthermore, NPTX2 repressed NF-kappa B activity by inhibiting AKT through a p53-PTEN-dependent pathway, thus explaining the hypermethylation and downregulation of NPTX2 in NF-kappa B-activated high-risk GBMs. Taken together, a 9-gene methylation signature was identified as an independent GBM prognosticator and could be used for GBM risk stratification. Prosurvival NF-kappa B pathway activation characterized high-risk patients with poor prognosis, indicating it to be a therapeutic target. (C) 2013 AACR.

A scaled unscented transformation based directed Gaussian sum filter for nonlinear dynamic system identification

Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.

Iterated gain-based stochastic filters for dynamic system identification

We propose a novel form of nonlinear stochastic filtering based on an iterative evaluation of a Kalman-like gain matrix computed within a Monte Carlo scheme as suggested by the form of the parent equation of nonlinear filtering (Kushner-Stratonovich equation) and retains the simplicity of implementation of an ensemble Kalman filter (EnKF). The numerical results, presently obtained via EnKF-like simulations with or without a reduced-rank unscented transformation, clearly indicate remarkably superior filter convergence and accuracy vis-a-vis most available filtering schemes and eminent applicability of the methods to higher dimensional dynamic system identification problems of engineering interest. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Identification and characterization of novel indole based small molecules as anticancer agents through SIRT1 inhibition

In our pursuit to develop new potential anticancer leads, we designed a combination of structural units of indole and substituted triazole; and a library of 1-{1-methyl-2-4-phenyl-5-(propan-2-ylsulfanyl)-4H-1,2,4-triazol-3-yl ]-1H-indol-3-yl}methanamine derivatives was synthesized and characterized. Cytotoxic evaluations of these molecules over a panel of three human cancer cell lines were carried out. Few molecules exhibited potent growth inhibitory action against the treated cancer cell lines at lower micro molar concentration. An in vitro assay investigation of these active compounds using recombinant human SIRT1 enzyme showed that one of the compounds (IT-14) inhibited the deacetylation activity of the enzyme. The in vivo study of IT-14 exemplified its promising action by reducing the prostate weight to the body weight ratio in prostate hyperplasia animal models. A remarkable decrease in the disruption of histoarchitecture of the prostate tissues isolated from IT-14 treated animal compared to that of the positive control was observed. The molecular interactions with SIRT1 enzyme were also supported by molecular docking simulations. Hence this compound can act as a lead molecule to treat prostatic hyperplasia. (C) 2013 Elsevier Masson SAS. All rights reserved.

A Kushner-Stratonovich Monte Carlo filter applied to nonlinear dynamical system identification

A Monte Carlo filter, based on the idea of averaging over characteristics and fashioned after a particle-based time-discretized approximation to the Kushner-Stratonovich (KS) nonlinear filtering equation, is proposed. A key aspect of the new filter is the gain-like additive update, designed to approximate the innovation integral in the KS equation and implemented through an annealing-type iterative procedure, which is aimed at rendering the innovation (observation prediction mismatch) for a given time-step to a zero-mean Brownian increment corresponding to the measurement noise. This may be contrasted with the weight-based multiplicative updates in most particle filters that are known to precipitate the numerical problem of weight collapse within a finite-ensemble setting. A study to estimate the a-priori error bounds in the proposed scheme is undertaken. The numerical evidence, presently gathered from the assessed performance of the proposed and a few other competing filters on a class of nonlinear dynamic system identification and target tracking problems, is suggestive of the remarkably improved convergence and accuracy of the new filter. (C) 2013 Elsevier B.V. All rights reserved.

Identification of heat shock factor binding protein in Plasmodium falciparum

Background: Heat shock factor binding protein (HSBP) was originally discovered in a yeast two-hybrid screen as an interacting partner of heat shock factor (HSF). It appears to be conserved in all eukaryotes studied so far, with yeast being the only exception. Cell biological analysis of HSBP in mammals suggests its role as a negative regulator of heat shock response as it appears to interact with HSF only during the recovery phase following exposure to heat stress. While the identification of HSF in the malaria parasite is still eluding biologists, this study for the first time, reports the presence of a homologue of HSBP in Plasmodium falciparum. Methods: PfHSBP was cloned and purified as his-tag fusion protein. CD (Circular dichroism) spectroscopy was performed to predict the secondary structure. Immunoblots and immunofluorescence approaches were used to study expression and localization of HSBP in P. falciparum. Cellular fractionation was performed to examine subcellular distribution of PfHSBP. Immunoprecipitation was carried out to identify HSBP interacting partner in P. falciparum. Results: PfHSBP is a conserved protein with a high helical content and has a propensity to form homo-oligomers. PfHSBP was cloned, expressed and purified. The in vivo protein expression profile shows maximal expression in trophozoites. The protein was found to exist in oligomeric form as trimer and hexamer. PfHSBP is predominantly localized in the parasite cytosol, however, upon heat shock, it translocates to the nucleus. This study also reports the interaction of PfHSBP with PfHSP70-1 in the cytoplasm of the parasite. Conclusions: This study emphasizes the structural and biochemical conservation of PfHSBP with its mammalian counterpart and highlights its potential role in regulation of heat shock response in the malaria parasite. Analysis of HSBP may be an important step towards identification of the transcription factor regulating the heat shock response in P. falciparum.

Titanium promoted reduction of imines with Grignards, silanes, and zinc: identification of a new mechanism with silanes

Aldimines react with reducing agents, such as Grignards, phenylsilane or zinc in the presence of titanium(IV) isopropoxide to form amines and reductively coupled imines (diamines). Using deuterium labeled reagents, the mechanism of reduction to form amines is described. Reducing agents, such as the Grignard and zinc result in the formation of low valent titanium (LVT), which in turn reduces the imine. On the other hand, phenylsilane reacts by a distinctly different mechanism and where a hydrogen atom from silicon is directly transferred to the titanium coordinated imine. (c) 2014 Elsevier Ltd. All rights reserved.

Identification of miRNAs from French bean (Phaseolus vulgaris) under low nitrate stress

Objective: In this study, we report the role of miRNAs involved under nitrogen starvation from widely grown vegetable crop, French bean. In recent years, a great deal of attention has been paid to the elucidation of miRNAs involved in low nitrate stress. Methods: To identify miRNAs expressed under stress, cDNA libraries were analyzed. Results: We reported the nine potential miRNAs with 67 targets involved in nutrient transporters and other stress specific genes. Among the miRNA sequences obtained 6 sequences belong to miR172 family, one with miR169. RT-PCR analysis of expression of miR172 family was induced upon low nitrate stress while miR169 family was repressed. In addition, Pvu-SN7b and Pvu-miR16 may be new members of miRNA172 and miR169 families, respectively. Conclusion: The targets of Pvu-SN7b were major protein kinases, one among which is the Protein Kinase CK2. CK2 Kinase is found to involve in transcription-directed signaling, gene control and cell-cycle regulation. Other targets of Pvu-SN7b were involved in DNA-dependent transcription regulation, photo-periodism, calcium-mediated signaling. Pvu-miR16 targets Thymidine kinase, the key enzyme of deoxy-nucleotide synthesis. The cleavage of these targets affects cell proliferation there by affecting nodule formation. Pvu-miR8 inhibits translation of its target protein Pre-protein translocase, a membrane-bound protein transporter involved in trans-membrane protein transportation. Together these results denote the response and role of miRNAs to nitrate-limiting conditions in French bean.