Mycobacterium tuberculosis Response Regulators, DevR and NarL, Interact in Vivo and Co-regulate Gene Expression during Aerobic Nitrate Metabolism

Mycobacterium tuberculosis genes Rv0844c/Rv0845 encoding the NarL response regulator and NarS histidine kinase are hypothesized to constitute a two-component system involved in the regulation of nitrate metabolism. However, there is no experimental evidence to support this. In this study, we established M. tuberculosis NarL/NarS as a functional two-component system and identified His(241) and Asp(61) as conserved phosphorylation sites in NarS and NarL, respectively. Transcriptional profiling between M. tuberculosis H37Rv and Delta narL mutant strain during exponential growth in broth cultures with or without nitrate defined an similar to 30-gene NarL regulon that exhibited significant overlap with DevR-regulated genes, thereby implicating a role for the DevR response regulator in the regulation of nitrate metabolism. Notably, expression analysis of a subset of genes common to NarL and DevR regulons in M. tuberculosis Delta devR, Delta devS Delta dosT, and Delta narL mutant strains revealed that in response to nitrite produced during aerobic nitrate metabolism, the DevRS/DosT regulatory system plays a primary role that is augmented by NarL. Specifically, NarL itself was unable to bind to the narK2, acg, and Rv3130c promoters in phosphorylated or unphosphorylated form; however, its interaction with DevR similar to P resulted in cooperative binding, thereby enabling co-regulation of these genes. These findings support the role of physiologically derived nitrite as a metabolic signal in mycobacteria. We propose NarL-DevR binding, possibly as a heterodimer, as a novel mechanism for co-regulation of gene expression by the DevRS/DosT and NarL/NarS regulatory systems.

An Optoelectronic Profiling and Ranging Sensor for Monitoring of Perimeters

Electronic monitoring of perimeters plays vital roles in homeland security, management of traffic and of humanwildlife conflict. This paper reports the design and development of an optical beam-interruption-based ranging and profiling sensor for monitoring perimeters. The developed sensor system can determine the distance of the object from the sensing units and its temporal height profile as the object crosses the system. Together, these quantities can also be used to classify the object and to determine its speed. The sensor is designed, fabricated, and evaluated. The design enables compact construction, high sensitivity, and low measurement crosstalk. The evaluation demonstrates accuracy better than 98.5% in the determination of height and over 94% in determination of the distance of an object from the sensing units. Finally, a strategy is proposed to classify the objects based on the obtained height profiles. The strategy is demonstrated to correctly classify the objects despite differences in their speed and the location at which they cross the system.

Chemical Shifts to Metabolic Pathways: Identifying Metabolic Pathways Directly from a Single 2D NMR Spectrum

Identifying cellular processes in terms of metabolic pathways is one of the avowed goals of metabolomics studies. Currently, this is done after relevant metabolites are identified to allow their mapping onto specific pathways. This task is daunting due to the complex nature of cellular processes and the difficulty in establishing the identity of individual metabolites. We propose here a new method: ChemSMP (Chemical Shifts to Metabolic Pathways), which facilitates rapid analysis by identifying the active metabolic pathways directly from chemical shifts obtained from a single two-dimensional (2D) C-13-H-1] correlation NMR spectrum without the need for identification and assignment of individual metabolites. ChemSMP uses a novel indexing and scoring system comprised of a ``uniqueness score'' and a ``coverage score''. Our method is demonstrated on metabolic pathways data from the Small Molecule Pathway Database (SMPDB) and chemical shifts from the Human Metabolome Database (HMDB). Benchmarks show that ChemSMP has a positive prediction rate of >90% in the presence of deduttered data and can sustain the same at 60-70% even in the presence of noise, such as deletions of peaks and chemical shift deviations. The method tested on NMR data acquired for a mixture of 20 amino acids shows a success rate of 93% in correct recovery of pathways. When used on data obtained from the cell lysate of an unexplored oncogenic cell line, it revealed active metabolic pathways responsible for regulating energy homeostasis of cancer cells. Our unique tool is thus expected to significantly enhance analysis of NMIR-based metabolomics data by reducing existing impediments.

Microbial community profiling shows dysbiosis in the lesional skin of Vitiligo subjects

Healthy human skin harbours a diverse array of microbes that comprise the skin microbiome. Commensal bacteria constitute an important component of resident microbiome and are intricately linked to skin health. Recent studies describe an association between altered skin microbial community and epidemiology of diseases, like psoriasis, atopic dermatitis etc. In this study, we compare the differences in bacterial community of lesional and non-lesional skin of vitiligo subjects. Our study reveals dysbiosis in the diversity of microbial community structure in lesional skin of vitiligo subjects. Although individual specific signature is dominant over the vitiligo-specific microbiota, a clear decrease in taxonomic richness and evenness can be noted in lesional patches. Investigation of community specific correlation networks reveals distinctive pattern of interactions between resident bacterial populations of the two sites (lesional and non-lesional). While Actinobacterial species constitute the central regulatory nodes (w.r.t. degree of interaction) in non-lesional skin, species belonging to Firmicutes dominate on lesional sites. We propose that the changes in taxonomic characteristics of vitiligo lesions, as revealed by our study, could play a crucial role in altering the maintenance and severity of disease. Future studies would elucidate mechanistic relevance of these microbial dynamics that can provide new avenues for therapeutic interventions.

Differential proteomic and genomic profiling of mouse striatal cell model of Huntington's disease and control; probable implications to the disease biology

Huntington's disease (HD) is an autosomal dominant disorder of central nervous system caused by expansion of CAG repeats in exon1 of the huntingtin gene (Htt). Among various dysfunctions originated from the mutation in Htt gene, transcriptional deregulation has been considered to be one of the most important abnormalities. Large numbers of investigations identified altered expressions of genes in brains of HD patients and many models of HD. In this study we employed 2D SDS-PAGE/MALDI-MS coupled with 2D-DIGE and real-time PCR experiments of an array of genes focused to HD pathway to determine altered protein and gene expressions in STHdh(Q111)/Hdh(Q111) cells, a cell model of HD and compared with STHdh(Q7)/Hdh(Q7) cells, its wild type counterpart. We annotated 76 proteins from these cells and observed differential expressions of 31 proteins (by 2D-DIGE) involved in processes like unfolded protein binding, negative regulation of neuron apoptosis, response to superoxides etc. Our PCR array experiments identified altered expressions of 47 genes. Altogether significant alteration of 77 genes/proteins could be identified in this HD cell line with potential relevance to HD biology. Biological significance: In this study we intended to find out differential proteomic and genomic profiles in HD condition. We used the STHdh cells, a cellular model for HD and control. These are mouse striatal neuronal cell lines harboring 7 and 111 knock -in CAG repeats in their two alleles. The 111Q containing cell line (STHdh(Q111)/Hdh(Q111)) mimics diseased condition, whereas the 7Q containing ones (STHdh(Q7)/Hdh(Q7)), serves as the proper control cell line. Proteomic experiments were performed earlier to obtain differential expressions of proteins in R6/2 mice models, Hdh(Q) knock -in mice and in plasma and CSF from HD patients. However, no earlier report on proteomic alterations in these two HD cell lines and control was available in literature. It was, therefore, an important objective to find out differential expressions of proteins in these two cell lines. In this study, we annotated 76 proteins from STHdh(Q7)/Hdh(Q7) and STHdh(Q111)/Hdh(Q111) cells using 2D-gel/mass spectrometry. Next, by performing 2D-DIGE, we observed differential expressions of 31 proteins (16 upregulated and 15 downregulated) between these two cell lines. We also performed customized qRT-PCR array focused to HD pathway and found differential expressions of 47 genes (8 gene exptessions increased and 39 genes were decreased significantly). A total of 77 genes/proteins (Htt downregulated in both the studies) were found to be significantly altered from both the experimental paradigms. We validated the differential expressions of Vim, Hypk, Ran, Dstn, Hspa5 and Sod2 either by qRT-PCR or Western blot analysis or both. Out of these 77, similar trends in alteration of 19 out of 31 and 38 out of 47 proteins/genes were reported in earlier studies. Thus our study confirmed earlier observations on differential gene/protein expressions in HD and are really useful. Additionally, we observed differential expression of some novel genes/proteins. One of this was Hypk, a Htt-interacting chaperone protein with the ability to solubilize mHtt aggregated structures in cell lines. We propose that downregulation of Hypk in STHdh-Qm (Q111)/Hdh(Q111) has a causal effect towards HD pathogenesis. Thus the novel findings from our study need further research and might be helpful to understand the molecular mechanism behind HD pathogenesis. (C) 2015 Elsevier B.V. All rights reserved.

PIB: Profiling Influential Blogger in Online Social Networks, A Knowledge Driven Data Mining Approach

Online Social Networks (OSNs) facilitate to create and spread information easily and rapidly, influencing others to participate and propagandize. This work proposes a novel method of profiling Influential Blogger (IB) based on the activities performed on one's blog documents who influences various other bloggers in Social Blog Network (SBN). After constructing a social blogging site, a SBN is analyzed with appropriate parameters to get the Influential Blog Power (IBP) of each blogger in the network and demonstrate that profiling IB is adequate and accurate. The proposed Profiling Influential Blogger (PIB) Algorithm survival rate of IB is high and stable. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).