Prediction of Essential Proteins of Klebsiella pneumoniae using Integrative Bioinformatics and Systems Biology Approach: Unveiling New Avenues for Drug Discovery.

Klebsiella pneumoniae is an opportunistic multidrug-resistant bacterial pathogen responsible for various health care-associated infections. The prediction of proteins that are essential for the survival of bacterial pathogens can greatly facilitate the drug development and discovery pipeline toward target identification. To this end, the present study reports a comprehensive computational approach integrating bioinformatics and systems biology-based methods to identify essential proteins of K. pneumoniae involved in vital processes. From the proteome of this pathogen, we predicted a total of 854 essential proteins based on sequence, protein-protein interaction (PPI) and genome-scale metabolic model methods. These predicted essential proteins are involved in vital processes for cellular regulation such as translation, metabolism, and biosynthesis of essential factors, among others. Cluster analysis of the PPI network revealed the highly connected modules involved in the basic functionality of the organism. Further, the predicted consensus set of essential proteins of K. pneumoniae was evaluated by comparing them with existing resources (NetGenes and PATHOgenex) and literature. The findings of this study offer guidance toward understanding cell functionality, thereby facilitating the understanding of pathogen systems and providing a way forward to shortlist potential therapeutic candidates for developing novel antimicrobial agents against K. pneumoniae. In addition, the research strategy presented herein is a fusion of sequence and systems biology-based approaches that offers prospects as a model to predict essential proteins for other pathogens.

Anti-quorum sensing potential of selenium nanoparticles against LasI/R, RhlI/R, and PQS/MvfR in Pseudomonas aeruginosa: a molecular docking approach.

Pseudomonas aeruginosa is an infectious pathogen which has the ability to cause primary and secondary contagions in the blood, lungs, and other body parts of immunosuppressed individuals, as well as community-acquired diseases, such as folliculitis, osteomyelitis, pneumonia, and others. This opportunistic bacterium displays drug resistance and regulates its pathogenicity via the quorum sensing (QS) mechanism, which includes the LasI/R, RhlI/R, and PQS/MvfR systems. Targeting the QS systems might be an excellent way to treat P. aeruginosa infections. Although a wide array of antibiotics, namely, newer penicillins, cephalosporins, and combination drugs are being used, the use of selenium nanoparticles (SeNPs) to cure P. aeruginosa infections is extremely rare as their mechanistic interactions are weakly understood, which results in carrying out this study. The present study demonstrates a computational approach of binding the interaction pattern between SeNPs and the QS signaling proteins in P. aeruginosa, utilizing multiple bioinformatics approaches. The computational investigation revealed that SeNPs were acutely 'locked' into the active region of the relevant proteins by the abundant residues in their surroundings. The PatchDock-based molecular docking analysis evidently indicated the strong and significant interaction between SeNPs and the catalytic cleft of LasI synthase (Phe105-Se = 2.7 Å and Thr121-Se = 3.8 Å), RhlI synthase (Leu102-Se = 3.7 Å and Val138-Se = 3.2 Å), transcriptional receptor protein LasR (Lys42-Se = 3.9 Å, Arg122-Se = 3.2 Å, and Glu124-Se = 3.9 Å), RhlR (Tyr43-Se = 2.9 Å, Tyr45-Se = 3.4 Å, and His61-Se = 3.5 Å), and MvfR (Leu208-Se = 3.2 Å and Arg209-Se = 4.0 Å). The production of acyl homoserine lactones (AHLs) was inhibited by the use of SeNPs, thereby preventing QS as well. Obstructing the binding affinity of transcriptional regulatory proteins may cause the suppression of LasR, RhlR, and MvfR systems to become inactive, thereby blocking the activation of QS-regulated virulence factors along with their associated gene expression. Our findings clearly showed that SeNPs have anti-QS properties against the established QS systems of P. aeruginosa, which strongly advocated that SeNPs might be a potent solution to tackle drug resistance and a viable alternative to conventional antibiotics along with being helpful in therapeutic development to cure P. aeruginosa infections.

Protein Therapeutic Target Candidates Against Acinetobacter baumannii, a Pathogen of Concern to Planetary Health: A Network-Based Integrative Omics Drug Discovery Approach.

Acinetobacter baumannii, an opportunistic gram-negative pathogen responsible for several nosocomial infections, has developed resistance to various antibiotics. Proteins involved in the two-component system (TCS), virulence, and antibiotic resistance (AR), help this pathogen in regulating antibiotic susceptibility and virulence mechanisms. The present study reports a network-based integrative omics approach to drug discovery to identify key regulatory proteins as therapeutic candidates against A. baumannii. We collected data on the TCS, virulence, and AR proteins from various databases (P2CS, VFDB, ARDB, and PAIDB), which were subjected to network, host-pathogen, and gene expression data analysis. Network analysis identified 43 hubs, and 10 proteins were found to be interacting with human proteins associated with vital pathways. Of the 53 (43 + 10) pathogen proteins, 46 had no orthologs in the human host. Twelve proteins, namely, RpfC, Wzc, OmpR, EnvZ, BfmS, PilG, histidine kinase, ABC 3 transport family protein, outer membrane porin OprD family, CsuD, Pgm, and LpxA, were differentially expressed in the resistant strain. We propose these proteins as key regulators that warrant evaluation as therapeutic target candidates in the future. Furthermore, structure prediction of ABC 3 transport family protein was performed as a case study. The findings from this study are poised to facilitate and inform drug discovery and development against A. baumannii.

Substantive Morphological Descriptions, Phylogenetic Analysis and Single Nucleotide Polymorphisms of Aspergillus Species From Foeniculum vulgare.

Ascomycetous fungi are found associated with a wide variety of substrates which range from fresh water to marine ecosystems, tropical to temperate forest soils and deserts, throughout the world over. These demystifying fungi exist as endophytes, pathogens and saprobes. They have been studied due to their ability to contaminate foods and feedstuffs, causing an elaboration of mycotoxins. The objectives of the study included extensive analyses of the morphological features of fungi, especially Aspergilli, which have been presented while studying them on specific mycological media. It is also an elaborate compilation of substantive macro- and micro-morphological characterization of different Aspergilli isolated from the spice Foeniculum vulgare used in India and other countries in the world. Further, a first of its kind attempt has been made to study their relative abundance and frequency of occurrence, molecular phylogeny and genetic relatedness to characterize the Aspergilli into specific sections, groups and clades. Single nucleotide polymorphism (SNP) analysis was carried out to evaluate the functional consequences of nucleotide variations, synonymous and non-synonymous mutations in the protein structure. The study resulted in a total of 3,506 Aspergillus isolates, which were obtained from seventy (70) fennel samples, representing 14 Aspergillus species. The two most frequently found species were A. niger and A. flavus with a relative abundance of 32.24 and 11.63%, respectively. The taxonomy and current placements have been reappraised with suggestions and prospects for future research from six sections namely Terrei, Flavi, Fumigati, Nidulantes, Nigri, and Versicolores. In addition, a total number of 27 isolates were studied and deposited at the National Centre for Biotechnology Information (NCBI) and five Aspergillus species have been identified and are being reported for the first time from the fennel seeds, based on partial sequence analysis of the official fungal barcode namely, Internal Transcribed Spacer (ITS) and a functional gene, beta tubulin gene locus, coupled with phenotypic characterization. SNPs for specific DNA regions have been used to identify variants in Aspergilli obtained from Indian fennel seeds for the first time. The need for a polyphasic approach of morphological identification and genetic characterization of Aspergilli from Foeniculum vulgare is addressed and presented here in adequate detail. Our current work makes extensive use of partial beta-tubulin gene sequences analyses to evaluate the association between SNPs in five Aspergillus species sections.

In silico analysis of Leishmania proteomes and protein-protein interaction network: Prioritizing therapeutic targets and drugs for repurposing to treat leishmaniasis.

Leishmaniasis is a serious world health problem and its current therapies have several limitations demanding to develop novel therapeutics for this disease. The present study aims to prioritize novel broad-spectrum targets using proteomics and protein-protein interaction network (PPIN) data for 11 Leishmania species. Proteome comparison and host non-homology analysis resulted in 3605 pathogen-specific conserved core proteins. Gene ontology analysis indicated their involvement in major molecular functions like DNA binding, transportation, dioxygenase, and catalytic activity. PPIN analysis of these core proteins identified eight hub proteins (viz., vesicle-trafficking protein (LBRM2903_190011800), ribosomal proteins S17 (LBRM2903_34004790) and L2 (LBRM2903_080008100), eukaryotic translation initiation factor 3 (LBRM2903_350086700), replication factor A (LBRM2903_150008000), U3 small nucleolar RNA-associated protein (LBRM2903_340025600), exonuclease (LBRM2903_200021800), and mitochondrial RNA ligase (LBRM2903_200074100)). Among the hub proteins, six were classified as drug targets and two as vaccine candidates. Further, druggability analysis indicated three hub proteins, namely eukaryotic translation initiation factor 3, ribosomal proteins S17 and L2 as druggable. Their three-dimensional structures were modelled and docked with the identified ligands (2-methylthio-N6-isopentenyl-adenosine-5'-monophosphate, artenimol and omacetaxine mepesuccinate). These ligands could be experimentally validated (in vitro and in vivo) and repurposed for the development of novel antileishmanial agents.

The phytochemical brazilin suppress DNMT1 expression by recruiting p53 to its promoter resulting in the epigenetic restoration of p21 in MCF7cells.

BACKGROUND: Cancer is an outcome of uncontrolled cell division eventually associated with dysregulated epigenetic mechanisms, including DNA methylation. DNA methyltransferase 1 is ubiquitously expressed in the proliferating cells and is essential for the maintenance of DNA methylation. It causes the abnormal silencing of tumor suppressor genes in human cancer which is necessary for proliferation, cell cycle progression, and survival. DNMT1 is involved in tumorigenesis of several cancers, its upregulation potentially upscale the promoter level inactivation of transcription of a tumor inhibitory gene by introducing repressive methylation marks on the CpG islands. This epigenetic perturbation caused by DNMT is targeted for cancer therapeutics. PURPOSE: To demonstrate the proliferative inhibitory potential of brazilin in human breast cancer cell line (MCF-7) with concurrent mitigation of DNMT1 functional expression and to understand its effect on downstream targets like cell cycle inhibitor p21. STUDY DESIGN/ METHODS: The impact of brazilin on the growth and proliferation of the MCF-7 cells was determined using the XTT assay. The global DNA 5-methyl cytosine methylation pattern was analyzed upon brazilin treatment. The gene and protein expression of DNMTs were determined with quantitative RTPCR and western blots respectively. The potential binding sites of transcription factors in the human DNMT1 promoter were predicted using the MatInspector tool on the Genomatix software. The chromatin immunoprecipitation (ChIP) assay was performed to demonstrate the transcription factors occupancy at the promoter. Methylation of promoter CpG islands was determined by the methylation-specific PCR (MSP) upon brazilin treatment. The molecular docking of the human DNMT1 with brazilin (ligand) was performed using the Schrödinger suite. RESULTS: The heterotetracyclic compound brazilin, present in the wood of Caesalpinia sappan, inhibited the proliferation of the human breast cancer cell line (MCF-7) and reduced the DNMT1 expression with a decrease in global DNA methylation. Brazilin, by activating p38 MAPK and elevating p53 levels within the exposed cells. The elevated level of p53 enriched the occupancy at binding sites within 200 bp upstream to the transcription start site in the DNMT1 promoter, resulting in reduced DNMT1 gene expression. Furthermore, the brazilin restored the p21 levels in the exposed cells as the CpGs in the p21 promoter (-128 bp/+17 bp) were significantly demethylated as observed in the methylation-specific PCR (MSP). CONCLUSION: Highly potential anti-proliferative molecule brazilin can modulate the DNMT1 functional expression and restore the cell cycle inhibitor p21expression. We propose that brazilin can be used in therapeutic interventions to restore the deregulated epigenetic mechanisms in cancer.

A Comparative Genomics Approach for Shortlisting Broad-Spectrum Drug Targets in Nontuberculous Mycobacteria.

Many members of nontuberculous mycobacteria (NTM) are opportunistic pathogens causing several infections in animals. The incidence of NTM infections and emergence of drug-resistant NTM strains are rising worldwide, emphasizing the need to develop novel anti-NTM drugs. The present study is aimed to identify broad-spectrum drug targets in NTM using a comparative genomics approach. The study identified 537 core proteins in NTM of which 45 were pathogen specific and essential for the survival of pathogens. Furthermore, druggability analysis indicated that 15 were druggable among those 45 proteins. These 15 proteins, which were core proteins, pathogen-specific, essential, and druggable, were considered as potential broad-spectrum candidates. Based on their locations in cytoplasm and membrane, targets were classified as drug and vaccine targets. The identified 15 targets were different enzymes, carrier proteins, transcriptional regulator, two-component system protein, ribosomal, and binding proteins. The identified targets could further be utilized by researchers to design inhibitors for the discovery of antimicrobial agents.

Novel Target Exploration from Hypothetical Proteins of Klebsiella pneumoniae MGH 78578 Reveals a Protein Involved in Host-Pathogen Interaction.

The opportunistic pathogen Klebsiella pneumoniae is a causative agent of several hospital-acquired infections. It has become resistant to a wide range of currently available antibiotics, leading to high mortality rates among patients; this has further led to a demand for novel therapeutic intervention to treat such infections. Using a series of in silico analyses, the present study aims to explore novel drug/vaccine candidates from the hypothetical proteins of K. pneumoniae. A total of 540 proteins were found to be hypothetical in this organism. Analysis of these 540 hypothetical proteins revealed 30 pathogen-specific proteins essential for pathogen survival. A motifs/domain family analysis, similarity search against known proteins, gene ontology, and protein-protein interaction analysis of the shortlisted 30 proteins led to functional assignment for 17 proteins. They were mainly cataloged as enzymes, lipoproteins, stress-induced proteins, transporters, and other proteins (viz., two-component proteins, skeletal proteins and toxins). Among the annotated proteins, 16 proteins, located in the cytoplasm, periplasm, and inner membrane, were considered as potential drug targets, and one extracellular protein was considered as a vaccine candidate. A druggability analysis indicated that the identified 17 drug/vaccine candidates were "novel". Furthermore, a host-pathogen interaction analysis of these identified target candidates revealed a betaine/carnitine/choline transporters (BCCT) family protein showing interactions with five host proteins. Structure prediction and validation were carried out for this protein, which could aid in structure-based inhibitor design.

Exploring microRNAs, Target mRNAs and their Functions in Leguminous Plant Arachis hypogaea.

BACKGROUND: MicroRNAs (miRNAs) are a class of small non-coding, endogenous RNAs that regulate gene expression at post-transcriptional level. In plants, miRNAs are usually of 18-24 nucleotide in length and play humongous role by aiding in development, growth, defense, biotic and abiotic stress responses, etc. Objective: Arachis hypogaea is an economically important oil seed crop and human dietary source cultivated mostly in tropical and subtropical regions. In the present study, an initiative was taken to uncover miRNAs, their targets and functions in this important plant species. METHOD: Comparative genomics strategy coupled with bioinformatics approaches was deployed for the identification of miRNAs, their corresponding targets and functions by exploiting biological databases and tools. RESULTS: The study was able to identify 34 conserved miRNA candidates, belonging to 17 miRNA families, contributed by 23 and 3 precursor miRNAs from A. hypogaea Expressed Sequence Tags (EST) and Genome Survey Sequences (GSS), respectively. As well, 495 EST and 917 unigene sequences were predicted as targets for the identified miRNAs. Herein, psRNAtarget server and TargetFinder tool were used to predict unigene targets, whereas comparative genomics strategy was used for identifying EST targets. Functional annotation of the identified targets revealed that the identified miRNAs regulate mRNAs that participate in key biological and metabolic processes. Pathway enrichment analysis using KEGG database also revealed that they regulate important metabolic pathways including antibiotic biosynthesis, biosynthesis of unsaturated fatty acids, amino acids metabolism and flavonoid biosynthesis. CONCLUSION: The outcome of the study would aid experimental biologists to focus on these miRNAs to facilitate improved crop development and yield.

Computational Approaches and Related Tools to Identify MicroRNAs in a Species: A Bird's Eye View.

MicroRNAs (miRNAs) are a family of non-coding RNAs that play a central role in fine-tuning gene expression regulation. Over the past decade, identification and annotation of miRNAs have become a major focus in epigenomics research. However, detection and characterization of miRNA are challenging due to its small size (~22 nucleotide-long) and susceptibility to degradation. The difficulties involved in experimental prediction and characterization of miRNA coding genes have led to the development of in silico-based approaches. Although several algorithms have been developed in recent years, a comprehensive assessment of the principles, methodological insights, and estimate of the strengths and weaknesses of computational methods are limited. The present review is dealt with the detailed methodological insights of different tools used for identifying miRNA coding genes falling under four computational approaches. The parameters considered in these tools along with their specificity are also delineated. Furthermore, the strengths and weaknesses of these four computational approaches, and the bioinformatics resources pertaining to target identification, expression analysis, regulatory network analysis, and SNP identification are stated in this review. The methodological details of miRNA prediction methods and bioinformatics resources related to miRNA research in one platform would facilitate the miRNA research community to develop efficient tools for uncovering novel miRNAs and understanding their role in regulatory networks.

Functional assignment for essential hypothetical proteins of Staphylococcus aureus N315.

Staphylococcus aureus, the causative agent of nosocomial infections worldwide, has acquired resistance to almost all antibiotics stressing the need to develop novel drugs against this pathogen. In S. aureus N315, 302 genes have been identified as essential genes, indispensable for growth and survival of the pathogen. The functions of 40 proteins encoded by S. aureus essential genes were found to be hypothetical and thus referred as essential hypothetical proteins (EHPs). The present study aims to carry out functional characterization of EHPs using bioinformatics tools/databases, whose performance was assessed by Receiver operating characteristic curve analysis. Evaluation of physicochemical parameters, homology search against known proteins, domain analysis, subcellular localization analysis and virulence prediction assisted us to characterize EHPs. Functional assignment for 35 EHPs was made with high confidence. They belong to different functional classes like enzymes, binding proteins, miscellaneous proteins, helicases, transporters and virulence factors. Around 35% of EHPs were from hydrolases family. A group of EHPs (32.5%) were predicted as virulence factors. Of 35, 19 essential pathogen-specific proteins were considered as probable drug targets. Two targets were found to be druggable and others were novel targets. Outcome of the study could aid to identify novel drugs for better treatment of S. aureus infections.

Computational analysis of protein interaction networks for infectious diseases.

Infectious diseases caused by pathogens, including viruses, bacteria and parasites, pose a serious threat to human health worldwide. Frequent changes in the pattern of infection mechanisms and the emergence of multidrug-resistant strains among pathogens have weakened the current treatment regimen. This necessitates the development of new therapeutic interventions to prevent and control such diseases. To cater to the need, analysis of protein interaction networks (PINs) has gained importance as one of the promising strategies. The present review aims to discuss various computational approaches to analyse the PINs in context to infectious diseases. Topology and modularity analysis of the network with their biological relevance, and the scenario till date about host-pathogen and intra-pathogenic protein interaction studies were delineated. This would provide useful insights to the research community, thereby enabling them to design novel biomedicine against such infectious diseases.

Unraveling novel broad-spectrum antibacterial targets in food and waterborne pathogens using comparative genomics and protein interaction network analysis.

Food and waterborne diseases are a growing concern in terms of human morbidity and mortality worldwide, even in the 21st century, emphasizing the need for new therapeutic interventions for these diseases. The current study aims at prioritizing broad-spectrum antibacterial targets, present in multiple food and waterborne bacterial pathogens, through a comparative genomics strategy coupled with a protein interaction network analysis. The pathways unique and common to all the pathogens under study (viz., methane metabolism, d-alanine metabolism, peptidoglycan biosynthesis, bacterial secretion system, two-component system, C5-branched dibasic acid metabolism), identified by comparative metabolic pathway analysis, were considered for the analysis. The proteins/enzymes involved in these pathways were prioritized following host non-homology analysis, essentiality analysis, gut flora non-homology analysis and protein interaction network analysis. The analyses revealed a set of promising broad-spectrum antibacterial targets, present in multiple food and waterborne pathogens, which are essential for bacterial survival, non-homologous to host and gut flora, and functionally important in the metabolic network. The identified broad-spectrum candidates, namely, integral membrane protein/virulence factor (MviN), preprotein translocase subunits SecB and SecG, carbon storage regulator (CsrA), and nitrogen regulatory protein P-II 1 (GlnB), contributed by the peptidoglycan pathway, bacterial secretion systems and two-component systems, were also found to be present in a wide range of other disease-causing bacteria. Cytoplasmic proteins SecG, CsrA and GlnB were considered as drug targets, while membrane proteins MviN and SecB were classified as vaccine targets. The identified broad-spectrum targets can aid in the design and development of antibacterial agents not only against food and waterborne pathogens but also against other pathogens.

Identification and characterization of potential therapeutic candidates in emerging human pathogen Mycobacterium abscessus: a novel hierarchical in silico approach.

Mycobacterium abscessus, a non-tuberculous rapidly growing mycobacterium, is recognized as an emerging human pathogen causing a variety of infections ranging from skin and soft tissue infections to severe pulmonary infections. Lack of an optimal treatment regimen and emergence of multi-drug resistance in clinical isolates necessitate the development of better/new drugs against this pathogen. The present study aims at identification and qualitative characterization of promising drug targets in M. abscessus using a novel hierarchical in silico approach, encompassing three phases of analyses. In phase I, five sets of proteins were mined through chokepoint, plasmid, pathway, virulence factors, and resistance genes and protein network analysis. These were filtered in phase II, in order to find out promising drug target candidates through subtractive channel of analysis. The analysis resulted in 40 therapeutic candidates which are likely to be essential for the survival of the pathogen and non-homologous to host, human anti-targets, and gut flora. Many of the identified targets were found to be involved in different metabolisms (viz., amino acid, energy, carbohydrate, fatty acid, and nucleotide), xenobiotics degradation, and bacterial pathogenicity. Finally, in phase III, the candidate targets were qualitatively characterized through cellular localization, broad spectrum, interactome, functionality, and druggability analysis. The study explained their subcellular location identifying drug/vaccine targets, possibility of being broad spectrum target candidate, functional association with metabolically interacting proteins, cellular function (if hypothetical), and finally, druggable property. Outcome of the present study could facilitate the identification of novel antibacterial agents for better treatment of M. abscesses infections.

Clostridium-DT(DB): a comprehensive database for potential drug targets of Clostridium difficile.

Clostridium difficile is considered to be one of the most important causes of health care-associated infections currently. The prevalence and severity of C. difficile infection have increased significantly worldwide in the past decade which has led to the increased research interest. Here, using comparative genomics strategy coupled with bioinformatics tools we have identified potential drug targets in C. difficile and determined their three-dimensional structures in order to develop a database, named Clostridium-DT(DB). Currently, the database comprises the potential drug targets with their structural information from three strains of C. difficile, namely hypervirulent PCR-ribotype 027 strain R20291, PCR-ribotype 012 strain 630, and PCR-ribotype 027 strain CD196.

Identification of potential drug targets in Yersinia pestis using metabolic pathway analysis: MurE ligase as a case study.

Sporadic outbreaks of plague, lack of a vaccine, emergence of multidrug-resistant strains of Yersinia pestis, and its potential use in bioterrorism, call for an urgent need to develop new drugs for plague. We have used comparative metabolic pathway analysis to identify 245 drug-target candidate enzymes in Y. pestis CO92 which are non-homologous to host Homo sapiens and likely to be essential for the pathogen's survival. Further analysis revealed that 25 of these are potential choke point enzymes. As a case study, structure of a choke point enzyme, MurE ligase, was modeled and docking studies performed against a library of compounds leading to identification of a potential inhibitor. This approach enables rapid potential drug-target identification, thereby facilitating search for new antimicrobials.

A Bioinformatics Resource for TWEAK-Fn14 Signaling Pathway.

TNF-related weak inducer of apoptosis (TWEAK) is a new member of the TNF superfamily. It signals through TNFRSF12A, commonly known as Fn14. The TWEAK-Fn14 interaction regulates cellular activities including proliferation, migration, differentiation, apoptosis, angiogenesis, tissue remodeling and inflammation. Although TWEAK has been reported to be associated with autoimmune diseases, cancers, stroke, and kidney-related disorders, the downstream molecular events of TWEAK-Fn14 signaling are yet not available in any signaling pathway repository. In this paper, we manually compiled from the literature, in particular those reported in human systems, the downstream reactions stimulated by TWEAK-Fn14 interactions. Our manual amassment of the TWEAK-Fn14 pathway has resulted in cataloging of 46 proteins involved in various biochemical reactions and TWEAK-Fn14 induced expression of 28 genes. We have enabled the availability of data in various standard exchange formats from NetPath, a repository for signaling pathways. We believe that this composite molecular interaction pathway will enable identification of new signaling components in TWEAK signaling pathway. This in turn may lead to the identification of potential therapeutic targets in TWEAK-associated disorders.

Analysis of the genome and proteome composition of Bdellovibrio bacteriovorus: indication for recent prey-derived horizontal gene transfer.

The genome/proteome composition of Bdellovibrio bacteriovorus, the predatory microorganism that preys on other Gram-negative bacteria, has been analyzed. The study elucidates that translational selection plays a major role in genome compositional variation with higher intensity compared to other deltaproteobacteria. Other sources of variations having relatively minor contributions are local GC-bias, horizontal gene transfer and strand-specific mutational bias. The study identifies a group of AT-rich genes with distinct codon composition that is presumably acquired by Bdellovibrio recently from Gram-negative prey-bacteria other than deltaproteobacteria. The proteome composition of this species is influenced by various physico-chemical factors, viz, alcoholicity, residue-charge, aromaticity and hydropathy. Cell-wall-surface-anchor-family (CSAPs) and transporter proteins with distinct amino acid composition and specific secondary-structure also contribute notably to proteome compositional variation. CSAPs, which are low molecular-weight, outer-membrane proteins with highly disordered secondary-structure, have preference toward polar-uncharged residues and cysteine that presumably help in prey-predator interaction by providing particular bonds of attachment.

Genus specific evolution of codon usage and nucleotide compositional traits of poxviruses.

Poxviruses are complex in their nucleotide compositional features of the coding regions. The codon usages in Poxviruses are in accordance with their compositional bias. In the Poxviridae family, codon usage patterns and nucleotide compositional traits are widely divergent across species but some conservation was observed within a genus. Viruses from six Chordopox genera, i.e., Avipoxvirus, Capripoxvirus, Cervidpoxvirus, Orthopoxvirus, Suipoxvirus, Yatapoxvirus, and one Entomopox genus- Betaentomopoxvirus, and some unclassified Entomopoxvirus are significantly rich in AT composition. Four other Chordopox genera- Molluscipoxvirus, Orthopoxvirus, Parapoxvirus, and some unclassified Chordopoxvirus are dominated by the GC rich viruses. Poxviruses from these AT rich and GC rich genera preferred AT or GC ending codons owing to their respective nucleotide compositional bias. For example, viruses from AT rich Orthopoxvirus, or GC rich Parapoxvirus have evolved with mutually exclusive type codon preferences following their genus-specific nucleotide compositions. Additional factors like gene length and expression level also influenced their codon usage patterns to some extent in some Poxvirus genera. Evidences from correspondence analysis and cluster analysis on the extent of divergence in codon usage also support this genus specific evolution of Poxvirus codon usage. Analyzes suggest that most of the Poxviruses from different genera, have evolved in almost two different evolutionary trajectory in context of their nucleotide composition and codon usage.

A Signaling Network of Thyroid-Stimulating Hormone.

Human thyroid stimulating hormone (TSH) is a glycoprotein secreted by the anterior part of the pituitary gland. TSH plays an important physiological role in the regulation of hypothalamic-pituitary-thyroid axis by modulating the release of the thyroid hormones from the thyroid gland. It induces iodine uptake by the thyroid, promotes thyroid epithelial differentiation and growth, and protects thyroid cells from apoptosis. Impairment of TSH signal transduction pathway leads to thyroid disorders such as goitre, hypothyroidism and hyperthyroidism, which can have complex clinical manifestations. TSH signaling is largely effected through two separate pathways, the adenylate cyclase and the phospholipase C pathways. In spite of its biomedical importance, a concise signaling map of TSH pathway is not available in the public domain. Therefore, we have generated a detailed signaling map of TSH pathway by systematically cataloging the molecular reactions induced by TSH including protein-protein interactions, post-translational modifications, protein translocation events and activation/inhibition reactions. We have cataloged 40 molecular association events, 42 enzyme-substrate reactions and 16 protein translocation events in TSH signaling pathway resource. Additionally, we have documented 208 genes, which are differentially regulated by TSH. We have provided the details of TSH pathway through NetPath (http://www.netpath.org), which is a publicly available resource for human signaling pathways developed by our group. We have also depicted the map of TSH signaling using NetSlim criteria (http://www.netpath.org/netslim/) and provided pathway maps in Wikipathways (http://www.wikipathways.org/). We anticipate that the availability of TSH pathway as a community resource will enhance further biomedical investigations into the function and effects of this important hormone.