Abstract: Host responses to infections represent an important pathogenicity determiner, and delineation of host responses can elucidate pathogenesis processes and inform the development of anti-infection therapies. Low cost, high throughput, easy quantitation, and rich descriptions have made gene expression profiling generated by DNA microarrays an optimal approach for describing host transcriptional responses (HTRs). However, efforts to characterize the landscape of HTRs to diverse pathogens are far from offering a comprehensive view. Here, we developed an HTR Connectivity Map based on systematic assessment of pairwise similarities of HTRs to 50 clinically important human pathogens using 1353 gene-expression profiles generated from >60 human cells/tissues. These 50 pathogens were further partitioned into eight robust "HTR communities" (i.e., groups with more consensus internal HTR similarities). These communities showed enrichment in specific infection attributes and differential gene expression patterns. Using query signatures of HTRs to external pathogens, we demonstrated four distinct modes of HTR associations among different pathogens types/class, and validated the reliability of the HTR community divisions for differentiating and categorizing pathogens from a host-oriented perspective. These findings provide a first-generation HTR Connectivity Map of 50 diverse pathogens, and demonstrate the potential for using annotated HTR community to detect functional associations among infectious pathogens.

Abstract: UNLABELLED: As diet is considered the major regulator of the gut ecosystem, the overall objective of this work was to demonstrate that a detailed knowledge of the phytochemical composition of food could add to our understanding of observed changes in functionality and activity of the gut microbiota. We used metatranscriptomic data from a human dietary intervention study to develop a network that consists of >400 compounds present in the administered plant-based diet linked to 609 microbial targets in the gut. Approximately 20% of the targeted bacterial proteins showed significant changes in their gene expression levels, while functional and topology analyses revealed that proteins in metabolic networks with high centrality are the most "vulnerable" targets. This global view and the mechanistic understanding of the associations between microbial gene expression and dietary molecules could be regarded as a promising methodological approach for targeting specific bacterial proteins that impact human health. IMPORTANCE: It is a general belief that microbiome-derived drugs and therapies will come to the market in coming years, either in the form of molecules that mimic a beneficial interaction between bacteria and host or molecules that disturb a harmful interaction or proteins that can modify the microbiome or bacterial species to change the balance of "good" and "bad" bacteria in the gut microbiome. However, among the numerous factors, what has proven the most influential for modulating the microbial composition of the gut is diet. In line with this, we demonstrate here that a systematic analysis of the interactions between the small molecules present in our diet and the gut bacterial proteome holds great potential for designing dietary interventions to improve human health.

Abstract: BACKGROUND: Elucidation of human disease similarities has emerged as an active research area, which is highly relevant to etiology, disease classification, and drug repositioning. In pioneer studies, disease similarity was commonly estimated according to clinical manifestation. Subsequently, scientists started to investigate disease similarity based on gene-phenotype knowledge, which were inevitably biased to well-studied diseases. In recent years, estimating disease similarity according to transcriptomic behavior significantly enhances the probability of finding novel disease relationships, while the currently available studies usually mine expression data through differential expression analysis that has been considered to have little chance of unraveling dysfunctional regulatory relationships, the causal pathogenesis of diseases. METHODS: We developed a computational approach to measure human disease similarity based on expression data. Differential coexpression analysis, instead of differential expression analysis, was employed to calculate differential coexpression level of every gene for each disease, which was then summarized to the pathway level. Disease similarity was eventually calculated as the partial correlation coefficients of pathways' differential coexpression values between any two diseases. The significance of disease relationships were evaluated by permutation test. RESULTS: Based on mRNA expression data and a differential coexpression analysis based method, we built a human disease network involving 1326 significant Disease-Disease links among 108 diseases. Compared with disease relationships captured by differential expression analysis based method, our disease links shared known disease genes and drugs more significantly. Some novel disease relationships were discovered, for example, Obesity and cancer, Obesity and Psoriasis, lung adenocarcinoma and S. pneumonia, which had been commonly regarded as unrelated to each other, but recently found to share similar molecular mechanisms. Additionally, it was found that both the type of disease and the type of affected tissue influenced the degree of disease similarity. A sub-network including Allergic asthma, Type 2 diabetes and Chronic kidney disease was extracted to demonstrate the exploration of their common pathogenesis. CONCLUSION: The present study produces a global view of human diseasome for the first time from the viewpoint of regulation mechanisms, which therefore could provide insightful clues to etiology and pathogenesis, and help to perform drug repositioning and design novel therapeutic interventions.

Abstract: As the level of interest in aging research increases, there is a growing number of geroprotectors, or therapeutic interventions that aim to extend the healthy lifespan and repair or reduce aging-related damage in model organisms and, eventually, in humans. There is a clear need for a manually-curated database of geroprotectors to compile and index their effects on aging and age-related diseases and link these effects to relevant studies and multiple biochemical and drug databases. Here, we introduce the first such resource, Geroprotectors (http://geroprotectors.org). Geroprotectors is a public, rapidly explorable database that catalogs over 250 experiments involving over 200 known or candidate geroprotectors that extend lifespan in model organisms. Each compound has a comprehensive profile complete with biochemistry, mechanisms, and lifespan effects in various model organisms, along with information ranging from chemical structure, side effects, and toxicity to FDA drug status. These are presented in a visually intuitive, efficient framework fit for casual browsing or in-depth research alike. Data are linked to the source studies or databases, providing quick and convenient access to original data. The Geroprotectors database facilitates cross-study, cross-organism, and cross-discipline analysis and saves countless hours of inefficient literature and web searching. Geroprotectors is a one-stop, knowledge-sharing, time-saving resource for researchers seeking healthy aging solutions.

Abstract: There is on-going effort in the biomedical research community to leverage Next Generation Sequencing (NGS) technology to identify genetic variants that affect our health. The main challenge facing researchers is getting enough samples from individuals either sick or healthy - to be able to reliably identify the few variants that are causal for a phenotype among all other variants typically seen among individuals. At the same time, more and more individuals are having their genome sequenced either out of curiosity or to identify the cause of an illness. These individuals may benefit from of a way to view and understand their data. QIAGEN's Ingenuity Variant Analysis is an online application that allows users with and without extensive bioinformatics training to incorporate information from published experiments, genetic databases, and a variety of statistical models to identify variants, from a long list of candidates, that are most likely causal for a phenotype as well as annotate variants with what is already known about them in the literature and databases. Ingenuity Variant Analysis is also an information sharing platform where users may exchange samples and analyses. The Empowered Genome Community (EGC) is a new program in which QIAGEN is making this on-line tool freely available to any individual who wishes to analyze their own genetic sequence. EGC members are then able to make their data available to other Ingenuity Variant Analysis users to be used in research. Here we present and describe the Empowered Genome Community in detail. We also present a preliminary, proof-of-concept study that utilizes the 200 genomes currently available through the EGC. The goal of this program is to allow individuals to access and understand their own data as well as facilitate citizen-scientist collaborations that can drive research forward and spur quality scientific dialogue in the general public.

Abstract: The emergence of a number of publicly available bioactivity databases, such as ChEMBL, PubChem BioAssay and BindingDB, has raised awareness about the topics of data curation, quality and integrity. Here we provide an overview and discussion of the current and future approaches to activity, assay and target data curation of the ChEMBL database. This curation process involves several manual and automated steps and aims to: (1) maximise data accessibility and comparability; (2) improve data integrity and flag outliers, ambiguities and potential errors; and (3) add further curated annotations and mappings thus increasing the usefulness and accuracy of the ChEMBL data for all users and modellers in particular. Issues related to activity, assay and target data curation and integrity along with their potential impact for users of the data are discussed, alongside robust selection and filter strategies in order to avoid or minimise these, depending on the desired application.

Abstract: Corynebacterium species are increasingly recognized as important pathogens in granulomatous mastitis. Currently, there are no published treatment protocols for Corynebacterium breast infections. This study describes antimicrobial treatment options in the context of other management strategies used for granulomatous mastitis. Corynebacterium spp. isolated from breast tissue and aspirate samples stored from 2002 to 2013 were identified and determined to the species level using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), 16S RNA sequencing, and rpoB gene targets. The MICs for 12 antimicrobials were performed using Etest for each isolate. Correlations of these with antimicrobial characteristics, choice of antimicrobial, and disease outcome were evaluated. Corynebacterium spp. from breast tissue and aspirate samples were confirmed in 17 isolates from 16 patients. Based on EUCAST breakpoints, Corynebacterium kroppenstedtii isolates (n = 11) were susceptible to seven antibiotic classes but resistant to beta-lactam antibiotics. Corynebacterium tuberculostearicum isolates (n = 4) were multidrug resistant. Two nonlipophilic species were isolated, Corynebacterium glucuronolyticum and Corynebacterium freneyi, both of which have various susceptibilities to antimicrobial agents. Short-course antimicrobial therapy was common (median, 6 courses per subject; range, 1 to 9 courses). Patients with C. kroppenstedtii presented with a hot painful breast mass and underwent multiple surgical procedures (median, 4 procedures; range, 2 to 6 procedures). The management of Corynebacterium breast infections requires a multidisciplinary approach and includes culture and appropriate sensitivity testing to guide antimicrobial therapy. Established infections have a poor outcome, possibly because adequate concentrations of some drugs will be difficult to achieve in lipophilic granulomata. Lipophilic antimicrobial therapy may offer a therapeutic advantage. The role of immunotherapy has not been defined.

Abstract: The diseases caused by dermatophytes are common among several other infections which cause serious threat to human health. It is evident that enzyme squalene epoxidase is responsible for prolonged dermatophyte infection and it is appealing to note that this enzyme is also responsible for fatty acid synthesis in these groups of fungi. In the present study, terbinafine drug which targets enzyme squalene epoxidase has been explored to design its various novel analogues. The present study suggests that many more prominent drug analogues could be constituted which may be crucial towards designing new drug candidates. In the present study, we have designed a series of such analogues viz. [(2E)-6,6-dimethylhept-2-en-4-yn-1-yl](methyl)(naphthalen-1-ylmethyl)amine, N-[8-({[(2E)-6,6-dimethylhept-2-en-4-yn-1-yl](methyl)amino}methyl)naphthalen-1-yl ]-2-(sulfoamino) acetamide, {[4-(dihydroxyamino)-8-({[(2E)-6,6-dimethylhept-2-en-4-yn-1-yl](methyl)amino}meth yl)naphthalen-1-yl]sulfanyl}methanol and (R)-{[4-({[(2E,6R)-6,7-dimethyloct-2-en-4-yn-1-yl](methyl)amino}methyl)-5-[(hydro xysulfamoyl)amino]naphthalen-1-yl]amino}sulfinic acid. Moreover, further by molecular docking approach the binding between enzyme and designed analogues was further analysed. The present preliminary report suggested a considerably good docking interaction score of -338.75 kcal/mol between terbinafine and squalene epoxidase from Trichophyton rubrum. This preliminary study implies that few designed candidate ligands can be effectual towards the activity of this enzyme and can play crucial role in pathogenesis control of T. rubrum.

Abstract: Cytochrome c (cyt c) release from mitochondria is accepted to be the point of no return for eliciting a cascade of interactions that lead to apoptosis. A strategy for containing sustained apoptosis is to reduce the mitochondrial permeability pore opening. Pore opening is enhanced by peroxidase activity of cyt c gained upon its complexation with cardiolipin in the presence of reactive oxygen species. Blocking access to the heme group has been proposed as an effective intervention method for reducing, if not eliminating, the peroxidase activity of cyt c. In the present study, using a combination of druggability simulations, pharmacophore modeling, virtual screening, and in vitro fluorescence measurements to probe peroxidase activity, we identified three repurposable drugs and seven compounds that are validated to effectively inhibit the peroxidase activity of cyt c.

Abstract: The identification of synergistic chemotherapeutic agents from a large pool of candidates is highly challenging. Here, we present a Ranking-system of Anti-Cancer Synergy (RACS) that combines features of targeting networks and transcriptomic profiles, and validate it on three types of cancer. Using data on human beta-cell lymphoma from the Dialogue for Reverse Engineering Assessments and Methods consortium we show a probability concordance of 0.78 compared with 0.61 obtained with the previous best algorithm. We confirm 63.6% of our breast cancer predictions through experiment and literature, including four strong synergistic pairs. Further in vivo screening in a zebrafish MCF7 xenograft model confirms one prediction with strong synergy and low toxicity. Validation using A549 lung cancer cells shows similar results. Thus, RACS can significantly improve drug synergy prediction and markedly reduce the experimental prescreening of existing drugs for repurposing to cancer treatment, although the molecular mechanism underlying particular interactions remains unknown.