RESUMEN
Corynebacterium pseudotuberculosis (Cp) is a pathogenic bacterium that causes caseous lymphadenitis (CLA), ulcerative lymphangitis, mastitis, and edematous to a broad spectrum of hosts, including ruminants, thereby threatening economic and dairy industries worldwide. Currently there is no effective drug or vaccine available against Cp. To identify new targets, we adopted a novel integrative strategy, which began with the prediction of the modelome (tridimensional protein structures for the proteome of an organism, generated through comparative modeling) for 15 previously sequenced C. pseudotuberculosis strains. This pan-modelomics approach identified a set of 331 conserved proteins having 95-100% intra-species sequence similarity. Next, we combined subtractive proteomics and modelomics to reveal a set of 10 Cp proteins, which may be essential for the bacteria. Of these, 4 proteins (tcsR, mtrA, nrdI, and ispH) were essential and non-host homologs (considering man, horse, cow and sheep as hosts) and satisfied all criteria of being putative targets. Additionally, we subjected these 4 proteins to virtual screening of a drug-like compound library. In all cases, molecules predicted to form favorable interactions and which showed high complementarity to the target were found among the top ranking compounds. The remaining 6 essential proteins (adk, gapA, glyA, fumC, gnd, and aspA) have homologs in the host proteomes. Their active site cavities were compared to the respective cavities in host proteins. We propose that some of these proteins can be selectively targeted using structure-based drug design approaches (SBDD). Our results facilitate the selection of C. pseudotuberculosis putative proteins for developing broad-spectrum novel drugs and vaccines. A few of the targets identified here have been validated in other microorganisms, suggesting that our modelome strategy is effective and can also be applicable to other pathogens.
Asunto(s)
Antibacterianos/farmacología , Proteínas Bacterianas/efectos de los fármacos , Vacunas Bacterianas , Biología Computacional , Corynebacterium pseudotuberculosis/efectos de los fármacos , Corynebacterium pseudotuberculosis/genética , Sistemas de Liberación de Medicamentos , Proteoma/genética , Secuencia de Aminoácidos , Animales , Proteínas Bacterianas/química , Proteínas Bacterianas/genética , Simulación por Computador , Secuencia Conservada , Corynebacterium pseudotuberculosis/metabolismo , Diseño de Fármacos , Genes Esenciales , Humanos , Programas Informáticos , Relación Estructura-ActividadRESUMEN
Lung cancer accounts for the highest number of cancer-related deaths worldwide. Early diagnosis significantly increases the disease-free survival rate and a large amount of effort has been expended in screening trials and the development of early molecular diagnostics. However, a gold standard diagnostic strategy is not yet available. Here, based on miRNA expression profile in lung cancer and using a novel in silico reverse-transcriptomics approach, followed by analysis of the interactome; we have identified potential transcription factor (TF) markers that would facilitate diagnosis of subtype specific lung cancer. A subset of seven TF markers has been used in a microarray screen and was then validated by blood-based qPCR using stage-II and IV non-small cell lung carcinomas (NSCLC). Our results suggest that overexpression of HMGA1, E2F6, IRF1, and TFDP1 and downregulation or no expression of SUV39H1, RBL1, and HNRPD in blood is suitable for diagnosis of lung adenocarcinoma and squamous cell carcinoma sub-types of NSCLC. Here, E2F6 was, for the first time, found to be upregulated in NSCLC blood samples. The miRNA-TF-miRNA interaction based molecular mechanisms of these seven markers in NSCLC revealed that HMGA1 and TFDP1 play vital roles in lung cancer tumorigenesis. The strategy developed in this work is applicable to any other cancer or disease and can assist in the identification of potential biomarkers.
Asunto(s)
Biomarcadores de Tumor/sangre , Biomarcadores de Tumor/genética , Simulación por Computador , Perfilación de la Expresión Génica/métodos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patología , Transcripción Reversa/genética , Carcinoma de Pulmón de Células no Pequeñas/sangre , Carcinoma de Pulmón de Células no Pequeñas/genética , Carcinoma de Pulmón de Células no Pequeñas/patología , Ciclo Celular/genética , Regulación Neoplásica de la Expresión Génica , Redes Reguladoras de Genes , Humanos , Neoplasias Pulmonares/sangre , MicroARNs/genética , MicroARNs/metabolismo , Anotación de Secuencia Molecular , Reacción en Cadena de la Polimerasa , Reproducibilidad de los Resultados , Carcinoma Pulmonar de Células Pequeñas/sangre , Carcinoma Pulmonar de Células Pequeñas/genética , Carcinoma Pulmonar de Células Pequeñas/patología , Factores de Transcripción/metabolismoRESUMEN
UNLABELLED: miRNAs regulate post transcriptional gene expression by targeting multiple mRNAs and hence can modulate multiple signalling pathways, biological processes, and patho-physiologies. Therefore, understanding of miRNA regulatory networks is essential in order to modulate the functions of a miRNA. The focus of several existing databases is to provide information on specific aspects of miRNA regulation. However, an integrated resource on the miRNA regulome is currently not available to facilitate the exploration and understanding of miRNA regulomics. miRegulome attempts to bridge this gap. The current version of miRegulome v1.0 provides details on the entire regulatory modules of miRNAs altered in response to chemical treatments and transcription factors, based on validated data manually curated from published literature. Modules of miRegulome (upstream regulators, downstream targets, miRNA regulated pathways, functions, diseases, etc) are hyperlinked to an appropriate external resource and are displayed visually to provide a comprehensive understanding. Four analysis tools are incorporated to identify relationships among different modules based on user specified datasets. miRegulome and its tools are helpful in understanding the biology of miRNAs and will also facilitate the discovery of biomarkers and therapeutics. With added features in upcoming releases, miRegulome will be an essential resource to the scientific community. AVAILABILITY: http://bnet.egr.vcu.edu/miRegulome.
Asunto(s)
MicroARNs/genética , Programas Informáticos , Animales , Bases de Datos Genéticas , Redes Reguladoras de Genes , Humanos , Bases del Conocimiento , Interferencia de ARNRESUMEN
Diabetes is known to be regulated by cytokines secreted from Th1 cells, while allergic rhinitis (AR) is mainly regulated by Th2 cytokines. In recent past we have reported the development of diabetes in response to parthinium induced AR to rats. These results were contradictory to Th1/Th2 paradigm which suggests that Th1 and Th2 cells reciprocally counteract each other. Subsequently in silico interactome analysis further revealed that Th2 cytokines may signal to increase the level of Th1 along with the proteins involved in the development of diabetes. In present study we tried to understand the diabetogenic changes on the background of ovalbumin induced allergic rhinitis (OVA). Three groups of seven rats were considered; group I control (Ctrl); group II OVA and group III OVA+L-cetrizine (OVA+ D). The study continued for 48 days and the experiment was terminated on day 49, while L-cetrizine was administered for last 07 days (42-48 days). Group II showed increased levels of Th1 (IL-2) and Th2 cytokines, induction of allergic rhinitis and changes in the proteins involved in diabetes. In group III, most of the changes were reverted back towards normalcy. Induction of allergic rhinitis triggers Th2 cytokines that result increase IL-2 (Th1) and alterations in the metabolic parameters led to the condition of prediabetes.