Evaluation of Vibrio cholerae O1 El Tor variants circulating in Sindh Pakistan.

OBJECTIVE: To investigate the existence of genetically diverse vibrio cholerae variant strains in a rural Sindh district, and to find out the phylogenetic relationship of indigenous vibrio cholerae strains. METHODS: The cross-sectional study was conducted from April 2014 to May 2016 in Khairpur, Pakistan, and comprised stool samples/rectal swabs collected from the main and city branches of the Khairpur Medical College Teaching Hospital, and the Pir Abdul Qadir Shah Jeelani Institute of Medical Sciences, Gambat. The samples were identified using standard microbiological, biochemical, serological techniques and polymerase chain reaction targeting the ompW gene. Whole genome sequencing and bioinformatics tool MUMmer 3.2.3 was used to compare indigenous and contemporary vibrio cholerae strains circulating in the province of Sindh. Neighbour-joining tree method was used to construct the phylogenic tree. RESULTS: Of the 360 samples, 76(21.11%) were found positive for vibrio cholera strains. The species-specific ompW gene was amplified at the correct size of 588bp. The isolates belonged to serogroup Inaba, O1, biotype El Tor. Unique sequences with same genomic coordinates showed that test strains were not similar to the reference sequence. Conserved genome sequences showed that 12 Out of 16 (75%) of the test strains were similar to each Other except the 3 strains isolated from Khairpur and 1 from Karachi. Multiple sequence alignment of the regions translated into protein showed that 13 out of 16 (81.25%) test strains were similar except 2 strains from Khairpur and 1 From Karachi. The phylogenetic tree showed that all isolated strains descended from the same ancestor along with the reference strain. CONCLUSIONS: Vibrio cholerae O1 El Tor variant existed in Khairpur.

Effect of environmental, economic and health factors on CoVid-19 transmission.

The severe acute respiratory syndrome (SARS) is affected by meteorological parameters such as temperature and humidity. It is also observed that people having asthma are at risk for SARS. Therefore, it is of interest to report the effect of environmental, economic, and health factors on the spread of CoVid-19. We used data reporting CoVid-19 cases from 24 cities in eight different countries for this analysis. Data was analyzed using multiple linear regressions between these parameters. Data shows that temperature has effects on CoVid-19. A one-degree rise in temperature causes a -0.19 decrease in CoVid-19 cases per million people (log natural value per million populations). The effect of humidity is not significant at a p value of 0.26. Moreover, one-unit increase in asthma and GDP cases per million people show 0.06 and 0.46 increases in CoVid-19 cases, respectively.

Identification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasets.

Gene expression governs cell fate, and is regulated via a complex interplay of transcription factors and molecules that change chromatin structure. Advances in sequencing-based assays have enabled investigation of these processes genome-wide, leading to large datasets that combine information on the dynamics of gene expression, transcription factor binding and chromatin structure as cells differentiate. While numerous studies focus on the effects of these features on broader gene regulation, less work has been done on the mechanisms of gene-specific transcriptional control. In this study, we have focussed on the latter by integrating gene expression data for the in vitro differentiation of murine ES cells to macrophages and cardiomyocytes, with dynamic data on chromatin structure, epigenetics and transcription factor binding. Combining a novel strategy to identify communities of related control elements with a penalized regression approach, we developed individual models to identify the potential control elements predictive of the expression of each gene. Our models were compared to an existing method and evaluated using the existing literature and new experimental data from embryonic stem cell differentiation reporter assays. Our method is able to identify transcriptional control elements in a gene specific manner that reflect known regulatory relationships and to generate useful hypotheses for further testing.

Molecular docking analysis of timepidium with Acetylcholine and lumacaftor with GABA(A) activator.

Epilepsy is a chronic disorder characterized by disturbed tissue related molecular activity within the brain irrespective of age. The cause is very difficult to understand towards a suitable treatment. However, its symptoms like seizures are treated and suppressed by known medications. Moreover, the condition is linked with neuro-transmitters such as GABA (gamma amino butyric acid) and acetylcholine. Therefore, it is of interest to design and develop inhibitors for these targets. Hence, we describe the molecular binding features of timepidium with acetylcholine and lumacaftor with GABA(A) activator using molecular docking based geometric optimization and screening analysis for further consideration.

Cancer somatic mutations cluster in a subset of regulatory sites predicted from the ENCODE data.

BACKGROUND: Transcriptional regulation of gene expression is essential for cellular differentiation and function, and defects in the process are associated with cancer. The ENCODE project has mapped potential regulatory sites across the complete genome in many cell types, and these regions have been shown to harbour many of the somatic mutations that occur in cancer cells, suggesting that their effects may drive cancer initiation and development. The ENCODE data suggests a very large number of regulatory sites, and methods are needed to identify those that are most relevant and to connect them to the genes that they control. METHODS: Predictive models of gene expression were developed by integrating the ENCODE data for regulation, including transcription factor binding and DNase1 hypersensitivity, with RNA-seq data for gene expression. A penalized regression method was used to identify the most predictive potential regulatory sites for each transcript. Known cancer somatic mutations from the COSMIC database were mapped to potential regulatory sites, and we examined differences in the mapping frequencies associated with sites chosen in regulatory models and other (rejected) sites. The effects of potential confounders, for example replication timing, were considered. RESULTS: Cancer somatic mutations preferentially occupy those regulatory regions chosen in our models as most predictive of gene expression. CONCLUSION: Our methods have identified a significantly reduced set of regulatory sites that are enriched in cancer somatic mutations and are more predictive of gene expression. This has significance for the mechanistic interpretation of cancer mutations, and the understanding of genetic regulation.