MOLECULAR CHARACTERIZATION OF MYCOBACTERIUM AVIUM SUBSP. PARATUBERCULOSIS ISOLATES

Objective: Johne's disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), is highly prevalent in domestic ruminants. In India, the exact prevalence of MAP genotypes still remains unknown limited, and the systematic disease control programs are also limited. This study was undertaken to study the molecular characterization of MAP isolates.Methods: About 22 MAP isolates were from cattle, sheep, and goat under gone the molecular characterization by three different methods (1) IS1311 polymerase chain reaction (PCR) with restriction enzyme analysis (REA), (2) GyrA and GyrB PCR with sequencing, and (3) digital microfluidic chip (DMC)-PCR. The study demonstrated that a) IS1311 PCR with REA (based on point mutations) identified all 22 MAP isolates as intermediate type†irrespective of a host of origin and also belong to Indian Bison type. Molecular typing based on the gyrA and gyrB genes partial amplification and sequencing revealed that the MAP isolates exhibited more lineages toward the reference Type III, Intermediate strain.Results: The MAP isolate of sheep origin showed more lineages toward the sheep type than the isolates of cattle and goats. This variation may be due to host-pathogen interactions and adaptation to different hosts and environmental conditions in the nature.Conclusions: The DMC-PCR, which is based on sequence difference at 5` end of IS900 of MAP, differentiated rapidly all the isolates as sheep type. The application of DMC-PCR to differentiate sheep and Intermediate types is limited as the Intermediate type (Type III) and sheep type (Type I) are very closely related to each other and all the MAP isolates were confirmed as Intermediate or Type III by three different methods which are commonly present in India, Spain, and Iceland. Â

Gene Expression Programs of Mouse Endothelial Cells in Kidney Development and Disease

Endothelial cells are remarkably heterogeneous in both morphology and function, and they play critical roles in the formation of multiple organ systems. In addition endothelial cell dysfunction can contribute to disease processes, including diabetic nephropathy, which is a leading cause of end stage renal disease. In this report we define the comprehensive gene expression programs of multiple types of kidney endothelial cells, and analyze the differences that distinguish them. Endothelial cells were purified from Tie2-GFP mice by cell dissociation and fluorescent activated cell sorting. Microarrays were then used to provide a global, quantitative and sensitive measure of gene expression levels. We examined renal endothelial cells from the embryo and from the adult glomerulus, cortex and medulla compartments, as well as the glomerular endothelial cells of the db/db mutant mouse, which represents a model for human diabetic nephropathy. The results identified the growth factors, receptors and transcription factors expressed by these multiple endothelial cell types. Biological processes and molecular pathways were characterized in exquisite detail. Cell type specific gene expression patterns were defined, finding novel molecular markers and providing a better understanding of compartmental distinctions. Further, analysis of enriched, evolutionarily conserved transcription factor binding sites in the promoters of co-activated genes begins to define the genetic regulatory network of renal endothelial cell formation. Finally, the gene expression differences associated with diabetic nephropathy were defined, providing a global view of both the pathogenic and protective pathways activated. These studies provide a rich resource to facilitate further investigations of endothelial cell functions in kidney development, adult compartments, and disease

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology. © 2014 Erwin et al

The 2022 solar fuels roadmap

Funder: Alfred P. Sloan Foundation; doi: http://dx.doi.org/10.13039/100000879Funder: Thistledown FoundationFunder: Research Corporation for Science Advancement; doi: http://dx.doi.org/10.13039/100001309Funder: TomKat Foundation; doi: http://dx.doi.org/10.13039/100018042Funder: Taiwan Ministry of Education and Taiwan and Ministry of ScienceFunder: the Netherlands Ministry of Economic Affairs and Climate PolicyFunder: Nederlandse Organisatie voor Wetenschappelijk Onderzoek; doi: http://dx.doi.org/10.13039/501100003246Abstract Renewable fuel generation is essential for a low carbon footprint economy. Thus, over the last five decades, a significant effort has been dedicated towards increasing the performance of solar fuels generating devices. Specifically, the solar to hydrogen efficiency of photoelectrochemical cells has progressed steadily towards its fundamental limit, and the faradaic efficiency towards valuable products in CO2 reduction systems has increased dramatically. However, there are still numerous scientific and engineering challenges that must be overcame in order to turn solar fuels into a viable technology. At the electrode and device level, the conversion efficiency, stability and products selectivity must be increased significantly. Meanwhile, these performance metrics must be maintained when scaling up devices and systems while maintaining an acceptable cost and carbon footprint. This roadmap surveys different aspects of this endeavor: system benchmarking, device scaling, various approaches for photoelectrodes design, materials discovery, and catalysis. Each of the sections in the roadmap focuses on a single topic, discussing the state of the art, the key challenges and advancements required to meet them. The roadmap can be used as a guide for researchers and funding agencies highlighting the most pressing needs of the field.</jats:p

The 2022 solar fuels roadmap

Renewable fuel generation is essential for a low carbon footprint economy. Thus, over the last five decades, a significant effort has been dedicated towards increasing the performance of solar fuels generating devices. Specifically, the solar to hydrogen efficiency of photoelectrochemical cells has progressed steadily towards its fundamental limit, and the faradaic efficiency towards valuable products in CO2 reduction systems has increased dramatically. However, there are still numerous scientific and engineering challenges that must be overcame in order to turn solar fuels into a viable technology. At the electrode and device level, the conversion efficiency, stability and products selectivity must be increased significantly. Meanwhile, these performance metrics must be maintained when scaling up devices and systems while maintaining an acceptable cost and carbon footprint. This roadmap surveys different aspects of this endeavor: system benchmarking, device scaling, various approaches for photoelectrodes design, materials discovery, and catalysis. Each of the sections in the roadmap focuses on a single topic, discussing the state of the art, the key challenges and advancements required to meet them. The roadmap can be used as a guide for researchers and funding agencies highlighting the most pressing needs of the field