Bovine viral diarrhea virus (BVDV) is one of the most important viruses affecting the health and well-being of bovine species throughout the world. Here, we used CRISPR-mediated homology-directed repair and somatic cell nuclear transfer to produce a live calf with a six amino acid substitution in the BVDV binding domain of bovine CD46. The result was a gene-edited calf with dramatically reduced susceptibility to infection as measured by reduced clinical signs and the lack of viral infection in white blood cells. The edited calf has no off-target edits and appears normal and healthy at 20 months of age without obvious adverse effects from the on-target edit. This precision bred, proof-of-concept animal provides the first evidence that intentional genome alterations in the CD46 gene may reduce the burden of BVDV-associated diseases in cattle and is consistent with our stepwise, in vitro and ex vivo experiments with cell lines and matched fetal clones.
A grand goal in neuroscience research is to understand how the interplay of structural, chemical and electrical signals in and between cells of nervous tissue gives rise to behavior. We are rapidly approaching this horizon as neuroscientists make use of an increasingly powerful arsenal of tools and technologies for obtaining data, from the level of molecules to nervous systems, and engage in the arduous and challenging process of adapting and assembling neuroscience data at all scales of resolution and across disciplines into computerized databases. This talk will highlight projects where development and application of new contrasting methods and imaging tools have allowed us to see otherwise hidden relationships between cellular, subcellular and molecular constituents of nervous systems. New chemistries for carrying out correlated light and electron microscopy will be described, as well as recent advances in large-scale high-resolution 3D reconstruction with TEM and SEM based methods. The Whole Brain Catalog (WBC), a Google Earth-like open-source virtual model of the mouse brain, will also be described. The WBC is as an example of an informatics framework and web-based tool whose purpose is partly to facilitate integration of 3D image data from multiple microscopy methods and to enable the linking of information derived from other analytical approaches to imaging data shared in the publically accessible catalog.
Bovine viral diarrhea virus (BVDV) is one of the most important viruses affecting the health and well-being of bovine species throughout the world. Here we used CRISPR-mediated homology-directed repair and somatic cell nuclear transfer to produce a live calf with a six amino acid substitution in the BVDV binding domain of bovine CD46. The result was a gene-edited calf with dramatically reduced susceptibility to infection as measured by clinical signs and the lack of viral infection in white blood cells. The edited calf has no off-target edits and appears normal and healthy at 16 months of age without obvious adverse effects from the on-target edit. This precision bred, proof-of-concept animal provides the first evidence that intentional genome alterations in CD46 may reduce the burden of BVDV-associated diseases in cattle, and is consistent with our stepwise, in vitro and ex vivo experiments with cell lines and matched fetal clones.
Using the 18S (partial), ITS1 (Internal Transcribed Spacer 1), 5.8S, ITS2 (Internal Transcribed Spacer 2) regions of the genomic SSU (small subunit) DNA, we are able to use basic bioinformatics tools to create an effective phylogenetic tree. Sanger sequencing produces a 1.2–1.5 kb region for each individual species that is annotated into four elements, (partial 18S, ITS1, 5.8S, and ITS2) and is formatted for stand‐alone MAFFT v6.903b (Multiple Alignment using Fast Fourier Transform). The multiple alignment is then carried out on each element and concatenated to remove the potential overlap between the elements. Stand‐alone PhyML v3.0 (Phylogenetic estimation using Maximum Likelihood) is then used on the multiple alignment data, and a tree can be viewed using FigTree v1.3.1 (a phylogenetic tree editor and viewer program). The results of this method gives well‐defined clades that are now being used in genera and even species level determination. Using our simplistic method is an effective way to engaging the problem of green algae identification.
The object of this project is to identify changes in soil microbial community DNA and Fatty Acid profiles caused by storage, using capillary electrophoresis single‐strand conformation polymorphism (CE‐SSCP) and fatty acid methyl ester (FAME) analysis.There were six different storage treatments tested (−80°C, −20°C, 4°C, freeze dried, air dried, oven dried) on soil samples collected from 4 different locations in Nebraska. Samples were taken at a depth of 0.0 cm to 5.0 cm from three biological replicates at each collection site. After collection, soils were sieved and subsamples were placed into each storage treatment for five weeks then analyzed, with the exception of one subsample (fresh) which had DNA and fatty acids extracted within 36 hours of collection. Additional fresh samples were collected and processed two weeks after initial collection and seasonally.The CE‐SSCP and FAME analysis will illustrate the microbial community and its diversity for an individual soil sample through the number of peaks, molecular size of peaks and relative peak heights. Using statistical analysis it can be determined which storage treatments altered the soil microbial community profile when compared to the fresh subsample. Results will be presented to show the effectiveness of these two methods to detect small variations in the soil microbial community. Funded by National Institute of Justice (25‐6228‐0159‐001).
In order to develop a further understanding of the evolutionary relationships between different Chlorella algal strains and related species, methods of algal DNA extraction, PCR, sequencing, and analysis were tailored to our project. With the goal of understanding algal relationships and an intent of affecting algal biofuel production, DNA from multiple regions of algal cells was targeted. Ribosomal DNA including the 18S, ITS1, 5.8S, ITS2, and 28S regions; Chloroplastic DNA (the RuBisCO large subunit coding region); Genomic DNA (the RuBisCO small subunit coding region); and Mitochondrial DNA (Cytochrome C Oxidase subunit I coding region) were picked to be analyzed from each of our algal strains. The comparison of the phylogenetic trees is then being used to determine relationship grouping patterns with increasingly robust trees as more sequencing data is obtained. Further analysis and sequencing of the four regions should give a better understanding of relationships and help to determine the proximity of certain chlorella‐like algal species to one another. Furthermore, extended distance between two strains of the same species provides ground for questioning the nomenclature of certain strains with comparison to their actual genetic composition. Funding provided by NSF‐EPSCoR: 1004–094.
Capillary electrophoresis can separate fragments of nucleic acids using single strand conformation polymorphism (SSCP) and terminal restriction fragment length polymorphism (T‐RFLP). These methods have been increasingly used in microbial ecology to develop fingerprints of the microbial community within soil. T‐RFLP is based on amplifying a region of DNA common to multiple species using conserved PCR primers whereas SSCP detects mutations in DNA fragments due to changes in the secondary structure of single‐stranded DNA fragments. The objective of this study is to use soil samples to compare molecular profiles generated by CE‐SSCP and T‐RFLP in detail. The soil samples will be collected from four locations representing four soil types. One set of soil subsamples will be analyzed immediately following collection and six subsamples will be placed in different storage treatments: cooling at −4C, freezing at −20C, freezing at −80C, freeze drying, air drying, and oven drying. DNA will be extracted from the samples, run through polymerase chain reaction (PCR) to amplify and fluorescently tag the genes of interest. T‐RFLP uses restriction enzyme MspI after PCR, while SSCP does not. Then, the microbial community fingerprints are analyzed. We hypothesize CE‐SSCP and T‐RFLP will generate similar fingerprints of the microbial community within soil. Supported by National Institute of Justice (25‐6228‐0159‐001).
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