Bidirectional lipid droplet velocities are controlled by differential binding strengths of HCV Core DII protein

Host cell lipid droplets (LD) are essential in the hepatitis C virus (HCV) life cycle and are targeted by the viral capsid core protein. Core-coated LDs accumulate in the perinuclear region and facilitate viral particle assembly, but it is unclear how mobility of these LDs is directed by core. Herein we used two-photon fluorescence, differential interference contrast imaging, and coherent anti-Stokes Raman scattering microscopies, to reveal novel core-mediated changes to LD dynamics. Expression of core protein’s lipid binding domain II (DII-core) induced slower LD speeds, but did not affect directionality of movement on microtubules. Modulating the LD binding strength of DII-core further impacted LD mobility, revealing the temporal effects of LD-bound DII-core. These results for DII-core coated LDs support a model for core-mediated LD localization that involves core slowing down the rate of movement of LDs until localization at the perinuclear region is accomplished where LD movement ceases. The guided localization of LDs by HCV core protein not only is essential to the viral life cycle but also poses an interesting target for the development of antiviral strategies against HCV

Disease Gene Characterization through Large-Scale Co-Expression Analysis

In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET).Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2) and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis

Unexpected Inheritance: Multiple Integrations of Ancient Bornavirus and Ebolavirus/Marburgvirus Sequences in Vertebrate Genomes

Vertebrate genomes contain numerous copies of retroviral sequences, acquired over the course of evolution. Until recently they were thought to be the only type of RNA viruses to be so represented, because integration of a DNA copy of their genome is required for their replication. In this study, an extensive sequence comparison was conducted in which 5,666 viral genes from all known non-retroviral families with single-stranded RNA genomes were matched against the germline genomes of 48 vertebrate species, to determine if such viruses could also contribute to the vertebrate genetic heritage. In 19 of the tested vertebrate species, we discovered as many as 80 high-confidence examples of genomic DNA sequences that appear to be derived, as long ago as 40 million years, from ancestral members of 4 currently circulating virus families with single strand RNA genomes. Surprisingly, almost all of the sequences are related to only two families in the Order Mononegavirales: the Bornaviruses and the Filoviruses, which cause lethal neurological disease and hemorrhagic fevers, respectively. Based on signature landmarks some, and perhaps all, of the endogenous virus-like DNA sequences appear to be LINE element-facilitated integrations derived from viral mRNAs. The integrations represent genes that encode viral nucleocapsid, RNA-dependent-RNA-polymerase, matrix and, possibly, glycoproteins. Integrations are generally limited to one or very few copies of a related viral gene per species, suggesting that once the initial germline integration was obtained (or selected), later integrations failed or provided little advantage to the host. The conservation of relatively long open reading frames for several of the endogenous sequences, the virus-like protein regions represented, and a potential correlation between their presence and a species' resistance to the diseases caused by these pathogens, are consistent with the notion that their products provide some important biological advantage to the species. In addition, the viruses could also benefit, as some resistant species (e.g. bats) may serve as natural reservoirs for their persistence and transmission. Given the stringent limitations imposed in this informatics search, the examples described here should be considered a low estimate of the number of such integration events that have persisted over evolutionary time scales. Clearly, the sources of genetic information in vertebrate genomes are much more diverse than previously suspected

NeatMap - non-clustering heat map alternatives in R

<p>Abstract</p> <p>Background</p> <p>The clustered heat map is the most popular means of visualizing genomic data. It compactly displays a large amount of data in an intuitive format that facilitates the detection of hidden structures and relations in the data. However, it is hampered by its use of cluster analysis which does not always respect the intrinsic relations in the data, often requiring non-standardized reordering of rows/columns to be performed post-clustering. This sometimes leads to uninformative and/or misleading conclusions. Often it is more informative to use dimension-reduction algorithms (such as Principal Component Analysis and Multi-Dimensional Scaling) which respect the topology inherent in the data. Yet, despite their proven utility in the analysis of biological data, they are not as widely used. This is at least partially due to the lack of user-friendly visualization methods with the visceral impact of the heat map.</p> <p>Results</p> <p>NeatMap is an R package designed to meet this need. NeatMap offers a variety of novel plots (in 2 and 3 dimensions) to be used in conjunction with these dimension-reduction techniques. Like the heat map, but unlike traditional displays of such results, it allows the entire dataset to be displayed while visualizing relations between elements. It also allows superimposition of cluster analysis results for mutual validation. NeatMap is shown to be more informative than the traditional heat map with the help of two well-known microarray datasets.</p> <p>Conclusions</p> <p>NeatMap thus preserves many of the strengths of the clustered heat map while addressing some of its deficiencies. It is hoped that NeatMap will spur the adoption of non-clustering dimension-reduction algorithms.</p

PROTDES: CHARMM toolbox for computational protein design

We present an open-source software able to automatically mutate any residue positions and find the best aminoacids in an arbitrary protein structure without requiring pairwise approximations. Our software, PROTDES, is based on CHARMM and it searches automatically for mutations optimizing a protein folding free energy. PROTDES allows the integration of molecular dynamics within the protein design. We have implemented an heuristic optimization algorithm that iteratively searches the best aminoacids and their conformations for an arbitrary set of positions within a structure. Our software allows CHARMM users to perform protein design calculations and to create their own procedures for protein design using their own energy functions. We show this by implementing three different energy functions based on different solvent treatments: surface area accessibility, generalized Born using molecular volume and an effective energy function. PROTDES, a tutorial, parameter sets, configuration tools and examples are freely available at http://soft.synth-bio.org/protdes.html

A SU(2) recipe for mutually unbiased bases

A simple recipe for generating a complete set of mutually unbiased bases in dimension (2j+1)**e, with 2j + 1 prime and e positive integer, is developed from a single matrix acting on a space of constant angular momentum j and defined in terms of the irreducible characters of the cyclic group C(2j+1). As two pending results, this matrix is used in the derivation of a polar decomposition of SU(2) and of a FFZ algebra.Comment: v2: abstract enlarged, a corollary added, acknowledgments added, one reference added, presentation improved; v3: two misprints correcte

A [SU(6)]4^4 FLAVOR MODEL WITHOUT MIRROR FERMIONS

We introduce a three family extension of the Pati-Salam model which is anomaly-free and contains in a single irreducible representation the known quarks and leptons without mirror fermions. Assuming that the breaking of the symmetry admits the implementation of the survival hypothesis, we calculate the mass scales using the renormalization group equation. Finally we show that the proton remains perturbatively stable.Comment: Z PHYS. C63, 339 (1994