Anthrax is a zoonotic disease that occurs naturally in wild and domestic animals but has been used by both state-sponsored programs and terrorists as a biological weapon. A Soviet industrial production facility in Sverdlovsk, USSR, proved deficient in 1979 when a plume of spores was accidentally released and resulted in one of the largest known human anthrax outbreaks. In order to understand this outbreak and others, we generated a Bacillus anthracis population genetic database based upon whole-genome analysis to identify all single-nucleotide polymorphisms (SNPs) across a reference genome. Phylogenetic analysis has defined three major clades (A, B, and C), B and C being relatively rare compared to A. The A clade has numerous subclades, including a major polytomy named the trans-Eurasian (TEA) group. The TEA radiation is a dominant evolutionary feature of B. anthracis, with many contemporary populations having resulted from a large spatial dispersal of spores from a single source. Two autopsy specimens from the Sverdlovsk outbreak were deep sequenced to produce draft B. anthracis genomes. This allowed the phylogenetic placement of the Sverdlovsk strain into a clade with two Asian live vaccine strains, including the Russian Tsiankovskii strain. The genome was examined for evidence of drug resistance manipulation or other genetic engineering, but none was found. The Soviet Sverdlovsk strain genome is consistent with a wild-type strain from Russia that had no evidence of genetic manipulation during its industrial production. This work provides insights into the world’s largest biological weapons program and provides an extensive B. anthracis phylogenetic reference.
Purpose: Separase, an endopeptidase, plays a pivotal role in chromosomal segregation by separating sister chromatids during the metaphase to anaphase transition. Using a mouse mammary tumor model we have recently shown that overexpression of Separase induces aneuploidy and tumorigenesis (Zhang et al., Proc Natl Acad Sci 2008;105:13033). In the present study, we have investigated the expression level of Separase across a wide range of human tumors. Experimental Design: To examine the expression levels and localization of Separase in human tumors, we have performed immunofluorescence microscopy using human Separase antibody and tumor tissue arrays from osteosarcoma, colorectal, breast, and prostate cancers with appropriate normal controls. Results: We show that Separase is significantly overexpressed in osteosarcoma, breast, and prostate tumor specimens. There is a strong correlation of tumor status with the localization of Separase into the nucleus throughout all stages of the cell cycle. Unlike the normal control tissues, where Separase localization is exclusively cytoplasmic in nondividing cells, human tumor samples show significantly higher number of resting cells with a strong nuclear Separase staining. Additionally, overexpression of Separase transcript strongly correlates with high incidence of relapse, metastasis, and lower 5-year overall survival rate in breast and prostate cancer patients. Conclusion: These results further strengthen our hypothesis that Separase might be an oncogene, whose overexpression induces tumorigenesis, and indicates that Separase overexpression and aberrant nuclear localization are common in many tumor types and may predict outcome in some human cancers.An evolutionarily conserved protein complex called cohesin holds sister chromatids together to allow accurate separation of sister chromatids into two daughter cells. At the onset of anaphase, Separase, an endopeptidase, is activated and cleaves the cohesin subunit Rad21 (also called SCC1 or MCD1), which releases sister chromatid cohesion. Separase activity is tightly regulated via several mechanisms (for details, see refs. 1 -3) to ensure accurate and precise activation of cohesin Rad21 cleavage during the metaphase to anaphase transition (2 -4).Separase is activated after its inhibitory chaperone securin is degraded by APC-mediated phosphorylation and ubiquitinmediated degradation (1, 5 -8). Additionally, phosphorylation of Separase on Ser 1126 and Thr 1326 residues is a second mechanism to inhibit Separase activity (9, 10). Therefore, Securin null cells are viable and appear to have a nearly normal cell cycle (11 -13). However, premature separation of sister chromatids, for example, by premature activation of Separase or by insufficient inhibition of overexpressed Separase, is thought to result in aneuploidy (14).Knockout of the Separase gene results in embryonic lethality in mice (13,15). Small interfering RNA-mediated knockdown of Separase results in genomic instability (8, 16), also seen in Separase-deficient mouse ...
Background: Structural genomics projects such as the Protein Structure Initiative (PSI) yield many new structures, but often these have no known molecular functions. One approach to recover this information is to use 3D templates -structure-function motifs that consist of a few functionally critical amino acids and may suggest functional similarity when geometrically matched to other structures. Since experimentally determined functional sites are not common enough to define 3D templates on a large scale, this work tests a computational strategy to select relevant residues for 3D templates.
We present results of the correlation analysis of distributions of the presence/absence of short nucleotide subsequences of different length ('n-mers', n = 5-20) in more than 1500 microbial and virus genomes, together with five genomes of multicellular organisms (including human). We calculate whether a given n-mer is present or absent (frequency of presence) in a given genome, which is not the usually calculated number of appearances of n-mers in one or more genomes (frequency of appearance). For organisms that are not close relatives of each other, the presence/absence of different 7-20mers in their genomes are not correlated. For close biological relatives, somecorrelation of the presence of n-mers in this range appears, but is not as strong as expected. Suppressed correlations among the n-mers present in different genomes leads to the possibility of using random sets of n-mers (with appropriately chosen n) to discriminate genomes of different organisms and possibly individual genomes of the same species including human with a low probability of error.
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