Draft Genome Sequence of \u3cem\u3eDesulfurobacterium thermolithotrophum\u3c/em\u3e Strain HR11, a Novel Thermophilic Autotrophic Subspecies from a Deep-Sea Hydrothermal Vent

Desulfurobacterium sp. strain HR11 was isolated from a hydrothermal vent on the Juan de Fuca Ridge. We present the 1.55-Mb genome sequence of HR11, which contains 1,624 putative protein-coding sequences. Overall genome relatedness index analyses indicate that HR11 is a novel subspecies of D. thermolithotrophum

Identifying Pathway Proteins in Networks using Convergence

One of the key goals of systems biology concerns the analysis of experimental biological data available to the scientific public. New technologies are rapidly developed to observe and report whole-scale biological phenomena; however, few methods exist with the ability to produce specific, testable hypotheses from this noisy ‘big’ data. In this work, we propose an approach that combines the power of data-driven network theory along with knowledge-based ontology to tackle this problem. Network models are especially powerful due to their ability to display elements of interest and their relationships as internetwork structures. Additionally, ontological data actually supplements the confidence of relationships within the model without clouding critical structure identification. As such, we postulate that given a (gene/protein) marker set of interest, we can systematically identify the core of their interactions (if they are indeed working together toward a biological function), via elimination of original markers and addition of additional necessary markers. This concept, which we refer to as “convergence,” harnesses the idea of “guilt-by-association” and recursion to identify whether a core of relationships exists between markers. In this study, we test graph theoretic concepts such as shortest-path, k-Nearest- Neighbor and clustering) to identify cores iteratively in data- and knowledge-based networks in the canonical yeast Pheromone Mating Response pathway. Additionally, we provide results for convergence application in virus infection, hearing loss, and Parkinson’s disease. Our results indicate that if a marker set has common discrete function, this approach is able to identify that function, its interacting markers, and any new elements necessary to complete the structural core of that function. The result below find that the shortest path function is the best approach of those used, finding small target sets that contain a majority or all of the markers in the gold standard pathway. The power of this approach lies in its ability to be used in investigative studies to inform decisions concerning target selection

Msh2 ATPase Activity Is Essential for Somatic Hypermutation at A-T Basepairs and for Efficient Class Switch Recombination

Somatic hypermutation (SHM) and class switch recombination (CSR) are initiated by activation-induced cytidine deaminase–mediated cytidine deamination of immunoglobulin genes. MutS homologue (Msh) 2−/− mice have reduced A-T mutations and CSR. This suggests that Msh2 may play a role in repairing activation-induced cytidine deaminase–generated G-U mismatches. However, because Msh2 not only initiates mismatch repair but also has other functions, such as signaling for apoptosis, it is not known which activity of Msh2 is responsible for the effects observed, and consequently, many models have been proposed. To further dissect the role of Msh2 in SHM and CSR, mice with a “knockin” mutation in the Msh2 gene that inactivates the adenosine triphosphatase domain were examined. This mutation (i.e., Msh2G674A), which does not affect apoptosis signaling, allows mismatches to be recognized but prevents Msh2 from initiating mismatch repair. Here, we show that, similar to Msh2−/− mice, SHM in Msh2G674A mice is biased toward G-C mutations. However, CSR is partially reduced, and switch junctions are more similar to those of postmeiotic segregation 2−/− mice than to Msh2−/− mice. These results indicate that Msh2 adenosine triphosphatase activity is required for A-T mutations, and suggest that Msh2 has more than one role in CSR

Oxidative Protein Folding Is Driven by the Electron Transport System

AbstractDisulfide bond formation is catalyzed in vivo by DsbA and DsbB. Here we reconstitute this oxidative folding system using purified components. We have found the sources of oxidative power for protein folding and show how disulfide bond formation is linked to cellular metabolism. We find that disulfide bond formation and the electron transport chain are directly coupled. DsbB uses quinones as electron acceptors, allowing various choices for electron transport to support disulfide bond formation. Electrons flow via cytochrome bo oxidase to oxygen under aerobic conditions or via cytochrome bd oxidase under partially anaerobic conditions. Under truly anaerobic conditions, menaquinone shuttles electrons to alternate final electron acceptors such as fumarate. This flexibility reflects the vital nature of the disulfide catalytic system

Structure of the Polycomb Group Protein PCGF1 in Complex with BCOR Reveals Basis for Binding Selectivity of PCGF Homologs

SummaryPolycomb-group RING finger homologs (PCGF1, PCGF2, PCGF3, PCGF4, PCGF5, and PCGF6) are critical components in the assembly of distinct Polycomb repression complex 1 (PRC1)-related complexes. Here, we identify a protein interaction domain in BCL6 corepressor, BCOR, which binds the RING finger- and WD40-associated ubiquitin-like (RAWUL) domain of PCGF1 (NSPC1) and PCGF3 but not of PCGF2 (MEL18) or PCGF4 (BMI1). Because of the selective binding, we have named this domain PCGF Ub-like fold discriminator (PUFD). The structure of BCOR PUFD bound to PCGF1 reveals that (1) PUFD binds to the same surfaces as observed for a different Polycomb group RAWUL domain and (2) the ability of PUFD to discriminate among RAWULs stems from the identity of specific residues within these interaction surfaces. These data show the molecular basis for determining the binding preference for a PCGF homolog, which ultimately helps determine the identity of the larger PRC1-like assembly

The mating-specific Gα interacts with a kinesin-14 and regulates pheromone-induced nuclear migration in budding yeast

As a budding yeast cell elongates toward its mating partner, cytoplasmic microtubules connect the nucleus to the cell cortex at the growth tip. The Kar3 kinesin-like motor protein is then thought to stimulate plus-end depolymerization of these microtubules, thus drawing the nucleus closer to the site where cell fusion and karyogamy will occur. Here, we show that pheromone stimulates a microtubule-independent interaction between Kar3 and the mating-specific Gα protein Gpa1 and that Gpa1 affects both microtubule orientation and cortical contact. The membrane localization of Gpa1 was found to polarize early in the mating response, at about the same time that the microtubules begin to attach to the incipient growth site. In the absence of Gpa1, microtubules lose contact with the cortex upon shrinking and Kar3 is improperly localized, suggesting that Gpa1 is a cortical anchor for Kar3. We infer that Gpa1 serves as a positional determinant for Kar3-bound microtubule plus ends during mating. © 2009 by The American Society for Cell Biology

High-throughput, quantitative analyses of genetic interactions in E. coli.

Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in Saccharomyces cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here we describe a method based on F factor-driven conjugation, which allows for high-throughput generation of double mutants in Escherichia coli. This method, termed genetic interaction analysis technology for E. coli (GIANT-coli), permits us to systematically generate and array double-mutant cells on solid media in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify previously unidentified negative (synthetic sickness or lethality) and positive (suppressive or epistatic) relationships. Finally, we describe a complementary strategy for genome-wide suppressor-mutant identification. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli

Computational Prediction and Experimental Verification of New MAP Kinase Docking Sites and Substrates Including Gli Transcription Factors

In order to fully understand protein kinase networks, new methods are needed to identify regulators and substrates of kinases, especially for weakly expressed proteins. Here we have developed a hybrid computational search algorithm that combines machine learning and expert knowledge to identify kinase docking sites, and used this algorithm to search the human genome for novel MAP kinase substrates and regulators focused on the JNK family of MAP kinases. Predictions were tested by peptide array followed by rigorous biochemical verification with in vitro binding and kinase assays on wild-type and mutant proteins. Using this procedure, we found new ‘D-site’ class docking sites in previously known JNK substrates (hnRNP-K, PPM1J/PP2Czeta), as well as new JNK-interacting proteins (MLL4, NEIL1). Finally, we identified new D-site-dependent MAPK substrates, including the hedgehog-regulated transcription factors Gli1 and Gli3, suggesting that a direct connection between MAP kinase and hedgehog signaling may occur at the level of these key regulators. These results demonstrate that a genome-wide search for MAP kinase docking sites can be used to find new docking sites and substrates

Characterization of the ZBTB42 gene in humans and mice

A 12 kb haplotype upstream of the key signaling protein gene, AKT1, has been associated with insulin resistance and metabolic syndrome (Devaney et al. 2010). The region contains the first exon and promoter sequences of AKT1, but also includes the complete transcript unit for a highly conserved yet uncharacterized zinc finger-containing protein (ZBTB42). One of the component SNPs of the 12 kb haplotype metabolic syndrome haplotype changes a conserved amino acid in the predicted ZBTB42 protein, increasing the potential significance of the ZBTB42 transcript unit for contributing to disease risk. Using RT-PCR of human and mouse cells, we verified that the two exon ZBTB42 was expressed and correctly spliced in human skeletal muscle, and murine C2C12 cells. Production of peptide antibodies showed the expected protein in human (47 kD) and mouse (49 kD) immunoblots, and murine tissue distribution showed strongest expression in muscle and ovary. Immunostaining showed nuclear localization of the ZBTB42 protein in human muscle. Confocal imaging analyses of murine muscle showed ZBTB42 distributed in the nucleoplasm, with particular enrichment in nuclei underlying the neuromuscular junctions. The genetic association data of metabolic syndrome, coupled with the molecular characterization of the ZBTB42 transcript unit and encoded protein presented here, suggests that ZBTB42 may be involved in metabolic syndrome phenotypes