The genome sequence of Bacillus anthracis Ames and comparison to closely related bacteria

Bacillus anthracis is an endospore-forming bacterium that causes inhalational anthrax. Key virulence genes are found on plasmids (extra-chromosomal, circular, double-stranded DNA molecules) pXO1 (ref. 2) and pXO2 (ref. 3). To identify additional genes that might contribute to virulence, we analysed the complete sequence of the chromosome of B. anthracis Ames (about 5.23 megabases). We found several chromosomally encoded proteins that may contribute to pathogenicity--including haemolysins, phospholipases and iron acquisition functions--and identified numerous surface proteins that might be important targets for vaccines and drugs. Almost all these putative chromosomal virulence and surface proteins have homologues in Bacillus cereus, highlighting the similarity of B. anthracis to near-neighbours that are not associated with anthrax. By performing a comparative genome hybridization of 19 B. cereus and Bacillus thuringiensis strains against a B. anthracis DNA microarray, we confirmed the general similarity of chromosomal genes among this group of close relatives. However, we found that the gene sequences of pXO1 and pXO2 were more variable between strains, suggesting plasmid mobility in the group. The complete sequence of B. anthracis is a step towards a better understanding of anthrax pathogenesis.     

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.