Molecular cloning and characterization of the srdBCA operon, encoding the respiratory selenate reductase complex, from the selenate-reducing bacterium Bacillus selenatarsenatis SF-1.

Previously, we isolated a selenate- and arsenate-reducing bacterium, designated strain SF-1, from selenium-contaminated sediment and identified it as a novel species, Bacillus selenatarsenatis. B. selenatarsenatis strain SF-1 independently reduces selenate to selenite, arsenate to arsenite, and nitrate to nitrite by anaerobic respiration. To identify the genes involved in selenate reduction, 17 selenate reduction-defective mutant strains were isolated from a mutant library generated by random insertion of transposon Tn916. Tn916 was inserted into the same genome position in eight mutants, and the representative strain SF-1AM4 did not reduce selenate but did reduce nitrate and arsenate to the same extent as the wild-type strain. The disrupted gene was located in an operon composed of three genes designated srdBCA, which were predicted to encode a putative oxidoreductase complex by the BLASTX program. The plasmid vector pGEMsrdBCA, containing the srdBCA operon with its own promoter, conferred the phenotype of selenate reduction in Escherichia coli DH5α, although E. coli strains containing plasmids lacking any one or two of the open reading frames from srdBCA did not exhibit the selenate-reducing phenotype. Domain structure analysis of the deduced amino acid sequence revealed that SrdBCA had typical features of membrane-bound and molybdopterin-containing oxidoreductases. It was therefore proposed that the srdBCA operon encoded a respiratory selenate reductase complex. This is the first report of genes encoding selenate reductase in gram-positive bacteria.

Bacillus selenatarsenatis sp. nov., a selenate- and arsenate-reducing bacterium isolated from the effluent drain of a glass-manufacturing plant.

A facultatively anaerobic, selenate- and arsenate-reducing bacterium, designated strain SF-1(T), was isolated from a selenium-contaminated sediment obtained from an effluent drain of a glass-manufacturing plant in Japan. The bacterium stained Gram-positive and was a motile, spore-forming rod capable of respiring with selenate, arsenate and nitrate as terminal electron acceptors. The major cellular fatty acids of the strain were iso-C(15 : 0), iso-C(17 : 1)omega10c and C(16 : 1)omega7c alcohol. The G+C content of the genomic DNA was 42.8 mol%. Though the nearest phylogenetic neighbour was Bacillus jeotgali JCM 10885(T), with a 16S rRNA gene sequence similarity of 99.6 %, DNA-DNA hybridization studies showed only 14 % relatedness between these strains, a level that is clearly below the value recommended to delimit different species. This, together with the phenotypic differences (utilization of electron acceptors, NaCl tolerance), suggests that strain SF-1(T) represents a novel species of the genus Bacillus, for which the name Bacillus selenatarsenatis sp. nov. is proposed. The type strain is SF-1(T) (=JCM 14380(T)=DSM 18680(T)).

High-performance computing service over the internet for intraoperative image processing.

This paper presents a framework for a cluster system that is suited for high-resolution image processing over the Internet during surgery. The system realizes high-performance computing (HPC) assisted surgery, which allows surgeons to utilize HPC resources remote from the operating room. One application available in the system is an intraoperative estimator for the range of motion (ROM) adjustment in total hip replacement (THR) surgery. In order to perform this computation-intensive estimation during surgery, we parallelize the ROM estimator on a cluster of 64 PCs, each with two CPUs. Acceleration techniques such as dynamic load balancing and data compression methods are incorporated into the system. The system also provides a remote-access service over the Internet with a secure execution environment. We applied the system to an actual THR surgery performed at Osaka University Hospital and confirmed that it realizes intraoperative ROM estimation without degrading the resolution of images and limiting the area for estimations.