Genome sequence determination and metagenomic characterization of a Dehalococcoides mixed culture grown on cis-1,2-dichloroethene.

A Dehalococcoides-containing bacterial consortium that performed dechlorination of 0.20 mM cis-1,2-dichloroethene to ethene in 14 days was obtained from the sediment mud of the lotus field. To obtain detailed information of the consortium, the metagenome was analyzed using the short-read next-generation sequencer SOLiD 3. Matching the obtained sequence tags with the reference genome sequences indicated that the Dehalococcoides sp. in the consortium was highly homologous to Dehalococcoides mccartyi CBDB1 and BAV1. Sequence comparison with the reference sequence constructed from 16S rRNA gene sequences in a public database showed the presence of Sedimentibacter, Sulfurospirillum, Clostridium, Desulfovibrio, Parabacteroides, Alistipes, Eubacterium, Peptostreptococcus and Proteocatella in addition to Dehalococcoides sp. After further enrichment, the members of the consortium were narrowed down to almost three species. Finally, the full-length circular genome sequence of the Dehalococcoides sp. in the consortium, D. mccartyi IBARAKI, was determined by analyzing the metagenome with the single-molecule DNA sequencer PacBio RS. The accuracy of the sequence was confirmed by matching it to the tag sequences obtained by SOLiD 3. The genome is 1,451,062 nt and the number of CDS is 1566, which includes 3 rRNA genes and 47 tRNA genes. There exist twenty-eight RDase genes that are accompanied by the genes for anchor proteins. The genome exhibits significant sequence identity with other Dehalococcoides spp. throughout the genome, but there exists significant difference in the distribution RDase genes. The combination of a short-read next-generation DNA sequencer and a long-read single-molecule DNA sequencer gives detailed information of a bacterial consortium.

GPAT2, a mitochondrial outer membrane protein, in piRNA biogenesis in germline stem cells.

piRNA (PIWI-interacting RNA) is a germ cell-specific small RNA in which biogenesis PIWI (P-element wimpy testis) family proteins play crucial roles. MILI (mouse Piwi-like), one of the three mouse PIWI family members, is indispensable for piRNA production, DNA methylation of retrotransposons presumably through the piRNA, and spermatogenesis. The biogenesis of piRNA has been divided into primary and secondary processing pathways; in both of these MILI is involved in mice. To analyze the molecular function of MILI in piRNA biogenesis, we utilized germline stem (GS) cells, which are derived from testicular stem cells and possess a spermatogonial phenotype. We established MILI-null GS cell lines and their revertant, MILI-rescued GS cells, by introducing the Mili gene with Sendai virus vector. Comparison of wild-type, MILI-null, and MILI-rescued GS cells revealed that GS cells were quite useful for analyzing the molecular mechanisms of piRNA production, especially the primary processing pathway. We found that glycerol-3-phosphate acyltransferase 2 (GPAT2), a mitochondrial outer membrane protein for lysophosphatidic acid, bound to MILI using the cells and that gene knockdown of GPAT2 brought about impaired piRNA production in GS cells. GPAT2 is not only one of the MILI bound proteins but also a protein essential for primary piRNA biogenesis.

Pretreatment prediction of interferon-alfa efficacy in chronic hepatitis C patients.

BACKGROUND & AIMS: Interferon has been used widely to treat patients with chronic hepatitis C infections. Prediction of interferon efficacy before treatment has been performed mainly by using viral information, such as viral load and genotype. This information has allowed the successful prediction of sustained responders (SR) and non-SRs, which includes transient responders (TR) and nonresponders (NR). In the current study we examined whether liver messenger RNA expression profiles also can be used to predict interferon efficacy. METHODS: RNA was isolated from 69 liver biopsy samples from patients receiving interferon monotherapy and was analyzed on a complementary DNA microarray. Of these 69 samples, 31 were used to develop an algorithm for predicting interferon efficacy, and 38 were used to validate the precision of the algorithm. We also applied our methodology to the prediction of the efficacy of interferon/ribavirin combination therapy using an additional 56 biopsy samples. RESULTS: Our microarray analysis combined with the algorithm was 94% successful at predicting SR/TR and NR patients. A validation study confirmed that this algorithm can predict interferon efficacy with 95% accuracy and a P value of less than .00001. Similarly, we obtained a 93% prediction efficacy and a P value of less than .0001 for patients receiving combination therapy. CONCLUSIONS: By using only host data from the complementary DNA microarray we are able to successfully predict SR/TR and NR patients for interferon therapy. Therefore, this technique can help determine the appropriate treatment for hepatitis C patients.

A low-density cDNA microarray with a unique reference RNA: pattern recognition analysis for IFN efficacy prediction to HCV as a model.

We have designed and established a low-density (295 genes) cDNA microarray for the prediction of IFN efficacy in hepatitis C patients. To obtain a precise and consistent microarray data, we collected a data set from three spots for each gene (mRNA) and using three different scanning conditions. We also established an artificial reference RNA representing pseudo-inflammatory conditions from established hepatocyte cell lines supplemented with synthetic RNAs to 48 inflammatory genes. We also developed a novel algorithm that replaces the standard hierarchical-clustering method and allows handling of the large data set with ease. This algorithm utilizes a standard space database (SSDB) as a key scale to calculate the Mahalanobis distance (MD) from the center of gravity in the SSDB. We further utilized sMD (divided by parameter k: MD/k) to reduce MD number as a predictive value. The efficacy prediction of conventional IFN mono-therapy was 100% for non-responder (NR) vs. transient responder (TR)/sustained responder (SR) (P < 0.0005). Finally, we show that this method is acceptable for clinical application.