piRNA-like small RNAs are responsible for the maternal-specific knockdown in the ascidian Ciona intestinalis Type A

The mRNAs stored in eggs are crucial for embryogenesis. To address functions of maternal mRNAs, we recently reported the novel method MASK (maternal mRNA-specific knockdown), which we used to specifically knockdown maternal transcripts in the ascidian Ciona intestinalis Type A. In MASK, the cis element of a maternal gene is fused with eGFP or Kaede reporter gene, and the cassette is introduced into Ciona genome by transposon-mediated transgenesis. In eggs of the transgenic lines, the maternal expression of the gene whose cis element is used for driving the reporter gene is suppressed. The zygotic expression of the gene is not suppressed, suggesting that the MASK method can distinguish between maternal and zygotic functions of a gene. Here we investigated the cis and trans factors responsible for MASK results. In the ovaries in which knockdown of a maternal gene occurs, a number of antisense small RNAs are expressed that are complementary to the sequence of the knocked-down genes. We suspect that these antisense small RNAs are the factor responsible for MASK results. The antisense small RNAs have several features that are seen in PIWI-interacting RNAs (piRNAs), suggesting that MASK is likely to use a piRNA-mediated mechanism to knock down maternal mRNAs

Improved Adsorption of an Enterococcus faecalis Bacteriophage ΦEF24C with a Spontaneous Point Mutation

Some bacterial strains of the multidrug-resistant Gram-positive bacteria Enterococcus faecalis can significantly reduce the efficacy of conventional antimicrobial chemotherapy. Thus, the introduction of bacteriophage (phage) therapy is expected, where a phage is used as a bioagent to destroy bacteria. E. faecalis phage ΦEF24C is known to be a good candidate for a therapeutic phage against E. faecalis. However, this therapeutic phage still produces nonuniform antimicrobial effects with different bacterial strains of the same species and this might prove detrimental to its therapeutic effects. One solution to this problem is the preparation of mutant phages with higher activity, based on a scientific rationale. This study isolated and analyzed a spontaneous mutant phage, ΦEF24C-P2, which exhibited higher infectivity against various bacterial strains when compared with phage ΦEF24C. First, the improved bactericidal effects of phage ΦEF24C-P2 were attributable to its increased adsorption rate. Moreover, genomic sequence scanning revealed that phage ΦEF24C-P2 had a point mutation in orf31. Proteomic analysis showed that ORF31 (mw, 203 kDa) was present in structural components, and immunological analysis using rabbit-derived antibodies showed that it was a component of a long, flexible fine tail fiber extending from the tail end. Finally, phage ΦEF24C-P2 also showed higher bactericidal activity in human blood compared with phage ΦEF24C using the in vitro assay system. In conclusion, the therapeutic effects of phage ΦEF24C-P2 were improved by a point mutation in gene orf31, which encoded a tail fiber component

Nuclear translocation of glutathione S-transferase π is mediated by a non-classical localization signal.

Glutathione S-transferase π (GSTπ), a member of the GST family of multifunctional enzymes, is highly expressed in human placenta and involved in the protection of cellular components against electrophilic compounds or oxidative stress. We have recently found that GSTπ is expressed in the cytoplasm, mitochondria, and nucleus in some cancer cells, and that the nuclear expression of GSTπ appears to correlate with resistance to anti-cancer drugs. Although the mitochondrial targeting signal of GSTπ was previously identified in the amino-terminal region, the mechanism of nuclear translocation remains completely unknown. In this study, we find that the region of GSTπ195-208 is critical for nuclear translocation, which is mediated by a novel and non-classical nuclear localization signal. In addition, using an in vitro transport assay, we demonstrate that the nuclear translocation of GSTπ depends on the cytosolic extract and ATP. Although further experiments are needed to understand in depth the precise mechanism of nuclear translocation of GSTπ, our results may help to establish more efficient anti-cancer therapy, especially with respect to resistance to anti-cancer drugs

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries