Distributed Early Worm Detection Based on Payload Histograms

科研費報告書収録論文(課題番号:18300017/研究代表者:根元義章/通信データ列特徴量の類似性に基づいた不正アクセス逆探知方式)68

Structural basis for recognition of cognate tRNA by tyrosyl-tRNA synthetase from three kingdoms

The specific aminoacylation of tRNA by tyrosyl-tRNA synthetases (TyrRSs) relies on the identity determinants in the cognate tRNATyrs. We have determined the crystal structure of Saccharomyces cerevisiae TyrRS (SceTyrRS) complexed with a Tyr-AMP analog and the native tRNATyr(GΨA). Structural information for TyrRS–tRNATyr complexes is now full-line for three kingdoms. Because the archaeal/eukaryotic TyrRSs–tRNATyrs pairs do not cross-react with their bacterial counterparts, the recognition modes of the identity determinants by the archaeal/eukaryotic TyrRSs were expected to be similar to each other but different from that by the bacterial TyrRSs. Interestingly, however, the tRNATyr recognition modes of SceTyrRS have both similarities and differences compared with those in the archaeal TyrRS: the recognition of the C1-G72 base pair by SceTyrRS is similar to that by the archaeal TyrRS, whereas the recognition of the A73 by SceTyrRS is different from that by the archaeal TyrRS but similar to that by the bacterial TyrRS. Thus, the lack of cross-reactivity between archaeal/eukaryotic and bacterial TyrRS-tRNATyr pairs most probably lies in the different sequence of the last base pair of the acceptor stem (C1-G72 vs G1-C72) of tRNATyr. On the other hand, the recognition mode of Tyr-AMP is conserved among the TyrRSs from the three kingdoms

A Proposal for Practical Diagnosis of Renal Hypouricemia : Evidenced from Genetic Studies of Nonfunctional Variants of URAT1/SLC22A12 among 30,685 Japanese Individuals

Background: Renal hypouricemia (RHUC) is characterized by a low serum uric acid (SUA) level and high fractional excretion of uric acid (FEUA). Further studies on FEUA in hypouricemic individuals are needed for a more accurate diagnosis of RHUC. Methods: In 30,685 Japanese health-examination participants, we genotyped the two most common nonfunctional variants of URAT1 (NFV-URAT1), W258X (rs121907892) and R90H (rs121907896), in 1040 hypouricemic individuals (SUA ≤ 3.0 mg/dL) and 2240 individuals with FEUA data. The effects of NFV-URAT1 on FEUA and SUA were also investigated using linear and multiple regression analyses. Results: Frequency of hypouricemic individuals (SUA ≤ 3.0 mg/dL) was 0.97% (male) and 6.94% (female) among 30,685 participants. High frequencies of those having at least one allele of NFV-URAT1 were observed in 1040 hypouricemic individuals. Furthermore, NFV-URAT1 significantly increased FEUA and decreased SUA, enabling FEUA and SUA levels to be estimated. Conversely, FEUA and SUA data of hypouricemic individuals are revealed to be useful to predict the number of NFV-URAT1. Conclusions: Our findings reveal that specific patterns of FEUA and SUA data assist with predicting the number of nonfunctional variants of causative genes for RHUC, and can also be useful for practical diagnosis of RHUC even before genetic tests

Assessment of Border Control Measures and Community Containment Measures Used in Japan during the Early Stages of Pandemic (H1N1) 2009

In the early stages of Pandemic (H1N1) 2009, border control measures were taken by quarantine stations to block the entry of infected individuals into Japan and community containment measures were implemented to prevent the spreading. The objectives of this study were to describe these measures and the characteristics of infected individuals, and to assess the measures' effectiveness.Border control and community containment measures implemented from April to June (Period I: April 28-May 21, Period II: May 22-June 18) 2009 were described. Number of individuals identified and disease characteristics were analyzed. For entry screening, a health declaration form and an infrared thermoscanner were used to detect symptomatic passengers. Passengers indicated for the rapid influenza test underwent the test followed by RT-PCR. Patients positive for H1N1 were isolated, and close contacts were quarantined. Entry cards were handed out to all asymptomatic passengers informing them about how to contact a health center in case they developed symptoms. Nine individuals were identified by entry screening and 1 during quarantine to have Pandemic (H1N1) 2009. Health monitoring by health centers was performed in period I for passengers arriving from affected countries and in period II for those who had come into contact with the individuals identified by entry screening. Health monitoring identified 3 infected individuals among 129,546 in Period I and 5 among 746 in Period II. Enhanced surveillance, which included mandatory reporting of details of the infected individuals, identified 812 individuals, 141 (18%) of whom had a history of international travel. Twenty-four of these 141 passengers picked up by enhanced surveillance had been developing symptoms on entry and were missed at screening.Symptomatic passengers were detected by the various entry screening measures put in place. Enhanced surveillance provided data for the improvement of public health measures in future pandemics

Subtype-specific gout susceptibility loci and enrichment of selection pressure on ABCG2 and ALDH2 identified by subtype genome-wide meta-analyses of clinically defined gout patients

Objectives Genome-wide meta-analyses of clinically defined gout were performed to identify subtype-specific susceptibility loci. Evaluation using selection pressure analysis with these loci was also conducted to investigate genetic risks characteristic of the Japanese population over the last 2000–3000 years. Methods Two genome-wide association studies (GWASs) of 3053 clinically defined gout cases and 4554 controls from Japanese males were performed using the Japonica Array and Illumina Array platforms. About 7.2 million single-nucleotide polymorphisms were meta-analysed after imputation. Patients were then divided into four clinical subtypes (the renal underexcretion type, renal overload type, combined type and normal type), and meta-analyses were conducted in the same manner. Selection pressure analyses using singleton density score were also performed on each subtype. Results In addition to the eight loci we reported previously, two novel loci, PIBF1 and ACSM2B, were identified at a genome-wide significance level (p<5.0×10–8) from a GWAS meta-analysis of all gout patients, and other two novel intergenic loci, CD2-PTGFRN and SLC28A3-NTRK2, from normal type gout patients. Subtype-dependent patterns of Manhattan plots were observed with subtype GWASs of gout patients, indicating that these subtype-specific loci suggest differences in pathophysiology along patients’ gout subtypes. Selection pressure analysis revealed significant enrichment of selection pressure on ABCG2 in addition to ALDH2 loci for all subtypes except for normal type gout. Conclusions Our findings on subtype GWAS meta-analyses and selection pressure analysis of gout will assist elucidation of the subtype-dependent molecular targets and evolutionary involvement among genotype, phenotype and subtype-specific tailor-made medicine/prevention of gout and hyperuricaemia

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts