SummaryThe integration of metabolomics and transcriptomics can provide precise information on gene-to-metabolite networks for identifying the function of unknown genes unless there has been a post-transcriptional modification. Here, we report a comprehensive analysis of the metabolome and transcriptome of Arabidopsis thaliana over-expressing the PAP1 gene encoding an MYB transcription factor, for the identification of novel gene functions involved in flavonoid biosynthesis. For metabolome analysis, we performed flavonoid-targeted analysis by high-performance liquid chromatography-mass spectrometry and non-targeted analysis by Fourier-transform ion-cyclotron mass spectrometry with an ultrahigh-resolution capacity. This combined analysis revealed the specific accumulation of cyanidin and quercetin derivatives, and identified eight novel anthocyanins from an array of putative 1800 metabolites in PAP1 over-expressing plants. The transcriptome analysis of 22 810 genes on a DNA microarray revealed the induction of 38 genes by ectopic PAP1 overexpression. In addition to well-known genes involved in anthocyanin production, several genes with unidentified functions or annotated with putative functions, encoding putative glycosyltransferase, acyltransferase, glutathione S-transferase, sugar transporters and transcription factors, were induced by PAP1. Two putative glycosyltransferase genes (At5g17050 and At4g14090) induced by PAP1 expression were confirmed to encode flavonoid 3-O-glucosyltransferase and anthocyanin 5-O-glucosyltransferase, respectively, from the enzymatic activity of their recombinant proteins in vitro and results of the analysis of anthocyanins in the respective T-DNA-inserted mutants. The functional genomics approach through the integration of metabolomics and transcriptomics presented here provides an innovative means of identifying novel gene functions involved in plant metabolism.

Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1–5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

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Background: Tranilast, N-(3,4-dimethoxycinnamoyl) anthranilic acid, suppresses collagen synthesis by various cells, including macrophages and fibroblasts, by interfering with the actions of transforming growth factor-beta 1. We investigated the effect of tranilast on progression of diabetic nephropathy (DN), since this process is associated with accumulation of collagens in the glomerulus and interstitium. Methods: Tranilast (100 mg, 3 times daily) was administered to 9 outpatients with advanced DN who were receiving an angiotensin-converting enzyme inhibitor or an angiotensin II receptor antagonist and who exhibited a progressive decline in renal function. The decline in renal function before and during tranilast treatment was evaluated for each patient on the basis of the slope in reciprocal serum creatinine (1/S_Cr) over time. Urinary type IV collagen (U-IV·C) and protein (U-P) excretions were measured just before commencement of tranilast treatment and every 2 months during the treatment. Results: One male patient dropped out soon after commencement of tranilast treatment due to development of lung cancer, and hemodialysis was introduced in one female patient 6 months after the start of treatment. In the 8 patients who did not drop out, 1/S_Cr was significantly less steep during tranilast treatment than before treatment (–0.00748 ± 0.00700 vs. –0.01348 ± 0.00636 dl/mg/month, respectively; p = 0.0374). U-IV·C and U-P tended to decrease with time, although the decrease was statistically insignificant. Conclusions: Our data suggest that tranilast treatment may suppress accumulation of collagens in renal tissue and may be therapeutically useful for reducing the progression of advanced DN.

The COVID-19 pandemic of 2020 posed an historic challenge to healthcare systems around the world. Besides mounting a massive response to the viral outbreak, healthcare systems needed to consider provision of clinical services to other patients in need. Surgical services for patients with thoracic disease were maintained to different degrees across various regions of Asia, ranging from significant reductions to near-normal service. Key determinants of robust thoracic surgery service provision included: preexisting plans for an epidemic response, aggressive early action to "flatten the curve", ability to dedicate resources separately to COVID-19 and routine clinical services, prioritization of thoracic surgery, and the volume of COVID-19 cases in that region. The lessons learned can apply to other regions during this pandemic, and to the world, in preparation for the next one.

Background We aimed to elucidate differences in the characteristics of patients with coronavirus disease 2019 (COVID-19) requiring hospitalization in Japan, by COVID-19 waves, from conventional strains to the Delta variant. Methods We used secondary data from a database and performed a retrospective cohort study that included 3261 patients aged ≥ 18 years enrolled from 78 hospitals that participated in the Japan COVID-19 Task Force between February 2020 and September 2021. Results Patients hospitalized during the second (mean age, 53.2 years [standard deviation {SD}, ± 18.9]) and fifth (mean age, 50.7 years [SD ± 13.9]) COVID-19 waves had a lower mean age than those hospitalized during the other COVID-19 waves. Patients hospitalized during the first COVID-19 wave had a longer hospital stay (mean, 30.3 days [SD ± 21.5], p < 0.0001), and post-hospitalization complications, such as bacterial infections (21.3%, p < 0.0001), were also noticeable. In addition, there was an increase in the use of drugs such as remdesivir/baricitinib/tocilizumab/steroids during the latter COVID-19 waves. In the fifth COVID-19 wave, patients exhibited a greater number of presenting symptoms, and a higher percentage of patients required oxygen therapy at the time of admission. However, the percentage of patients requiring invasive mechanical ventilation was the highest in the first COVID-19 wave and the mortality rate was the highest in the third COVID-19 wave. Conclusions We identified differences in clinical characteristics of hospitalized patients with COVID-19 in each COVID-19 wave up to the fifth COVID-19 wave in Japan. The fifth COVID-19 wave was associated with greater disease severity on admission, the third COVID-19 wave had the highest mortality rate, and the first COVID-19 wave had the highest percentage of patients requiring mechanical ventilation.

Paenibacillus curdlanolyticus B-6 showed effective degradation activities for xylan and cellulose and produced an extracellular multienzyme complex (approximately 1,450 kDa) containing several xylanases and cellulases. To characterize the multienzyme complex, we purified the complex from culture supernatants by four kind of chromatography. The purified multienzyme complex was composed of a 280-kDa protein with xylanase activity, a 260-kDa protein that was a truncated form on the C-terminal side of the 280-kDa protein, two xylanases of 40 and 48 kDa, and 60 and 65 kDa proteins having both xylanase and carboxymethyl cellulase activities. The 280-kDa protein resembled the scaffolding proteins of cellulosomes based on its migratory behavior in polyacrylamide gels and as a glycoprotein. Cloning of the 40-kDa major xylanase subunit named Xyn11A revealed that Xyn11A contained two functional domains which belonged to glycosyl hydrolase family-11 and to carbohydrate-binding module family-36, respectively, and a glycine- and asparagine-rich linker. However, an amino acid sequence similar to a dockerin domain, which is crucial to cellulosome assembly, was not found in Xyn11A. These results suggest that the multienzyme complex produced by P. curdlanolyticus B-6 should assemble by a mechanism distinct from the cohesin-dockerin interactions known in cellulosomes.

Service restoration problem in distribution systems is formulated as a multi-objective optimization problem which is demanded not only for minimizing the amount of unrestored total loads but also for minimizing the number of the switching operations. The solution of the multi-objective optimization problem is usually obtained with a set of Pareto optimal solutions. The Pareto optimal solutions for the service restoration problem are useful for users to obtain their desired restoration by comparing a Pareto optimal solution with the others. However, the conventional methods cannot obtain plural Pareto optimal solutions in one trial. Therefore, this paper proposes a method for obtaining a Pareto optimal set for the service restoration problem with a genetic algorithm. The genetic algorithm produces many possible solutions in its search process. By utilizing this feature, the proposed method can obtain the Pareto optimal set.