Crystal Structure of Barley Limit Dextrinase-Limit Dextrinase Inhibitor (LD-LDI) Complex Reveals Insights into Mechanism and Diversity of Cereal Type Inhibitors

Molecular details underlying regulation of starch mobilization in cereal seed endosperm remain unknown despite the paramount role of this process in plant growth. The structure of the complex between the starch debranching enzyme barley limit dextrinase (LD), hydrolyzing α-1,6-glucosidic linkages, and its endogenous inhibitor (LDI) was solved at 2.7 Å. The structure reveals an entirely new and unexpected binding mode of LDI as compared with previously solved complex structures of related cereal type family inhibitors (CTIs) bound to glycoside hydrolases but is structurally analogous to binding of dual specificity CTIs to proteases. Site-directed mutagenesis establishes that a hydrophobic cluster flanked by ionic interactions in the protein-protein interface is vital for the picomolar affinity of LDI to LD as assessed by analysis of binding by using surface plasmon resonance and also supported by LDI inhibition of the enzyme activity. A phylogenetic analysis identified four LDI-like proteins in cereals among the 45 sequences from monocot databases that could be classified as unique CTI sequences. The unprecedented binding mechanism shown here for LDI has likely evolved in cereals from a need for effective inhibition of debranching enzymes having characteristic open active site architecture. The findings give a mechanistic rationale for the potency of LD activity regulation and provide a molecular understanding of the debranching events associated with optimal starch mobilization and utilization during germination. This study unveils a hitherto not recognized structural basis for the features endowing diversity to CTIs

Goal-directed haemodynamic therapy during general anaesthesia for noncardiac surgery:a systematic review and meta-analysis

BACKGROUND: During general anaesthesia for noncardiac surgery, there remain knowledge gaps regarding the effect of goal-directed haemodynamic therapy on patient-centred outcomes. METHODS: Included clinical trials investigated goal-directed haemodynamic therapy during general anaesthesia in adults undergoing noncardiac surgery and reported at least one patient-centred postoperative outcome. PubMed and Embase were searched for relevant articles on March 8, 2021. Two investigators performed abstract screening, full-text review, data extraction, and bias assessment. The primary outcomes were mortality and hospital length of stay, whereas 15 postoperative complications were included based on availability. From a main pool of comparable trials, meta-analyses were performed on trials with homogenous outcome definitions. Certainty of evidence was evaluated using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). RESULTS: The main pool consisted of 76 trials with intermediate risk of bias for most outcomes. Overall, goal-directed haemodynamic therapy might reduce mortality (odds ratio=0.84; 95% confidence interval [CI], 0.64 to 1.09) and shorten length of stay (mean difference=–0.72 days; 95% CI, –1.10 to –0.35) but with low certainty in the evidence. For both outcomes, larger effects favouring goal-directed haemodynamic therapy were seen in abdominal surgery, very high-risk surgery, and using targets based on preload variation by the respiratory cycle. However, formal tests for subgroup differences were not statistically significant. Goal-directed haemodynamic therapy decreased risk of several postoperative outcomes, but only infectious outcomes and anastomotic leakage reached moderate certainty of evidence. CONCLUSIONS: Goal-directed haemodynamic therapy during general anaesthesia might decrease mortality, hospital length of stay, and several postoperative complications. Only infectious postoperative complications and anastomotic leakage reached moderate certainty in the evidence

Fraction of Inspired Oxygen During General Anesthesia for Non-Cardiac Surgery:Systematic Review and Meta-Analysis

BACKGROUND: Controversy exists regarding the effects of a high versus a low intraoperative fraction of inspired oxygen (FiO(2)) in adults undergoing general anesthesia. This systematic review and meta‐analysis investigated the effect of a high versus a low FiO(2) on postoperative outcomes. METHODS: PubMed and Embase were searched on March 22, 2022 for randomized clinical trials investigating the effect of different FiO(2) levels in adults undergoing general anesthesia for non‐cardiac surgery. Two investigators independently reviewed studies for relevance, extracted data, and assessed risk of bias. Meta‐analyses were performed for relevant outcomes, and potential effect measure modification was assessed in subgroup analyses and meta‐regression. The evidence certainty was evaluated using GRADE. RESULTS: This review included 25 original trials investigating the effect of a high (mostly 80%) versus a low (mostly 30%) FiO(2). Risk of bias was intermediate for all trials. A high FiO(2) did not result in a significant reduction in surgical site infections (OR: 0.91, 95% CI 0.81–1.02 [p = .10]). No effect was found for all other included outcomes, including mortality (OR = 1.27, 95% CI: 0.90–1.79 [p = .18]) and hospital length of stay (mean difference = 0.03 days, 95% CI −0.25 to 0.30 [p = .84). Results from subgroup analyses and meta‐regression did not identify any clear effect modifiers across outcomes. The certainty of evidence (GRADE) was rated as low for most outcomes. CONCLUSIONS: In adults undergoing general anesthesia for non‐cardiac surgery, a high FiO(2) did not improve outcomes including surgical site infections, length of stay, or mortality. However, the certainty of the evidence was assessed as low

Bioinformatics-Driven Identification and Examination of Candidate Genes for Non-Alcoholic Fatty Liver Disease

ObjectiveCandidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes.Research Design and MethodsBy integrating public database text mining, trans-organism protein-protein interaction transferal, and information on liver protein expression a protein-protein interaction network was constructed and from this a smaller isolated interactome was identified. Five genes from this interactome were selected for genetic analysis. Twenty-one tag single-nucleotide polymorphisms (SNPs) which captured all common variation in these genes were genotyped in 10,196 Danes, and analyzed for association with NAFLD-related quantitative traits, type 2 diabetes (T2D), central obesity, and WHO-defined metabolic syndrome (MetS).Results273 genes were included in the protein-protein interaction analysis and EHHADH, ECHS1, HADHA, HADHB, and ACADL were selected for further examination. A total of 10 nominal statistical significant associations (P<0.05) to quantitative metabolic traits were identified. Also, the case-control study showed associations between variation in the five genes and T2D, central obesity, and MetS, respectively. Bonferroni adjustments for multiple testing negated all associations.ConclusionsUsing a bioinformatics approach we identified five candidate genes for NAFLD. However, we failed to provide evidence of associations with major effects between SNPs in these five genes and NAFLD-related quantitative traits, T2D, central obesity, and MetS

The EADGENE Microarray Data Analysis Workshop (Open Access publication)

Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses

Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication)

A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies

Meta-analysis of exome array data identifies six novel genetic loci for lung function [version 1; peer review:1 approved, 1 approved with reservations]

Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and the ratio of FEV1 to FVC (FEV1/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P&lt;2•8x10 -7 ) associations with six SNPs: a nonsynonymous variant in RPAP1, which is predicted to be damaging, three intronic SNPs (SEC24C, CASC17 and UQCC1) and two intergenic SNPs near to LY86 and FGF10. Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including TYRO3 and PLAU. Conclusions: Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease.</p

Identification and Functional Characterization of <i>G6PC2</i> Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the <i>G6PC2-ABCB11</i> Locus

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights