Profiling of Haemophilus influenzae strain R2866 with carbohydrate-based covalent probes.

We demonstrate the application of four covalent probes based on anomerically pure d-galactosamine and d-glucosamine scaffolds for the profiling of Haemophilus influenzae strain R2866. The probes have been used successfully for the labelling of target proteins not only in cell lysates, but also in intact cells. Differences in the labelling patterns between lysates and intact cells indicate that the probes can penetrate into the periplasm, but not the cytoplasm of H. influenzae. Analysis of selected target proteins by LC-MS/MS suggests predominant labelling of nucleotide-binding proteins, including several known antibacterial drug targets. Our protocols will aid the identification of molecular determinants of bacterial pathogenicity in Haemophilus influenzae and other bacterial pathogens

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants with Treatment Resistance in Schizophrenia

Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10501) and individuals with non-TRS (n = 20325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results: The study included a total of 85490 participants (48635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P =.001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P =.04). Conclusions and Relevance: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance

C. difficle p-cresol production

To identify the cellular localisation of the HpdBCA decarboxylase complex, a plasmid based HpdB-SNAP-tag translational fusion was constructed using a C. difficile compatible plasmid (pMTL84151) under control of the hpdBCA promoter. The hpdB coding sequence omitting the stop codon, was fused via a linker to a SNAP-tag (Table 1). Confirmation of HpdB linked to the SNAP-tag was carried out via western blot, and mass spectrometry, in which we identified six peptides, four with 100% identity and two with 99% identity unique to HpdB. Localisation of HpdB was visualised by confocal microscopy in 630Δerm and the p-cresol deficient mutant (hpdC::CT) (carrying the HpdB-SNAP-tag fusion (PhpdB-CDS-SNAP), in the presence and absence of p-HPA) to induce HpdBCA production

Protein S-sulfenylation is a fleeting molecular switch that regulates non-enzymatic oxidative folding

The post-translational modification S-sulfenylation functions as a key sensor of oxidative stress. Yet the dynamics of sulfenic acid in proteins remains largely elusive due to its fleeting nature. Here we use single-molecule force-clamp spectroscopy and mass spectrometry to directly capture the reactivity of an individual sulfenic acid embedded within the core of a single Ig domain of the titin protein. Our results demonstrate that sulfenic acid is a crucial short-lived intermediate that dictates the protein's fate in a conformation-dependent manner. When exposed to the solution, sulfenic acid rapidly undergoes further chemical modification, leading to irreversible protein misfolding; when cryptic in the protein's microenvironment, it readily condenses with a neighbouring thiol to create a protective disulfide bond, which assists the functional folding of the protein. This mechanism for non-enzymatic oxidative folding provides a plausible explanation for redox-modulated stiffness of proteins that are physiologically exposed to mechanical forces, such as cardiac titin

Tailoring protein nanomechanics with chemical reactivity

AbstractThe nanomechanical properties of elastomeric proteins determine the elasticity of a variety of tissues. A widespread natural tactic to regulate protein extensibility lies in the presence of covalent disulfide bonds, which significantly enhance protein stiffness. The prevalent in vivo strategy to form disulfide bonds requires the presence of dedicated enzymes. Here we propose an alternative chemical route to promote non-enzymatic oxidative protein folding via disulfide isomerization based on naturally occurring small molecules. Using single-molecule force-clamp spectroscopy, supported by DFT calculations and mass spectrometry measurements, we demonstrate that subtle changes in the chemical structure of a transient mixed-disulfide intermediate adduct between a protein cysteine and an attacking low molecular-weight thiol have a dramatic effect on the protein’s mechanical stability. This approach provides a general tool to rationalize the dynamics of S-thiolation and its role in modulating protein nanomechanics, offering molecular insights on how chemical reactivity regulates protein elasticity.</jats:p

What determines social capital in a social-ecological system? Insights from a network perspective

Social capital is an important resource that can be mobilized for purposive action or competitive gain. The distribution of social capital in social–ecological systems can determine who is more productive at extracting ecological resources and who emerges as influential in guiding their management, thereby empowering some while disempowering others. Despite its importance, the factors that contribute to variation in social capital among individuals have not been widely studied. We adopt a network perspective to examine what determines social capital among individuals in social–ecological systems. We begin by identifying network measures of social capital relevant for individuals in this context, and review existing evidence concerning their determinants. Using a complete social network dataset from Hawaii's longline fishery, we employ social network analysis and other statistical methods to empirically estimate these measures and determine the extent to which individual stakeholder attributes explain variation within them. We find that ethnicity is the strongest predictor of social capital. Measures of human capital (i.e., education, experience), years living in the community, and information-sharing attitudes are also important. Surprisingly, we find that when controlling for other factors, industry leaders and formal fishery representatives are generally not well connected. Our results offer new quantitative insights on the relationship between stakeholder diversity, social networks, and social capital in a coupled social–ecological system, which can aid in identifying barriers and opportunities for action to overcome resource management problems. Our results also have implications for achieving resource governance that is not only ecologically and economically sustainable, but also equitable