Sequence and Structural Differences between Enzyme and Nonenzyme Homologs

AbstractTo improve our understanding of the evolution of novel functions, we performed a sequence, structural, and functional analysis of homologous enzymes and nonenzymes of known three-dimensional structure. In most examples identified, the nonenzyme is derived from an ancestral catalytic precursor (as opposed to the reverse evolutionary scenario, nonenzyme to enzyme), and the active site pocket has been disrupted in some way, owing to the substitution of critical catalytic residues and/or steric interactions that impede substrate binding and catalysis. Pairwise sequence identity is typically insignificant, and almost one-half of the enzyme and nonenzyme pairs do not share any similarity in function. Heterooligomeric enzymes comprising homologous subunits in which one chain is catalytically inactive and enzyme polypeptides that contain internal catalytic and noncatalytic duplications of an ancient enzyme domain are also discussed

Comprehensive reanalysis of transcription factor knockout expression data in Saccharomyces cerevisiae reveals many new targets

Transcription factor (TF) perturbation experiments give valuable insights into gene regulation. Genome-scale evidence from microarray measurements may be used to identify regulatory interactions between TFs and targets. Recently, Hu and colleagues published a comprehensive study covering 269 TF knockout mutants for the yeast Saccharomyces cerevisiae. However, the information that can be extracted from this valuable dataset is limited by the method employed to process the microarray data. Here, we present a reanalysis of the original data using improved statistical techniques freely available from the BioConductor project. We identify over 100 000 differentially expressed genes—nine times the total reported by Hu et al. We validate the biological significance of these genes by assessing their functions, the occurrence of upstream TF-binding sites, and the prevalence of protein–protein interactions. The reanalysed dataset outperforms the original across all measures, indicating that we have uncovered a vastly expanded list of relevant targets. In summary, this work presents a high-quality reanalysis that maximizes the information contained in the Hu et al. compendium. The dataset is available from ArrayExpress (accession: E-MTAB-109) and it will be invaluable to any scientist interested in the yeast transcriptional regulatory system

Increasing frailty is associated with higher prevalence and reduced recognition of delirium in older hospitalised inpatients: results of a multi-centre study

Purpose: Delirium is a neuropsychiatric disorder delineated by an acute change in cognition, attention, and consciousness. It is common, particularly in older adults, but poorly recognised. Frailty is the accumulation of deficits conferring an increased risk of adverse outcomes. We set out to determine how severity of frailty, as measured using the CFS, affected delirium rates, and recognition in hospitalised older people in the United Kingdom. Methods: Adults over 65 years were included in an observational multi-centre audit across UK hospitals, two prospective rounds, and one retrospective note review. Clinical Frailty Scale (CFS), delirium status, and 30-day outcomes were recorded. Results: The overall prevalence of delirium was 16.3% (483). Patients with delirium were more frail than patients without delirium (median CFS 6 vs 4). The risk of delirium was greater with increasing frailty [OR 2.9 (1.8–4.6) in CFS 4 vs 1–3; OR 12.4 (6.2–24.5) in CFS 8 vs 1–3]. Higher CFS was associated with reduced recognition of delirium (OR of 0.7 (0.3–1.9) in CFS 4 compared to 0.2 (0.1–0.7) in CFS 8). These risks were both independent of age and dementia. Conclusion: We have demonstrated an incremental increase in risk of delirium with increasing frailty. This has important clinical implications, suggesting that frailty may provide a more nuanced measure of vulnerability to delirium and poor outcomes. However, the most frail patients are least likely to have their delirium diagnosed and there is a significant lack of research into the underlying pathophysiology of both of these common geriatric syndromes

A Search for type 1 diabetes susceptibility genes in families from the United Kingdom

Genetic analysis of a mouse model of major histocompatability complex (MHC)-associated autoimmune type 1 (insulin-dependent) diabetes mellitus (IDDM) has shown that the disease is caused by a combination of a major effect at the MHC and at least ten other susceptibility loci elsewhere in the genome. A genome-wide scan of 93 affected sibpair families (ASP) from the UK (UK93) indicated a similar genetic basis for human type 1 diabetes, with the major genetic component at the MHC locus (IDDM1) explaining 34% of the familial clustering of the disease (λs=2.5; refs 3.4). In the present report, we have analysed a further 263 multiplex families from the same population (UK263) to provide a total UK data set of 356 ASP families (UK356). Only four regions of the genome outside IDDM1/MHC, which was still the only major locus detected, were not excluded at λs=3 and lod=-2, of which two showed evidence of linkage: chromosome 10p13-p11 (maximum lod score (MLS)=4.7, P=3x10-6, λs=1.56) and chromosome 16q22-16q24 (MLS=3.4, P=6.5x10-5, λs)= 1.6). These and other novel regions, including chromosome 14q12-q21 and chromosome 19p1319q13, could potentially harbour disease loci but confirmation and fine mapping cannot be pursued effectively using conventional linkage analysis. Instead, more powerful linkage disequilibrium-based and haplotype mapping approaches must be used; such data is already emerging for several type 1 diabetes loci detected initially by linkage