Molecular characterizations of the coagulase-negative staphylococci species causing urinary tract infection in Tanzania : a laboratory-based cross-sectional study

Funding: This study is part of the Holistic Approach to Unravel Antibacterial Resistance in East Africa (HATUA) project funded by the National Institute for Health Research, Medical Research Council and the Department of Health and Social Care, Award (MR/S004785/1).Background: There is a growing body of evidence on the potential involvement of coagulase-negative Staphylococci (CoNS) in causing urinary tract infections (UTIs). The aim of this study was to delineate virulence potential, antimicrobial resistance genes, and sequence types of CoNS isolated from patients with UTI symptoms and pyuria in Tanzania. Methods: CoNS from patients with UTI symptoms and more than 125 leucocytes/μL were retrieved, subcultured, and whole-genome sequenced. Results: Out of 65 CoNS isolates, 8 species of CoNS were identified; Staphylococcus haemolyticus, n = 27 (41.5%), and Staphylococcus epidermidis, n = 24 (36.9%), were predominant. The majority of S. haemolyticus were sequence type (ST) 30, with 8 new ST138-145 reported, while the majority of S. epidermidis were typed as ST490 with 7 new ST1184-1190 reported. Sixty isolates (92.3%) had either one or multiple antimicrobial resistance genes. The most frequently detected resistance genes were 53 (21%) dfrG, 32 (12.9%) blaZ, and 26 (10.5%) mecA genes conferring resistance to trimethoprim, penicillin, and methicillin, respectively. Out of 65 isolates, 59 (90.8%) had virulence genes associated with UTI, with a predominance of the icaC 47 (46.5%) and icaA 14 (13.9%) genes. Conclusion: S. haemolyticus and S. epidermidis harboring icaC, dfrG, blaZ, and mecA genes were the predominant CoNS causing UTI in Tanzania. Laboratories should carefully interpret the significant bacteriuria due to CoNS in relation to UTI symptoms and pyuria before labeling them as contaminants. Follow-up studies to document the outcome of the treated patients is needed to add more evidence that CoNS are UTI pathogens.Publisher PDFPeer reviewe

Allele distribution and phenotypic resistance to ciprofloxacin and gentamicin among extended-spectrum β-lactamase-producing Escherichia coli isolated from the urine, stool, animals, and environments of patients with presumptive urinary tract infection in Tanzania

BackgroundAdditional antimicrobial resistance to extended-spectrum β-lactamase (ESBL)-producing E. coli exhausts treatment options. We investigated allele distribution and resistance to ciprofloxacin and gentamicin among ESBL-producing E. coli isolates from the urine, stool, animals, and environments of presumptive urinary tract infection (UTI) patients, in order to gain a crucial insight toward devising prevention and control measures and treatment guidelines.MethodsArchived ESBL-producing E. coli isolates from the urine, stool, animals, and surrounding environments of presumptive UTI patients were retrieved. Antimicrobial susceptibility profiles for ciprofloxacin and gentamicin were done followed by multiplex Polymerase chain reaction (PCR) for blaCTX-M, blaTEM, and blaSHV, to determine ESBL allele distribution. Data were analyzed using STATA version 17.ResultsA total of 472 confirmed ESBL-producing E. coli isolates from Mwanza 243 (51.5%), Kilimanjaro 143 (30.3%), and Mbeya 86 (18.2%) were analyzed. Of these, 75 (15.9%) were from urine, 199 (42.2%) from stool, 58 (12.3%) from rectal/cloaca swabs of animals, and 140 (29.7%) from surrounding environments. Out of the 472 ESBL-producing E. coli, 98.9% (467) had at least one ESBL allele. The most frequent allele was blaCTX-M, which was detected in 88.1% (416/472) of isolates, followed by the blaTEM allele, which was detected in 51.5% (243/472) of isolates. A total of 40.7% (192/472) of isolates harbored dual blaCTX-M + blaTEMalleles and only 0.2% (1/472) of isolates had dual blaCTX-M + blaSHValleles, whereas 2.3% (11/472) of isolates had a combination of all three alleles (blaCTX-M + blaTEM + blaSHV). None of the isolates harbored a combination of blaTEM + blaSHVonly. Resistance to ciprofloxacin and gentamicin was observed in 70.8% (334/472) and 46.0% (217/472) of isolates, respectively. There was a significant difference in the distribution of resistance to ciprofloxacin as well as gentamicin among ESBL-producing E. coli isolated from various sources (p-value < 0.001 and 0.002, respectively).ConclusionAlmost all ESBL-producing E. coli isolates carry blaCTX-M, blaTEM, and blaSHV either alone or in combination, with the most common allele being blaCTX-M.The resistance to ciprofloxacin and gentamicin, which are frontline antibiotics for UTIs among ESBL-producing E. coli, is high. This implies the need to continually revise the local guidelines used for optimal empirical therapy for UTIs, and for continual research and surveillance using one health approach

Bayesian inference of accurate population sizes and FRET efficiencies from single diffusing biomolecules.

It is of significant biophysical interest to obtain accurate intramolecular distance information and population sizes from single-molecule Förster resonance energy transfer (smFRET) data obtained from biomolecules in solution. Experimental methods of increasing cost and complexity are being developed to improve the accuracy and precision of data collection. However, the analysis of smFRET data sets currently relies on simplistic, and often arbitrary methods, for the selection and denoising of fluorescent bursts. Although these methods are satisfactory for the analysis of simple, low-noise systems with intermediate FRET efficiencies, they display systematic inaccuracies when applied to more complex systems. We have developed an inference method for the analysis of smFRET data from solution studies based on rigorous model-based Bayesian techniques. We implement a Monte Carlo Markov chain (MCMC) based algorithm that simultaneously estimates population sizes and intramolecular distance information directly from a raw smFRET data set, with no intermediate event selection and denoising steps. Here, we present both our parametric model of the smFRET process and the algorithm developed for data analysis. We test the algorithm using a combination of simulated data sets and data from dual-labeled DNA molecules. We demonstrate that our model-based method systematically outperforms threshold-based techniques in accurately inferring both population sizes and intramolecular distances.This is the final published version. It's also available from ACS in Analytical Chemistry: http://pubs.acs.org/doi/pdf/10.1021/ac501188r

Drug discovery: Insights from the invertebrate Caenorhabditis elegans

Therapeutic drug development is a long, expensive, and complex process that usually takes 12–15 years. In the early phases of drug discovery, in particular, there is a growing need for animal models that ensure the reduction in both cost and time. Caenorhabditis elegans has been traditionally used to address fundamental aspects of key biological processes, such as apoptosis, aging, and gene expression regulation. During the last decade, with the advent of large-scale platforms for screenings, this invertebrate has also emerged as an essential tool in the pharmaceutical research industry to identify novel drugs and drug targets. In this review, we discuss the reasons why C. elegans has been positioned as an outstanding cost-effective option for drug discovery, highlighting both the advantages and drawbacks of this model. Particular attention is paid to the suitability of this nematode in large-scale genetic and pharmacological screenings. High-throughput screenings in C. elegans have indeed contributed to the breakthrough of a wide variety of candidate compounds involved in extensive fields including neurodegeneration, pathogen infections and metabolic disorders. The versatility of this nematode, which enables its instrumentation as a model of human diseases, is another attribute also herein underscored. As illustrative examples, we discuss the utility of C. elegans models of both human neurodegenerative diseases and parasitic nematodes in the drug discovery industry. Summing up, this review aims to demonstrate the impact of C. elegans models on the drug discovery pipeline.Fil: Giunti, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: Andersen, Natalia Denise. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: Rayes, Diego Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: de Rosa, Maria Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; Argentin

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome