Dutch patients, retail chicken meat and poultry share the same ESBL genes, plasmids and strains

Intestinal carriage of extended-spectrum beta-lactamase (ESBL) -producing bacteria in food-producing animals and contamination of retail meat may contribute to increased incidences of infections with ESBL-producing bacteria in humans. Therefore, distribution of ESBL genes, plasmids and strain genotypes in Escherichia coli obtained from poultry and retail chicken meat in the Netherlands was determined and defined as ‘poultry-associated’ (PA). Subsequently, the proportion of E. coli isolates with PA ESBL genes, plasmids and strains was quantified in a representative sample of clinical isolates. The E. coli were derived from 98 retail chicken meat samples, a prevalence survey among poultry, and 516 human clinical samples from 31 laboratories collected during a 3-month period in 2009. Isolates were analysed using an ESBL-specific microarray, sequencing of ESBL genes, PCR-based replicon typing of plasmids, plasmid multi-locus sequence typing (pMLST) and strain genotyping (MLST). Six ESBL genes were defined as PA (blaCTX-M-1, blaCTX-M-2, blaSHV-2, blaSHV-12, blaTEM-20, blaTEM-52): 35% of the human isolates contained PA ESBL genes and 19% contained PA ESBL genes located on IncI1 plasmids that were genetically indistinguishable from those obtained from poultry (meat). Of these ESBL genes, 86% were blaCTX-M-1 and blaTEM-52 genes, which were also the predominant genes in poultry (78%) and retail chicken meat (75%). Of the retail meat samples, 94% contained ESBL-producing isolates of which 39% belonged to E. coli genotypes also present in human samples. These findings are suggestive for transmission of ESBL genes, plasmids and E. coli isolates from poultry to humans, most likely through the food chain

Neutrophil and Eosinophil Responses Remain Abnormal for Several Months in Primary Care Patients With COVID-19 Disease

IntroductionNeutrophil and eosinophil activation and its relation to disease severity has been understudied in primary care patients with COVID-19. In this study, we investigated whether the neutrophil and eosinophil compartment were affected in primary care patients with COVID-19.MethodsCOVID-19 patients, aged ≥ 40 years with cardiovascular comorbidity presenting to the general practitioner with substantial symptoms, partaking in the COVIDSat@Home study between January and April 2021, were included. Blood was drawn during and 3 to 6 months after active COVID-19 disease and analyzed by automated flow cytometry, before and after stimulation with a formyl-peptide (fNLF). Mature neutrophil and eosinophil markers at both time points were compared to healthy controls. A questionnaire was conducted on disease symptoms during and 3 to 6 months after COVID-19 disease.ResultsThe blood of 18 COVID-19 patients and 34 healthy controls was analyzed. During active COVID-19 disease, neutrophils showed reduced CD10 (p = 0.0360), increased CD11b (p = 0.0002) and decreased CD62L expression (p < 0.0001) compared to healthy controls. During active COVID-19 disease, fNLF stimulated neutrophils showed decreased CD10 levels (p < 0.0001). Three to six months after COVID-19 disease, unstimulated neutrophils showed lowered CD62L expression (p = 0.0003) and stimulated neutrophils had decreased CD10 expression (p = 0.0483) compared to healthy controls. Both (un)stimulated CD10 levels increased 3 to 6 months after active disease (p = 0.0120 and p < 0.0001, respectively) compared to during active disease. Eosinophil blood counts were reduced during active COVID-19 disease and increased 3 to 6 months after infection (p < 0.0001). During active COVID-19, eosinophils showed increased unstimulated CD11b (p = 0.0139) and decreased (un)stimulated CD62L expression (p = 0.0036 and p = 0.0156, respectively) compared to healthy controls. Three to six months after COVID-19 disease, (un)stimulated eosinophil CD62L expression was decreased (p = 0.0148 and p = 0.0063, respectively) and the percentage of CD11bbright cells was increased (p = 0.0083 and p = 0.0307, respectively) compared to healthy controls.ConclusionAutomated flow cytometry analysis reveals specific mature neutrophil and eosinophil activation patterns in primary care patients with COVID-19 disease, during and 3 to 6 months after active disease. This suggests that the neutrophil and eosinophil compartment are long-term affected by COVID-19 in primary care patients. This indicates that these compartments may be involved in the pathogenesis of long COVID

Expression of miR-21 and its targets (PTEN, PDCD4, TM1) in flat epithelial atypia of the breast in relation to ductal carcinoma in situ and invasive carcinoma

<p>Abstract</p> <p>Background</p> <p>Flat epithelial atypia (FEA) of the breast is characterised by a few layers of mildly atypical luminal epithelial cells. Genetic changes found in ductal carcinoma in situ (DCIS) and invasive ductal breast cancer (IDC) are also found in FEA, albeit at a lower concentration. So far, miRNA expression changes associated with invasive breast cancer, like miR-21, have not been studied in FEA.</p> <p>Methods</p> <p>We performed miRNA in-situ hybridization (ISH) on 15 cases with simultaneous presence of normal breast tissue, FEA and/or DCIS and 17 additional cases with IDC. Expression of the miR-21 targets PDCD4, TM1 and PTEN was investigated by immunohistochemistry.</p> <p>Results</p> <p>Two out of fifteen cases showed positive staining for miR-21 in normal breast ductal epithelium, seven out of fifteen cases were positive in the FEA component and nine out of twelve cases were positive in the DCIS component. A positive staining of miR-21 was observed in 15 of 17 IDC cases. In 12 cases all three components were present in one tissue block and an increase of miR-21 from normal breast to FEA and to DCIS was observed in five cases. In three cases the FEA component was negative, whereas the DCIS component was positive for miR-21. In three other cases, normal, FEA and DCIS components were negative for miR-21 and in the last case all three components were positive. Overall we observed a gradual increase in percentage of miR-21 positive cases from normal, to FEA, DCIS and IDC. Immunohistochemical staining for PTEN revealed no obvious changes in staining intensities in normal, FEA, DCIS and IDC. Cytoplasmic staining of PDCD4 increased from normal to IDC, whereas, the nuclear staining decreased. TM1 staining decreased from positive in normal breast to negative in most DCIS and IDC cases. In FEA, the staining pattern for TM1 was similar to normal breast tissue.</p> <p>Conclusion</p> <p>Upregulation of miR-21 from normal ductal epithelial cells of the breast to FEA, DCIS and IDC parallels morphologically defined carcinogenesis. No clear relation was observed between the staining pattern of miR-21 and its previously reported target genes.</p

Cell Specific eQTL Analysis without Sorting Cells

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn’s disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus

Improved imputation quality of low-frequency and rare variants in European samples using the ‘Genome of The Netherlands'

Although genome-wide association studies (GWAS) have identified many common variants associated with complex traits, low-frequency and rare variants have not been interrogated in a comprehensive manner. Imputation from dense reference panels, such as the 1000 Genomes Project (1000G), enables testing of ungenotyped variants for association. Here we present the results of imputation using a large, new population-specific panel: the Genome of The Netherlands (GoNL). We benchmarked the performance of the 1000G and GoNL reference sets by comparing imputation genotypes with ‘true' genotypes typed on ImmunoChip in three European populations (Dutch, British, and Italian). GoNL showed significant improvement in the imputation quality for rare variants (MAF 0.05–0.5%) compared with 1000G. In Dutch samples, the mean observed Pearson correlation, r2, increased from 0.61 to 0.71. We also saw improved imputation accuracy for other European populations (in the British samples, r2 improved from 0.58 to 0.65, and in the Italians from 0.43 to 0.47). A combined reference set comprising 1000G and GoNL improved the imputation of rare variants even further. The Italian samples benefitted the most from this combined reference (the mean r2 increased from 0.47 to 0.50). We conclude that the creation of a large population-specific reference is advantageous for imputing rare variants and that a combined reference panel across multiple populations yields the best imputation results

A high-quality human reference panel reveals the complexity and distribution of genomic structural variants

Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation. Here, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100 bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals

WGS-based telomere length analysis in Dutch family trios implicates stronger maternal inheritance and a role for RRM1 gene

Telomere length (TL) regulation is an important factor in ageing, reproduction and cancer development. Genetic, hereditary and environmental factors regulating TL are currently widely investigated, however, their relative contribution to TL variability is still understudied. We have used whole genome sequencing data of 250 family trios from the Genome of the Netherlands project to perform computational measurement of TL and a series of regression and genome-wide association analyses to reveal TL inheritance patterns and associated genetic factors. Our results confirm that TL is a largely heritable trait, primarily with mother’s, and, to a lesser extent, with father’s TL having the strongest influence on the offspring. In this cohort, mother’s, but not father’s age at conception was positively linked to offspring TL. Age-related TL attrition of 40 bp/year had relatively small influence on TL variability. Finally, we have identified TL-associated variations in ribonuclease reductase catalytic subunit M1 (RRM1 gene), which is known to regulate telomere maintenance in yeast. We also highlight the importance of multivariate approach and the limitations of existing tools for the analysis of TL as a polygenic heritable quantitative trait

A framework for the detection of de novo mutations in family-based sequencing data

Germline mutation detection from human DNA sequence data is challenging due to the rarity of such events relative to the intrinsic error rates of sequencing technologies and the uneven coverage across the genome. We developed PhaseByTransmission (PBT) to identify de novo single nucleotide variants and short insertions and deletions (indels) from sequence data collected in parent-offspring trios. We compute the joint probability of the data given the genotype likelihoods in the individual family members, the known familial relationships and a prior probability for the mutation rate. Candidate de novo mutations (DNMs) are reported along with their posterior probability, providing a systematic way to prioritize them for validation. Our tool is integrated in the Genome Analysis Toolkit and can be used together with the ReadBackedPhasing module to infer the parental origin of DNMs based on phase-informative reads. Using simulated data, we show that PBT outperforms existing tools, especially in low coverage data and on the X chromosome. We further show that PBT displays high validation rates on empirical parent-offspring sequencing data for whole-exome data from 104 trios and X-chromosome data from 249 parent-offspring families. Finally, we demonstrate an association between father's age at conception and the number of DNMs in female offspring's X chromosome, consistent with previous literature reports