Inflammation, Pathogen-Zell-Interaktionen und Stamm-Charakterisierung von Streptococcus gallolyticus subsp. gallolyticus als Erreger der infektiösen Endokarditis

Weinstock M. Inflammation, Pathogen-Zell-Interaktionen und Stamm-Charakterisierung von Streptococcus gallolyticus subsp. gallolyticus als Erreger der infektiösen Endokarditis. Bielefeld: Universitätsbibliothek Bielefeld; 2014

Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value OBFC1indicated the independent signals colocalized with cell-type specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated our TL polygenic trait scores (PTS) were associated with increased risk of cancer-related phenotypes

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

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Strain-dependent interactions of Streptococcus gallolyticus subsp. gallolyticus with human blood cells

Abstract Background Streptococcus gallolyticus subsp. gallolyticus (S. gallolyticus) is the causative pathogen in up to 20% of streptococcal-induced infective endocarditis (IE) cases. However, the underlying mechanisms of pathogenesis in S. gallolyticus have not yet been solved. Pathogens causing IE need to employ virulent strategies to initiate and establish infections, such as escape the bloodstream, invade the host-cell, and persist intracellularly. In this study, we examined the induction of inflammation by different S. gallolyticus strains in relation to their survival in whole blood and cell culture models as well as their ability to induce platelet aggregation. Phagocytosis of these bacteria by macrophages, followed by intracellular survival, was also quantified. Methods In whole blood and THP-1 cell culture assays bacterial growth kinetics was determined by plating, followed by colony counting. Induction of interleukin (IL)-6 expression in whole blood of three healthy volunteers, caused by different strains, was quantified by ELISA. Gene expression of cytokines (IL1B, IL6 and IL8) was quantified by real-time PCR after stimulating THP-1 monocytes with bacteria. Induction of platelet aggregation was analyzed by light transmission aggregometry using the BORN method. A macrophage model was used to analyze phagocytosis of strains and their survival in macrophages within 48 h. Results Strains promoted IL-6 secretion in a time-dependent fashion. For example, DSM16831 induced IL-6 secretion in whole blood earlier than other isolates, and was eliminated in the whole blood of one volunteer, whereas UCN34 could grow. Platelet aggregation depended on the different isolates used and on the individual platelet donor. Two strains (AC1181 and 010672/01) induced cytokine gene expression in THP-1 monocytes only marginally, compared to other strains. The phagocytosis rate of S. gallolyticus isolates differed significantly, and the isolates UCN34 and BAA-2069 could persist for a considerable time in the phagocytes. Conclusion The strain-dependent differences of S. gallolyticus isolates, observed during interaction with human blood cells, support the hypotheses that divergences in individual virulence factors determine a distinct pathogenicity of the isolates. These data constitute an additional step towards the elucidation of mechanisms in the complex, multifactorial pathogenesis of this IE pathogen

Genetic Variants in Genes of the Inflammatory Response in Association with Infective Endocarditis

<div><p>Aims</p><p>Inflammation in infective endocarditis (IE) is a complex network including interactions of inflammatory cytokines and other components of host response. Certainly, any variation in this network could influence susceptibility or disease progression of IE. In this study, 14 single nucleotide variants (SNVs) in genes coding for interleukin-1β, interleukin-6, interleukin-10, toll–like receptor-4, tumor necrosis factor-α, selectin E and intercellular adhesion molecule-1 were analyzed for an association with susceptibility to IE and correlated with disease-related laboratory parameters. Furthermore, the occurrence of SNVs was examined to elucidate pathogen-dependent associations.</p><p>Methods and Results</p><p>The distribution of SNVs was determined in IE-patients and healthy blood donors by RFLP analysis. White blood cells (WBC) were counted using flow cytometry, concentration of C-reactive protein and procalcitonin was measured immunologically. Interleukin-6 c.471+870G>A genotypes differed significantly between IE patients and controls. The frequency of the heterozygote genotype GA was considerably higher in the patient group (68.9% vs. 43.8%, P_c<0.0003). Interleukin-6 c.-237 minor allele frequency was increased in patients, although not statistically significant. Additionally, we detected a potential relation between interleukin-1β c.315C>T and IE. Pathogen-dependent analysis showed no significantly associated subgroup in relation to IE susceptibility, but gave hints towards alterations regarding <i>Enterococcus</i>-caused IE cases. Patients with genotype selectin-E c.-19 GT tend to have higher preoperative WBC counts than patients with genotype GG. We further showed an association between two interleukin-1β SNVs and laboratory biomarkers.</p><p>Conclusion</p><p>This study shows genetic predispositions for the establishment of IE. Furthermore, correlation of SNVs with disease-related biomarkers suggests a role of genetic variants regarding the inflammatory response in IE.</p></div

Allele and genotype frequencies of IL1B, TLR4, SELE, ICAM1, IL10, TNF and IL6 gene variants in IE patients and healthy controls (<b>P_χ:</b> P-value of χ² test; P_F: P-value after Fisher’s exact test; P_c: corresponding P-values after Bonferroni correction).

<p>Allele and genotype frequencies of IL1B, TLR4, SELE, ICAM1, IL10, TNF and IL6 gene variants in IE patients and healthy controls (<b>P_χ:</b> P-value of χ² test; P_F: P-value after Fisher’s exact test; P_c: corresponding P-values after Bonferroni correction).</p

Pre- and postoperative PCT levels (mean ± SEM), as well as factorial change Q_(post/pre) of PCT in the course of surgical intervention in patient sera (ns: not significant; nd: not determined, * = P<0.05).

<p>3A–C: PCT levels in correlation with TNF c.-418G>A; A: Preoperative PCT level, B: Postoperative PCT level, C: Q_(post/pre) of PCT in the course of surgical intervention; 3E–G: PCT levels in correlation with IL1B c.302-64G>A; A: Preoperative PCT level, B: Postoperative PCT level, C: Q_(post/pre) of PCT in the course of surgical operative intervention.</p

Pre- (A) and postoperative (B) CRP levels (mean ± SEM), as well as factorial change Q_(post/pre) of CRP (C) in the course of surgical intervention in patient sera in correlation with IL1B c.315C>T genotype (ns: not significant; * = P<0.05).

<p>Pre- (A) and postoperative (B) CRP levels (mean ± SEM), as well as factorial change Q_(post/pre) of CRP (C) in the course of surgical intervention in patient sera in correlation with IL1B c.315C>T genotype (ns: not significant; * = P<0.05).</p