A novel approach to probe host-pathogen interactions of bovine digital dermatitis, a model of a complex polymicrobial infection

Background: Polymicrobial infections represent a great challenge for the clarification of disease etiology and the development of comprehensive diagnostic or therapeutic tools, particularly for fastidious and difficult-to-cultivate bacteria. Using bovine digital dermatitis (DD) as a disease model, we introduce a novel strategy to study the pathogenesis of complex infections. Results: The strategy combines meta-transcriptomics with high-density peptide-microarray technology to screen for in vivo-expressed microbial genes and the host antibody response at the site of infection. Bacterial expression patterns supported the assumption that treponemes were the major DD pathogens but also indicated the active involvement of other phyla (primarily Bacteroidetes). Bacterial genes involved in chemotaxis, flagellar synthesis and protection against oxidative and acidic stress were among the major factors defining the disease. Conclusions: The extraordinary diversity observed in bacterial expression, antigens and host antibody responses between individual cows pointed toward microbial variability as a hallmark of DD. Persistence of infection and DD reinfection in the same individual is common; thus, high microbial diversity may undermine the host's capacity to mount an efficient immune response and maintain immunological memory towards DD. The common antigenic markers identified here using a high-density peptide microarray address this issue and may be useful for future preventive measures against DD.Fil: Marcatili, Paolo. Technical University of Denmark; DinamarcaFil: Nielsen, Martin W.. Technical University of Denmark; DinamarcaFil: Sicheritz Ponten, Thomas. Technical University of Denmark; DinamarcaFil: Jensen, Tim K.. Technical University of Denmark; DinamarcaFil: Schafer Nielsen, Claus. Schafer-N ApS; DinamarcaFil: Boye, Mette. Hospital of Southern Jutland; DinamarcaFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Klitgaard, Kirstine. Technical University of Denmark; Dinamarc

HLA Class II Specificity Assessed by High-Density Peptide Microarray Interactions

The ability to predict and/or identify MHC binding peptides is an essential component of T cell epitope discovery, something that ultimately should benefit the development of vaccines and immunotherapies. In particular, MHC class I prediction tools have matured to a point where accurate selection of optimal peptide epitopes is possible for virtually all MHC class I allotypes; in comparison, current MHC class II (MHC-II) predictors are less mature. Because MHC-II restricted CD4+ T cells control and orchestrated most immune responses, this shortcoming severely hampers the development of effective immunotherapies. The ability to generate large panels of peptides and subsequently large bodies of peptide-MHC-II interaction data are key to the solution of this problem, a solution that also will support the improvement of bioinformatics predictors, which critically relies on the availability of large amounts of accurate, diverse, and representative data. In this study, we have used rHLA-DRB1*01:01 and HLA-DRB1*03:01 molecules to interrogate high-density peptide arrays, in casu containing 70,000 random peptides in triplicates. We demonstrate that the binding data acquired contains systematic and interpretable information reflecting the specificity of the HLA-DR molecules investigated, suitable of training predictors able to predict T cell epitopes and peptides eluted from human EBV-transformed B cells. Collectively, with a cost per peptide reduced to a few cents, combined with the flexibility of rHLA technology, this poses an attractive strategy to generate vast bodies of MHC-II binding data at an unprecedented speed and for the benefit of generating peptide-MHC-II binding data as well as improving MHC-II prediction tools.Fil: Osterbye, Thomas. Universidad de Copenhagen; DinamarcaFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Dudek, Nadine L.. Monash University; AustraliaFil: Ramarathinam, Sri H.. Monash University; AustraliaFil: Purcell, Anthony W.. Monash University; AustraliaFil: Schafer-Nielsen, Claus. No especifíca;Fil: Buus, Soren. University Of Copenhagen, Faculty Of Health Sciences

The association between perceived stress and mortality among people with multimorbidity: a prospective population-based cohort study

Multimorbidity is common and is associated with poor mental health and high mortality. Nevertheless, no studies have evaluated whether mental health may affect the survival of people with multimorbidity. We investigated the association between perceived stress and mortality in people with multimorbidity by following a population-based cohort of 118,410 participants from the Danish National Health Survey 2010 for up to 4 years. Information on perceived stress and lifestyle was obtained from the survey. We assessed multimorbidity using nationwide register data on 39 conditions and identified 4,229 deaths for the 453,648 person-years at risk. Mortality rates rose with increasing levels of stress in a dose-response relationship (P-trend < 0.0001), independently of multimorbidity status. Mortality hazard ratios (highest stress quintile vs. lowest) were 1.51 (95% confidence interval (CI): 1.25, 1.84) among persons without multimorbidity, 1.39 (95% CI: 1.18, 1.64) among those with 2 or 3 conditions, and 1.43 (95% CI: 1.18, 1.73) among those with 4 or more conditions, when adjusted for disease severities, lifestyle, and socioeconomic status. The numbers of excess deaths associated with high stress were 69 among persons without multimorbidity, 128 among those with 2 or 3 conditions, and 255 among those with 4 or more conditions. Our findings suggested that perceived stress contributes significantly to higher mortality rates in a dose-response pattern, and more stress-associated deaths occurred in people with multimorbidity

Zoom in on antibody aggregates:A potential pitfall in the search of rare EV populations

High-resolution flow cytometers (hFCM) are used for the detection of extracellular vesicles (EV) in various biological fluids. Due to the increased sensitivity of hFCM, new artifacts with the potential of interfering with data interpretation are introduced, such as detection of antibody aggregates. The aim of this study was to investigate the extent of aggregates in labels commonly used for the characterization of EVs by hFCM. Furthermore, we aimed to compare the efficacy of centrifugation and filtering treatments to remove aggregates, as well as to quantify the effect of the treatments in reducing aggregates. For this purpose, we labeled phosphate buffered saline (PBS) with fluorescently conjugated protein labels and antibodies after submitting them to 5, 10, or 30 min centrifugation, filtering or washed filtering. We investigated samples by hFCM and quantified the amount of aggregates found in PBS labeled with untreated and pre-treated labels. We found a varying amount of aggregates in all labels investigated, and further that filtering is most efficient in removing all but the smallest aggregates. Filtering protein labels can reduce the extent of aggregates; however, how much remains depends on the specific labels and their combination. Therefore, it is still necessary to include appropriate controls in a hFCM study of EVs

Inference of α\alpha-particle density profiles from ITER collective Thomson scattering

The primary purpose of the collective Thomson scattering (CTS) diagnostic at ITER is to measure the properties of fast-ion populations, in particular those of fusion-born $\alpha$-particles. Based on the present design of the diagnostic, we compute and fit synthetic CTS spectra for the ITER baseline plasma scenario, including the effects of noise, refraction, multiple fast-ion populations, and uncertainties on nuisance parameters. As part of this, we developed a model for CTS that incorporates spatial effects of frequency-dependent refraction. While such effects will distort the measured ITER CTS spectra, we demonstrate that the true $\alpha$-particle densities can nevertheless be recovered to within ~10% from noisy synthetic spectra, using existing fitting methods that do not take these spatial effects into account. Under realistic operating conditions, we thus find the predicted performance of the ITER CTS system to be consistent with the ITER measurement requirements of a 20% accuracy on inferred $\alpha$-particle density profiles at 100 ms time resolution.Comment: 17 pages, 11 figures. Accepted for publication in Nucl. Fusio