Project description:In the last two years, the coronavirus disease 19 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a scientific and social challenge worldwide. Vaccines have been the most effective intervention for reducing virus transmission and disease severity. However, virus genetic variants are still circulating among vaccinated individuals with different symptomatology disease cases. Understanding the protective or disease associated mechanisms in vaccinated individuals is relevant to advance in vaccine development and implementation. To address this objective, serum protein profiles were characterized by quantitative proteomics and data analysis algorithms in four cohorts of vaccinated individuals uninfected and SARS-CoV-2 infected with asymptomatic, nonsevere and severe disease symptomatology. The results showed that immunoglobulins were the most overrepresented proteins in infected cohorts when compared to PCR-negative individuals. The immunoglobulin profile varied between different infected cohorts and correlated with protective or disease associated capacity. Overrepresented immunoglobulins in PCR-positive individuals correlated with protective response against SARS-CoV-2, other viruses, and thrombosis in asymptomatic cases. In nonsevere cases, correlates of protection against SARS-CoV-2 and HBV together with risk of myasthenia gravis and allergy and autoantibodies were observed. Patients with severe symptoms presented risk for allergy, chronic idiopathic thrombocytopenic purpura, and autoantibodies. The analysis of underrepresented immunoglobulins in PCR-positive compared to PCR-negative individuals identified vaccine-induced protective epitopes in various coronavirus proteins including the Spike receptor-binding domain RBD. Non-immunoglobulin proteins were associated with COVID-19 symptoms and biological processes. These results evidence host-associated differences in response to vaccination and the possibility of improving vaccine efficacy against SARS-CoV-2.
Project description:In order to better understand the functional properties of this type of cells under different circumstances, we integrated the single-cell RNA-seq data of peripheral blood CD8+ T cells from healthy subjects, MS patients and COVID-19 patients generated from the 10X Genomics platform using the Seurat package. KIR+CD8+ T cells from different conditions (healthy, MS, and COVID-19) formed a distinct cluster with high expression of effector genes (GZMB and PRF1) as well as KIR transcripts. These findings reveal the commonality of KIR+CD8+ T cells across physiological and diseased status as well as their uniqueness relative to other CD8+ T cells.
Project description:ChAdOx1 nCov-19 and Ad26.COV2.S are approved vaccines inducing protective immunity against SARS-CoV-2 infection in humans by expressing the Spike protein of SARS-CoV-2. We analyzed protein content and protein composition of ChAdOx1 nCov-19 and Ad26.COV2.S by biochemical methods and by mass spectrometry. Four out of four tested lots of ChAdOx1 nCoV-19 contained significantly higher than expected levels of host cell proteins (HCPs) and of free viral proteins. The most abundant contaminating HCPs belonged to the heat-shock protein and cytoskeletal protein families. The HCP content exceeded the 400 ng specification limit per vaccine dose, as set by the European Medicines Agency (EMA) for this vaccine, by at least 25-fold and the manufacturer's batch-release data in some of the lots by several hundred-fold. In contrast, three tested lots of the Ad26.COV2.S vaccine contained only very low amounts of HCPs. As shown for Ad26.COV2.S production of clinical grade adenovirus vaccines of high purity is feasible at an industrial scale. Correspondingly, purification procedures of the ChAdOx1 nCov-19 vaccine should be modified to remove protein impurities as good as possible. Our data also indicate that standard quality assays, as they are used in the manufacturing of proteins, have to be adapted for vectored vaccines.
Project description:Blood collected from adults pre vaccination and post vaccination to study the immune effects of COVID-19 vaccination and how they relate to antibody and T-cell responses.
Project description:1H NMR spectra of sera have been used to define the changes induced by vaccination with Pfizer-BioNTech vaccine (2 shots, 21 days apart) in 10 COVID-19-recovered subjects and 10 COVID-19-naïve subjects at different time points, starting from before vaccination, then weekly until 7 days after second injection, and finally 1 month after the second dose. The data show that vaccination does not induce any significant variation in the metabolome, whereas it causes changes at the level of lipoproteins. The effects are different in the COVID-19-recovered subjects with respect to the naïve subjects, suggesting that a previous infection reduces the vaccine modulation of the lipoproteome composition.
Project description:We performed quantitative proteomic profiling of 786 plasma samples from COVID-19 inpatients, treated at two different hospitals (Charité – Universitätsmedizin Berlin and University Hospital of Innsbruck). Sampling was performed at multiple time points throughout the course of the disease, to create a time-resolved map of COVID-19 progression. Full DIA-NN analysis reports are provided, as well as raw files for the QC runs.
Project description:The objective of the present investigation was to consider the level of variation in the protein expression patterns of closely related Salmonella serovars, in order to search for protein factors with levels of expression or posttranslational modifications characteristic for each serovar. For the comparative expression analysis we have utilised classic 2D GE approach which revealed several proteins with serovar specific expression as well as proteins which do not alter their expression levels between serovars and strains. The proteins of interest were identified using LC/MS/MS. Keywords: 2D GE, MS/MS Analysis of 12 strains of S. enterica representing five different serovars.
Project description:cDNA microarrays have been shown to be useful for monitoring global gene expression patterns in normal and disease states and in response to various environmental stimuli. In this study we have used a cattle cDNA microarray containing 7653 elements to analyze expression profiles in 19 different cattle tissues. Signal intensities from all tissue sample RNAs were compared to a reference standard RNA created from different tissues and cell lines. Data analysis identified a subset of genes significantly differentially expressed between tissues and the reference standard that were further subdivided according to fold change. Log transformed ratios were normalized using the intensity-based regional Lowess algorithm. A global error model, to account for the dependence of variation on signal intensities, was used to identify lists of genes for effect of tissue on gene expression taking into account an experiment-wise significance of 0.05, using either a Bonferroni correction (663 genes) or Benjamini and Hochbergâ??s False Discovery Rate (3350 genes). Non-supervised cluster analysis revealed groups of genes common to nerve, muscle, immune or digestive tissues. Discriminant analysis was used to support physiological functional categories and embryonic origin of tissues. Unique profiles were constructed with genes preferentially expressed in specific tissues or tissue groups in order to define gene expression for individual tissues. Global expression along a large collection of tissues revealed tissue specific expression of enzyme isomers and utilization in specific metabolic pathways. A comprehensive matrix of all possible pair-wise comparisons for individual genes among tissues was constructed to further identify genes with tissue-specific behavior and possibly unique function. A reference design was used to compare 19 cattle tissues. All tissues were compared to a universal control consisting of a mix of cattle cell lines. All samples were duplicated with a dye swap.