Biology subjects

Schierack, P.

Publications and source records attributed to Schierack, P..

3 recordsLinked to original sources

bioRxiv2021

Anti-prothrombin autoantibodies enriched after infection with SARS-CoV-2 and influenced by strength of antibody response against SARS-CoV-2 proteins

Antiphospholipid antibodies (aPL), assumed to cause antiphospholipid syndrome (APS), are notorious for their heterogeneity and detect phospholipids and phospholipid-binding proteins. The persistent presence of Lupus anticoagulant and/or aPL against cardiolipin and/or {beta}2 glycoprotein I have been shown to be independent risk factors for vascular thrombosis and pregnancy morbidity in APS. aPL production is thought to be triggered by - among other factors - viral infections, though infection-associated aPL have mostly been considered non-pathogenic. Recently, the potential pathogenicity of infection-associated aPL has gained momentum since an increasing number of patients infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been described with coagulation abnormalities and hyperinflammation, together with the presence of aPL. Here, we present data from a multicentric, mixed-severity study including three cohorts of individuals who contracted SARS-CoV-2 as well as non-infected blood donors. We simultaneously measured 10 different criteria and non-criteria aPL (IgM and IgG) by using a line immunoassay. Further, IgG antibody response against three SARS-CoV-2 proteins was investigated using tripartite automated blood immunoassay technology. Our analyses revealed that selected non-criteria aPL were enriched concomitant to or after an infection with SARS-CoV-2. Linear mixed-effects models suggest an association of aPL to prothrombin (PT) with the strength of the antibody response against SARS-CoV-2 and that it is further influenced by SARS-CoV-2 disease severity and sex of the individuals. In conclusion, our study is the first to report an association between disease severity, anti-SARS-CoV-2 immunoreactivity and aPL against PT in patients with SARS-CoV-2.

immunology↗

bioRxiv2021

PCRedux: A Data Mining and Machine Learning Toolkit for qPCR Experiments

MotivationQuantitative Real-time PCR (qPCR) is a widely used -omics method for the precise quantification of nucleic acids, in which the result is associated with the presence/absence or quantity of a specific nucleic acid sequence. As the amount of qPCR data increases worldwide, the manual assessment of results becomes challenging and difficult to reproduce. To overcome this, some automatable characteristics of amplification curves have been described in the literature, often with an appropriate "rule of thumb". ResultsWe developed PCRedux to analyze and calculate 90 numerical qPCR amplification curve descriptors ( features") from large datasets of qPCR amplification curves that are aimed for interpretable machine learning and development of decision support systems. In a case study of a diverse dataset with 3181 positive, negative and ambiguous amplification curves, as assessed by three human raters, we demonstrate a sensitivity >99 % and specificity >97 % in detecting positive and negative amplification. PCRedux is unique as it goes beyond traditional qPCR analysis to capture curvature properties that improve the characterization and classification of amplification curves. The calculation of the features is reproducible and objective, since R is used as a controllable working environment. PCRedux is not a black box, but open source software following on the principle of mathematically interpretable features. These can be combined with user-defined labels for automatic multi-category classification and regression in machine learning. Availabilityhttps://cran.r-project.org/package=PCRedux. Web server: http://shtest.evrogen.net/PCRedux-app/. Documentation: https://PCRuniversum.github.io/PCRedux/.

bioinformatics↗

bioRxiv2021

A multiplex microchamber diffusion assay for the antibody-based detection of microRNAs on randomly ordered microbeads

BackgroundMicroRNAs (miRNAs) are small, conserved, noncoding RNAs regulating gene expression that functions in RNA silencing and post-transcriptional regulation of gene expression. Altered miRNA profiles have been implicated in many human diseases, and due to their circulating abilities, they have excited great interest in their use as clinical biomarkers. The development of innovative methods for miRNA detection has become of high scientific and clinical interest. MethodsWe developed a diffusion-driven microbead assay and combined it with an antibody-based miRNA detection. The diffusion process was carried out in two different approaches a) co-diffusion of miRNA and antibodies (termed diffusion approach I, DAI) and b) diffusion of miRNA in an antibody-saturated environment (DAII). In both approaches, neutravidin-coated microbeads were loaded with specific biotinylated DNA capture probes, which targets either miR-21-5p, miR-30a-3p or miR-93-5p. The miRNAs were time- and dose-dependently detected in a diffusion microchamber by primary anti-DNA:RNA hybrid and fluorescence-labeled secondary antibodies using our in-house developed inverse fluorescence microscope imaging platform VideoScan. ResultsOur assay offers the advantage that several target molecules can be detected simultaneously and in real-time in one reaction environment (multiplex), without any amplification steps. We recorded the diffusion process over a period of 24 h and found that the reaction was almost completed after 2 h. The specificity of the assay was 96.7 % for DAI and 92.3 % for DAII. The detection limits were in a concentration range of 0.03-0.43 nM for DAI and 0.14-1.09 nM for DAII, depending on the miRNA. ConclusionThe miRNAs are successively exposed to the capture probe-loaded randomly ordered microbeads (p value of CSR 0.23-0.96), which leads to microbeads that become saturated with the target molecules first in front rows. Non-bonded miRNAs continue to diffuse further and can therefore subsequently bind to the microbeads with free binding sites. Our detection principle differs from other microbead assays, in which all microbeads are simultaneously mixed with the sample solution, so that all target molecules bind equally distributed to the microbeads, resulting in an averaged signal intensity.

biochemistry↗