The repertoire of T- and B-cell receptor sequences encodes the antigen specificity of adaptive immunity system, determines its present state and guides its ability to mount effective response against encountered antigens in future. High throughput sequencing of immune repertoires (Rep-Seq) is a promising technique that allows to profile millions of antigen receptors of an individual in a single experiment. While a substantial number of tools for mapping and assembling Rep-Seq data were published recently, the field still lacks an intuitive and flexible tool that can be used by researchers with little or no computational background for in-depth analysis of immune repertoire profiles. Here we report VDJviz, a web tool that can be used to browse, analyze and perform quality control of Rep-Seq results generated by various pre-processing software. On a set of real data examples we show that VDJviz can be used to explore key repertoire characteristics such as spectratype, repertoire clonality, V-(D)-J recombination patterns and to identify shared clonotypes. We also demonstrate the utility of VDJviz in detection of critical Rep-Seq biases such as artificial repertoire diversity and cross-sample contamination. VDJviz is a versatile and lightweight tool that can be easily employed by biologists, immunologists and immunogeneticists for routine analysis and quality control of Rep-Seq data. The software is freely available for non-commercial purposes, and can be downloaded from: https://github.com/antigenomics/vdjviz .
DNA repair is essential for the maintenance of genome stability in all living beings. Genome size as well as the repertoire and abundance of DNA repair components may vary among prokaryotic species. The bacteria of the Mollicutes class feature a small genome size, absence of a cell wall, and a parasitic lifestyle. A small number of genes make Mollicutes a good model for a “minimal cell” concept.
The global SARS-CoV-2 pandemic has united the efforts of many scientists all over the world to develop wet-lab techniques and computational approaches aimed at the identification of antigen-specific T and B cells. The latter provide specific humoral immunity that is essential for the survival of COVID-19 patients, and vaccine development has essentially been based on these cells. Here, we implemented an approach that integrates the sorting of antigen-specific B cells and B-cell receptor mRNA sequencing (BCR-seq), followed by computational analysis. This rapid and cost-efficient method allowed us to identify antigen-specific B cells in the peripheral blood of patients with severe COVID-19 disease. Subsequently, specific BCRs were extracted, cloned, and produced as full antibodies. We confirmed their reactivity toward the spike RBD domain. Such an approach can be effective for the monitoring and identification of B cells participating in an individual immune response.