De novo Inference of Diversity Genes and Analysis of Non-canonical V(DD)J Recombination in Immunoglobulins

The V(D)J recombination forms the immunoglobulin genes by joining the variable (V), diversity (D), and joining (J) germline genes. Since variations in germline genes have been linked to various diseases, personalized immunogenomics aims at finding alleles of germline genes across various patients. Although recent studies described algorithms for de novo inference of V and J genes from immunosequencing data, they stopped short of solving a more difficult problem of reconstructing D genes that form the highly divergent CDR3 regions and provide the most important contribution to the antigen binding. We present the IgScout algorithm for de novo D gene reconstruction and apply it to reveal new alleles of human D genes and previously unknown D genes in camel, an important model organism in immunology. We further analyze non-canonical V(DD)J recombination that results in unusually long CDR3s with tandem fused IGHD genes and thus expands the diversity of the antibody repertoires. We demonstrate that tandem CDR3s represent a consistent and functional feature of all analyzed immunosequencing datasets, reveal ultra-long CDR3s, and shed light on the mechanism responsible for their formation

Targeted isolation of diverse human protective broadly neutralizing antibodies against SARS-like viruses

The emergence of current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) and potential future spillovers of SARS-like coronaviruses into humans pose a major threat to human health and the global economy. Development of broadly effective coronavirus vaccines that can mitigate these threats is needed. Here, we utilized a targeted donor selection strategy to isolate a large panel of human broadly neutralizing antibodies (bnAbs) to sarbecoviruses. Many of these bnAbs are remarkably effective in neutralizing a diversity of sarbecoviruses and against most SARS-CoV-2 VOCs, including the Omicron variant. Neutralization breadth is achieved by bnAb binding to epitopes on a relatively conserved face of the receptor-binding domain (RBD). Consistent with targeting of conserved sites, select RBD bnAbs exhibited protective efficacy against diverse SARS-like coronaviruses in a prophylaxis challenge model in vivo. These bnAbs provide new opportunities and choices for next-generation antibody prophylactic and therapeutic applications and provide a molecular basis for effective design of pan-sarbecovirus vaccines

Research of extractors for the extraction of target components from plant materials of various internal structures

Manufacturers prefer berries and fruits, but there are also other products made with seeds, aromatic and medicinal herbs, spices, as well as other components. The main production stage for obtaining tinctures and aromatic alcohols is the extraction process. Currently, a large number of designs of extractors for solid-liquid system of periodic and continuous action have been developed. All of them are different from each other in terms of efficiency, energy consumption and applicability in a particular production. The purpose of this work is to study and analyze the influence of the structure of raw materials on the efficiency of extraction in equipment of various types. To carry out the research, three types of raw materials were selected from various groups: rose hips, penny root and chaga mushrooms. The most suitable and promising extractor designs are the Soxlhet extractor; centrifugal extractor; rotary-pulsating apparatus. The results of the work, it was concluded that the most versatile apparatus is the rotary-pulsating apparatus, since during its operation the raw material is crushed. Plant raw materials give the most complete target components with list time. In devices of similar designs, the different internal structure of raw materials does not affect the quality of the extracts obtained

Automated analysis of immunosequencing datasets reveals novel immunoglobulin D genes across diverse species.

Immunoglobulin genes are formed through V(D)J recombination, which joins the variable (V), diversity (D), and joining (J) germline genes. Since variations in germline genes have been linked to various diseases, personalized immunogenomics focuses on finding alleles of germline genes across various patients. Although reconstruction of V and J genes is a well-studied problem, the more challenging task of reconstructing D genes remained open until the IgScout algorithm was developed in 2019. In this work, we address limitations of IgScout by developing a probabilistic MINING-D algorithm for D gene reconstruction, apply it to hundreds of immunosequencing datasets from multiple species, and validate the newly inferred D genes by analyzing diverse whole genome sequencing datasets and haplotyping heterozygous V genes

DataSheet_1_A scalable model for simulating multi-round antibody evolution and benchmarking of clonal tree reconstruction methods.pdf

Affinity maturation (AM) of B cells through somatic hypermutations (SHMs) enables the immune system to evolve to recognize diverse pathogens. The accumulation of SHMs leads to the formation of clonal lineages of antibody-secreting b cells that have evolved from a common naïve B cell. Advances in high-throughput sequencing have enabled deep scans of B cell receptor repertoires, paving the way for reconstructing clonal trees. However, it is not clear if clonal trees, which capture microevolutionary time scales, can be reconstructed using traditional phylogenetic reconstruction methods with adequate accuracy. In fact, several clonal tree reconstruction methods have been developed to fix supposed shortcomings of phylogenetic methods. Nevertheless, no consensus has been reached regarding the relative accuracy of these methods, partially because evaluation is challenging. Benchmarking the performance of existing methods and developing better methods would both benefit from realistic models of clonal lineage evolution specifically designed for emulating B cell evolution. In this paper, we propose a model for modeling B cell clonal lineage evolution and use this model to benchmark several existing clonal tree reconstruction methods. Our model, designed to be extensible, has several features: by evolving the clonal tree and sequences simultaneously, it allows modeling selective pressure due to changes in affinity binding; it enables scalable simulations of large numbers of cells; it enables several rounds of infection by an evolving pathogen; and, it models building of memory. In addition, we also suggest a set of metrics for comparing clonal trees and measuring their properties. Our results show that while maximum likelihood phylogenetic reconstruction methods can fail to capture key features of clonal tree expansion if applied naively, a simple post-processing of their results, where short branches are contracted, leads to inferences that are better than alternative methods.</p

Simulated barcoded Rep-seq datasets (IGH, barcode length: 15 nt)

<p>Simulated barcoded Rep-seq libraries with various amplification error rates for repertoire from doi.org/10.5281/zenodo.823351. Barcode errors, barcode collisions and chimeric reads are introduced into datasets. Barcodes are encoded in headers.</p

Simulated B-cells Rep-Seq datasets (called SIMULATED) from "Reconstructing antibody repertoires from error-prone immunosequencing datasets" paper

Simulated test datasets used for benchmarking of immunorepertoire construction tool