Imprints of somatic hypermutation on B-cell receptor immunoglobulins post-infection versus post-vaccination against SARS-CoV-2.

Published evidence supports significant heterogeneity of immune responses among individuals infected with or vaccinated against SARS-CoV-2. This highlights the need for in-depth investigation of the implicated processes toward refined understanding and improved management of COVID-19. The main objective of the present study was to investigate the dynamics of B cell responses to SARS-CoV-2, focusing on how initial infection and subsequent vaccination influence the immunoglobulin gene repertoire, with special emphasis on the impact of somatic hypermutation (SHM) on antibody maturation.

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data.

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population.

IκBε deficiency accelerates disease development in chronic lymphocytic leukemia.

The NFKBIE gene, which encodes the NF-κB inhibitor IκBε, is mutated in 3-7% of patients with chronic lymphocytic leukemia (CLL). The most recurrent alteration is a 4-bp frameshift deletion associated with NF-κB activation in leukemic B cells and poor clinical outcome. To study the functional consequences of NFKBIE gene inactivation, both in vitro and in vivo, we engineered CLL B cells and CLL-prone mice to stably down-regulate NFKBIE expression and investigated its role in controlling NF-κB activity and disease expansion.

Intranuclear inclusions of polyQ-expanded ATXN1 sequester RNA molecules.

Spinocerebellar ataxia type 1 (SCA1) is an autosomal dominant neurodegenerative disease caused by a trinucleotide (CAG) repeat expansion in the ATXN1 gene. It is characterized by the presence of polyglutamine (polyQ) intranuclear inclusion bodies (IIBs) within affected neurons. In order to investigate the impact of polyQ IIBs in SCA1 pathogenesis, we generated a novel protein aggregation model by inducible overexpression of the mutant ATXN1(Q82) isoform in human neuroblastoma SH-SY5Y cells.

High risk HPV-positive women cervicovaginal microbial profiles in a Greek cohort: a retrospective analysis of the GRECOSELF study.

Increasing evidence supports a role for the vaginal microbiome (VM) in the severity of HPV infection and its potential link to cervical intraepithelial neoplasia. However, a lot remains unclear regarding the precise role of certain bacteria in the context of HPV positivity and persistence of infection. Here, using next generation sequencing (NGS), we comprehensively profiled the VM in a series of 877 women who tested positive for at least one high risk HPV (hrHPV) type with the COBAS 4,800 assay, after self-collection of a cervico-vaginal sample.

Software pipelines for RNA-Seq, ChIP-Seq and germline variant calling analyses in common workflow language (CWL).

Automating data analysis pipelines is a key requirement to ensure reproducibility of results, especially when dealing with large volumes of data. Here we assembled automated pipelines for the analysis of High-throughput Sequencing (HTS) data originating from RNA-Seq, ChIP-Seq and Germline variant calling experiments. We implemented these workflows in Common workflow language (CWL) and evaluated their performance by: i) reproducing the results of two previously published studies on Chronic Lymphocytic Leukemia (CLL), and ii) analyzing whole genome sequencing data from four Genome in a Bottle Consortium (GIAB) samples, comparing the detected variants against their respective golden standard truth sets.

Context-dependent T-cell Receptor Gene Repertoire Profiles in Proliferations of T Large Granular Lymphocytes.

T cell large granular lymphocyte (T-LGL) lymphoproliferations constitute a disease spectrum ranging from poly/oligo to monoclonal. Boundaries within this spectrum of proliferations are not well established. T-LGL lymphoproliferations co-occur with a wide variety of other diseases ranging from autoimmune disorders, solid tumors, hematological malignancies, post solid organ, and hematopoietic stem cell transplantation, and can therefore arise as a consequence of a wide variety of antigenic triggers.

N-Glycosylation of the Ig Receptors Shapes the Antigen Reactivity in Chronic Lymphocytic Leukemia Subset #201.

Subset #201 is a clinically indolent subgroup of patients with chronic lymphocytic leukemia defined by the expression of stereotyped, mutated IGHV4-34/IGLV1-44 BCR Ig. Subset #201 is characterized by recurrent somatic hypermutations (SHMs) that frequently lead to the creation and/or disruption of N-glycosylation sites within the Ig H and L chain variable domains. To understand the relevance of this observation, using next-generation sequencing, we studied how SHM shapes the subclonal architecture of the BCR Ig repertoire in subset #201, particularly focusing on changes in N-glycosylation sites.

Chromatin activation profiling of stereotyped chronic lymphocytic leukemias reveals a subset 8-specific signature.

The chromatin activation landscape of chronic lymphocytic leukemia (CLL) with stereotyped B-cell receptor immunoglobulin is currently unknown. In this study, we report the results of a whole-genome chromatin profiling of histone 3 lysine 27 acetylation of 22 CLLs from major subsets, which were compared against nonstereotyped CLLs and normal B-cell subpopulations. Although subsets 1, 2, and 4 did not differ much from their nonstereotyped CLL counterparts, subset 8 displayed a remarkably distinct chromatin activation profile.

T cell receptor gene repertoire profiles in subgroups of patients with chronic lymphocytic leukemia bearing distinct genomic aberrations.

Background: Microenvironmental interactions of the malignant clone with T cells are critical throughout the natural history of chronic lymphocytic leukemia (CLL). Indeed, clonal expansions of T cells and shared clonotypes exist between different CLL patients, strongly implying clonal selection by antigens. Moreover, immunogenic neoepitopes have been isolated from the clonotypic B cell receptor immunoglobulin sequences, offering a rationale for immunotherapeutic approaches.

Evidence of somatic hypermutation in the antigen binding sites of patients with CLL harboring IGHV genes with 100% germline identity.

Classification of patients with chronic lymphocytic leukemia (CLL) based on the somatic hypermutation (SHM) status of the clonotypic immunoglobulin heavy variable (IGHV) gene has established predictive and prognostic relevance. The SHM status is assessed based on the number of mutations within the IG heavy variable domain sequence, albeit only over the rearranged IGHV gene excluding the variable heavy complementarity determining region 3 (VH CDR3). This may lead to an underestimation of the actual impact of SHM, in fact overlooking the most critical region for antigen-antibody interactions, i.

Detecting SARS-CoV-2 lineages and mutational load in municipal wastewater and a use-case in the metropolitan area of Thessaloniki, Greece.

The COVID-19 pandemic represents an unprecedented global crisis necessitating novel approaches for, amongst others, early detection of emerging variants relating to the evolution and spread of the virus. Recently, the detection of SARS-CoV-2 RNA in wastewater has emerged as a useful tool to monitor the prevalence of the virus in the community. Here, we propose a novel methodology, called lineagespot, for the monitoring of mutations and the detection of SARS-CoV-2 lineages in wastewater samples using next-generation sequencing (NGS).

InterTADs: integration of multi-omics data on topologically associated domains, application to chronic lymphocytic leukemia.

The integration of multi-omics data can greatly facilitate the advancement of research in Life Sciences by highlighting new interactions. However, there is currently no widespread procedure for meaningful multi-omics data integration. Here, we present a robust framework, called InterTADs, for integrating multi-omics data derived from the same sample, and considering the chromatin configuration of the genome, i.

miRkit: R framework analyzing miRNA PCR array data.

Objective: The characterization of microRNAs (miRNA) in recent years is an important advance in the field of gene regulation. To this end, several approaches for miRNA expression analysis and various bioinformatics tools have been developed over the last few years. It is a common practice to analyze miRNA PCR Array data using the commercially available software, mostly due to its convenience and ease-of-use.

Exploring plant diversity through soil DNA in Thai national parks for influencing land reform and agriculture planning.

Background: The severe deforestation, as indicated in national forest data, is a recurring problem in many areas of Northern Thailand, including Doi Suthep-Pui National Park. Agricultural expansion in these areas, is one of the major drivers of deforestation, having adverse consequences on local plant biodiversity. Conserving biodiversity is mainly dependent on the biological monitoring of species distribution and population sizes.

UMIc: A Preprocessing Method for UMI Deduplication and Reads Correction.

A recent refinement in high-throughput sequencing involves the incorporation of unique molecular identifiers (UMIs), which are random oligonucleotide barcodes, on the library preparation steps. A UMI adds a unique identity to different DNA/RNA input molecules through polymerase chain reaction (PCR) amplification, thus reducing bias of this step. Here, we propose an alignment free framework serving as a preprocessing step of fastq files, called UMIc, for deduplication and correction of reads building consensus sequences from each UMI.

A Computational Framework for Pattern Detection on Unaligned Sequences: An Application on SARS-CoV-2 Data.

The exponential growth of genome sequences available has spurred research on pattern detection with the aim of extracting evolutionary signal. Traditional approaches, such as multiple sequence alignment, rely on positional homology in order to reconstruct the phylogenetic history of taxa. Yet, mining information from the plethora of biological data and delineating species on a genetic basis, still proves to be an extremely difficult problem to consider.

TRIP - T cell receptor/immunoglobulin profiler.

Background: Antigen receptors are characterized by an extreme diversity of specificities, which poses major computational and analytical challenges, particularly in the era of high-throughput immunoprofiling by next generation sequencing (NGS). The T cell Receptor/Immunoglobulin Profiler (TRIP) tool offers the opportunity for an in-depth analysis based on the processing of the output files of the IMGT/HighV-Quest tool, a standard in NGS immunoprofiling, through a number of interoperable modules. These provide detailed information about antigen receptor gene rearrangements, including variable (V), diversity (D) and joining (J) gene usage, CDR3 amino acid and nucleotide composition and clonality of both T cell receptors (TR) and B cell receptor immunoglobulins (BcR IG), and characteristics of the somatic hypermutation within the BcR IG genes.