DNA Damage and L1 Retrotransposition

Barbara McClintock was the first to suggest that transposons are a source of genome instability and that genotoxic stress assisted in their mobilization. The generation of double-stranded DNA breaks (DSBs) is a severe form of genotoxic stress that threatens the integrity of the genome, activates cell cycle checkpoints, and, in some cases, causes cell death. Applying McClintock's stress hypothesis to humans, are L1 retrotransposons, the most active autonomous mobile elements in the modern day human genome, mobilized by DSBs? Here, evidence that transposable elements, particularly retrotransposons, are mobilized by genotoxic stress is reviewed. In the setting of DSB formation, L1 mobility may be affected by changes in the substrate for L1 integration, the DNA repair machinery, or the L1 element itself. The review concludes with a discussion of the potential consequences of L1 mobilization in the setting of genotoxic stress

The Future of Blood Testing Is the Immunome

It is increasingly clear that an extraordinarily diverse range of clinically important conditions-including infections, vaccinations, autoimmune diseases, transplants, transfusion reactions, aging, and cancers-leave telltale signatures in the millions of V(D)J-rearranged antibody and T cell receptor [TR per the Human Genome Organization (HUGO) nomenclature but more commonly known as TCR] genes collectively expressed by a person's B cells (antibodies) and T cells. We refer to these as the immunome. Because of its diversity and complexity, the immunome provides singular opportunities for advancing personalized medicine by serving as the substrate for a highly multiplexed, near-universal blood test. Here we discuss some of these opportunities, the current state of immunome-based diagnostics, and highlight some of the challenges involved. We conclude with a call to clinicians, researchers, and others to join efforts with the Adaptive Immune Receptor Repertoire Community (AIRR-C) to realize the diagnostic potential of the immunome

Gamma radiation increases endonuclease-dependent L1 retrotransposition in a cultured cell assay

Long Interspersed Elements (LINE-1s, L1s) are the most active mobile elements in the human genome and account for a significant fraction of its mass. The propagation of L1 in the human genome requires disruption and repair of DNA at the site of integration. As Barbara McClintock first hypothesized, genotoxic stress may contribute to the mobilization of transposable elements, and conversely, element mobility may contribute to genotoxic stress. We tested the ability of genotoxic agents to increase L1 retrotransposition in a cultured cell assay. We observed that cells exposed to gamma radiation exhibited increased levels of L1 retrotransposition. The L1 retrotransposition frequency was proportional to the number of phosphorylated H2AX foci, an indicator of genotoxic stress. To explore the role of the L1 endonuclease in this context, endonuclease-deficient tagged L1 constructs were produced and tested for their activity in irradiated cells. The activity of the endonuclease-deficient L1 was very low in irradiated cells, suggesting that most L1 insertions in irradiated cells still use the L1 endonuclease. Consistent with this interpretation, DNA sequences that flank L1 insertions in irradiated cells harbored target site duplications. These results suggest that increased L1 retrotransposition in irradiated cells is endonuclease dependent. The mobilization of L1 in irradiated cells potentially contributes to genomic instability and could be a driving force for secondary mutations in patients undergoing radiation therapy

RS rearrangement frequency as a marker of receptor editing in lupus and type 1 diabetes

Continued antibody gene rearrangement, termed receptor editing, is an important mechanism of central B cell tolerance that may be defective in some autoimmune individuals. We describe a quantitative assay for recombining sequence (RS) rearrangement that we use to estimate levels of antibody light chain receptor editing in various B cell populations. RS rearrangement is a recombination of a noncoding gene segment in the κ antibody light chain locus. RS rearrangement levels are highest in the most highly edited B cells, and are inappropriately low in autoimmune mouse models of systemic lupus erythematosus (SLE) and type 1 diabetes (T1D), including those without overt disease. Low RS rearrangement levels are also observed in human subjects with SLE or T1D

ImmuneDB, a Novel Tool for the Analysis, Storage, and Dissemination of Immune Repertoire Sequencing Data

ImmuneDB is a system for storing and analyzing high-throughput immune receptor sequencing data. Unlike most existing tools, which utilize flat-files, ImmuneDB stores data in a well-structured MySQL database, enabling efficient data queries. It can take raw sequencing data as input and annotate receptor gene usage, infer clonotypes, aggregate results, and run common downstream analyses such as calculating selection pressure and constructing clonal lineages. Alternatively, pre-annotated data can be imported and analyzed data can be exported in a variety of common Adaptive Immune Receptor Repertoire (AIRR) file formats. To validate ImmuneDB, we compare its results to those of another pipeline, MiXCR. We show that the biological conclusions drawn would be similar with either tool, while ImmuneDB provides the additional benefits of integrating other common tools and storing data in a database. ImmuneDB is freely available on GitHub at https://github.com/arosenfeld/immunedb, on PyPi at https://pypi.org/project/ImmuneDB, and a Docker container is provided at https://hub.docker.com/r/arosenfeld/immunedb. Full documentation is available at http://immunedb.com

AIRR Community Guide to Planning and Performing AIRR-Seq Experiments

The development of high-throughput sequencing of adaptive immune receptor repertoires (AIRR-seq of IG and TR rearrangements) has provided a new frontier for in-depth analysis of the immune system. The last decade has witnessed an explosion in protocols, experimental methodologies, and computational tools. In this chapter, we discuss the major considerations in planning a successful AIRR-seq experiment together with basic strategies for controlling and evaluating the outcome of the experiment. Members of the AIRR Community have authored several chapters in this edition, which cover step-by-step instructions to successfully conduct, analyze, and share an AIRR-seq project

Circulating B cells in type 1 diabetics exhibit fewer maturation-associated phenotypes

Although autoantibodies have been used for decades as diagnostic and prognostic markers in type 1 diabetes (T1D), further analysis of developmental abnormalities in B cells could reveal tolerance checkpoint defects that could improve individualized therapy. To evaluate B cell developmental progression in T1D, immunophenotyping was used to classify circulating B cells into transitional, mature naïve, mature activated, and resting memory subsets. Then each subset was analyzed for the expression of additional maturation-associated markers. While the frequencies of B cell subsets did not differ significantly between patients and controls, some T1D subjects exhibited reduced proportions of B cells that expressed transmembrane activator and CAML interactor (TACI) and Fas receptor (FasR). Furthermore, some T1D subjects had B cell subsets with lower frequencies of class switching. These results suggest circulating B cells exhibit variable maturation phenotypes in T1D. These phenotypic variations may correlate with differences in B cell selection in individual T1D patients

Computational Evaluation of B-Cell Clone Sizes in Bulk Populations

B cell clones expand and contract during adaptive immune responses and can persist or grow uncontrollably in lymphoproliferative disorders. One way to monitor and track B cell clones is to perform large-scale sampling of bulk cell populations, amplifying, and sequencing antibody gene rearrangements by next-generation sequencing (NGS). Here, we describe a series of computational approaches for estimating B cell clone size in NGS immune repertoire profiling data of antibody heavy chain gene rearrangements. We define three different measures of B cell clone size—copy numbers, instances, and unique sequences—and show how these measures can be used to rank clones, analyze their diversity, and study their distribution within and between individuals. We provide a detailed, step-by-step procedure for performing these analyses using two different data sets of spleen samples from human organ donors. In the first data set, 19 independently generated biological replicates from a single individual are analyzed for B cell clone size, diversity and sampling sufficiency for clonal overlap analysis. In the second data set, B cell clones are compared in eight different organ donors. We comment upon frequently encountered pitfalls and offer practical advice with alternative approaches. Overall, we provide a series of pragmatic analytical approaches and show how different clone size measures can be used to study the clonal landscape in bulk B cell immune repertoire profiling data

Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling

Use of adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread, providing new insights into the immune system with potential broad clinical and diagnostic applications. However, like many high-throughput technologies, it comes with several problems, and the AIRR Community was established to understand and help solve them. We, the AIRR Community's Biological Resources Working Group, have surveyed scientists about the need for standards and controls in generating and annotating AIRR-seq data. Here, we review the current status of AIRR-seq, provide the results of our survey, and based on them, offer recommendations for developing AIRR-seq standards and controls, including future work. Keywords: B-cell Receptor (BCR); IG; T-cell Receptor (TCR); TR; antibody; immunoglobulin; immunology; inflammation; next generation sequencing (NGS)