Simple paired heavy- and light-chain antibody repertoire sequencing using endoplasmic reticulum microsomes

The dengue-specific immune response and antibody identification with machine learning

Dengue virus poses a serious threat to global health and there is no specific therapeutic for it. Broadly neutralizing antibodies recognizing all serotypes may be an effective treatment. High-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) and bioinformatic analysis enable in-depth understanding of the B-cell immune response. Here, we investigate the dengue antibody response with these technologies and apply machine learning to identify rare and underrepresented broadly neutralizing antibody sequences. Dengue immunization elicited the following signatures on the antibody repertoire: (i) an increase of CDR3 and germline gene diversity; (ii) a change in the antibody repertoire architecture by eliciting power-law network distributions and CDR3 enrichment in polar amino acids; (iii) an increase in the expression of JNK/Fos transcription factors and ribosomal proteins. Furthermore, we demonstrate the applicability of computational methods and machine learning to AIRR-seq datasets for neutralizing antibody candidate sequence identification. Antibody expression and functional assays have validated the obtained results.

The clinical applications of immunosequencing

Technological advances in high-throughput sequencing have opened the door for the interrogation of adaptive immune responses at unprecedented scale. It is now possible to determine the sequences of antibodies or T-cell receptors produced by individual B and T cells in a sample. This capability, termed immunosequencing, has transformed the study of both infectious and non-infectious diseases by allowing the tracking of dynamic changes in B and T cell clonal populations over time. This has improved our understanding of the pathology of cancers, autoimmune diseases, and infectious diseases. However, to date there has been only limited clinical adoption of the technology. Advances over the last decade and on the horizon that reduce costs and improve interpretability could enable widespread clinical use. Many clinical applications have been proposed and, while most are still undergoing research and development, some methods relying on immunosequencing data have been implemented, the most widespread of which is the detection of measurable residual disease. Here, we review the diagnostic, prognostic, and therapeutic applications of immunosequencing for both infectious and non-infectious diseases.

Accurate profiling of full-length Fv in highly homologous antibody libraries using UMI tagged short reads

Deep parallel sequencing (NGS) is a viable tool for monitoring scFv and Fab library dynamics in many antibody engineering high-throughput screening efforts. Although very useful, the commonly used Illumina NGS platform cannot handle the entire sequence of scFv or Fab in a single read, usually focusing on specific CDRs or resorting to sequencing VH and VL variable domains separately, thus limiting its utility in comprehensive monitoring of selection dynamics. Here we present a simple and robust method for deep sequencing repertoires of full length scFv, Fab and Fv antibody sequences. This process utilizes standard molecular procedures and unique molecular identifiers (UMI) to pair separately sequenced VH and VL. We show that UMI assisted VH-VL matching allows for a comprehensive and highly accurate mapping of full length Fv clonal dynamics in large highly homologous antibody libraries, as well as identification of rare variants. In addition to its utility in synthetic antibody discovery processes, our method can be instrumental in generating large datasets for machine learning (ML) applications, which in the field of antibody engineering has been hampered by conspicuous paucity of large scale full length Fv data.

Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences

The antibody repertoires of individuals and groups have been used to explore disease states, understand vaccine responses, and drive therapeutic development. The arrival of B‐cell receptor repertoire sequencing has enabled researchers to get a snapshot of these antibody repertoires, and as more data are generated, increasingly in‐depth studies are possible. However, most publicly available data only exist as raw FASTQ files, making the data hard to access, process, and compare. The Observed Antibody Space (OAS) database was created in 2018 to offer clean, annotated, and translated repertoire data. In this paper, we describe an update to OAS that has been driven by the increasing volume of data and the appearance of paired (VH/VL) sequence data. OAS is now accessible via a new web server, with standardized search parameters and a new sequence‐based search option. The new database provides both nucleotides and amino acids for every sequence, with additional sequence annotations to make the data Minimal Information about Adaptive Immune Receptor Repertoire compliant, and comments on potential problems with the sequence. OAS now contains 25 new studies, including severe acute respiratory syndrome coronavirus 2 data and paired sequencing data. The new database is accessible at http://opig.stats.ox.ac.uk/webapps/oas/, and all data are freely available for download.

Beyond bulk single-chain sequencing: Getting at the whole receptor

Recent advancements in paired B-cell receptor sequencing technologies have accelerated the development of simpler, high-throughput pipelines for generating native antibody heavy and light chain pairs used to elucidate novel antibodies and provide insights into antibody response against pathogenic targets. These technologies involve single-cell isolation, using either single wells or emulsified droplets to maintain physical separation of individual cells, followed by sequencing. The development of novel single wells and emulsion-based workflows addresses key challenges by improving throughput of single-cell analyses, reducing method complexity, and integrating functional assays into existing workflows. Enabled by paired B-cell receptor sequencing, functional characterization of pathogen-specific antibodies reveals immunological insights beyond bulk sequencing.

A facile technology for the high-throughput sequencing of the paired VH:VL and TCRβ:TCRα repertoires

Natively paired sequencing (NPS) of B cell receptors [variable heavy (VH) and light (VL)] and T cell receptors (TCRb and TCRa) is essential for the understanding of adaptive immunity in health and disease. Despite many recent technical advances, determining the VH:VL or TCRb:a repertoire with high accuracy and throughput remains challenging. We discovered that the recently engineered xenopolymerase, RTX, is exceptionally resistant to cell lysate inhibition in single-cell emulsion droplets. We capitalized on the characteristics of this enzyme to develop a simple, rapid, and inexpensive in-droplet overlap extension reverse transcription polymerase chain reaction method for NPS not requiring microfluidics or other specialized equipment. Using this technique, we obtained high yields (5000 to >20,000 per sample) of paired VH:VL or TCRb:a clonotypes at low cost. As a demonstration, we performed NPS on peripheral blood plasmablasts and T follicular helper cells following seasonal influenza vaccination and discovered high-affinity influenza-specific antibodies and TCRb:a.

Antibody-based nanotechnology

Antibodies are considered the hallmark of the adaptive immune system in that they mediate various key biological functions, such as direct neutralization and recruitment of effector immune cells to eliminate invading pathogens. Antibodies exhibit several unique properties, including high diversity (enabling binding to a wide range of targets), high specificity and structural integrity. These properties and the understanding that antibodies can be utilized in a wide range of applications have motivated the scientific community to develop new approaches for antibody repertoire analysis and rapid monoclonal antibody discovery. Today, antibodies are key modules in the pharmaceutical and diagnostic industries. By virtue of their high affinity and specificity to their targets and the availability of technologies to engineer different antibodies to a wide range of targets, antibodies have become the most promising natural biological molecules in a range of biotechnological applications, such as: highly specific and sensitive nanobiosensors for the diagnostics of different biomarkers; nanoparticle-based targeted drug delivery systems to certain cells or tissues; and nanomachines, which are nanoscale mechanical devices that enable energy conversion into precise mechanical motions in response to specific molecular inputs. In this review, we start by describing the unique properties of antibodies, how antibody diversity is generated, and the available technologies for antibody repertoire analysis and antibody discovery. Thereafter, we provide an overview of some antibody-based nanotechnologies and discuss novel and promising approaches for the application of antibodies in the nanotechnology field. Overall, we aim to bridge the knowledge gap between the nanotechnology and antibody engineering disciplines by demonstrating how technological advances in the antibody field can be leveraged to develop and/or enhance new technological approaches in the nanotechnology field.