Cloning antibodies from single cells in pooled sequence libraries by selective PCR

Single-Cell B-Cell Sequencing to Generate Natively Paired scFab Yeast Surface Display Libraries

The immune cell profiling capabilities of single-cell RNA sequencing (scRNA-seq) are powerful tools that can be applied to the design of theranostic monoclonal antibodies (mAbs). Using scRNA-seq to determine natively paired B-cell receptor (BCR) sequences of immunized mice as a starting point for design, this method outlines a simplified workflow to express single-chain antibody fragments (scFabs) on the surface of yeast for high-throughput characterization and further refinement with directed evolution experiments. While not extensively detailed in this chapter, this method easily accommodates the implementation of a growing body of in silico tools that improve affinity and stability among a range of other developability criteria (e.g., solubility and immunogenicity).

Heavy chain sequence-based classifier for the specificity of human antibodies

Antibodies specifically bind to antigens and are an essential part of the immune system. Hence, antibodies are powerful tools in research and diagnostics. High-throughput sequencing technologies have promoted comprehensive profiling of the immune repertoire, which has resulted in large amounts of antibody sequences that remain to be further analyzed. In this study, antibodies were downloaded from IMGT/LIGM-DB and Sequence Read Archive databases. Contributing features from antibody heavy chains were formulated as numerical inputs and fed into an ensemble machine learning classifier to classify the antigen specificity of six classes of antibodies, namely anti-HIV-1, anti-influenza virus, anti-pneumococcal polysaccharide, anti-citrullinated protein, anti-tetanus toxoid and anti-hepatitis B virus. The classifier was validated using cross-validation and a testing dataset. The ensemble classifier achieved a macro-average area under the receiver operating characteristic curve (AUC) of 0.9246 from the 10-fold cross-validation, and 0.9264 for the testing dataset. Among the contributing features, the contribution of the complementarity-determining regions was 53.1% and that of framework regions was 46.9%, and the amino acid mutation rates occupied the first and second ranks among the top five contributing features. The classifier and insights provided in this study could promote the mechanistic study, isolation and utilization of potential therapeutic antibodies.

Transforming nanobodies into high-precision tools for protein function analysis

Single-domain antibodies, derived from camelid heavy antibodies (nanobodies) or shark variable new antigen receptors, have attracted increasing attention in recent years due to their extremely versatile nature and the opportunities they offer for downstream modification. Discovered more than three decades ago, these 120-amino acid (∼15-kDa) antibody fragments are known to bind their target with high specificity and affinity. Key features of nanobodies that make them very attractive include their single-domain nature, small size, and affordable high-level expression in prokaryotes, and their cDNAs are routinely obtained in the process of their isolation. This facilitates and stimulates new experimental approaches. Hence, it allows researchers to formulate new answers to complex biomedical questions. Through elementary PCR-based technologies and chemical modification strategies, their primary structure can be altered almost at leisure while retaining their specificity and biological activity, transforming them into highly tailored tools that meet the increasing demands of current-day biomedical research. In this review, various aspects of camelid nanobodies are expounded, including intracellular delivery in recombinant format for manipulation of, i.e., cytoplasmic targets, their derivatization to improve nanobody orientation as a capturing device, approaches to reversibly bind their target, their potential as protein-silencing devices in cells, the development of strategies to transfer nanobodies through the blood-brain barrier and their application in CAR-T experimentation. We also discuss some of their disadvantages and conclude with future prospects.