Trends in Immunology
Volume 38, Issue 7, July 2017, Pages 471-482
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Review
Novel Approaches to Analyze Immunoglobulin Repertoires

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Trends

Advances in next-generation sequencing have ushered in a new era of immunoglobulin (Ig) repertoire analysis.

Platforms for large-scale single-cell sequencing allow us to obtain both Ig chains of a cell in the correct association and thus enable cloning and recombinant expression of the respective antibody.

Computational tools now allow the reconstitution of antibody lineages and the analysis of somatic hypermutation. However, the prediction of antigen binding directly from an antibody sequence remains elusive.

Data sharing and reporting standards are currently elaborated by the Adaptive Immune Receptor Repertoire Community to facilitate data exchange and secondary analysis by third parties.

Analysis of immunoglobulin (Ig) repertoires aims to comprehend Ig diversity with the goal of predicting humoral immune responses in the context of infection, vaccination, autoimmunity, and malignancies. The first next-generation sequencing (NGS) analyses of bulk B cell populations dramatically advanced sampling depth over previous low-throughput single-cell-based protocols, albeit at the expense of accuracy and loss of chain-pairing information. In recent years the field has substantially differentiated, with bulk analyses becoming more accurate while single-cell approaches have gained in throughput. Additionally, new platforms striving to combine high throughput and chain pairing have been developed as well as various computational tools for analysis. Here we review the developments of the past 4–5 years and discuss the open challenges.

Section snippets

Diversity in the Ig Repertoire

Since the seminal discovery of genetic rearrangement as the primary mechanism of Ig variability [1], immunologists have used sequence analysis to measure and interpret the vast diversity of the Ig repertoire [2]. Iterative studies aiming to estimate the number of gene segments available (see Glossary) to the recombination process 3, 4 were successfully concluded with the availability of multiple high-resolution mammalian genomes, setting the numbers used today (Table 1). Based on these variable

Conventional Bulk Sequencing

Bulk sequencing of B cell populations by NGS was first reported in 2009 [8]. The main considerations in this experimental approach center on the choice of tissue and cell population, the number of cells, and the type of nucleic acid to be used as the template (Table 2). Most workflows use cell subsets defined by flow cytometry as the starting material; however, as Ig rearrangement is restricted to B cells and only the rearranged locus can be amplified by PCR (Figure 1), a wide range of sample

Addressing the Amplification Bias

As discussed above, one central shortcoming of conventional bulk sequencing has been its inability to reliably infer the initial amount of template nucleic acid in a sample from the number of sequence reads observed for a given rearrangement. As quantification is a central aim in many repertoire analyses, various approaches have been developed to address this issue. It should, however, be noted that the problem of non-uniform Ig expression is not mitigated by any of them.

Unique Molecular Identifiers (UMIs)

UMIs are inserted

Insights

The use of Ig repertoire analysis has become especially widespread in human immunology. Here, vertical study designs face various technical and legal restrictions that limit the use of exogenous labels to track cells. In addition, they are often limited to peripheral blood as the sample material. Repertoire analysis offers a unique opportunity for cellular tracking by using Ig sequences as molecular barcodes. It can thus provide unprecedented insight by assessing not only the size and phenotype

The Unknowns of Individual Germline Diversity

The prevalent approach to the identification of unmutated V, D, and J segments is the alignment of the query sequence against a reference germline database (GLDB). Thus, the quality of the utilized GLDB is critical to data evaluation, including downstream analysis steps like clustering that depend on the identified gene segments. For an individual species, the ideal GLDB should be both complete and accurate; that is, contain all existing segments and only existing segments. Building such a GLDB

Concluding Remarks

Given the large diagnostic potential of repertoire studies, future technical development is expected to be significantly influenced by the type of additional information that can be used to leverage the plain sequencing data (e.g., cell type classification). Here microfluidic devices will gain prominence if they succeed in providing sampling depth comparable with the current methods. Single-cell approaches are likely to capitalize on their ability to provide high-dimensional, in-depth

Glossary

Antibody-secreting cell (ASC)
a functional classification for plasma cells and plasmablasts independent of their differentiation status.
B cell receptor (BCR)
the protein complex on the surface of B cells comprising a membrane-bound Ig and various signal transduction components like Igα and Igβ. Note that the exact stoichiometry of the components can vary depending on the Ig isotype.
Birthday effect
the fact that possible overlaps within a set of sequences scales with the square of the sequence

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