The human adaptive immune system consists of B-cells and T-cells to help recognize and respond to a near infinite number of different endogenous and environmental challenges. The sum of all T cell and B cell receptors of one individual is termed immune repertoire.

The main challenge while studying the immune repertoire, or immune profiling, is the enormous diversity of TCRs and BCRs.

Diversification of Immune Repertoire

Both T cells and B cells go through a process called V(D)J recombination, the underlying genetic principle by which diversity is generated and for which Susumu Tonegawa was awarded the Nobel Prize. During V(D)J recombination, one random allele from each of the V(D)J gene groups are randomly recombined to form a functional variable region for antigen recognition. Additionally, random nucleotides are added at the junction sites between the gene segments. In this way, a fixed set of gene segments are able to generate an enormous repertoire of antigen receptor sequences, estimated to be between 10 7 to 10 9 unique TCRs and BCRs. While T cells only go through VDJ recombination, the B cells’ gene sequences can change themselves by introducing random mutations in the V-regions when the B cell expressing a particular antibody is stimulated by a matching antigen. This mutational process happens at a higher rate compared to somatic mutation, thus was coined the term "somatic hypermutation".

Applications of Immune Repertoire Analysis

The human adaptive immune system has a s trong impact on human health. Compared to normal individuals, patients with different diseases, such as cancer, autoimmune, inflammatory and infectious diseases, may have their immune repertoire changed greatly with the onset and progression of these diseases. Traditional methods of the isolation and identification of antibodies require multiple large blood samples during a highly complicated process.

Efficient and effective analysis of immune repertoire diversity and clonal expansion can greatly accelerate translational research. The ultimate goal is to leverage an individual’s own immune system by optimizing the manufacture and engineer of beneficial T cells and B cells. New approaches based on investigating the immune repertoire of these patients can be developed to improve and provide better diagnosis and treatment, and advance precision oncology.

Discover immune response biomarkers

Study mechanisms of immune system developments

Identify immunodeficiency and autoimmune events

Optimize and engineer therapeutic T cells

NGS and Cloud Computing

Next Generation gene-Sequencing (NGS) methods have recently become invaluable in studying the immune repertoire. Deep immune system profiling using high-throughput sequencing is a powerful approach for unraveling the in-depth composition of CDR3s in a given sample at the sequence level. But as high throughput sequencing technologies continue to improve, these repertoire sequencing experiments are producing ever larger datasets, with tens of repertoires and millions of clonotypes to compare, group, and evaluate. Specifically, the immense heterogeneity of the immune repertoire poses significant computational challenges.

Our NGS solution has been optimized to run in parallel on the latest cloud computing architecture. Also, we take data ownership very seriously — you have full control of your data from raw sequencing data to clustering annotation in a fully transparent analysis pipeline. We offer exceptionally sensitive and accurate immune repertoire sequencing analysis with turnaround time surpassing conventional methods by several orders of magnitude.

The majority of observable TCRs and BCRs are rare. If the starting material is of low quantities, it can be a limiting factor. However, our library kits and bioinformatics tools can accommodate different sample constraints, sequencing depth, and application preferences to characterize immune profile from a single sample of blood or tissue.

Independent of the library preparation method, there will always be PCR amplification and sequencing errors. Immune repertoire sequencing is particularly vulnerable to these errors, since low frequency clonotypes may differ from one another by only a single nucleotide. Different techniques have been developed to overcome the experimental errors as well as the threat of batch effects. We use unique molecular identifiers (UMIs) and sophisticated error detection and correction algorithms to evaluate the quality of the sequencing run and remove PRC driven bias.

Since immune repertoire data is sparse and long tailed, curating and narrowing dimensions can help increase information density. In addition to basic repertoire statistics, we designed and developed exploratory and explanatory web visualization tools for repertoire comparison, clustering, and somatic hypermutation analysis. By combining comprehensive tabular output with automatic report generation, we offer full turnkey solutions for basic medical science as well as advanced immunotherapy research.