Literature DB >> 33096477

An innovative and affordable quantitative assessment of human TCR repertoire.

Roberta Amoriello1, Clara Ballerini2.   

Abstract

Entities:  

Year:  2020        PMID: 33096477      PMCID: PMC7578669          DOI: 10.1016/j.ebiom.2020.103021

Source DB:  PubMed          Journal:  EBioMedicine        ISSN: 2352-3964            Impact factor:   8.143


× No keyword cloud information.
Current techniques available to describe the individual T cell receptor (TCR) repertoire are highly expensive and necessitate specific computational analysis tools in order to describe the repertoires qualitatively and quantitatively and to correct sequencing errors. Montagne et al. [1] in their work propose a new approach to TCR repertoire sequencing investigation. The diversity of the TCR repertoire is the result of multiple processes of DNA stochastic somatic recombination and it is responsible for effective immunity against pathogens. A TCR molecule is a heterodimer composed of alpha and beta chains and in humans of a minor population of delta and gamma chains. These chains are very diverse, because of the imprecise rearrangements of either V and J segments (alpha chain) or V, D and J segments (beta chain), that determine the non-template addition or removal of DNA base pairs, resulting in a huge variety of complementary determining regions (CDR3) and in an extraordinary genomic diversity, similar only to the ones we find in the antibodies [2]. For many years it was a challenge to investigate this hypervariable molecule and a complete description of the TCR repertoire has never been achieved. Recent advances in high-throughput sequencing (HTS) techniques paved the way to explore the TCR repertoire dynamics bridging cell-based methods and computational ones into qualitative and quantitative receptor description [3] and antigen discovery [4]. Of note, HTS is not as accurate as Sanger sequencing and introduces errors during library amplification and/or during sequencing [5], therefore, several expensive strategies and different algorithms have been developed to attenuate the impact of errors on the TCR repertoire analysis and on the consequent biological data interpretation [6,7]. In their work, Montagne et al. developed an original experimental pipeline to sequence TCR and analyze CDR3 repertoire, dropping the cost (from a mean of $500–$1000 to $20 per sample) for primers and for unique molecular identifiers (UMIs) to correct amplification bias. The proposed Framework Region 3 AmplifiKation sequencing (FR3AK-seq), is a simplified multiplex PCR-based involving a minimal primer set targeting the upstream sequence of the complementarity determining region 3 (CDR3), the framework region 3 (FR3). Authors use the TCRB FR3 regions, collected from the Immunogenetics reference directory (IMGT/GENE-DB) [8] for primers design. They individuate 47 distinct 3′-sequences of 20 nucleotides (20-mers) that represent the 128 functional TCRBV alleles in IMGT; using these sequences as target allows scientists to significantly minimize CDR3 amplicon length. Therefore, from the selected 47 TCRB FR3 3′ 20-mers, Montagne et al. obtained three sets of primers: 1MM set (34 primers), Compact set (20 primers) and Full set (47 primers) required to multiply CDR3 region of TCR beta chains. The combinations of this experimental pipeline with an algorithm that they have personally developed, Inferring Sequences via Efficiency Projection and Primer Incorporation (ISEPPI), permitted the determination of linkage between CDR3 and corresponding V fragment of the TCR beta chain, as further verification of FR3AK-seq performance. The accuracy of ISEPPI was found to be maximal for the Full primer set, ranging between 67.7 and 72.4% depending on CDR3s clone counts (≥10 - ≥100). To verify the reliability of FR3AK-seq technology, the authors compared their method to two sensitive and quantitative existing commercial methods specialized in TCR sequencing from adaptive Biotechnologies and ArcherDX's and subsequently found no differences in the performance of FR3AK-seq in terms of CDR3 quantification and amplification bias. In order to apply this methodology to a pathology, Montagne et al. analyzed TCR repertoire on a large cohort of patients with idiopathic inflammatory myopathies (IIMs), an inflammatory heterogeneous disease in which the pathogenic role of T cells is still unknown [9], and compared them with healthy donors. TCR repertoire was successfully described in peripheral blood lymphocytes and in muscle infiltrating cells, demonstrating that a cluster of closely related TCRs is present in muscle from patients with sporadic inclusion myositis (IBM). To summarize, the strategy of targeting the 3′ terminus of FR3 successfully allow us to minimize the number of primers and amplicon length, while preserving sequencing depth and providing a reliable capture of TCR repertoire clonal abundance, comparable to the currently available industrial sequencing platforms. We believe that Montagne et al. [1] proposed FR3AK-seq technology may pave the way to an affordable and reliable TCR sequencing, broadening our knowledge of the TCR repertoire in disease pathogenesis and immune modulating treatments.

Declaration of Competing Interest

The authors declare no conflicts of interest.
  8 in total

1.  Performance comparison of benchtop high-throughput sequencing platforms.

Authors:  Nicholas J Loman; Raju V Misra; Timothy J Dallman; Chrystala Constantinidou; Saheer E Gharbia; John Wain; Mark J Pallen
Journal:  Nat Biotechnol       Date:  2012-05       Impact factor: 54.908

Review 2.  Bioinformatic and Statistical Analysis of Adaptive Immune Repertoires.

Authors:  Victor Greiff; Enkelejda Miho; Ulrike Menzel; Sai T Reddy
Journal:  Trends Immunol       Date:  2015-10-25       Impact factor: 16.687

Review 3.  T-cell antigen receptor genes and T-cell recognition.

Authors:  M M Davis; P J Bjorkman
Journal:  Nature       Date:  1988-08-04       Impact factor: 49.962

4.  An Economical, Quantitative, and Robust Protocol for High-Throughput T Cell Receptor Sequencing from Tumor or Blood.

Authors:  Imran Uddin; Kroopa Joshi; Theres Oakes; James M Heather; Charles Swanton; Benny Chain
Journal:  Methods Mol Biol       Date:  2019

Review 5.  Risk factors and disease mechanisms in myositis.

Authors:  Frederick W Miller; Janine A Lamb; Jens Schmidt; Kanneboyina Nagaraju
Journal:  Nat Rev Rheumatol       Date:  2018-04-20       Impact factor: 20.543

6.  IMGT/GENE-DB: a comprehensive database for human and mouse immunoglobulin and T cell receptor genes.

Authors:  Véronique Giudicelli; Denys Chaume; Marie-Paule Lefranc
Journal:  Nucleic Acids Res       Date:  2005-01-01       Impact factor: 16.971

7.  immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking.

Authors:  Cédric R Weber; Rahmad Akbar; Alexander Yermanos; Milena Pavlović; Igor Snapkov; Geir K Sandve; Sai T Reddy; Victor Greiff
Journal:  Bioinformatics       Date:  2020-06-01       Impact factor: 6.937

8.  Ultra-efficient sequencing of T Cell receptor repertoires reveals shared responses in muscle from patients with Myositis.

Authors:  Janelle M Montagne; Xuwen Alice Zheng; Iago Pinal-Fernandez; Jose C Milisenda; Lisa Christopher-Stine; Thomas E Lloyd; Andrew L Mammen; H Benjamin Larman
Journal:  EBioMedicine       Date:  2020-09-03       Impact factor: 8.143

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.