Facilitating application of NGS to analysis of livestock T-cell receptor repertoires

The livestock sectors of many LMIC are negatively impacted by pathogens for which no viable vaccines are currently available. T-cells are known to contribute to protection against a number of these pathogens (e.g. tuberculosis, East Coast Fever) and current efforts are directed to better understanding the role these cells plays in conferring immunity and defining the 'correlates of protection' that can be used to rationalise future vaccine development.

One parameter that has been advocated for inclusion in comprehensive analysis of T-cell responses is the repertoire of the expressed TCR, which can be exploited to study the clonotypic structure, kinetics and recall of pathogen-specific T-cells. TCRs are heterodimeric, clonotypically distributed receptors composed of alpha (TRA) and beta (TRB) chains that determine the antigenic-specificity of individual T-cells. Somatic V(D)J recombination and non-germline editing of the V(D)J junction generates a vastly diverse TCR repertoire, that in humans has been estimated to be ~2x10'7. Upon encountering their cognate antigen, either during vaccination or pathogen exposure, T-cells undergo clonotypic expansion which can be evaluated by the increased expression of the clonotypic TRA and/or TRB chains. However, achieving sufficient sequencing depth of the TCR repertoire to reliably detect such clonal expansions in highly complex T-cell populations (e.g. in vivo PBMC or primary T-cell cultures) was difficult before development of NGS platforms.

In the last decade, development of a number of bioinformatic pipelines (e.g. MiTCR and IMGT-HighV-Quest) has enabled TCR analysis using NGS data to be applied to the study of human and murine T-cell populations. The pre-requisites for these analyses are i) TCR chain-specific PCR protocols that generate unbiased TCR chain amplicons, ii) a comprehensive database of V and J gene segment sequences and iii) sophisticated algorithms that can align TCR sequences to the relevant V and J gene segment databases (and so define V and J usage and the hypervariable CDR3 sequence of individual TCR chains) and also compensate and correct for the inevitable PCR/sequencing errors that can significantly compromise sequence data interpretation. The principles used in bioinformatic pipelines developed for human and murine TCR analysis are generic and in recent studies we have demonstrated that given the appropriate V and J gene databases the pipelines can be modified and applied to NGS sequence data from other species (in this case European Bos taurus cattle). In this project we propose to:

1 - Design PCR protocols to enable unbiased PCR amplification of TRA and TRB chains from the relevant livestock populations. Optimised SMART-based PCR amplification protocols for pig, goat, sheep and water buffalo TRA and TRB chains will be validated.
2 - Sequence sufficient full length TRA/TRB amplicons to enable comprehensive coverage of the expressed TRA and TRB repertoires. Amplicons generated from 5 representative individuals from different LMIC and European breeds will be subjected to PacBio sequencing to obtain full length amplicon sequence.
3 - Bio-informatically de-construct somatically recombined TRA and TRB chains to construct database of germline V and J gene segments sequences. Pipelines to de-construct recombined TRA/TRB chains will be developed to enable germline sequences of the constituent V and J gene segments to be established and a comprehensive database populated.
4 - Modify existing algorithms to enable these databases to be employed in NGS analysis of TCR repertoires (and provide TRBV, TRBJ, TRAV and TRAJ databases to managers of publicly accessible TCR analysis algorithms). A modified version of the MiTCR algorithm which will enable the utilisation of the livestock species databases will be established and hosted by the CTLGH bioinformatics repository. In addition, the databases will be hosted by the publicly available Milaboratory website.

Development of vaccines capable of eliciting protective T-cell responses is required for a number of livestock diseases prevalent in LMIC. By providing high resolution details on the clonotypic composition of T-cell responses, NGS analysis of TCR repertoires can contribute to the identification of 'correlates of protection' that will accelerate efforts to develop such vaccines. Integration of such data into livestock vaccine research is impeded by the absence of the necessary bioinformatic resources. We have recently demonstrated that bioinformatic workflows for NGS TCR analysis can be transferred to TRB repertoire analysis of Bos taurus cattle. We propose here to develop the protocols, databases and bioinformatic infra-structure required for NGS TCR repertoire analysis to be applied to breeds of sheep, pig, cattle, goat and water buffalo that are economical important in LMIC. To do this it is necessary to i) optimise unbiased SMART-PCR amplification of TRA/TRB chains in relevant species, ii) generate comprehensive databases of V and J gene sequences and iii) manage integration of these databases into the sophisticated TCR analysis algorithms that have been developed for humans. We plan to optimise and then apply the SMART-PCR protocol to generate TRA/TRB amplicons from representatives of LMIC breeds of livestock and use PacBio to obtain near-full length TRA/TRB chain sequences of these amplicons. These sequence will be 'de-constructed' into the germline V and J gene (and non-germline CDR3) components and this data used to generate the V/J sequence databases. These databases will be incorporated into TCR algorithms publicly available through the Milaboratory website (https://milaboratory.com) and the MiTCR algorithm will be modified to facilitate livestock species TCR analysis. Together the outputs of this study will provide both the methodologies and databases required to implement TCR repertoire analysis in livestock species critical to LMIC countries.

This study will provide a novel tool and the required bioinformatic framework to analyse TCR repertoires of T-cell responses that can be used to inform on the clonality, diversity and other critical parameters of T-cell responses that can be used to better understand T-cell mediated immunity induced by candidate vaccines and so accelerate vaccine development. By doing so the study has the potential to have a major impact on;

Livestock producers in LMIC: In developing countries the livestock sector accounts for upto 80% of agricultural GDP and in many LMIC countries a majority of the rural poor raise livestock. With increasing demand in LMIC countries for animal-derived food, increasing local animal production offers an obvious pathway for poverty reduction. To exploit this opportunity it is necessary that policies that ensure farmers in LMIC have the facilities to increase production, including the means of reducing losses through disease burden, are implemented. Infectious diseases continue to be a major constraint on the economic performance of the livestock sector in many LMIC. For small holder farmers outbreaks of diseases such as ECF, FMD, CBPP (Contagious Bovine Pleuropnuemonia) and ASF (African Swine Fever) can be devastating. Rational development of novel vaccines against these diseases requires a comprehensive knowledge of the role of different components of the immune responses against these pathogens.

Livestock producers in non-LMIC: Integration of TCR analysis into candidate vaccine evaluation programmes could also accelerate vaccine development programmes for diseases that have significance for livestock-producers in non-LMIC. Some of the diseases for which improved vaccines are most urgently required (e.g. TB and FMD) are of relevance to both LMIC and non-LMIC.

Global food security: The livestock sector is a key provider of global food security. The continuing increase in the demand for animal-derived foodstuffs, whilst providing an economic opportunity for farmers in LMIC countries (see above), also increases competition, and so compounds concerns over global food security.