Quantification of HTLV-1 Clonality and TCR Diversity

Daniel J. Laydon, Anat Melamed, Aaron Sim, Nicolas A. Gillet, Kathleen Sim, Sam Darko, J. Simon Kroll, Daniel C. Douek, David A. Price, Charles R. M. Bangham, Becca Asquith

Abstract: Author Summary The “unseen species problem” is ubiquitous in biology and is frequently encountered outside its original setting in population ecology. For example, the human retrovirus HTLV-1 persists within hosts in multiple, genetically identical clones of infected cells. However, the number of clones in one host is unknown; this knowledge is required for an understanding of how the virus survives despite a strong host immune response. The problem arises again in estimating the diversity of the T-cell repertoire, which influences adaptive immunity. For example, the T-cell diversity may influence the outcome of viral challenge. While there have been numerous attempts to address the unseen species problem, there is currently no consensus on how to do so in immunology and microbiology. The aim of this study was to identify a suitable method to estimate the number of species in immunological and microbiological populations. We found that five existing estimators we tested performed poorly across three data sources (HTLV-1 clonality, T cell receptor, and microbial data). We therefore developed a new estimator, DivE, which significantly outperformed the other estimators. Accurate diversity quantification allows better evaluation of the impact on immunity from factors such as ageing and infection.