Idiosyncratic T-cell receptor repertoire perturbation and loss of diversity in HIV+ individuals revealed by deep-sequencing

We have developed a protocol that combines unbiased amplification, high-throughput DNA sequencing and error-correcting bioinformatic protocols to extract T-cell receptor (TCR) repertoire data from small, easily collected samples of unfractionated blood. We have applied this protocol to study the effect of HIV infection (and subsequent treatment) upon TCR repertoires. <p>Whole blood samples were collected from 16 HIV+ patients immediately before, and shortly after commencing antiretroviral therapy (ART): repertoires were sequenced and compared to those of ten healthy controls.</p> <p>The TCR repertoires of HIV-infected individuals were highly perturbed, showing a considerable loss of diversity relative to controls primarily through accumulation of a small number of very highly-expanded sequences. </p> <p><a></a> TCR sequences in HIV patients' repertoires diverged in their TCR gene usage, both from uninfected donors and from one another. Sequences were also more likely to be retained in HIV+ individuals during ART than those in healthy donors over the same period, but were less likely to be shared between individuals, demonstrating comparatively highly individualistic TCR repertoires. Moreover the majority of dysregulated repertoire features failed to revert to healthy parameter ranges over the short course of therapy between samples, despite a significant increase in CD4+ T-cell levels.</p> <p>Repertoires were also searched for sequences belonging to published invariant or epitope-specific TCRs, revealing significantly fewer mucosally associated invariant T (MAIT) cell sequences in HIV patients relative to controls, and a loss of HIV-associated CDR3s during treatment.</p> <p>TCR repertoire sequencing of HIV infected individuals is therefore able to produce qualitative and quantitative data pertaining to a variety of perturbations to patient immune systems, which could inform treatment and potentially lead to development of biomarkers for patient stratification.</p