TCRs with Distinct Specificity Profiles Use Different Binding Modes to Engage an Identical Peptide-HLA Complex.

The molecular rules driving TCR cross-reactivity are poorly understood and, consequently, it is unclear the extent to which TCRs targeting the same Ag recognize the same off-target peptides. We determined TCR-peptide-HLA crystal structures and, using a single-chain peptide-HLA phage library, we generated peptide specificity profiles for three newly identified human TCRs specific for the cancer testis Ag NY-ESO-1157-165-HLA-A2. Two TCRs engaged the same central peptide feature, although were more permissive at peripheral peptide positions and, accordingly, possessed partially overlapping peptide specificity profiles. The third TCR engaged a flipped peptide conformation, leading to the recognition of off-target peptides sharing little similarity with the cognate peptide. These data show that TCRs specific for a cognate peptide recognize discrete peptide repertoires and reconciles how an individual's limited TCR repertoire following negative selection in the thymus is able to recognize a vastly larger antigenic pool.

Characterisation of retroviruses in the horse genome and their transcriptional activity via transcriptome sequencing.

The recently released draft horse genome is incompletely characterised in terms of its repetitive element profile. This paper presents characterisation of the endogenous retrovirus (ERVs) of the horse genome based on a data-mining strategy using murine leukaemia virus proteins as queries. 978 ERV gene sequences were identified. Sequences were identified from the gamma, epsilon and betaretrovirus genera. At least one full length gammaretroviral locus was identified, though the gammaretroviral sequences are very degenerate. Using these data the RNA expression of these ERVs were derived from RNA transcriptome data from a variety of equine tissues. Unlike the well studied human and murine ERVs there do not appear to be particular phylogenetic groups of equine ERVs that are more transcriptionally active. Using this novel approach provided a more technically feasible method to characterise ERV expression than previous studies.