The ability to map T cell epitopes efficiently is important to determine the breadth of the response to a natural infection or vaccine. Our optimized method for configuration of peptide pool matrices enables construction of a single matrix encompassing a set of overlapping peptides spanning a large antigen (several hundred peptides). Peptide matrices have been used to map T cell responses to CMV, a large DNA virus with 213 open reading frames (11
). The use of one large matrix reduces the amount of sample required to deconvolute the entire T cell response (9
). However, as the method is based on peptides, sequence variability between the antigen and the synthetic peptides in the matrix can hamper identification of peptide-specific responses. The sequence variability of HIV both within an individual and between individuals exemplifies this problem for mapping of HIV-specific T cell responses. It has been shown previously that the HIV-specific T cell response is underestimated when using consensus versus autologous sequences for peptide epitope mapping (15
). The experimental evaluation of this method in this study yielded several observations: 1) many HIV-derived peptide antigens from several different gene products were identified in three HIV+ individuals using a single matrix of 720 peptides; 2) sequence variability affected peptide identification; 3) the method was reproducible; and 4) setting a frequency threshold for responses is an essential and influential step in the deconvolution process.
The method was efficient and reproducible. Positive peptides were missed in several instances for several reasons. Low frequency peptide-specific T cell responses sometimes fell below the limit of detection. Such peptides either elicited a low frequency T cell response individually or when combined with other peptides in a given peptide pool. Indeed, we found a peptide (FRKQNPDMVIYQYMD, Pol329-343
) for which the frequency of responding T cells was much lower when stimulation was performed in the presence of other peptides than when this peptide was tested individually, suggesting peptide competition for binding to HLA can occur and reduce the ability to elicit a peptide-specific response. Despite these limitations, we believe this method holds advantages over other mapping strategies, such as using previously identified or bioinformatically predicted epitopes (6
) , which requires HLA identification and may not be comprehensive, and combinatorial peptide library approaches (18
), which require outgrowth of T cell clones, a process that can be highly selective and eliminate marginally-growing clonotypes.
Our initial optimization of matrix configuration assumed a qualitative assessment of positivity. However, analysis of the experimental results required translating a quantitative value into the qualitative determination of “positive” or “negative.” We accomplished this through use of a threshold, below which values were considered negative. Determining the threshold is a tradeoff between the number of second round tests and sensitivity. Lowering the threshold increases the number of peptides requiring testing in the second round. On the other hand, raising the threshold reduces the number of tests but can also eliminate identification of low frequency responses. Thus, the cost of higher sensitivity (and identification of more responses) is the use of a much greater amount of patient sample as well as labor and materials.
Not surprisingly, certain matrices identified responses in some individuals better than others, most likely reflecting the amount of sequence identity shared between the matrix and the HIV species of the donor. With each matrix, some peptides were missed; on average, a given matrix could identify only 57% of responses. Thus, for HIV, this would seem to suggest that epitope mapping should be performed using autologous sequences. While this would be the best approach to identify the complete breadth of the response, it is a very impractical approach. Whole genome sequencing and synthesis of such numbers of peptides are expensive and time-consuming; moreover, matrix construction is extremely labor-intensive. Each of our matrices in this study required >3,000 pipettings, excluding initial reconstitution of peptides and subsequent dilution of individual peptides to be retested in second round assays. Fortunately, mapping of HIV-specific T cell responses in vaccinated individuals, in whom the sequence is pre-determined, enables construction of one matrix that can be used for all vaccinees.
Taken together, the results from these experiments provide the basis for a number of recommendations for epitope deconvolution. (1) Matrices should be optimized for a higher number of epitopes than is predicted in sample material. The number of tests required to deconvolute a response increases exponentially with the number of positive peptides; thus, the cost of having an under-configured matrix is substantial. (2) The number of peptides that are positive is usually about 50% greater than the number of epitopes, due to overlap of epitopes across peptides. The optimization should thus be for the predicted number of peptides (not epitopes). (3) Sample permitting, the “n-1 rule” should be used when optimizing configurations and analyzing first-round results to provide a greater flexibility that accounts for possible peptide interference in pools and allows for lower responses to be detected. (4) Selecting a threshold for positivity in the first round must be done by balancing the number of second round tests required and the sensitivity desired.
When deconvoluting the response to a variable antigen, such as HIV, using multiple matrices that differ in peptide sequence may increase the number of epitopes identified. However, the only potential estimate for how well any given matrix will identify all positive epitopes from an individual is the sequence identity between the matrix and autologous sequence, which is often not known and varies over time. Constructing autologous sequence matrices is very tedious, time-consuming, and expensive. Recently, Frahm and colleagues have reported that using “toggled” peptides, where alternative amino acids are incorporated at variable positions, can increase detection of HIV-specific T cell responses (19
). For studies that draw conclusions based on the number of epitopes recognized between individuals, the use of multiple or autologous matrices, or toggled peptide sets, would strengthen the data. However, for routine deconvolution, one matrix may be sufficient.
In conclusion, use of a single peptide pool matrix encompassing hundreds of peptides allows for efficient deconvolution of T cell peptides. Using the ELISpot assay as a functional readout, this method requires a relatively low number of cells (10-20 million for mapping of HIV-specific responses) and is a highly powerful tool for determining the breadth of a pathogen-specific T cell response.