CEI: A Clonal Expansion Identifier for T-cell receptor clones following SARS-CoV-2 vaccination

TL;DR

Application of the statistical methods shows a robust identification of TCR sequences that respond to SARS-CoV-2 vaccination in vivo, illustrating the feasibility of quantifying the clone-specific dynamics of T-cell abundance changes following immunological perturbations.

Abstract

Each T cell typically carries a specific T-cell receptor (TCR) that determines its specificity against an epitope presented by the HLA complex on a target cell. Antigenic challenge triggers the expansion of reactive cells within a diverse pool of T cells with randomly generated receptors, a process that results in epitope-driven shifts of TCR frequencies over time. Here, we analyze the effects of SARS-CoV-2 vaccination on the TCR populations in peripheral blood drawn from seven COVID-naive individuals, before vaccines were widely available. To identify SARS-CoV-2 vaccine-associated TCR sequences among the $\sim 10^{5}-10^{6}$ TCR sequences sampled before and after vaccination, we develop statistical criteria to detect significant increases in abundance of positive TCR clones. Application of our statistical methods shows a robust identification of TCR sequences that respond to SARS-CoV-2 vaccination in vivo, illustrating the feasibility of quantifying the clone-specific dynamics of T-cell abundance changes following immunological perturbations.

Figures (17)

• Figure 1: Comparisons between the positive sequences called by each method for individual CLE0101. The blue and green circles represent sets of clones identified by the CEI-Joint and CEI-ACAT methods, respectively. The size of each circle indicates the number of positive clones detected. The yellow portion illustrates the overlap of positive clones identified by both the CEI-Joint and CEI-ACAT methods. Left: Clones identified through comparison of sample P1 to sample B. Middle: Clones identified through comparison of sample P2 to sample B. Right: Clones identified through comparison of sample P2 to sample P1.
• Figure 2: Comparisons between the positive sequences sampled at different times for subject CLE0101. The subplots, left and right, represent comparisons using the CEI-Joint and CEI-ACAT methods, respectively. Red, blue, and purple circles correspond to positive clones identified by comparing sample P1 with B, P2 with B, and P2 with P1. The size of each circle reflects the number of positive clones identified. Left: Clones identified via the CEI-Joint method. Right: Clones identified by the CEI-ACAT method.
• Figure 3: Abundances of individual TCR clones before vaccination (B) are plotted along the x-axis, while their abundances after vaccination (P1) are plotted along the y-axis. (a) and (b) correspond to subjects CLE0083 and CLE0101, respectively. Clones that are statistically significantly expanded (blue) are identified by a corrected binomial model stats and additionally, a threshold of at least a 2-fold increase or decrease from B to P1. Each dot corresponds to a unique TCR clone: grey circles represent robust clones with an abundance greater than $5$ templates, while clones with fewer than $5$ templates are shown in white to indicate they fall below the threshold for reliable detection. Purple squares represent the expanded clones called by our ACAT method using a FDR at $1\%$, while green circles denote the expanded clones identified by the standard heuristic approach. Similarly, clones that have been detected by edgeR are indicated by the red triangles. These results illustrate the overlap between the clones identified by the ACAT method, the clones detected using the standard heuristic criteria, and those called by edgeR for differential abundance analysis.
• Figure 4: For subject CLE0136, the boxplots compare clone frequencies between time points for the clones called by each method ($n$ listed below panels): (a) B vs P1, (b) B vs P2, and (c) P1 vs P2. For each contrast, boxplots display the frequencies of the identified clones by comparing two samples using three different methods: CEI-Joint, CEI-ACAT, and edgeR (with the number of calls, $n$, under each method). The CEI-Joint method yields significantly higher frequencies at both baseline and post-vaccination samples. Note that edgeR calls no positive sequences any significant expansion in the B vs P1 comparison, even when we relaxed the FDR.
• Figure 5: Sensitivity of the number of positive clones selected with respect to the FDR threshold $\alpha$, where $\alpha \in (0, 0.5]$. The dashed lines correspond to the CEI-ACAT method, while the solid lines correspond to the CEI-Joint method. (a) Sensitivity analysis conducted by comparing sample P1 with B. (b) Sensitivity analysis conducted by comparing sample P2 with B. (c) sensitivity analysis conducted by comparing sample P2 with P1.