The CD4 transmembrane GGXXG and juxtamembrane (C/F)CV+C motifs mediate pMHCII-specific signaling independently of CD4-LCK interactions

Abstract

CD4⁺ T cell activation is driven by 5-module receptor complexes. The T cell receptor (TCR) is the receptor module that binds composite surfaces of peptide antigens embedded within MHCII molecules (pMHCII). It associates with three signaling modules (CD3γε, CD3δε, and CD3ζζ) to form TCR-CD3 complexes. CD4 is the coreceptor module. It reciprocally associates with TCR-CD3-pMHCII assemblies on the outside of a CD4⁺ T cells and with the Src kinase, LCK, on the inside. Previously, we reported that the CD4 transmembrane GGXXG and cytoplasmic juxtamembrane (C/F)CV+C motifs found in eutherian (placental mammal) CD4 have constituent residues that evolved under purifying selection (Lee, et al., 2022). Expressing mutants of these motifs together in T cell hybridomas increased CD4-LCK association but reduced CD3ζ, ZAP70, and PLCγ1 phosphorylation levels, as well as IL-2 production, in response to agonist pMHCII. Because these mutants preferentially localized CD4-LCK pairs to non-raft membrane fractions, one explanation for our results was that they impaired proximal signaling by sequestering LCK away from TCR-CD3. An alternative hypothesis is that the mutations directly impacted signaling because the motifs normally play an LCK-independent role in signaling. The goal of this study was to discriminate between these possibilities. Using T cell hybridomas, our results indicate that: intracellular CD4-LCK interactions are not necessary for pMHCII-specific signal initiation; the GGXXG and (C/F)CV+C motifs are key determinants of CD4-mediated pMHCII-specific signal amplification; the GGXXG and (C/F)CV+C motifs exert their functions independently of direct CD4-LCK association. These data provide a mechanistic explanation for why residues within these motifs are under purifying selection in jawed vertebrates. The results are also important to consider for biomimetic engineering of synthetic receptors.

Figure 1.. Computational reconstruction of CD4 evolution.

The maximum likelihood phylogenetic tree clusters mammalian CD4 sequences. The tree highlights ancestral reconstructions of CD4 sequences from marsupials (kangaroo silhouette), Atlantogenata (elephant), and Boreoeutheria (wildcat). The logoplot of extant eutherian (Atlantogenata and Boreoeutheria) CD4 sequences show sequence conservation over evolutionary time. In these plots, the height of symbols indicates the relative frequency of each amino acid at that specific position. The mouse CD4 numbering (uniprot) is used as a reference, and residues are color-coded based on sidechain polarity. Evolutionary insertion or deletion events are indicated by dashes (−). Most recent common ancestor (MRCA) sequences are shown at each node in the tree (Node 1–4). As in our previous study (Lee et al., 2022), the ratio of synonymous (dS) and nonsynonymous (dN) substitution rates was calculated. Black dots indicate dN/dS ratios that are significantly below 1 across the entire dataset. Red dots indicate residues under purifying selection in the mammalian only dataset. Previously identified motifs are indicated by boxes, while the intracellular domain helix is shaded gray. The arrow at position 422 indicates where CD4 was truncated (CD4-T1), while TMD and T1-Palm show the mutations studied in this study.

Figure 2.. Truncating CD4 does not reduce CD3ζ phosphorylation.

(A) Representative IL-2 production is shown in response to a titration of MCC peptide from one experiment (left). Experiments were performed in triplicate and each symbol equals the mean +/− SEM at that peptide concentration. AUC analysis for the dose response is shown as a measure of the response magnitude for the average of three independent experiments performed with one independently generated set of cell lines (center). The average response to a low dose (41nM) of peptide is shown as a measure of sensitivity for three independent experiments performed with one independently generated set of cell lines (right). The data are representative of those obtained with 4 (WT vs T1) or 2 (WT vs T1^Δbind) independently generated sets of cell lines. (B) Phosphorylation intensity of CD3ζ (pCD3ζ) for WT and CD4-T1 (T1) (left), normalized pCD3ζ intensity for WT and T1 (center), and average % responders of pCD3ζ for WT and T1 (right). Five independently generated cell lines (biological replicates) were tested for WT and T1. For phosphorylation intensity, each pair of lines (connected symbols) was tested in three independent experiments. Data were analyzed and collected as in Figure 2 – figure supplement 3. One-way ANOVA was performed with a Dunnett’s posttest using GraphPad Prism9. For normalized intensity, all individual mutant cell line values were normalized to their paired control values. Average percent responders are presented. Bars represent the mean +/− SEM. One-way ANOVA with paired comparisons was performed with a Sidak’s posttest for specific comparisons of normalized values using GraphPad Prism9. All generated cells lines were considered for the multiple comparisons. (C) Phosphorylation intensity of pCD3ζ for T1 and T1^Δbind (left), normalized pCD3ζ intensity for T1 and T1^Δbind (center), and % responders of pCD3ζ for T1 and T1^Δbind (right) were performed and analyzed as in B, with the exception that the open symbols represent data from a single experiment whereas the closed symbols represent aggregate data from three independent experiments. Two-tailed t tests were performed to compare the single T1 vs T1^Δbind samples as no other samples were collected in parallel.

Figure 3.. The GGXXG and CV+C motifs are key determinants of CD4 function.

(A, B) Representative IL-2 production is shown in response to a titration of MCC peptide from one experiment (left). Experiments were performed in triplicate and each symbol equals the mean +/− SEM at that peptide concentration. AUC analysis for the dose response is shown as a measure of the response magnitude for the average of three independent experiments performed with one independently generated set of cell lines (center). The average response to a low dose (41nM) of peptide is shown as a measure of sensitivity for three independent experiments performed with one independently generated set of cell lines (right). Results are representative of those obtained with at least three independently generated sets of cell lines. One-way ANOVA was performed with a Dunnett’s posttest for comparisons with WT and T1 samples, and a Sidak’s posttest for comparisons between selected samples.

Figure 4.. The GGXXG and CV+C motifs reduce pCD3ζ levels.

(A) Phosphorylation intensity of CD3ζ for T1 and T1-TMD (left), T1 and T1-Palm (2C) (center), and T1 and T1-TP (2C) (right) are shown for independently generated pairs of (connecting line) T1 and T1-TMD (left), T1 and T1-Palm (2C) (center), and T1 and T1-TP (2C) (right) cell lines. Each pair of lines (connected closed symbols) was tested in three independent experiments (technical replicates). The data from those experiments was aggregated, and the symbols represent the mean intensity of the aggregated pCD3ζ intensity values. One-way ANOVA was performed with a Dunnett’s posttest using GraphPad Prims 9. (B) Data for each cell line in A are shown as the average pCD3ζ intensity for all T1-TMD (left), T1-Palm (2C) (center), and T1-TP (2C) (right) cell lines normalized to their paired T1 control. Dotted line is the normalized pCD3ζ intensity for T1^Δbind as a visual reference point for the contributions of CD4-pMHCII interactions. Bars represent the mean +/− SEM. One-way ANOVA was performed with a Sidak’s posttest for specific comparisons using GraphPad Prims 9. (C) The average % responders for phosphorylation of CD3ζ is shown for T1-TMD (left), T1-Palm (2C) (center), and T1-TP (2C) (right) compared to the average of their paired T1 control lines. Bars represent the mean +/− SEM. One-way ANOVA was performed with a Sidak’s posttest for specific comparisons using GraphPad Prims 9.

Figure 5.. The (C/F)CVRC motifs reduces proximal TCR-CD3 signaling.

(A) Phosphorylation intensity of CD3ζ for T1 and T1-Palm (3C) (left) and T1 and T1-TP (3C) (right) are shown for independently generated pairs of (connecting lines) T1 and T1-Palm (3C) (left) and T1 and T1-TP (3C) (right) cell lines. Analysis was performed as in Figure 4A. (B) Data for each mutant cell line in A are shown as the average pCD3ζ intensity values for T1-Palm (3C) (left) and T1-TP (3C) (right) normalized to their paired T1 controls. The dotted line represents the normalized phosphorylation CD3ζ intensity for T1^Δbind as a visual reference for the contributions of CD4-pMHCII interactions. Analysis was performed as in Figure 4C. (C) Average % responders for phosphorylation of CD3ζ is shown for T1-Palm (3C) (left) and T1-TP (3C) (right) are shown compared to the average of their paired T1 control. Analysis was performed as in Figure 4C.