Virus-specific CD4(+) memory-phenotype T cells are abundant in unexposed adults

Abstract

Although T cell memory is generally thought to require direct antigen exposure, we found an abundance of memory-phenotype cells (20%-90%, averaging over 50%) of CD4(+) T cells specific to viral antigens in adults who had never been infected. These cells express the appropriate memory markers and genes, rapidly produce cytokines, and have clonally expanded. In contrast, the same T cell receptor (TCR) specificities in newborns are almost entirely naïve, which might explain the vulnerability of young children to infections. One mechanism for this phenomenon is TCR cross-reactivity to environmental antigens, and in support of this, we found extensive cross-recognition by HIV-1 and influenza-reactive T lymphocytes to other microbial peptides and expansion of one of these after influenza vaccination. Thus, the presence of these memory-phenotype T cells has significant implications for immunity to novel pathogens, child and adult health, and the influence of pathogen-rich versus hygienic environments.

Figure 1. Peptide-MHCII tetramer-based enrichment is highly sensitive and specific

(A) HLA-DR4⁺ CD4⁺ lymphocytes were used as is or spiked into HLA-DR4⁻ lymphocytes to achieve 50- and 100-fold dilutions in a total of 55 million CD4⁺ T cells. Undiluted HLA-DR4⁻ lymphocytes were used as negative control. PB1 tetramer staining and enrichment were performed in parallel. Data are representative of one individual from 2 independent experiments. (B) A gp100-specific clone from single cell expansion that re-stained with gp100 tetramers but not with HIV-1 tetramers. IFN-γ is produced in response to stimulation by gp100 peptide, gp100 protein, but not to a control HIV-1 peptide. Data is representative of two gp100-specific clones. (C) Table showing T cell clones generated by expansion of single cells labeled with gp100, HIV-1, HA, or tetanus tetramers. The percentage of cells that retained staining with the same tetramer (% tet+) was calculated by dividing the number of tetramer positive clones by the total numbers of clones generated for each specificity (See also Fig. S1).

Figure 2. Frequency analysis of the human antigen-specific CD4⁺ lymphocytes

All blood samples were obtained from individuals seronegative for HIV and CMV exposures. HSV exposure is as indicated (naïve vs exposed). (A) Frequencies of tetramer tagged cells per million CD4⁺ T cells. Each symbol represents an antigen-specific population from one individual and the bar indicates the mean of experiments performed independently using blood obtained at different times. (B) Comparison between T cells recognizing a novel foreign antigen (pre: HIV-1, CMV, HSV-naïve), exposed foreign antigen (post: Flu, tetanus, HSV-exposed), and self antigen (self: Fib, gp100, PPins). Figure summarizes data from all 26 individuals. (C) Precursor frequencies of self-specific lymphocytes that recognized gp100, Fib, or PPins in people ages <40 (n= 7), 40–60 (n = 13), >60 (n = 6). (D) Precursor frequency of self-specific lymphocytes that recognized gp100, Fib, or PPins in males (n = 17) and females (n = 9) (See also Fig. S2).

Figure 3. Characterization of the memory phenotype in the CD4⁺ T cell repertoire

(A) Representative HA and HIV-1 tetramer labeling (left) and CD45RO antibody staining (right). Plots are representative of 15 individuals. (B) Percent of CD45RO⁺ memory cells within each tetramer tagged population. Each symbol represents an antigen-specific population from one individual and the bar indicates the mean of experiments performed independently using blood obtained at different times. (C) The percentage of memory phenotype among T cells recognizing a novel foreign antigen (pre: HIV-1, CMV, HSV-naïve), exposed foreign antigen (post: Flu, tetanus, HSV-exposed), and self antigen (self: Fib, gp100, PPins). Figure summarizes data from all 26 individuals. (D) Correlation plot combining all antigen-specific populations from all donors. Total cell frequency positively correlates with memory marker expression. Statistical analysis was performed using Spearman’s rank correlation. Regression was performed by least-square fit (See also Fig. S3).

Figure 4. Memory phenotype T cells in adults have the typical memory features and are absent in cord blood

(A) Contour plots showing IFN-γ response of HIV-1- and PB1-specific T cells to stimulation by PMA and ionomycin. Experiments were repeated twice using blood from 2 different individuals. (B) Gene expression of tetramer negative and HIV-1 tetramer labeled cells (TetNeg mem n = 48, TetNeg naïve n = 46, HIV-1 mem n = 53, HIV-1 naïve n = 52). Heatmap summarizes the fraction of cells expressing a particular gene out of the total number of cells assayed. The genes have been grouped by whether they associate with memory (top) or naïve T cells (bottom) and then ordered by ascending p value that compares the differences between HIV memory and HIV naïve T cells. (C) TCRβ sequencing of tetramer labeled CD45RO⁺ and CD45RO⁻ cells. Each pie chart represents TCR sequences from one individual. Dark gray: the fraction of cells expressing a TCR identical to that of another cell. Light gray: cells expressing unique TCRs. HIV-1 and HSV-specific T cells were obtained from individuals negative for these infections. (D) HA- and HIV-1-specific T cells in adult PBMC (top) or cord blood (bottom) were identified by tetramer staining followed by magnetic bead enrichment (left) and anti-CD45RO surface staining (right). Data is representative of two adults PBMCs and two cord bloods assayed in parallel (See also Fig. S4).

Figure 5. HIV-1-specific T cells exhibit extensive TCR cross-reactivity

(A) FACS plots of CFSE staining and cytokine production by a representative HIV-1-reactive clone (HIV-1 clone 5). T cell proliferation and cytokine production was observed in response to HIV-1, Micromonas, and B. bifidum derived peptides but not to an irrelevant HA peptide. (B) Table summarizing peptide cross-reactivity for five HIV-1-specific clones that recognize alternate peptide sequences. Response of each clone to peptide stimulation was repeated at least 3 times. (C) Contour plots showing two cross-reactive clones that bind HIV-1 and R. flavefaciens tetramers (HIV-1 clone 3) or HIV-1 and Micromonas tetramers (HIV-1 clone 5), but not HA tetramers. Data is representative of 3 independent experiments (See also Fig. S5).

Figure 6. Antigen-specific T cell response to the 2009 H1N1 vaccine

(A) Antibody response to A/California/7/2009 (H1N1) virus by HAI titer at various time points before and after influenza vaccination. (B) Contour plot showing expansion of HA(H1N1)-specific T cells of donor 1 nine days after vaccination. (C) The kinetics of HA(H1N1)-specific T cells. Error bars represent SEM. Experiments from each donor at each time point were performed 1–4 times, depending on sample availability. (D) The percentage of HA(H1N1)-specific T cells that are CD45RO⁺.

Figure 7. T cells responsive to flu vaccination also cross-recognized microbial peptides

(A) CFSE staining of a representative HA(H1N1)-specific clones that proliferated in response to HA 391–410 peptide and also to a F. magna and T. vaginalis derived peptides but not to a control HIV-1 peptide. T cell stimulation with each peptide was repeated at least 3 times. (B) Table showing the sequences of full length HA 391–410 peptide, HA 398–410 core sequence, F. magna peptide, and T. vaginalis peptide. Twenty-one clones from donor 1 and twelve clones from donor 2 were combined and assayed for response to each peptide. Data is representative of two independent experiments. (C) Tetramer labeling of two HA(H1N1)-reactive clones by HA(H1N1), F. magna, and T. vaginalis tetramers. Experiment was repeated two times. (D) Direct ex vivo analysis of HA(H1N1) and F. magna tetramer positive cells. A population of influenza and F. magna cross-reactive cells (F. magna cx) became detectable on day 9 and exhibited 100% memory phenotype. (E) Frequencies of the total HA(H1N1) tetramer positive cells and cross-reactive T cells co-labeled with F. magna tetramers (F. magna cx). Error bars represent SEM. Experiments at each time point were performed 1–3 times, depending on sample availability (See also Fig. S6 and S7).