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. 2024 Jul 1;221(7):e20231987.
doi: 10.1084/jem.20231987. Epub 2024 May 16.

γδ T cell profiling in a cohort of preterm infants reveals elevated frequencies of CD83+ γδ T cells in sepsis

Affiliations

γδ T cell profiling in a cohort of preterm infants reveals elevated frequencies of CD83+ γδ T cells in sepsis

Ximena León-Lara et al. J Exp Med. .

Abstract

Preterm infants are at high risk of developing neonatal sepsis. γδ T cells are thought to be an important set of effector cells in neonates. Here, γδ T cells were investigated in a longitudinal cohort of preterm neonates using next-generation sequencing, flow cytometry, and functional assays. During the first year of life, the Vγ9Vδ2 T cell subset showed dynamic phenotypic changes and elevated levels of fetal-derived Vγ9Vδ2 T cells were evident in infants with sepsis. Single-cell transcriptomics identified HLA-DRhiCD83+ γδ T cells in neonatal sepsis, which expressed genes related to antigen presentation. In vitro assays showed that CD83 was expressed on activated Vγ9Vδ2 T cells in preterm and term neonates, but not in adults. In contrast, activation of adult Vγ9Vδ2 T cells enhanced CD86 expression, which was presumably the key receptor to induce CD4 T cell proliferation. Together, we provide a map of the maturation of γδ T cells after preterm birth and highlight their phenotypic diversity in infections.

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Conflict of interest statement

Disclosures: S. Pirr reported grants from Deutsche Forschungsgemeinschaft and grants from the German Ministry of Education and Research outside the submitted work. No other disclosures were reported.

Figures

Figure S1.
Figure S1.
Longitudinal flow cytometric analyses of γδ T cells during the first year of life. (A and B) Frequency per donor of (A) Vγ9 T cells or (B) Vδ1 T cells among CD3 T cells by FACS at 0–14 days (d), 21–35 days, 6–9 mo (m), and 13–16 mo after preterm birth. The red bar indicates the median value. (C) Box plots of the frequency of Vγ9 T cells among γδ T cells in relation to the diagnosis of sepsis during the neonatal period. (D) Box plots of the absolute counts of total lymphocyte populations from peripheral blood of preterm infants with and without sepsis during the neonatal period. (E and F) Correlations of lymphocyte cell count with frequency of Vγ9 T cells (E) or Vδ1 T cells (F) among CD3 T cells at 0–14 days (d) or 21–35 d. P values were determined by linear mixed effects modeling (A and B) or Mann–Whitney U test (C and D). R and P values were determined by Spearman correlation test (E and F); ns = not significant, *P < 0.05, **P < 0.01, ***P < 0.001.
Figure 1.
Figure 1.
Sepsis results in increased Vγ9 T cell frequencies in preterm infants. (A and B) Box plots of the frequency of (A) Vγ9 T cells or (B) Vδ1 T cells among CD3 T cells by FACS during the first 0–14 days (d), 21–35 days, 6–9 mo (m), and 13–16 mo after birth in relation to the diagnosis of sepsis during the neonatal period. (C and D) Forest plots of the β-estimates ± 95% confidence intervals of the indicated variables on the frequency of (C) Vγ9 T cells or (D) Vδ1 T cells among CD3 T cells during the first month of life. The vertical dotted red line indicates null effect. P values were determined by Mann–Whitney U test (A and B) or linear mixed-effects modeling (C and D); ns = not significant, *P < 0.05, ***P < 0.001.
Figure S2.
Figure S2.
Longitudinal bulk TCR-seq of γδ T cells during the first year of life. (A) The total TRD repertoire of FACS-sorted γδ T cells from 58 preterm infants at four time points during the first year of life and five term infants aged 12–24 mo was clustered based on V(D)J characteristics, resulting in five TCR groups. Frequency of each TCR group was calculated per infant at the indicated time points after preterm birth and in term infants at 12–24 mo of age. (B) Histogram showing the introduction of random nucleotides (N additions) distribution of the clones per time point, colored by TRDJ usage. (C) Frequency of private, public, and shared public TRD clones per infant at the respective time points. (D) Box plots of the diversity index of the TRD repertoire at the indicated time points. (E) Box plots of the TRGJP gene element usage in the TRG repertoire at the respective time points after preterm birth in relation to the diagnosis of sepsis in the neonatal period. (A and C) The median value is indicated with a red bar. P values were determined by linear mixed effect modeling with multiple comparisons by Tukey (A, C, and D) or Mann–Whitney U test (E); ns = not significant, *P < 0.05, **P < 0.01, ***P < 0.001.
Figure 2.
Figure 2.
Polyclonal expansion of TRDV2+ TRD clones with fetal-like characteristics in neonatal sepsis. The total TRD repertoire of FACS-sorted γδ T cells from 58 longitudinally followed preterm infants and five term infants was clustered based on V(D)J characteristics, resulting in five TCR groups. (A) Frequency of each TCR group at 0–14 days (d), 21–35 days, 6–9 mo (m), or 13–16 mo after preterm birth in relation to the diagnosis of sepsis in the neonatal period. (B) Treemaps showing the TRD repertoire diversity in a representative donor diagnosed with sepsis on day 5 after birth. Each box represents one clone, and boxes are sized according to the clone frequency. Each clone (box) is color-coded according to the TRDVTRDJ pairing. (C) Diversity index of the TRD repertoire at the indicated time points in relation to the diagnosis of sepsis in the neonatal period. P values were determined by Mann–Whitney U test (A and C); ns = not significant, **P < 0.01.
Figure 3.
Figure 3.
Age-dependent maturation of γδ T cells during infancy. (A and B) PCA based on the frequency of positive cells for 15 surface markers on (A) Vγ9Vδ2 or (B) Vδ1 T cells measured by flow cytometry from 28 children without sepsis during the neonatal period. The PCA score plots were color-coded according to the age at sampling. The mean and the 95% confidence ellipses are shown for the corresponding age at sampling. (C) Box plots of the frequency of CCR4, CD4 co-expression, CD25, PD1, or CD27, CD28 co-expression on Vγ9Vδ2 T cells per donor by FACS at 0–14 days (d), 21–35 days, 6–9 mo (m), and 13–16 mo after preterm birth in infants diagnosed with and without neonatal sepsis. (D) Frequency of CCR5 on Vγ9Vδ2 T cells per donor and time point in relation to the diagnosis of sepsis in the neonatal period. (E) Box plots of the frequency of NKG2D, NKG2A, or CD57 on Vγ9Vδ2 T cells per donor and time point in relation to the diagnosis of sepsis in the neonatal period. P values were determined by Mann–Whitney U test (C, D, and E); ns = not significant, *P < 0.05.
Figure S3.
Figure S3.
Longitudinal surface marker profiles of γδ T cells during the first year of life. (A–D) Contribution of the top 10 variables to the (A) dimension 1 (Dim1) or (B) dimension 2 (Dim2) of the PCA for Vγ9Vδ2 T cells, and the (C) Dim1 or (D) Dim2 of the PCA for Vδ1 T cells. The dashed line indicates the expected average contribution, a variable with a contribution above this line was considered as an important contributor to the dimension. (E and F) Box plots of the frequency of (E) CD27, CCR7 co-expression, CCR4, CD25, CD69, (F) NKG2A, PD1, CD16, or CD57 on Vδ1 T cells per donor by FACS at four time points after preterm birth in infants diagnosed with and without neonatal sepsis. P values were determined by Mann–Whitney U test (E and F); ns = not significant, **P < 0.01.
Figure S4.
Figure S4.
Longitudinal single-cell transcriptome and TCR repertoire analysis of γδ T cells in preterm infants. (A) Bar plots of the absolute number of γδ T cells from each donor that were considered for the analysis, colored by the age at sampling. (B) UMAP visualization of the γδ T cell scRNA-seq dataset from the infants at the different time points, color-coded by the donor. (C) Heat map showing the averaged expression values of the top 100 DEGs (columns) between clusters (rows). (D) UMAP visualization of the scTCR-seq dataset showing the TRDV gene usage (NA: TRDV data not available). (E) Violin plots of the KLF2, PECAM1, or CCR9 expression at 0–14 days (yellow), 21–35 days (green), 6–9 mo (gray), or 13–16 mo (pink). (F) Bar plots of the frequency of TRDJ gene element segment usage in each cluster. Cells without a paired γδTCR were excluded.
Figure 4.
Figure 4.
Identification of HLA-DRAhi and CD83+ single-cell transcripts in preterm infants with sepsis. Single-cell libraries were generated from peripheral blood γδ T cells of infants with (n = 3) and without (n = 3) neonatal sepsis sorted at different time points during the first year of life. (A) UMAP visualization of the γδ T cell scRNA-seq dataset from the infants with and without neonatal sepsis in the sepsis period (below 1 mo of age) and sepsis-free period (older than 6 mo) color-coded by clusters (c1–c9). (B) Dot plot of the average gene expression (columns) per cluster (rows), sized by the percentage of cells per cluster that expressed the respective gene (% Expressed). (C) Bar plots of the frequency of paired γδTCR V-gene usage compositions (TRGV and TRDV) in each cluster. Cells without a paired γδTCR were excluded. (D) Box plots of the single-cell gene signature module score for RTE at the indicated time points according to the TRDV gene usage. The RTE module score was computed based on KLF2, CCR9, PECAM1, S1PR1, LEF1, TCF7, SOX4, NT5E, and SELL genes. (E) Bar plots of the frequency of each cluster (c1–c9) at 0–14 days (d), 21–35 days, 6–9 mo (m), or 13–16 mo after preterm birth in children with and without neonatal sepsis (control). P values were determined by linear mixed effect modeling with multiple comparisons by Tukey (D); *P < 0.05, ***P < 0.001.
Figure 5.
Figure 5.
Neonatal, but not adult blood, HMBPP-expanded Vγ9Vδ2 T cells become CD83+. (A) Scatter plots of the average expression between conditions of the gene profiles in each of the annotated clusters, highlighting the genes that are more expressed in sepsis (pink) or without sepsis (blue). (B) Gene expression of HLA-DRA, HLA-DRB1, CD83, CD86, CD74, and CD69 of γδ T cells from the children with and without neonatal sepsis in the sepsis period (<1 mo) and sepsis-free (>6 mo) period. (C) Frequency of CD83 on γδ T cells by flow cytometry in preterm or term neonates with sepsis (pink) during the first 2 days of diagnosis compared to age-matched uninfected controls (blue). (D) Frequency of HLA-DRA+, CD83+, and CD86+ cells of Vγ9Vδ2 T cells from term CBMCs (n = 7), preterm neonatal PBMCs (n = 6), and adult PBMC (n = 7) after 7 days of HMBPP (red) or IL-2 only (green) measured by flow cytometry in four independent experiments. Bar plots represent the mean ± standard error. P values were determined by Mann–Whitney U (B and C) or paired t test (D); ns = not significant, *P < 0.05, **P < 0.01, ***P < 0.001.
Figure S5.
Figure S5.
Adult and neonatal Vγ9Vδ2 T cells acquire different surface marker phenotypes in response to HMBPP stimulus. (A) Frequency of HLA-DRA, CD83, and CD86 surface expression on Vγ9Vδ2 T cells from CBMCs, and adult PBMC (aPBMC) after 7 days of different doses of HMBPP or IL-2 only stimulation measured by flow cytometry in two independent experiments. Bar plots represent the mean ± standard error. P values were determined by paired t test using IL-2 condition as the reference; ns = not significant, *P < 0.05, **P < 0.01, ***P < 0.001. (B) GO enrichment analysis of the upregulated differential expressed genes from the respective cluster (c1–c9). (C) Volcano plot shows the average expression of the DEGs between c9 in comparison to the rest of the clusters (c1–c8).
Figure 6.
Figure 6.
HMBPP-expanded Vγ9Vδ2 T cells from neonatal blood do not induce proliferation of CD4 T cells. (A) Representative dot plots showing the DQ-OVA signal (FITC) on Vγ9Vδ2 T cells from one term cord blood (tCBMC), one neonatal blood donor (nPBMC) and one adult blood donor (aPBMC) after 7 days with IL-2 or HMBPP stimulation. (B) Frequency of DQ-OVA signal (FITC) on HMBPP-expanded Vγ9Vδ2 T cells from term CBMCs (tCBMC, n = 7), neonatal PBMCs (nPBMC, n = 3), and adult aPBMC (n = 7) after 7 days of HMBPP (red) or IL-2 only (green) measured by flow cytometry in three independent experiments. (C–E) Vγ9Vδ2 T cells were isolated from term CBMC (tCBMC), neonatal PBMC (nPBMC), and adult PBMC (aPBMC) after 7 days of HMBPP stimulation, and cocultured after irradiation with allogenic sorted CD4 T cells (CD4+/γδneg/CD25lo/CD127+). Flow cytometry analysis was performed after 6 days of coculture. Proliferation of CD4 T cells was determined by CellTrace Blue dilution. Data were generated in two independent experiments. (C) Frequency of CellTrace Bluelo (proliferating) CD4 T cells after 6 days of co-culture with the indicated conditions. (D) Representative dot plots showing the CellTrace Blue dilution and CD25 expression of CD4 T cells of one adult donor in the presence of allogenic irradiated Vγ9Vδ2 T cells from one tCBMC, one nPBMC, and one aPBMC sample in comparison to IL-2 unstimulated control and antiCD3/antiCD28 control. (E) Frequency of CD25, CTLA-4 (intracellular), PD1, and HLA-DRA surface marker expression of CD4 T cells after 6 days of co-culture with the indicated conditions. P values were determined by paired t test using IL-2 condition as the reference (B, C, and E); ns = not significant, *P < 0.05, **P < 0.01, ***P < 0.001.

References

    1. Barisa, M., Kramer A.M., Majani Y., Moulding D., Saraiva L., Bajaj-Elliott M., Anderson J., and Gustafsson K.. 2017. E. coli promotes human Vγ9Vδ2 T cell transition from cytokine-producing bactericidal effectors to professional phagocytic killers in a TCR-dependent manner. Sci. Rep. 7:2805. 10.1038/s41598-017-02886-8 - DOI - PMC - PubMed
    1. Barros-Martins, J., Bruni E., Fichtner A.S., Cornberg M., and Prinz I.. 2022. OMIP-084: 28-color full spectrum flow cytometry panel for the comprehensive analysis of human γδ T cells. Cytometry A. 101:856–861. 10.1002/cyto.a.24564 - DOI - PubMed
    1. Bolotin, D.A., Poslavsky S., Mitrophanov I., Shugay M., Mamedov I.Z., Putintseva E.V., and Chudakov D.M.. 2015. MiXCR: Software for comprehensive adaptive immunity profiling. Nat. Methods. 12:380–381. 10.1038/nmeth.3364 - DOI - PubMed
    1. Brandes, M., Willimann K., Lang A.B., Nam K.-H., Jin C., Brenner M.B., Morita C.T., and Moser B.. 2003. Flexible migration program regulates γ δ T-cell involvement in humoral immunity. Blood. 102:3693–3701. 10.1182/blood-2003-04-1016 - DOI - PubMed
    1. Brandes, M., Willimann, K., Moser, B., 2005. Professional Antigen-Presentation Function by Human γδ T Cells. Science. 309:264–268. 10.1126/science.1110267 - DOI - PubMed

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