To tackle the complexity of cross-reactive and pathogen-specific T cell responses against related Salmonella serovars, we used mass cytometry, unbiased single-cell cloning, live fluorescence barcoding, and T cell–receptor sequencing to reconstruct the Salmonella-specific repertoire of circulating effector CD4+ T cells, isolated from volunteers challenged with Salmonella enterica serovar Typhi (S. Typhi) or Salmonella Paratyphi A (S. Paratyphi). We describe the expansion of cross-reactive responses against distantly related Salmonella serovars and of clonotypes recognizing immunodominant antigens uniquely expressed by S. Typhi or S. Paratyphi A. In addition, single–amino acid variations in two immunodominant proteins, CdtB and PhoN, lead to the accumulation of T cells that do not cross-react against the different serovars, thus demonstrating how minor sequence variations in a complex microorganism shape the pathogen-specific T cell repertoire. Our results identify immune-dominant, serovar-specific, and cross-reactive T cell antigens, which should aid in the design of T cell–vaccination strategies against Salmonella.
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Mucosal Immunology Open Access 03 November 2022
Invasive Salmonella exploits divergent immune evasion strategies in infected and bystander dendritic cell subsets
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Crump, J. A., Luby, S. P. & Mintz, E. D. The global burden of typhoid fever. Bull. World Health Organ. 82, 346–353 (2004).
Crump, J. A. & Mintz, E. D. Global trends in typhoid and paratyphoid fever. Clin. Infect. Dis. 50, 241–246 (2010).
Mogasale, V. et al. Burden of typhoid fever in low-income and middle-income countries: a systematic, literature-based update with risk-factor adjustment. Lancet Glob. Health 2, e570–e580 (2014).
Dougan, G. & Baker, S. Salmonella enterica serovar Typhi and the pathogenesis of typhoid fever. Annu. Rev. Microbiol. 68, 317–336 (2014).
Gal-Mor, O., Boyle, E. C. & Grassl, G. A. Same species, different diseases: how and why typhoidal and non-typhoidal Salmonella enterica serovars differ. Front. Microbiol. 5, 391 (2014).
McClelland, M. et al. Comparison of genome degradation in Paratyphi A and Typhi, human-restricted serovars of Salmonella enterica that cause typhoid. Nat. Genet. 36, 1268–1274 (2004).
Holt, K. E. et al. Pseudogene accumulation in the evolutionary histories of Salmonella enterica serovars Paratyphi A and Typhi. BMC Genomics 10, 36 (2009).
Coward, C. et al. The effects of vaccination and immunity on bacterial infection dynamics in vivo. PLoS Pathog. 10, e1004359 (2014).
Griffin, A. J. & McSorley, S. J. Development of protective immunity to Salmonella, a mucosal pathogen with a systemic agenda. Mucosal Immunol. 4, 371–382 (2011).
Lee, S. J., Dunmire, S. & McSorley, S. J. MHC class-I-restricted CD8 T cells play a protective role during primary Salmonella infection. Immunol. Lett. 148, 138–143 (2012).
Dunstan, S. J. et al. Variation at HLA-DRB1 is associated with resistance to enteric fever. Nat. Genet. 46, 1333–1336 (2014).
Waddington, C. S. et al. An outpatient, ambulant-design, controlled human infection model using escalating doses of Salmonella Typhi challenge delivered in sodium bicarbonate solution. Clin. Infect. Dis. 58, 1230–1240 (2014).
McCullagh, D. et al. Understanding paratyphoid infection: study protocol for the development of a human model of Salmonella enterica serovar Paratyphi A challenge in healthy adult volunteers. BMJ Open 5, e007481 (2015).
Blohmke, C. J. et al. Interferon-driven alterations of the host’s amino acid metabolism in the pathogenesis of typhoid fever. J. Exp. Med. 213, 1061–1077 (2016).
Levine, J. H. et al. Data-driven phenotypic dissection of aml reveals progenitor-like cells that correlate with prognosis. Cell 162, 184–197 (2015).
Krutzik, P. O. & Nolan, G. P. Fluorescent cell barcoding in flow cytometry allows high-throughput drug screening and signaling profiling. Nat. Methods 3, 361–368 (2006).
Haghjoo, E. & Galán, J. E. Salmonella typhi encodes a functional cytolethal distending toxin that is delivered into host cells by a bacterial-internalization pathway. Proc. Natl. Acad. Sci. USA 101, 4614–4619 (2004).
Song, J., Gao, X. & Galán, J. E. Structure and function of the Salmonella Typhi chimaeric A(2)B(5) typhoid toxin. Nature 499, 350–354 (2013).
Liang, L. et al. Immune profiling with a Salmonella Typhi antigen microarray identifies new diagnostic biomarkers of human typhoid. Sci. Rep. 3, 1043 (2013).
Rodriguez-Rivera, L. D., Bowen, B. M., den Bakker, H. C., Duhamel, G. E. & Wiedmann, M. Characterization of the cytolethal distending toxin (typhoid toxin) in non-typhoidal Salmonella serovars. Gut Pathog. 7, 19 (2015).
von Rhein, C. et al. ClyA cytolysin from Salmonella: distribution within the genus, regulation of expression by SlyA, and pore-forming characteristics. Int. J. Med. Microbiol. 299, 21–35 (2009).
Oscarsson, J. et al. Characterization of a pore-forming cytotoxin expressed by Salmonella enterica serovars typhi and paratyphi A. Infect. Immun. 70, 5759–5769 (2002).
Barat, S. et al. Immunity to intracellular Salmonella depends on surface-associated antigens. PLoS Pathog. 8, e1002966 (2012).
Stubbington, M. J. T. et al. T cell fate and clonality inference from single-cell transcriptomes. Nat. Methods 13, 329–332 (2016).
Lindestam Arlehamn, C. S. et al. Memory T cells in latent Mycobacterium tuberculosis infection are directed against three antigenic islands and largely contained in a CXCR3+CCR6+ Th1 subset. PLoS Pathog. 9, e1003130 (2013).
Bhuiyan, S. et al. Cellular and cytokine responses to Salmonella enterica serotype Typhi proteins in patients with typhoid fever in Bangladesh. Am. J. Trop. Med. Hyg. 90, 1024–1030 (2014).
Reynolds, C. J. et al. The serodominant secreted effector protein of Salmonella, SseB, is a strong CD4 antigen containing an immunodominant epitope presented by diverse HLA class II alleles. Immunology 143, 438–446 (2014).
Sheikh, A. et al. Interferon-γ and proliferation responses to Salmonella enterica serotype Typhi proteins in patients with S. Typhi bacteremia in Dhaka, Bangladesh. PLoS Negl. Trop. Dis. 5, e1193 (2011).
Wahid, R., Fresnay, S., Levine, M. M. & Sztein, M. B. Cross-reactive multifunctional CD4+ T cell responses against Salmonella enterica serovars Typhi, Paratyphi A and Paratyphi B in humans following immunization with live oral typhoid vaccine Ty21a. Clin. Immunol. 173, 87–95 (2016).
Fuentes, J. A., Villagra, N., Castillo-Ruiz, M. & Mora, G. C. The Salmonella Typhi hlyE gene plays a role in invasion of cultured epithelial cells and its functional transfer to S. Typhimurium promotes deep organ infection in mice. Res. Microbiol. 159, 279–287 (2008).
Galán, J. E. Typhoid toxin provides a window into typhoid fever and the biology of Salmonella Typhi. Proc. Natl. Acad. Sci. USA 113, 6338–6344 (2016).
Groisman, E. A. The pleiotropic two-component regulatory system PhoP-PhoQ. J. Bacteriol. 183, 1835–1842 (2001).
Dobinson, H. C. et al. Evaluation of the clinical and microbiological response to Salmonella paratyphi a infection in the first paratyphoid human challenge model. Clin. Infect. Dis. 64, 1066–1073 (2017).
Wong, M. T. et al. Mapping the diversity of follicular helper T cells in human blood and tonsils using high-dimensional mass cytometry analysis. Cell Reports 11, 1822–1833 (2015).
Finck, R. et al. Normalization of mass cytometry data with bead standards. Cytometry A 83, 483–494 (2013).
Chen, H. et al. Cytofkit: a Bioconductor package for an integrated mass cytometry data analysis pipeline. PLOS Comput. Biol. 12, e1005112 (2016).
Kotecha, N., Krutzik, P. O. & Irish, J. M. Web-based analysis and publication of flow cytometry experiments. Curr. Protoc. Cytom. 53, 10.17.1–10.17.24 (2010).
Traunecker, A., Oliveri, F. & Karjalainen, K. Myeloma based expression system for production of large mammalian proteins. Trends Biotechnol. 9, 109–113 (1991).
Olsen, L. R. et al. BlockLogo: visualization of peptide and sequence motif conservation. J. Immunol. Methods 400-401, 37–44 (2013).
Bolotin, D. A. et al. MiXCR: software for comprehensive adaptive immunity profiling. Nat. Methods 12, 380–381 (2015).
Shugay, M. et al. Towards error-free profiling of immune repertoires. Nat. Methods 11, 653–655 (2014).
Shugay, M. et al. VDJtools: unifying post-analysis of T cell receptor repertoires. PLOS Comput. Biol. 11, e1004503 (2015).
This work was supported by the UK Medical Research Council (MRC) (MR/K021222/1) (G.N., M.A.G., A.S., V.C., A.J.P.), Cancer Research UK (CRUK) (C399/A2291) (V.C.), the NIHR Clinical Research Network Thames Valley (A.J.P.), the Oxford Biomedical Research Centre (A.J.P., V.C.), the Bill & Melinda Gates Foundation (OPP1084259) (A.J.P.), the European Vaccine Initiative (PIM) (A.J.P.), and core funding from the Singapore Immunology Network (SIgN) (E.W.N.) and the SIgN immunomonitoring platform (E.W.N.). G.D. is supported by The Wellcome Trust. We thank C. Waugh and the WIMM FACS facility for assistance with cell sorting, and T. Rostron for assistance with next-generation sequencing. The DRB4 tetramers were provided by B. Kwok and I.-T. Chow, from the Tetramer Core Laboratory at the Benaroya Research Institute at Virginia Mason.
The authors declare no competing interests.
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Integrated supplementary information
(a)Gating strategy to identify CD4+ and CD4+Ki67+ cells in Mass Cytometry experiments. Frequency of Cluster 19 cells within Ki67+ (b) and total CD4+ T cells (c) at different time points after infection (n = 6). (b) Friedman Test p = 0.0147, Dunn’s Multiple Comparison Test D0 vs D4, D28, D90 p = ns, D0 vs EF p = 0.027. (c)Friedman Test p = 0.0159, Dunn’s Multiple Comparison Test D0 vs D4, D28, D90 p = ns, D0 vs EF p = 0.0247. (d) Total Ki67+ events (grey) and Cluster 19 events (red) across all samples were concatenated and expression of 20 markers against CD38 in the distinct populations is shown.
Supplementary Figure 2 CCR7–CD38+CD4+ cells are enriched in Ki67+ accumulating during enteric fever.
(a) Expression of CCR7 and CD38 in the 20 distinct clusters identified by PhenoGraph analysis. (b) Proportion of PhenoGraph clusters within Ki67+ CD38+CCR7- cells at the peak of Ki67+ cell accumulation. (c) Frequency of Ki67+ CD38+CCR7- cells (Friedman Test p = 0.0130, Dunn’s Multiple Comparison Test D0 vs D4, D28, D90p = ns, D0 vs EF p = 0.0139) and of KI67 + cells non comprised within CD38+CCR7- cells over time in challenged volunteers (n = 6) (Friedman Test p = 0.23, Dunn’s Multiple Comparison Test D0 vs D4, EF, D28, D90 p = ns). Box extends from the 25th to the 75th percentile and whiskers from the minimum to the maximum value; line indicates median.
Supplementary Figure 3 Accumulation of CD4+CD38+CCR7– in whole blood of volunteers with enteric fever
(a) Identification of CD4+CD38+CCR7- cells during enteric fever by Multicolour Flow Cytometry in whole blood from a representative volunteer challenged with S. Typhi, and one challenged with S. Paratyphi A. (b) Accumulation of CD38+CCR7- cells after diagnosis in volunteers challenged with S. Typhi and Paratyphi A who developed (Diagnosed) but not in those who did not develop enteric fever (Not Diagnosed). In challenged volunteers not diagnosed blood was collected 14 days after challenge (D14). Friedman Multi comparison Test p = 0.006 (S. Typhi), p < 0.0001 (S. Paratyphi). Dunn’s Multiple Comparison Test ED vs D0, p = 0.0065 (Typhi, n = 9); p = 0.0002 (S. Paratyphi A, n = 9). Box extends from the 25th to the 75th percentile and whiskers from the minimum to the maximum value; line indicates median.
Shown is an example with four live fluorescent dyes. Cell were labelled with 9 combinations of three distinct dilution of Violet and Far red dyes. Cells with each of the nine cluster were labelled with 6 combinations of 4 distinct dilutions of CFSE and and 3 of CMTMR orange dyes. Dilutions used for adjacent clusters across the 640-670 axis were labelled with alternate dilutions of CFSE and CMTMR Orange (as shown in the overlaid plots) in order to reduce spill-over in case of suboptimal separation between clusters across the channel-dye combination with the lowest stain index.
Supplementary Figure 5 Increased frequency of HlyE- and CdtB- specific T cells in volunteers diagnosed with enteric fever
(a) Frequency of HlyE, CdtB and Flu specific T cell responses 28 days after challenge measured by IFN-g ELISPOT in volunteers challenged with S. Typhi or S. Paratyphi A who developed (Diagnosed, D, n = 12) or did not develop (Not Diagnosed, ND, n = 9)) enteric fever compared to uninfected controls (HC. n = 10). Freshly isolated PBMC were rested overnight and incubated with 5μg/ml of HlyE or CdtB peptide pools, or with inactivated seasonal influenza vaccine (Flu). Mann Witney two tailed t-test. * = p < 0.05; ** = p < 0.005. Box extends from the 25th to the 75th percentile and whiskers from the minimum to the maximum value; line indicates median.
(a) Monocyte derived macrophages (MF) were differentiated for 5 days in the lower chamber of 24 well transwell plates. At day 5 a pool of 3 CdtB specific clones (T) was added to the upper well in the presence or absence of CdtB peptide pool (CdtB). After O.N. incubation, upper well was removed, macrophages were washed, infected with S. Typhimurium (LT2 strain) for 30 m, washed again and incubated with Gentamicin (30 mg/ml) to limit bacterial overgrowth. 2 h after infection cell culture supernatant was plated in agar plates and colonies counted after over night culture. Indicated is the percentage of bacterial growth compared to macrophages alone (n = 6, Friedman test (p = 0.0008) with Dunn’s multiple comparisons test (control vs T + CdtB p = 0.0169). Box extends from the 25th to the 75th percentile and whiskers from the minimum to the maximum value; line indicates median. (b) CFU after O.N. culture of macrophage supernatant in agar plate in one representative experiment.
Supplementary Figure 7 Increased frequency of CdtB, HlyE, and PhoN T cell responses after diagnosis with enteric fever
(a) Frequency of HlyE, CdtB, and Flu specific T cell responses at baseline and 28 days after challenge measured by IFN-g ELISPOT in frozen PBMC from volunteers challenged with S. Typhi or S. Paratyphi A who developed (n = 19) enteric fever (Wilcoxon matched-pairs signed rank test). (b) Frequency of HlyE, CdtB, PhoN and Flu specific T cell responses in HLADRB4 + and HLADRB4- volunteers 28 days after challenge (Mann Whitney test two-tailed p value). (c) Frequency of PhoN specific T cell responses at baseline and 28 days after challenge measured by IFN-g ELISPOT in frozen PBMC from volunteers challenged with S. Typhi or S. Paratyphi A who developed (n = 19) enteric fever and in HLADRB4+ and HLADRB4- individuals. ELISPOT analysis done on the same frozen samples as in panel a and b.
(a) Rarefaction curve describing the estimated diversity of the CDR3β repertoire of CD38+CCR7- and CD38-CCR7- subsets in volunteers P1 and T4. Dots between continuous and dashed curves indicate the number of TCRs identified within each sample. Number of cells probed: P1 CD38+CCR7- = 5087 cells, CD38-CCR7- = 1.15e105 cells; T4 CD38+CCR7- = 9130 cells, CD38-CCR7- = 1.3e105 cells. (b) Pathogen selectivity, antigen specificity, restriction, CDR3α and CDR3β sequence of clones isolated from volunteer P1. Starred(*) sequences were identified also in the polyclonal analysis. (c) Pie Chart depicting the frequency of CDR3β sequences within the polyclonal repertoire of CD38+CCR7- cells (5087 cells probed) from T4, highlighted are the CDR3β sequences identified in the isolated clones. (d) Frequency of CDR3β within the polyclonal repertoire of CD38+CCR7- cells and CD38-CCR7- cells in volunteer P1 (1.15e105 cells probed). Red circles represent CDR3β sequences identified in the isolated clones.
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Napolitani, G., Kurupati, P., Teng, K.W.W. et al. Clonal analysis of Salmonella-specific effector T cells reveals serovar-specific and cross-reactive T cell responses. Nat Immunol 19, 742–754 (2018). https://doi.org/10.1038/s41590-018-0133-z
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