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Tissue CD14+CD8+ T cells reprogrammed by myeloid cells and modulated by LPS

Abstract

The liver is bathed in bacterial products, including lipopolysaccharide transported from the intestinal portal vasculature, but maintains a state of tolerance that is exploited by persistent pathogens and tumours1,2,3,4. The cellular basis mediating this tolerance, yet allowing a switch to immunity or immunopathology, needs to be better understood for successful immunotherapy of liver diseases. Here we show that a variable proportion of CD8+ T cells compartmentalized in the human liver co-stain for CD14 and other prototypic myeloid membrane proteins and are enriched in close proximity to CD14high myeloid cells in hepatic zone 2. CD14+CD8+ T cells preferentially accumulate within the donor pool in liver allografts, among hepatic virus-specific and tumour-infiltrating responses, and in cirrhotic ascites. CD14+CD8+ T cells exhibit increased turnover, activation and constitutive immunomodulatory features with high homeostatic IL-10 and IL-2 production ex vivo, and enhanced antiviral/anti-tumour effector function after TCR engagement. This CD14+CD8+ T cell profile can be recapitulated by the acquisition of membrane proteins—including the lipopolysaccharide receptor complex—from mononuclear phagocytes, resulting in augmented tumour killing by TCR-redirected T cells in vitro. CD14+CD8+ T cells express integrins and chemokine receptors that favour interactions with the local stroma, which can promote their induction through CXCL12. Lipopolysaccharide can also increase the frequency of CD14+CD8+ T cells in vitro and in vivo, and skew their function towards the production of chemotactic and regenerative cytokines. Thus, bacterial products in the gut–liver axis and tissue stromal factors can tune liver immunity by driving myeloid instruction of CD8+ T cells with immunomodulatory ability.

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Fig. 1: CD14+CD8+ T cells in the human liver.
Fig. 2: Derivation of CD14+CD8+ T cells.
Fig. 3: Immunomodulatory function of CD14+CD8+ T cells.
Fig. 4: Bacterial LPS shapes CD14+CD8+ T cells.

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Data availability

The source data used within the main figures is available in the Supplementary Information and at Figshare (https://doi.org/10.6084/m9.figshare.21623379). scRNA-seq data have been deposited in the European Genome–Phenome Archive under accession number EGAS00001006885. Further datasets generated during and/or analysed as part of this study are available from the corresponding authors on reasonable request. Source data are provided with this paper.

Code availability

Custom codes used in this study are available at GitHub. For the heat-map visualization used to display the soluble mediator profiles of CD14-expressing CD8+ T cells, the custom code created is available at GitHub (https://github.com/ljpallett/pallettetal_2022_luminex). For the image mass cytometry analysis, the custom code created is available at GitHub (https://github.com/ljpallett/pallettetal_2022_imc).

References

  1. Crispe, I. N. Immune tolerance in liver disease. Hepatology 60, 2109–2117 (2014).

    Article  CAS  Google Scholar 

  2. Protzer, U., Maini, M. K. & Knolle, P. A. Living in the liver: hepatic infections. Nat. Rev. Immunol. 12, 201–213 (2012).

    Article  CAS  Google Scholar 

  3. Macpherson, A. J., Heikenwalder, M. & Ganal-Vonarburg, S. C. The liver at the nexus of host-microbial interactions. Cell Host Microbe 20, 561–571 (2016).

    Article  CAS  Google Scholar 

  4. Wiest, R., Lawson, M. & Geuking, M. Pathological bacterial translocation in liver cirrhosis. J. Hepatol. 60, 197–209 (2014).

    Article  Google Scholar 

  5. Tripathi, A. et al. The gut-liver axis and the intersection with the microbiome. Nat. Rev. Gastroenterol. Hepatol. 15, 397–411 (2018).

    Article  CAS  Google Scholar 

  6. Pallett, L. J. et al. IL-2high tissue-resident T cells in the human liver: sentinels for hepatotropic infection. J. Exp. Med. 214, 1567–1580 (2017).

    Article  CAS  Google Scholar 

  7. Burel, J. G. et al. Circulating T cell-monocyte complexes are markers of immune perturbations. eLife 8, e46045 (2019).

    Article  Google Scholar 

  8. Pallett, L. J. et al. Longevity and replenishment of human liver-resident memory T cells and mononuclear phagocytes. J. Exp. Med. 217, e20200050 (2020).

    Article  Google Scholar 

  9. Fernandez-Ruiz, D. et al. Liver-resident memory CD8+ T cells form a front-line defense against malaria liver-stage infection. Immunity 45, 889–902 (2016).

    Article  CAS  Google Scholar 

  10. Curbishley, S. M., Eksteen, B., Gladue, R. P., Lalor, P. & Adams, D. H. CXCR3 activation promotes lymphocyte transendothelial migration across human hepatic endothelium under fluid flow. Am. J. Pathol. 167, 887–899 (2005).

    Article  CAS  Google Scholar 

  11. Liepelt, A. & Tacke, F. Stromal cell-derived factor-1 (SDF-1) as a target in liver diseases. Am. J. Physiol. Gastrointest. Liver Physiol. 311, G203–G209 (2016).

    Article  Google Scholar 

  12. Neumann, K. et al. Chemokine transfer by liver sinusoidal endothelial cells contributes to the recruitment of CD4+ T cells into the murine liver. PLoS ONE 10, e0123867 (2015).

    Article  Google Scholar 

  13. Mazza, G. et al. Rapid production of human liver scaffolds for functional tissue engineering by high shear stress oscillation-decellularization. Sci. Rep. 7, 5534 (2017).

    Article  ADS  Google Scholar 

  14. McQuitty, C. E., Williams, R., Chokshi, S. & Urbani, L. Immunomodulatory role of the extracellular matrix within the liver disease microenvironment. Front. Immunol. 11, 574276 (2020).

    Article  CAS  Google Scholar 

  15. McNamara, H. A. et al. Up-regulation of LFA-1 allows liver-resident memory T cells to patrol and remain in the hepatic sinusoids. Sci. Immunol. 2, eaaj1996 (2017).

    Article  Google Scholar 

  16. Benechet, A. P. et al. Dynamics and genomic landscape of CD8+ T cells undergoing hepatic priming. Nature 574, 200–205 (2019).

    Article  CAS  ADS  Google Scholar 

  17. De Simone, G. et al. Identification of a Kupffer cell subset capable of reverting the T cell dysfunction induced by hepatocellular priming. Immunity 54, 2089–2100 (2021).

    Article  Google Scholar 

  18. Wei, Y. et al. Liver homeostasis is maintained by midlobular zone 2 hepatocytes. Science 371, eabb1625 (2021).

    Article  CAS  Google Scholar 

  19. Baumann, T. et al. Regulatory myeloid cells paralyze T cells through cell-cell transfer of the metabolite methylglyoxal. Nat. Immunol. 21, 555–566 (2020).

    Article  CAS  Google Scholar 

  20. Crispe, I. N. The liver as a lymphoid organ. Annu. Rev. Immunol. 27, 147–163 (2009).

    Article  CAS  Google Scholar 

  21. Huang, L. R. et al. Intrahepatic myeloid-cell aggregates enable local proliferation of CD8+ T cells and successful immunotherapy against chronic viral liver infection. Nat. Immunol. 14, 574–583 (2013).

    Article  CAS  Google Scholar 

  22. Krenkel, O. & Tacke, F. Liver macrophages in tissue homeostasis and disease. Nat. Rev. Immunol. 17, 306–321 (2017).

    Article  CAS  Google Scholar 

  23. Pallett, L. J. & Maini, M. K. Liver-resident memory T cells: life in lockdown. Semin. Immunopathol. 44, 813–825 (2022).

    Article  CAS  Google Scholar 

  24. Legut, M. et al. A genome-scale screen for synthetic drivers of T cell proliferation. Nature 603, 728–735 (2022).

    Article  CAS  ADS  Google Scholar 

  25. Kumar, B. V. et al. Human tissue-resident memory T cells are defined by core transcriptional and functional signatures in lymphoid and mucosal sites. Cell Rep. 20, 2921–2934 (2017).

    Article  CAS  Google Scholar 

  26. Smith, L. K. et al. Interleukin-10 directly inhibits CD8+ T cell function by enhancing N-glycan branching to decrease antigen sensitivity. Immunity 48, 299–312 (2018).

    Article  CAS  Google Scholar 

  27. Fioravanti, J. et al. Effector CD8+ T cell-derived interleukin-10 enhances acute liver immunopathology. J. Hepatol. 67, 543–548 (2017).

    Article  CAS  Google Scholar 

  28. Schurich, A. et al. Dynamic regulation of CD8 T cell tolerance induction by liver sinusoidal endothelial cells. J. Immunol. 184, 4107–4114 (2010).

    Article  CAS  Google Scholar 

  29. Tan, A. T. et al. Use of expression profiles of HBV-DNA integrated into genomes of hepatocellular carcinoma cells to select T Cells for immunotherapy. Gastroenterology 156, 1862–1876 (2019).

    Article  CAS  Google Scholar 

  30. Frey, E. A. et al. Soluble CD14 participates in the response of cells to lipopolysaccharide. J. Exp. Med. 176, 1665–1671 (1992).

    Article  CAS  Google Scholar 

  31. Komai-Koma, M., Gilchrist, D. S. & Xu, D. Direct recognition of LPS by human but not murine CD8+ T cells via TLR4 complex. Eur. J. Immunol. 39, 1564–1572 (2009).

    Article  CAS  Google Scholar 

  32. Yoshimura, A. et al. Cutting edge: recognition of Gram-positive bacterial cell wall components by the innate immune system occurs via Toll-like receptor 2. J. Immunol. 163, 1–5 (1999).

    Article  CAS  Google Scholar 

  33. Zanoni, I. & Granucci, F. Role of CD14 in host protection against infections and in metabolism regulation. Front. Cell Infect. Microbiol. 3, 32 (2013).

    Article  Google Scholar 

  34. Sakai, N. et al. Interleukin-33 is hepatoprotective during liver ischemia/reperfusion in mice. Hepatology 56, 1468–1478 (2012).

    Article  CAS  Google Scholar 

  35. Taub, R. Hepatoprotection via the IL-6/Stat3 pathway. J. Clin. Invest. 112, 978–980 (2003).

    Article  CAS  Google Scholar 

  36. Taub, D. D., Anver, M., Oppenheim, J. J., Longo, D. L. & Murphy, W. J. T lymphocyte recruitment by interleukin-8 (IL-8). IL-8-induced degranulation of neutrophils releases potent chemoattractants for human T lymphocytes both in vitro and in vivo. J. Clin. Invest. 97, 1931–1941 (1996).

    Article  CAS  Google Scholar 

  37. Gehring, A. J. et al. Licensing virus-specific T cells to secrete the neutrophil attracting chemokine CXCL-8 during hepatitis B virus infection. PLoS ONE 6, e23330 (2011).

    Article  CAS  ADS  Google Scholar 

  38. Foussat, A. et al. Production of stromal cell-derived factor 1 by mesothelial cells and effects of this chemokine on peritoneal B lymphocytes. Eur. J. Immunol. 31, 350–359 (2001).

    Article  CAS  Google Scholar 

  39. Albillos, A. et al. Increased lipopolysaccharide binding protein in cirrhotic patients with marked immune and hemodynamic derangement. Hepatology 37, 208–217 (2003).

    Article  CAS  Google Scholar 

  40. Sierro, F. et al. A liver capsular network of monocyte-derived macrophages restricts hepatic dissemination of intraperitoneal bacteria by neutrophil recruitment. Immunity 47, 374–388 (2017).

    Article  CAS  Google Scholar 

  41. Motwani, M. P. et al. Pro-resolving mediators promote resolution in a human skin model of UV-killed Escherichia coli-driven acute inflammation. JCI Insight 3, e94463 (2018).

    Article  Google Scholar 

  42. Nowarski, R., Jackson, R. & Flavell, R. A. The stromal intervention: regulation of immunity and inflammation at the epithelial-mesenchymal barrier. Cell 168, 362–375 (2017).

    Article  CAS  Google Scholar 

  43. Croft, A. P. et al. Distinct fibroblast subsets drive inflammation and damage in arthritis. Nature 570, 246–251 (2019).

    Article  CAS  ADS  Google Scholar 

  44. Krausgruber, T. et al. Structural cells are key regulators of organ-specific immune responses. Nature 583, 296–302 (2020).

    Article  CAS  ADS  Google Scholar 

  45. Gola, A. et al. Commensal-driven immune zonation of the liver promotes host defence. Nature 589, 131–136 (2021).

    Article  CAS  ADS  Google Scholar 

  46. Bonnardel, J. et al. Stellate cells, hepatocytes, and endothelial cells imprint the Kupffer cell identity on monocytes colonizing the liver macrophage niche. Immunity 51, 638–654 (2019).

    Article  CAS  Google Scholar 

  47. Seki, E. et al. TLR4 enhances TGF-β signaling and hepatic fibrosis. Nat. Med. 13, 1324–1332 (2007).

    Article  CAS  Google Scholar 

  48. Zanin-Zhorov, A. et al. Cutting edge: T cells respond to lipopolysaccharide innately via TLR4 signaling. J. Immunol. 179, 41–44 (2007).

    Article  CAS  Google Scholar 

  49. Seki, E. & Brenner, D. A. Toll-like receptors and adaptor molecules in liver disease: update. Hepatology 48, 322–335 (2008).

    Article  CAS  Google Scholar 

  50. Kucykowicz, S. et al. Isolation of human intrahepatic leukocytes for phenotypic and functional characterization by flow cytometry. STAR Protoc. 3, 101356 (2022).

    Article  CAS  Google Scholar 

  51. Cossarizza, A. et al. Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition). Eur. J. Immunol. 51, 2708–3145 (2021).

  52. Singh, H. D. et al. TRAIL regulatory receptors constrain human hepatic stellate cell apoptosis. Sci Rep. 7, 5514 (2017).

    Article  ADS  Google Scholar 

  53. Daubeuf, S., Puaux, A. L., Joly, E. & Hudrisier, D. A simple trogocytosis-based method to detect, quantify, characterize and purify antigen-specific live lymphocytes by flow cytometry, via their capture of membrane fragments from antigen-presenting cells. Nat. Protoc. 1, 2536–2542 (2006).

    Article  CAS  Google Scholar 

  54. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis Nat. Methods 9, 676–682 (2012).

  55. Schwabenland, M. et al. Deep spatial profiling of human COVID-19 brains reveals neuroinflammation with distinct microanatomical microglia-T-cell interactions. Immunity 54, 1594–1610 (2021).

    Article  CAS  Google Scholar 

  56. McAdam, S. et al. Cross-clade recognition of p55 by cytotoxic T lymphocytes in HIV-1 infection. Aids 12, 571–579 (1998).

    Article  CAS  Google Scholar 

  57. Schmittgen, T. D. & Livak, K. J. Analyzing real-time PCR data by the comparative CT method. Nat. Protoc. 3, 1101–1108 (2008).

    Article  CAS  Google Scholar 

  58. Picelli, S. et al. Full-length RNA-seq from single cells using Smart-seq2. Nat. Protoc. 9, 171–181 (2014).

    Article  CAS  Google Scholar 

  59. Popescu, D. M. et al. Decoding human fetal liver haematopoiesis. Nature 574, 365–371 (2019).

    Article  CAS  ADS  Google Scholar 

  60. Wolock, S. L., Lopez, R. & Klein, A. M. Scrublet: computational identification of cell doublets in single-cell transcriptomic data. Cell Syst. 8, 281–291 (2019).

    Article  CAS  Google Scholar 

  61. Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019).

    Article  CAS  Google Scholar 

  62. Pavesi, A. et al. A 3D microfluidic model for preclinical evaluation of TCR-engineered T cells against solid tumors. JCI Insight 2, e89762 (2017).

    Article  Google Scholar 

Download references

Acknowledgements

We thank all of the patients and control volunteers who participated in this study, and all of the clinical staff who helped with participant recruitment, including the members of the Tissue Access for Patient Benefit Initiative at The Royal Free Hospital; H. Stauss for his suggestions; D. Dixon for help with the cytospin microscopy; the support staff at the UCL Infection and Immunity Flow Cytometry Core Facility; and P. S. Chana for his help with the imaging cytometry analysis. This work was funded by Wellcome Investigator Awards (101849/Z/13/A and 214191/Z/18/Z), a Medical Research Council grant (G0801213), a CRUK Immunology grant (26603) and a Hunter Accelerator award to M.K.M.; a UKRI Future Leader Fellowship to L.J.P.; a Medical Research Foundation grant to L.S.; a Wellcome Clinical Research Training Fellowship to U.S.G. (107389/Z/15/Z); a European Research Council H2020 Starter grant (ERC-StG-2015-637304) and the Wellcome New Investigator award (104771/A/14/Z) to M. Dorner; and the Berta Ottenstein Programme and IMM-PACT-Programme for Clinician Scientists, University of Freiburg funded by the Deutsche Forschungsgemeinschaft 413517907 to M.S.

Author information

Authors and Affiliations

Authors

Contributions

L.J.P., A.S. and M.K.M. conceived the project. L.J.P., D.W.G., M. Dorner, B.B., A.S., B.M.C., M.H. and M.K.M. designed experiments. J.D., J.K.S., K.A.S., K.S., M. Diniz, A.R.B., I.U., O.E.A., E.S. and W.A.-A. prepared samples. L.J.P., L.S., M. Diniz, A.A.M., M.S., A.D.G., M.W., J.S., R.d.M., C.T., J.D., S.K., J.K.S., N.M.S., O.E.A., A.R.B., E.S., G.R., M.W., J.S., R.d.M., C.T., I.U. and A.M.O.-P. generated data. L.J.P., L.S., G.R., N.T., B.M.C., M.S., A.D.G., M.P., B.B., M.H. and M.K.M. analysed data. A.A.M., U.S.G., C.G., F.F., S.L., S.P.-D.-P., G.F., P.T.F.K., B.R.D., W.A.-A., G.M., M.N. and A.A. provided essential models or patient samples/clinical analysis. L.J.P. and M.K.M. prepared the manuscript and all of the other authors provided input to the manuscript.

Corresponding authors

Correspondence to Laura J. Pallett or Mala K. Maini.

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Competing interests

M.K.M. and L.J.P. have received project funding from Gilead for research unrelated to this manuscript. M.K.M. has sat on advisory boards/provided consultancy for Gilead, Roche, GSK and VirBiosciences. L.J.P. has sat on advisory boards/provided consultancy for Gilead and SQZ Biotech. M.K.M. and L.J.P. have a patent application P116607GB filed through UCL-Business on the use of CD14+CD8+ T cells.

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Extended data figures and tables

Extended Data Fig. 1 Confirmation of CD14+CD8+ T cells in human liver.

a Flow cytometric gating strategy defining CD14+CD8+ T cells in human liver with sequential exclusion of: debris and MNP by forward (FSC-A) and side scatter (SSC-A), doublets, dead cells, CD45, CD3, CD56+, CD19+, and CD3+CD4+ T cells. b Representative flow cytometric staining of peripheral and intrahepatic CD14+CD8+ T cells (using a different clone, and company than example shown in Fig. 1a). c Representative histograms of αβTCR and CD3ζ expression on intrahepatic CD14CD8+ T cells (black outline), CD14+CD8+ T cells (blue filled) and classical MNP (large SSC-A, LinHLA-DR+CD3CD14+; grey filled). d Summary data: cell size using FSC-A (n = 80) and CD45 expression (n = 28) on CD14CD8+ T cells and CD14+CD8+ T cells. e CD14 percentage on CD3CD56+ NK cells, CD3+CD8CD4+ T cells and CD3+CD4-CD8+ T cells from the same donors (n = 28). f Summary data: percentage of CD69 (n = 89) and CD103 (n = 96) on intrahepatic CD14CD8+ T cells or CD14+CD8+ T cells. g Representative plots showing the frequency of donor-derived (donor-HLA+) or recipient-derived (donor-HLA-) CD14CD8+ T cells and CD14+CD8+ T cells. h Frequency of donor-derived CD14+CD8+ T cells in liver allografts explanted after 8 months-11 yrs from HLA-haplotype disparate recipients (n = 5) using the gating strategy in Fig. 1h. Each dot (or pair of dots) represent(s) a study participant, processed, stained and analysed independently; bars represent mean. e and f solid lines: median, dotted lines: IQR. p-values determined using either a Kruskal-Wallis test (ANOVA) with Dunn’s multiple comparisons test e; or two-tailed Wilcoxon t Test d,f.

Extended Data Fig. 2 Residency and transcriptional features of CD14+CD8+ T cells.

a Representative plots: %CD14 on peripheral CD8+ T cells after PBMC and pHSC co-culture (representative of four PBMC donors with 3 pHSC donors). b Summary data: in vitro induction of CD14+CD8+ T cells after PBMC and pHSC co-culture (4d; PBMC donors used with: pHSC#1 n = 15; pHSC#2 n = 30; and pHSC#3 n = 24). c Summary data: MFI of TLR4 (n = 4) and TLR2 (n = 7) of pHSC-induced CD14CD8+ T cells (black outline) or CD14+CD8+ T cells (blue filled). d %CD14 on peripheral CD8+ T cells after PBMC cultured ± 3D de-cellularised human liver ‘extracellular matrix scaffolds’ (3 d; n = 12 PBMC donors; 3 experiments). e Frequency of peripheral CD14+CD8+ T cells after co-culture of purified CD8+ T cells with a varied ratio of autologous MNP (4d; n = 11). f Flow cytometric gating strategy used to isolate ex vivo or stromal-cell induced CD14+CD8+ T cells with the sequential exclusion of: debris and MNP by forward (FSC-A) and side scatter (SSC-A), doublets, dead cells, CD45, CD3, CD56+, CD3+CD4+ T cells and γδT-cells/Vα7.2+ T cells (strategy used for experiments shown in Fig. 4b and Extended Data Fig. 2g–i, 3g and 4b). g Assessment of CD14 mRNA by RT-PCR (relative to 18S control) of FACS-sorted Lin-HLA-DR+CD3-CD14+ MNP, ex vivo intrahepatic CD14CD8+ T cells and CD14+CD8+ T cells (n = 5). h Percentage expression and relative levels of T-cell genes by scRNAseq transcriptome analysis of FACS-sorted intrahepatic CD14CD8+ T cells, CD14+CD8+ T cells or LinHLA-DR+CD3CD14+ MNP (n = 2 liver samples). i Histogram plot: CD14 mRNA transcript expression and UMAP depicting the transcriptomic profile of FACS-sorted intrahepatic CD14CD8+ T cells (red), CD14+CD8+ T cells (green) or LinHLA-DR+CD3CD14+ MNP (blue; n = 2 samples). j Frequency of peripheral CD14+CD8+ T cells after co-culture of purified CD8+ T cells ± MNP supplemented with nocodozole (4d; n = 10). k MFI of CD14 on CD14+CD8+ T cells after co-culture ± MNP supplemented with latrunculin B or nocodozole (n = 10). l Representative and summary data: Percentage CD14 expression on CD8+ T cells post co-culture ± MDM or MNP isolated from the same donor (n = 9). m Representative confocal images of purified CD8+ T cells co-cultured with MDM (4d; images representative of 2 donors) and summary data: comparison of MFI of CD14 on the T-cell population post culture with media alone or autologous MDM (defined by identification of the cell boundary segmented using the extent of CD8+ expression). n (left panel) CD14 signal intensity of MDM-derived exosomes from 3 donors and (right panel) percentage CD14 after co-culture of purified CD8+ T cell with concentrated MDM-derived exosomes or the autologous MDM from which exosomes were derived (4d; n = 3). o Representative plots: MFI of MD-2, TLR4, HLA-DR and TLR2 on peripheral T-cells co-expressing (or lacking) CD14 and the biotin-streptavidin complex after exposure to biotin-labelled MNP. p Summary data: frequency of intrahepatic CD14+CD8+ T cells as determined by imaging mass cytometry (IMC) (mean ±S.E.M. of percentage expression in two distinct regions of interest/liver). q Representative IMC image of macroscopically healthy liver tissue sections (2 regions of interest captured from n = 3 sections) as shown in Fig. 2n with the demarcation of three liver zones defined by intensity of CYP1A2 staining (scale bar: 200 µm; magnification: 50 µm); enrichment scores of the zonal localization of intrahepatic CD14CD8+ T cells and CD14+CD8+ T cells. Each dot (or pair of dots) represent(s) a study participant, processed, stained and analysed independently; bars represent mean and error bars (where appropriate) represent ± S.E.M. b,e,j-m solid lines: median, dotted lines: IQR. p-values determined using either a Kruskal-Wallis test (ANOVA) with Dunn’s multiple comparisons test b (compared to media alone), j,k (compared to MNP + T-cells); or two-tailed Wilcoxon t Test c–d,l,m.

Extended Data Fig. 3 Nutrient transporter and immunomodulatory profile of intrahepatic CD14+CD8+ T cells and soluble mediator profile of stromal cell-derived CD14+CD8+ T cells.

Representative flow cytometric plots and summary data: MFI expression of a CD98 (n = 19) and CD71 (n = 14) and b Foxp3 (n = 32) and CTLA-4 (n = 19) of ex vivo intrahepatic CD14CD8+ T cell (black outline) and CD14+CD8+ T cells (blue filled). c Heatmap showing relative expression (fold change) of immunomodulatory markers on CD14+CD8+ T cells compared to their CD14CD8+ T cell counterparts. d Assessment of intrahepatic CD14+CD8+ T cell intracellular cytokine production ± 4 h anti-CD3/CD28 stimulation in the presence of brefeldin-A: IL-10 (n = 15) and IL-2 (n = 19) e Assessment of CD14+CD8+ T cell production of IL-10 (n = 15) and IL-2 (n = 19), and IFNγ (n = 19) andMIP1β (n = 12) afte 4 h anti-CD3/CD28 stimulation further defined by co-expression of CD69 and CD103. f Summary data: peripheral stromal cell-induced CD14CD8+ T cell and CD14+CD8+ T cell populations post-stimulation with anti-CD3/CD28 by flow cytometric intracellular cytokine staining for IL-2, IFNγ, TNF (n = 15) and CD107a (n = 12) (4 h; upper panel) and by supernatant luminex detection of secreted IL-2, IFNγ, TNF, IL-10 and granzyme B from FACS-sorted stromal cell-induced populations (n = 5; 16 h; lower panel). g Example flow cytometry plots: gating strategy for the FACS-sorting of TCR-transduced CD8+ T cells with or without CD14 staining using the murineTCRβ (mTCR) region contained within the transgene. Each dot (or pair of dots) represent(s) a study participant, processed, stained and analysed independently; bars represent mean, error bars (where appropriate) represent ± S.E.M. d solid lines: median, dotted lines: IQR. p-values determined using either a Kruskal-Wallis test (ANOVA) with Dunn’s multiple comparisons test d,f; or a two-tailed Wilcoxon t Test a–b,e.

Extended Data Fig. 4 LPS-induced effects on CD14+CD8+ T cells in vitro.

a MFI of bound LPSAlexaFluor488 on stromal cell and MNP-induced CD14CD8+ T cells or CD14+CD8+ T cells (n = 5) after culture for 120 min with LPSAlexaFluor488, or media alone. b UMAP: soluble mediator profiles produced by FACS-sorted stromal cell-induced CD14+CD8+ T cells ± stimulation with media alone (purple), 0.3 × 106 UV-killed E. coli (green) or anti-CD3/28 (orange). c Percentage CD14 on intrahepatic CD8+ T cells ± 72 h exposure to 0.3 × 106 UV-killed E. coli as a proportion of total CD8+ T cells (n = 14) or a proportion of total intrahepatic leukocytes (CD45+; n = 13). d CFSE dilution of intrahepatic CD14-labelled CD14+CD8+ T cells after 72 h culture in vitro in the presence of UV-killed E. coli and e the co-expression of intrahepatic CD14-labelled CD14+CD8+ T cells (APC; prelabelled on d 0) and further stained with CD14PE 72 h after in vitro culture in the presence of 0.3 × 106 UV-killed E. coli. f MFI expression of CD49b (n = 6) and CXCR4 (n = 8) on peripheral CD14 ± CD8+ T cells after co-culture in the presence of LPS. g Representative plots and summary data: MFI of TLR2 and TLR4 (n = 7) on ascitic CD14CD8+ T cells (black outline) or CD14+CD8+ T cells (blue filled) ex vivo. h Frequency of CD14+CD8+ T cells isolated from human skin punch biopsies (n = 6; taken from the forearm of healthy controls) or from skin blister aspirates (n = 7; control blister). i CD14+CD8+ T cells as a proportion of total leukocytes (CD45+) from blood (n = 8) or blister exudates (n = 8) with or without prior UV-killed E. coli intradermal injection. j TLR4 expression on CD8+ T cells aspirated from skin blisters ± UV-killed E. coli injection (representative of n = 3 blister exudates). k Expression of CD38 on CD14CD8+ T cells or CD14+CD8+ T cells from blister exudates ± UV-killed E. coli intradermal injection (n = 6). l Overview schematic of the functional role of CD14+CD8+ T cells. Each dot (or pair of dots) represent(s) a study participant, processed, stained and analysed independently; bars represent mean, error bars (where appropriate) represent ± S.E.M. a solid lines: median, dotted lines: IQR. p-values were determined using a Mann-Whitney U Test h; two-tailed Wilcoxon t Test c,g; or a two-tailed Kruskal-Wallis test (ANOVA) with Dunn’s multiple comparisons test f,i,k.

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Supplementary Tables 1 and 2: details of antibody fluorochromes, clones, manufacturers and the dilutions used for flow cytometry (Supplementary Table 1) and spectral imaging (Supplementary Table 2).

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Pallett, L.J., Swadling, L., Diniz, M. et al. Tissue CD14+CD8+ T cells reprogrammed by myeloid cells and modulated by LPS. Nature 614, 334–342 (2023). https://doi.org/10.1038/s41586-022-05645-6

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