Publisher Correction: Clonal analysis of Salmonella-specific effector T cells reveals serovar-specific and cross-reactive T cell responses.

In the version of this article initially published, the first affiliation lacked 'MRC'; the correct name of the institution is 'MRC Weatherall Institute of Molecular Medicine'. Two designations (SP110Y and ST110H) were incorrect in the legend to Fig. 6f,h,i. The correct text is as follows: for panel f, "...loaded with either the CdtB(105-125)SP110Y (DRB4*SP110Y) or the CdtB(105-125)ST110H (DRB4*ST110H) peptide variants..."; for panel h, "...decorated by the DRB4*SP110Y tetramer (lower-right quadrant), the DRB4*ST110H (upper-left quadrant)..."; and for panel i, "...stained ex vivo with DRB4*SP110Y, DRB4*ST110H...". In Fig. 8e, the final six residues (LTEAFF) of the sequence in the far right column of the third row of the table were missing; the correct sequence is 'CASSYRRTPPLTEAFF'. In the legend to Fig. 8d, a designation (HLyE) was incorrect; the correct text is as follows: "(HlyE?)." Portions of the Acknowledgements section were incorrect; the correct text is as follows: "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.),...the Oxford Biomedical Research Centre (A.J.P., V.C.),...and core funding from the Singapore Immunology Network (SIgN) (E.W.N.) and the SIgN immunomonitoring platform (E.W.N.)." Finally, a parenthetical element was phrased incorrectly in the final paragraph of the Methods subsection "T cell cloning and live fluorescence barcoding"; the correct phrasing is as follows: "...(which in all cases included HlyE, CdtB, Ty21a, Quailes, NVGH308, and LT2 strains and in volunteers T5 and T6 included PhoN)...". Also, in Figs. 3c and 4a, the right outlines of the plots were not visible; in the legend to Fig. 3, panel letter 'f' was not bold; and in Fig. 8f, 'ND' should be aligned directly beneath DRB4 in the key and 'ND' should be removed from the diagram at right, and the legend should be revised accordingly as follows: "...colors indicate the HLA class II restriction (gray indicates clones for which restriction was not determined (ND)). Clonotypes are grouped on the basis of pathogen selectivity (continuous line), protein specificity (dashed line) and epitope specificity; for ten HlyE-specific clones (pixilated squares), the epitope specificity was not determined...". The errors have been corrected in the HTML and PDF versions of the article.

Clonal analysis of Salmonella-specific effector T cells reveals serovar-specific and cross-reactive T cell responses.

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.

The impact of ischemia-reperfusion injuries on skin resident murine dendritic cells.

Pressure ulcers are a chronic problem for patients or the elderly who require extended periods of bed rest. The formation of ulcers is due to repeated cycles of ischemia-reperfusion (IR), which initiates an inflammatory response. Advanced ulcers disrupt the skin barrier, resulting in further complications. To date, the immunological aspect of skin IR has been understudied, partly due to the complexity of the skin immune cells. Through a combination of mass cytometry, confocal imaging and intravital multiphoton imaging, this study establishes a workflow for multidimensionality single cell analysis of skin myeloid cell responses in the context of IR injury with high spatiotemporal resolution. The data generated has provided us with previously uncharacterized insights into the distinct cellular behavior of resident dendritic cells (DCs) and recruited neutrophils post IR. Of interest, we observed a drop in DDC numbers in the IR region, which was subsequently replenished 48h post IR. More importantly, in these cells, we observe an attenuated response to repeated injuries, which may have implications in the subsequent wound healing process.

Establishing High Dimensional Immune Signatures from Peripheral Blood via Mass Cytometry in a Discovery Cohort of Stage IV Melanoma Patients.

The identification of blood-borne biomarkers correlating with melanoma patient survival remains elusive. Novel techniques such as mass cytometry could help to identify melanoma biomarkers, allowing simultaneous detection of up to 100 parameters. However, the evaluation of multiparametric data generated via time-of-flight mass cytometry requires novel analytical techniques because the application of conventional gating strategies currently used in polychromatic flow cytometry is not feasible. In this study, we have employed 38-channel time-of-flight mass cytometry analysis to generate comprehensive immune cell signatures using matrix boolean analysis in a cohort of 28 stage IV melanoma patients and 17 controls. Clusters of parameters were constructed from the abundance of cellular phenotypes significantly different between patients and controls. This approach identified patient-specific combinatorial immune signatures consisting of high-resolution subsets of the T cell, NK cell, B cell, and myeloid compartments. An association with superior survival was characterized by a balanced distribution of myeloid-derived suppressor cell-like and APC-like myeloid phenotypes and differentiated NK cells. The results of this study in a discovery cohort of melanoma patients suggest that multifactorial immune signatures have the potential to allow more accurate prediction of individual patient outcome. Further investigation of the identified immune signatures in a validation cohort is now warranted.

Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species.

Dendritic cells (DCs) are professional antigen-presenting cells that hold great therapeutic potential. Multiple DC subsets have been described, and it remains challenging to align them across tissues and species to analyze their function in the absence of macrophage contamination. Here, we provide and validate a universal toolbox for the automated identification of DCs through unsupervised analysis of conventional flow cytometry and mass cytometry data obtained from multiple mouse, macaque, and human tissues. The use of a minimal set of lineage-imprinted markers was sufficient to subdivide DCs into conventional type 1 (cDC1s), conventional type 2 (cDC2s), and plasmacytoid DCs (pDCs) across tissues and species. This way, a large number of additional markers can still be used to further characterize the heterogeneity of DCs across tissues and during inflammation. This framework represents the way forward to a universal, high-throughput, and standardized analysis of DC populations from mutant mice and human patients.

A High-Dimensional Atlas of Human T Cell Diversity Reveals Tissue-Specific Trafficking and Cytokine Signatures.

Depending on the tissue microenvironment, T cells can differentiate into highly diverse subsets expressing unique trafficking receptors and cytokines. Studies of human lymphocytes have primarily focused on a limited number of parameters in blood, representing an incomplete view of the human immune system. Here, we have utilized mass cytometry to simultaneously analyze T cell trafficking and functional markers across eight different human tissues, including blood, lymphoid, and non-lymphoid tissues. These data have revealed that combinatorial expression of trafficking receptors and cytokines better defines tissue specificity. Notably, we identified numerous T helper cell subsets with overlapping cytokine expression, but only specific cytokine combinations are secreted regardless of tissue type. This indicates that T cell lineages defined in mouse models cannot be clearly distinguished in humans. Overall, our data uncover a plethora of tissue immune signatures and provide a systemic map of how T cell phenotypes are altered throughout the human body.