Genome degradation correlates with host adaptation and systemic disease in Salmonella. Most lineages of the S. enterica subspecies Typhimurium cause gastroenteritis in humans; however, the recently emerged ST313 lineage II pathovar commonly causes systemic bacteremia in sub-Saharan Africa. ST313 lineage II displays genome degradation compared to gastroenteritis-associated lineages; yet, the mechanisms and causal genetic differences mediating these infection phenotypes are largely unknown. We find that the ST313 isolate D23580 hyperdisseminates from the gut to systemic sites, such as the mesenteric lymph nodes (MLNs), via CD11b⁺ migratory dendritic cells (DCs). This hyperdissemination was facilitated by the loss of sseI, which encodes an effector that inhibits DC migration in gastroenteritis-associated isolates. Expressing functional SseI in D23580 reduced the number of infected migratory DCs and bacteria in the MLN. Our study reveals a mechanism linking pseudogenization of effectors with the evolution of niche adaptation in a bacterial pathogen.

Given the limited efficacy of clinical approaches that rely on ex vivo generated dendritic cells (DCs), it is imperative to design strategies that harness specialized DC subsets in situ. This requires delineating the expression of surface markers by DC subsets among individuals and tissues. Here, we performed a multiparametric phenotypic characterization and unbiased analysis of human DC subsets in blood, tonsil, spleen, and skin. We uncovered previously unreported phenotypic heterogeneity of human cDC2s among individuals, including variable expression of functional receptors such as CD172a. We found marked differences in DC subsets localized in blood and lymphoid tissues versus skin, and a striking absence of the newly discovered Axl⁺ DCs in the skin. Finally, we evaluated the capacity of anti-receptor monoclonal antibodies to deliver vaccine components to skin DC subsets. These results offer a promising path for developing DC subset-specific immunotherapies that cannot be provided by transcriptomic analysis alone.

Experimental autoimmune encephalomyelitis is a model for multiple sclerosis. Here we show that induction generates successive waves of clonally expanded CD4⁺, CD8⁺ and γδ⁺ T cells in the blood and central nervous system, similar to gluten-challenge studies of patients with coeliac disease. We also find major expansions of CD8⁺ T cells in patients with multiple sclerosis. In autoimmune encephalomyelitis, we find that most expanded CD4⁺ T cells are specific for the inducing myelin peptide MOG_35-55. By contrast, surrogate peptides derived from a yeast peptide major histocompatibility complex library of some of the clonally expanded CD8⁺ T cells inhibit disease by suppressing the proliferation of MOG-specific CD4⁺ T cells. These results suggest that the induction of autoreactive CD4⁺ T cells triggers an opposing mobilization of regulatory CD8⁺ T cells.

Influenza is a significant cause of morbidity and mortality worldwide. Here we show changes in the abundance and activation states of more than 50 immune cell subsets in 35 individuals over 11 time points during human A/California/2009 (H1N1) virus challenge monitored using mass cytometry along with other clinical assessments. Peak change in monocyte, B cell, and T cell subset frequencies coincided with peak virus shedding, followed by marked activation of T and NK cells. Results led to the identification of CD38 as a critical regulator of plasmacytoid dendritic cell function in response to influenza virus. Machine learning using study-derived clinical parameters and single-cell data effectively classified and predicted susceptibility to infection. The coordinated immune cell dynamics defined in this study provide a framework for identifying novel correlates of protection in the evaluation of future influenza therapeutics.

Molecular characterization of cell types using single-cell transcriptome sequencing is revolutionizing cell biology and enabling new insights into the physiology of human organs. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. Using multiple tissues from a single donor enabled identification of the clonal distribution of T cells between tissues, identification of the tissue-specific mutation rate in B cells, and analysis of the cell cycle state and proliferative potential of shared cell types across tissues. Cell type-specific RNA splicing was discovered and analyzed across tissues within an individual.

Cell-free RNA from liquid biopsies can be analyzed to determine disease tissue of origin. We extend this concept to identify cell types of origin using the Tabula Sapiens transcriptomic cell atlas as well as individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset. We define cell type signature scores, which allow the inference of cell types that contribute to cell-free RNA for a variety of diseases.