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The role of Erythroid cells in immune regulation and immunosuppression is one of the emerging topics in modern immunology that still requires further clarification as Erythroid cells from different tissues and different species express different immunoregulatory molecules. In this study, we performed a thorough investigation of human bone marrow Erythroid cells from adult healthy donors and adult acute lymphoblastic leukemia patients using the state-of-the-art single-cell targeted proteomics and transcriptomics via BD Rhapsody and cancer-related gene copy number variation analysis via NanoString Sprint Profiler. We found that human bone marrow Erythroid cells express the ARG1, LGALS1, LGALS3, LGALS9 , and C10orf54 (VISTA) immunosuppressive genes, CXCL5, CXCL8 , and VEGFA cytokine genes, as well as the genes involved in antimicrobial immunity and MHC Class II antigen presentation. We also found that ARG1 gene expression was restricted to the single erythroid cell cluster that we termed ARG1-positive Orthochromatic erythroblasts and that late Erythroid cells lose S100A9 and gain MZB1 gene expression in case of acute lymphoblastic leukemia. These findings show that steady-state erythropoiesis bone marrow Erythroid cells express myeloid signature genes even without any transdifferentiating stimulus like cancer., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Perik-Zavodskii, Perik-Zavodskaia, Alrhmoun, Volynets, Shevchenko, Nazarov, Denisova and Sennikov.)

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Introduction: B cells play a pivotal role in adaptive immunity which has been extensively characterised primarily via flow cytometry-based gating strategies. This study addresses the discrepancies between flow cytometry-defined B cell subsets and their high-confidence molecular signatures using single-cell multi-omics approaches., Methods: By analysing multi-omics single-cell data from healthy individuals and patients across diseases, we characterised the level and nature of cellular contamination within standard flow cytometric-based gating, resolved some of the ambiguities in the literature surrounding unconventional B cell subsets, and demonstrated the variable effects of flow cytometric-based gating cellular heterogeneity across diseases., Results: We showed that flow cytometric-defined B cell populations are heterogenous, and the composition varies significantly between disease states thus affecting the implications of functional studies performed on these populations. Importantly, this paper draws caution on findings about B cell selection and function of flow cytometric-sorted populations, and their roles in disease. As a solution, we developed a simple tool to identify additional markers that can be used to increase the purity of flow-cytometric gated immune cell populations based on multi-omics data ( AlliGateR ). Here, we demonstrate that additional non-linear CD20, CD21 and CD24 gating can increase the purity of both naïve and memory populations., Discussion: These findings underscore the need to reconsider B cell subset definitions within the literature and propose leveraging single-cell multi-omics data for refined characterisation. We show that single-cell multi-omics technologies represent a powerful tool to bridge the gap between surface marker-based annotations and the intricate molecular characteristics of B cell subsets., Competing Interests: RB-R is a co-founder of Alchemab Therapeutics Ltd and consultant for Alchemab Therapeutics Ltd, Roche, Enara Bio, UCB and GSK. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Pernes, Alsayah, Tucci and Bashford-Rogers.)

Coronary artery disease (CAD) is a major cause of death worldwide. The role of CD8+ T cells in CAD is unknown. Recent studies suggest a breakdown of tolerance in atherosclerosis, resulting in active T cell receptor (TCR) engagement with self-antigens. We hypothesized that TCR engagement would leave characteristic gene expression signatures. In a single cell RNA-sequencing analysis of CD8+ T cells from 30 patients with CAD and 30 controls we found significant enrichment of TCR signaling pathways in CAD+ subjects, suggesting recent TCR engagement. We also found significant enrichment of cytotoxic and exhaustion pathways in CAD cases compared to controls. Highly significant upregulation of TCR signaling in CAD indicates that CD8 T cells reactive to atherosclerosis antigens are prominent in the blood of CAD cases compared to controls., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Iqneibi, Saigusa, Khan, Oliaeimotlagh, Armstrong Suthahar, Kumar, Alimadadi, Durant, Ghosheh, McNamara, Hedrick and Ley.)

Defining the immunological landscape of human tissue is an important area of research, but challenges include the impact of tissue disaggregation on cell phenotypes and the low abundance of immune cells in many tissues. Here, we describe methods to troubleshoot and standardize Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) for studies involving enzymatic digestion of human tissue. We tested epitope susceptibility of 92 antibodies commonly used to differentiate immune lineages and cell states on human peripheral blood mononuclear cells following treatment with an enzymatic digestion cocktail used to isolate islets. We observed CD4, CD8a, CD25, CD27, CD120b, CCR4, CCR6, and PD1 display significant sensitivity to enzymatic treatment, effects that often could not be overcome with alternate antibodies. Comparison of flow cytometry-based CITE-seq antibody titrations and sequencing data supports that for the majority of antibodies, flow cytometry accurately predicts optimal antibody concentrations for CITE-seq. Comparison by CITE-seq of immune cells in enzymatically digested islet tissue and donor-matched spleen not treated with enzymes revealed little digestion-induced epitope cleavage, suggesting increased sensitivity of CITE-seq and/or that the islet structure may protect resident immune cells from enzymes. Within islets, CITE-seq identified immune cells difficult to identify by transcriptional signatures alone, such as distinct tissue-resident T cell subsets, mast cells, and innate lymphoid cells (ILCs). Collectively this study identifies strategies for the rational design and testing of CITE-seq antibodies for single-cell studies of immune cells within islets and other tissues., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Colpitts, Budd, Monajemi, Reid, Murphy, Ivison, Verchere, Levings and Crome.)

Ankylosing spondylitis (AS) is an immune-mediated inflammatory disorder that primarily affects the axial skeleton, especially the sacroiliac joints and spine. This results in chronic back pain and, in extreme cases, ankylosis of the spine. Despite its debilitating effects, the pathogenesis of AS remains to be further elucidated. This study used single cell CITE-seq technology to analyze peripheral blood mononuclear cells (PBMCs) in AS and in healthy controls. We identified a number of molecular features associated with AS. CD52 was found to be overexpressed in both RNA and surface protein expression across several cell types in patients with AS. CD16 + monocytes overexpressed TNFSF10 and IL-18Rα in AS, while CD8 + T EM cells and natural killer cells overexpressed genes linked with cytotoxicity, including GZMH, GZMB , and NKG7 . Tregs underexpressed CD39 in AS, suggesting reduced functionality. We identified an overrepresented NK cell subset in AS that overexpressed CD16, CD161, and CD38, as well as cytotoxic genes and pathways. Finally, we developed machine learning models derived from CITE-seq data for the classification of AS and achieved an Area Under the Receiver Operating Characteristic (AUROC) curve of > 0.95. In summary, CITE-seq identification of AS-associated genes and surface proteins in specific cell subsets informs our understanding of pathogenesis and potential new therapeutic targets, while providing new approaches for diagnosis via machine learning., Competing Interests: WL has received research grant funding from Abbvie, Amgen, Janssen, Leo, Novartis, Pfizer, Regeneron, and TRex Bio. LG has received research/grant support from Novartis, Pfizer and UCB and consulting fees from AbbVie, Eli Lilly, Gilead, Janssen, Novartis, Pfizer and UCB. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Alber, Kumar, Liu, Huang, Paez, Hong, Chang, Bhutani, Gensler and Liao.)

Early diagnosis of psoriatic arthritis (PSA) is important for successful therapeutic intervention but currently remains challenging due, in part, to the scarcity of non-invasive biomarkers. In this study, we performed single cell profiling of transcriptome and cell surface protein expression to compare the peripheral blood immunocyte populations of individuals with PSA, individuals with cutaneous psoriasis (PSO) alone, and healthy individuals. We identified genes and proteins differentially expressed between PSA, PSO, and healthy subjects across 30 immune cell types and observed that some cell types, as well as specific phenotypic subsets of cells, differed in abundance between these cohorts. Cell type-specific gene and protein expression differences between PSA, PSO, and healthy groups, along with 200 previously published genetic risk factors for PSA, were further used to perform machine learning classification, with the best models achieving AUROC ≥ 0.87 when either classifying subjects among the three groups or specifically distinguishing PSA from PSO. Our findings thus expand the repertoire of gene, protein, and cellular biomarkers relevant to PSA and demonstrate the utility of machine learning-based diagnostics for this disease., Competing Interests: Author WL has received funding from Abbvie, Amgen, Janssen, Leo, Novartis, Pfizer, Regeneron, and TRex Bio. Author CY is a Scientific Advisory Board member for and holds equity in Related Sciences and ImmunAI, a consultant for and holds equity in Maze Therapeutics, and a consultant for TReX Bio. Author CY has received funding from Chan Zuckerberg Initiative, Chan Zuckerberg Biohub, and Genentech. Author LG has received funding from Novartis, Pfizer, UCB, AbbVie, Eli Lilly, Gilead, Janssen, Novartis, Pfizer and UCB. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Kumar, Hong, Huang, Paez, Castillo, Calvo, Chang, Cummins, Chung, Yeroushalmi, Bartholomew, Hakimi, Ye, Bhutani, Matloubian, Gensler and Liao.)

Immune cell activation assays have been widely used for immune monitoring and for understanding disease mechanisms. However, these assays are typically limited in scope. A holistic study of circulating immune cell responses to different activators is lacking. Here we developed a cost-effective high-throughput multiplexed single-cell RNA-seq combined with epitope tagging (CITE-seq) to determine how classic activators of T cells (anti-CD3 coupled with anti-CD28) or monocytes (LPS) alter the cell composition and transcriptional profiles of peripheral blood mononuclear cells (PBMCs) from healthy human donors. Anti-CD3/CD28 treatment activated all classes of lymphocytes either directly (T cells) or indirectly (B and NK cells) but reduced monocyte numbers. Activated T and NK cells expressed senescence and effector molecules, whereas activated B cells transcriptionally resembled autoimmune disease- or age-associated B cells (e.g., CD11c, T-bet). In contrast, LPS specifically targeted monocytes and induced two main states: early activation characterized by the expression of chemoattractants and a later pro-inflammatory state characterized by expression of effector molecules. These data provide a foundation for future immune activation studies with single cell technologies (https://czi-pbmc-cite-seq.jax.org/)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Lawlor, Nehar-Belaid, Grassmann, Stoeckius, Smibert, Stitzel, Pascual, Banchereau, Williams and Ucar.)