Normalizing and denoising protein expression data from droplet-based single cell profiling

Single-cell transcriptomic analysis identifies tissue-specific fibroblasts as the main modulators of myeloid cells in peritoneal metastasis of different origin

Colorectal cancer (CRC) peritoneal metastasis (CPM) is related to limited therapy options and poor prognosis. Although stromal cells heavily infiltrate most CPMs, interactions between different cell types in their microenvironment remain unclear. Here, we investigated tumor and distant normal tissue from CPM and CRC patients using single-cell RNA sequencing. Investigating the incoming and outgoing signals between cells revealed that fibroblasts dominate the CPM signaling landscape with myeloid cells as their strongest interaction partner. Using immunohistochemistry, we confirmed that fibroblasts co-localize with macrophages in the CPM microenvironment. A fibroblast sub-population detected only in CPM and normal peritoneum demonstrated immunoregulatory properties in co-culture experiments, and was further detected in additional peritoneal malignancies derived from ovarian and gastric origin. This novel fibroblast type and its communication with macrophages could be attractive targets for therapeutic interventions in CPM and potentially peritoneal surface malignancies in general.

Systems analysis unravels a common rural-urban gradient in immunological profile, function, and metabolic dependencies

Urbanization affects environmental exposures and lifestyle, shaping immune system variation and influencing disease susceptibility and vaccine responses. Here, we present systems analysis of immune profiles across the rural-urban gradient, comparing rural and urban Senegalese with urban Dutch individuals. By integrating single-cell phenotyping, metabolic profiling, and functional analysis, we reveal a trajectory of immune remodeling along the gradient. This includes enrichment of proinflammatory CD11c+ B cells associated with altered IgG Fc glycosylation, adaptive NK cells with reduced responsiveness to accessory cytokines, and CD161+CD4+T cells with enhanced cytokine production in rural settings. Metabolic perturbation studies demonstrated distinct dependencies on glycolysis, pentose phosphate pathway, and fatty acid synthesis for cellular cytokine responses across populations. We validate core rural-urban immune signatures in an independent Indonesian cohort, suggesting shared immunological adaptations to urbanization across ancestries and geographical areas. Our findings provide insights into rural-urban immune function in understudied populations.

Single-cell immune profiling at time of M. tuberculosis exposure reveals antigen-reactive programs that predict progression to active disease

Early delineation of host immune responses at the moment of Mycobacterium tuberculosis (Mtb) exposure and infection is critical to identify individuals at risk of progressing to active tuberculosis (TB). We performed single-cell transcriptional profiling of over 500,000 peripheral blood mononuclear cells from 57 HIV-negative close contacts of TB cases in Brazil, including 25 individuals who developed active disease within two years (progressors) and 32 matched controls who remained disease-free (non-progressors). Cells were stimulated separately with the MTB300 peptide pool or irradiated Mtb (gRV), enabling resolution of antigen-reactive states across adaptive (CD4⁺ T-cells expressing abundant cytokines including IFNG, TNF, and IL17F) and trained-innate lineages, such as NK cells (producing GM-CSF, IFNG, CCL3, CCL4) and monocytes (GM-CSF, IL12B, IL36G). Progressors exhibited early hyper-metabolic CD4⁺ T-cell programs and proliferative NK cell signatures, whereas non-progressors preferentially upregulated complement activation and CCL3/4-driven chemokine signaling in monocytes. Notably, among progressors, gene expression profiles within antigen-reactive CD4⁺ T-cells and monocytes predicted the timing of progression to active TB. Together, these findings reveal high frequencies and functional diversity of antigen-reactive cells in Mtb-exposed individuals and nominate tractable immune correlates for the rational design of next-generation TB vaccines.

CD147-high classical monocytes: a cellular biomarker for COVID-19 disease severity and treatment response

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can lead to severe coronavirus disease 2019 (COVID-19), which is characterized by cytokine storm and organ dysfunction. The spike S1 subunit induces inflammatory cytokine production, but the immune cell subsets that respond to S1 stimulation and contribute to disease severity remain unclear.

METHODS

We analyzed serum samples and peripheral blood mononuclear cells (PBMCs) from patients with COVID-19 (moderate: n = 7; severe: n = 25) and healthy controls (n = 38). Using mass cytometry (cytometry by time-of-flight; CyTOF), we analyzed immune cell responses to S1 subunit stimulation in PBMCs from healthy donors and patients with COVID-19. We examined correlations among identified cell populations, serum cytokine levels, and clinical parameters.

RESULTS

Serum S1 subunit levels correlated with disease severity and inflammatory cytokine concentrations. S1 subunit stimulation induced dose-dependent cytokine production from PBMCs, predominantly from myeloid cells. CyTOF analysis identified classical monocytes with high CD147 expression (CD147hi cMono) as the primary source of S1-induced cytokines. The proportion of CD147hi cMono increased significantly in severe COVID-19 and decreased with clinical improvement. The frequency of CD147hi cMono showed a stronger positive correlation with clinical severity markers in younger patients compared to older patients.

CONCLUSIONS

CD147hi cMono are the primary cellular source of S1-induced inflammatory cytokines and may serve as potential biomarkers for monitoring COVID-19 severity and treatment response.

A proteogenomic tool uncovers protein markers for human microglial states

Human microglial heterogeneity has been largely described using transcriptomic data. Here, we introduce a microglial proteomic data resource and a Cellular Indexing of Transcriptomes and Epitopes by Sequencing panel enhanced with antibodies targeting 17 microglial cell surface proteins (mCITE-Seq). We evaluated mCITE-Seq on HMC3 microglia-like cells, induced-pluripotent stem cell-derived microglia (iMG), and freshly isolated primary human microglia. We identified novel protein microglial markers such as CD51 and relate expression of 101 cell surface proteins to transcriptional programs. This results in the identification and validation of three protein marker combinations with which to purify microglia enriched with each of 23 transcriptional programs; for example, CD49D, HLA-DR and CD32 enrich for GPNMB high ("disease associated") microglia. Further, we identify and validate proteins - SIRPA, PDPN and CD162 - that differentiate microglia from infiltrating macrophages. The mCITE-Seq panel enables the transition from RNA-based classification and facilitates the functional characterization and harmonization of model systems.

Systems Human Immunology and AI: Immune Setpoint and Immune Health

The immune system, critical for human health and implicated in many diseases, defends against pathogens, monitors physiological stress, and maintains tissue and organismal homeostasis. It exhibits substantial variability both within and across individuals and populations. Recent technological and conceptual progress in systems human immunology has provided predictive insights that link personal immune states to intervention responses and disease susceptibilities. Artificial intelligence (AI), particularly machine learning (ML), has emerged as a powerful tool for analyzing complex immune data sets, revealing hidden patterns across biological scales, and enabling predictive models for individualistic immune responses and potentially personalized interventions. This review highlights recent advances in deciphering human immune variation and predicting outcomes, particularly through the concepts of immune setpoint, immune health, and use of the immune system as a window for measuring health. We also provide a brief history of AI; review ML modeling approaches, including their applications in systems human immunology; and explore the potential of AI to develop predictive models and personal immune state embeddings to detect early signs of disease, forecast responses to interventions, and guide personalized health strategies.

Early influenza virus exposure shapes the B cell response to influenza vaccination in individuals 50 years later

Pre-existing immunity impacts vaccine responses to influenza, but directly connecting influenza infections early in life with immune responses decades later is difficult. However, H2N2 stopped circulating in the human population in 1968, creating the opportunity to directly evaluate the impact of early H2N2 exposure on vaccine responses 50 years later. Here, we vaccinated individuals born before (H2 exposed) or after (H2 naive) 1968 with an H2 hemagglutinin (HA) DNA plasmid and/or a ferritin nanoparticle vaccine. H2-exposed individuals generated a rapid B cell recall response that was more potent, targeted more conserved epitopes, and differed phenotypically from the de novo response in H2-naive individuals. Furthermore, vaccinating with a DNA versus a protein nanoparticle vaccine altered the response in H2-naive but not H2-exposed individuals. This study establishes and describes the lifelong impact of influenza HA-specific memory B cells formed early in life on vaccine responses decades later.

T cell receptor usage and epitope specificity amongst CD8+ and CD4+ SARS-CoV-2-specific T cells

Introduction

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has highlighted the critical importance of understanding protective long-lasting immune responses. This study investigates the epitope specificity, T cell receptor (TCR) usage, and phenotypic changes in SARS-CoV-2-specfic CD8+ and CD4+ T cells over time in convalescent individuals with COVID-19.

Methods

Peripheral blood mononuclear cells (PBMCs) were collected from 28 unvaccinated individuals with primary SARS-CoV-2 infection (6 identified as the D614G variant, clade 20C) and analyzed up to 12 months post-symptom onset. Antigen-specific CD8+ and CD4+ T cells were analyzed using flow cytometry and single-cell RNA sequencing (scRNAseq) using specific dextramer and antibody reagents. TCR clonotypes and activation markers were characterized to explore T cell dynamics.

Results

SARS-CoV-2-specific CD8+ T cells exhibited waning frequencies long-term, transitioning from memory-like to a naïve-like state. scRNAseq revealed specificity against both spike and non-spike antigens with increased CD95 and CD127 expression over time, indicating that naïve-like T cells may represent stem cell memory T cells, which are multipotent and self-renewing, likely important for long-lived immunity. TCR clonal expansion was observed mainly in memory T cells, with overlapping TCR beta chain (TRB)-complementary determining region 3 (CDR3) sequences between participants, suggesting shared public TCR epitope-specific repertoires against SARS-CoV-2. Further, unique spike-specific CD4+ T cells with high CD95 and CD127 expression were identified, which may play a crucial role in long-term protection.

Discussion

This study highlights epitope-specificity heterogeneity, with some immunodominant responses, and suggests a potential role for long-lived SARS-CoV-2-specific T cell immunity. Shared TCR repertoires offers insights into cross-reactive and protective T cell clones, providing valuable information for optimizing vaccine strategies against emerging SARS-CoV-2 variants. The findings underscore the critical role of cellular immunity in long-term protection against SARS-CoV-2 and emphasizes the importance of understanding T cell dynamics.

Migration arrest and transendothelial trafficking of human pathogenic-like Th17 cells are mediated by differentially positioned chemokines

Human Th17/type 17 cells express the chemokine receptor CCR6, but the functions of CCR6 and other chemokine receptors in human type 17 Th cell extravasation have not been fully delineated. Here we show that human peripheral blood CD4+CCR6+ T cells co-expressing CCR2 have a pathogenic Th17 signature, can produce inflammatory cytokines without T cell receptor activation, and show enhanced expression of pathogenicity-associated and activation-associated genes in the cerebrospinal fluid of patients with multiple sclerosis as compared to controls. In flow chambers with activated endothelial cell (EC) monolayers, CD4+CCR6+CCR2+ T cells are efficient at transendothelial migration (TEM). Ligands for CCR5, CCR6 and CXCR3 localize to EC surfaces and mediate only arrest, whereas CCR2 ligands fail to bind well to ECs and mediate only TEM. Conversely, expressing a chimeric CCR2 ligand engineered to bind glycosaminoglycans on ECs results in CCR2-mediated arrest but blocks TEM induction. Our results from human pathogenic-like type 17 cells thus suggest that T cell migration arrest requires chemokine bound to EC surfaces, whereas TEM requires a transendothelial chemokine gradient.

MAIT cells protect against sterile lung injury

Mucosal-associated invariant T (MAIT) cells, the most abundant unconventional T cells in the lung, can exhibit a wide range of functional responses to different triggers via their T cell receptor (TCR) and/or cytokines. Their role, especially in sterile lung injury, is unknown. Using single-cell RNA sequencing (scRNA-seq), spectral analysis, and adoptive transfer in a bleomycin-induced sterile lung injury, we found that bleomycin activates murine pulmonary MAIT cells and is associated with a protective role against bleomycin-induced lung injury. MAIT cells drive the accumulation of type 1 conventional dendritic cells (cDC1s), limiting tissue damage in a DNGR-1-dependent manner. Human scRNA-seq data revealed that MAIT cells were activated, with increased cDC populations in idiopathic pulmonary fibrosis patients. Thus, MAIT cells enhance defense against sterile lung injury by fostering cDC1-driven anti-fibrotic pathways.

Dissecting the role of CAR signaling architectures on T cell activation and persistence using pooled screens and single-cell sequencing

Chimeric antigen receptor (CAR) T cells offer a promising cancer treatment, yet challenges such as limited T cell persistence hinder efficacy. Given its critical role in modulating T cell responses, it is crucial to understand how the CAR signaling architecture influences T cell function. Here, we designed a combinatorial CAR signaling domain library and performed repeated antigen stimulation assays, pooled screens, and single-cell sequencing to systematically investigate the impact of modifying CAR signaling domains on T cell activation and persistence. Our data reveal the predominant influence of membrane-proximal domains in driving T cell phenotype. Notably, CD40 costimulation was crucial for fostering robust and lasting T cell responses. Furthermore, we correlated in vitro generated CAR T cell phenotypes with clinical outcomes in patients treated with CAR T therapy, establishing the foundation for a clinically informed screening approach. This work deepens our understanding of CAR T cell biology and may guide future CAR engineering efforts.

Inhibition of CD226 co-stimulation suppresses diabetes development in the NOD mouse by augmenting regulatory T cells and diminishing effector T cell function

AIMS/HYPOTHESIS

Immunotherapeutics targeting T cells are crucial for inhibiting autoimmune disease progression proximal to disease onset in type 1 diabetes. There is an outstanding need to augment the durability and effectiveness of T cell targeting therapies by directly restraining proinflammatory T cell subsets, while simultaneously augmenting regulatory T cell (Treg) activity. Here, we present a novel strategy for preventing diabetes incidence in the NOD mouse model using a blocking monoclonal antibody targeting the type 1 diabetes risk-associated T cell co-stimulatory receptor, CD226.

METHODS

Female NOD mice were treated with anti-CD226 at 7-8 weeks of age and then monitored for diabetes incidence and therapeutic mechanism of action.

RESULTS

Compared with isotype-treated controls, anti-CD226-treated NOD mice showed reduced insulitis severity (0.84-fold, p=0.0002) at 12 weeks and decreased disease incidence (HR 0.41, p=0.015) at 30 weeks. Flow cytometric analysis performed 5 weeks post treatment demonstrated reduced proliferation of conventional CD4+ T cells (0.87-fold, p=0.030) and CD8+ (0.78-fold, p=0.0018) effector memory T cells in spleens of anti-CD226-treated mice. Phenotyping of pancreatic Tregs revealed increased CD25 expression (2.05-fold, p=0.0073) and signal transducer and activator of transcription 5 (STAT5) phosphorylation (1.39-fold, p=0.0007) following anti-CD226, with splenic Tregs displaying augmented suppression of CD4+ responder T cells (Tresps) (1.49-fold, p=0.0008, 1:2 Treg:Tresp) in vitro. Anti-CD226-treated mice exhibited reduced frequencies of islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP)-reactive CD8+ T cells in the pancreas, using both ex vivo tetramer staining (0.50-fold, p=0.0317) and single-cell T cell receptor sequencing (0.61-fold, p=0.022) approaches. 51Cr-release assays demonstrated reduced cell-mediated lysis of beta cells (0.61-fold, p<0.0001, 1:1 effector:target) by anti-CD226-treated autoreactive cytotoxic T lymphocytes.

CONCLUSIONS/INTERPRETATION

CD226 blockade reduces T cell cytotoxicity and improves Treg function, representing a targeted and rational approach for restoring immune regulation in type 1 diabetes.

Low-avidity T cells drive endogenous tumor immunity in mice and humans

T cells recognize neoepitope peptide-major histocompatibility complex class I on cancer cells. The strength (or avidity) of the T cell receptor-peptide-major histocompatibility complex class I interaction is a critical variable in immune control of cancers. Here, we analyze neoepitope-specific CD8 cells of distinct avidities and show that low-avidity T cells are the sole mediators of cancer control in mice and are solely responsive to checkpoint blockade in mice and humans. High-avidity T cells are ineffective and immune-suppressive. The mechanistic basis of these differences lies in the higher exhaustion status of high-avidity cells. High-avidity T cells have a distinct transcriptomic profile that is used here to calculate an 'avidity score', which we then use for in silico identification of low-avidity and high-avidity T cells in mice and humans. Surprisingly, CD8+ T cells with identical T cell receptors exhibit wide variation in avidities, suggesting an additional level of regulation of T cell activity. Aside from providing a better understanding of endogenous T cell responses to cancer, these findings might instruct future immunotherapy strategies.

Single-cell multiomics reveal divergent effects of DNMT3A- and TET2-mutant clonal hematopoiesis in inflammatory response

ABSTRACT

DNMT3A and TET2 are epigenetic regulator genes commonly mutated in age-related clonal hematopoiesis (CH). Despite having opposed epigenetic functions, these mutations are associated with increased all-cause mortality and a low risk for progression to hematologic neoplasms. Although individual impacts on the epigenome have been described using different model systems, the phenotypic complexity in humans remains to be elucidated. Here, we make use of a natural inflammatory response occurring during coronavirus disease 2019 (COVID-19), to understand the association of these mutations with inflammatory morbidity (acute respiratory distress syndrome [ARDS]) and mortality. We demonstrate the age-independent, negative impact of DNMT3A mutant (DNMT3Amt) CH on COVID-19-related ARDS and mortality. Using single-cell proteogenomics we show that DNMT3A mutations involve myeloid and lymphoid lineage cells. Using single-cell multiomics sequencing, we identify cell-specific gene expression changes associated with DNMT3A mutations, along with significant epigenomic deregulation affecting enhancer accessibility, resulting in overexpression of interleukin-32 (IL-32), a proinflammatory cytokine that can result in inflammasome activation in monocytes and macrophages. Finally, we show with single-cell resolution that the loss of function of DNMT3A is directly associated with increased chromatin accessibility in mutant cells. Hence, we demonstrate the negative prognostic impact of DNMT3Amt CH on COVID-19-related ARDS and mortality. DNMT3Amt CH in the context of COVID-19, was associated with inflammatory transcriptional priming, resulting in overexpression of IL32. This overexpression was secondary to increased chromatic accessibility, specific to DNMT3Amt CH cells. DNMT3Amt CH can thus serve as a potential biomarker for adverse outcomes in COVID-19.

Multimodal hierarchical classification of CITE-seq data delineates immune cell states across lineages and tissues

Single-cell RNA sequencing (scRNA-seq) is invaluable for profiling cellular heterogeneity and transcriptional states, but transcriptomic profiles do not always delineate subsets defined by surface proteins. Cellular indexing of transcriptomes and epitopes (CITE-seq) enables simultaneous profiling of single-cell transcriptomes and surface proteomes; however, accurate cell-type annotation requires a classifier that integrates multimodal data. Here, we describe multimodal classifier hierarchy (MMoCHi), a marker-based approach for accurate cell-type classification across multiple single-cell modalities that does not rely on reference atlases. We benchmark MMoCHi using sorted T lymphocyte subsets and annotate a cross-tissue human immune cell dataset. MMoCHi outperforms leading transcriptome-based classifiers and multimodal unsupervised clustering in its ability to identify immune cell subsets that are not readily resolved and to reveal subset markers. MMoCHi is designed for adaptability and can integrate annotation of cell types and developmental states across diverse lineages, samples, or modalities.

Systematic benchmark of single-cell hashtag demultiplexing approaches reveals robust performance of a clustering-based method

Single-cell technology opened up a new avenue to delineate cellular status at a single-cell resolution and has become an essential tool for studying human diseases. Multiplexing allows cost-effective experiments by combining multiple samples and effectively mitigates batch effects. It starts by giving each sample a unique tag and then pooling them together for library preparation and sequencing. After sequencing, sample demultiplexing is performed based on tag detection, where cells belonging to one sample are expected to have a higher amount of the corresponding tag than cells from other samples. However, in reality, demultiplexing is not straightforward due to the noise and contamination from various sources. Successful demultiplexing depends on the efficient removal of such contamination. Here, we perform a systematic benchmark combining different normalization methods and demultiplexing approaches using real-world data and simulated datasets. We show that accounting for sequencing depth variability increases the separability between tagged and untagged cells, and the clustering-based approach outperforms existing tools. The clustering-based workflow is available as an R package from https://github.com/hwlim/hashDemux.

Multiomics dissection of human RAG deficiency reveals distinctive patterns of immune dysregulation but a common inflammatory signature

Human recombination-activating gene (RAG) deficiency can manifest with distinct clinical and immunological phenotypes. By applying a multiomics approach to a large group of RAG-mutated patients, we aimed at characterizing the immunopathology associated with each phenotype. Although defective T and B cell development is common to all phenotypes, patients with hypomorphic RAG variants can generate T and B cells with signatures of immune dysregulation and produce autoantibodies to a broad range of self-antigens, including type I interferons. T helper 2 (TH2) cell skewing and a prominent inflammatory signature characterize Omenn syndrome, whereas more hypomorphic forms of RAG deficiency are associated with a type 1 immune profile both in blood and tissues. We used cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) analysis to define the cell lineage-specific contribution to the immunopathology of the distinct RAG phenotypes. These insights may help improve the diagnosis and clinical management of the various forms of the disease.

Circulating tumor-reactive KIR+CD8+ T cells suppress anti-tumor immunity in patients with melanoma

Effective anti-tumor immunity is driven by cytotoxic CD8+ T cells with specificity for tumor antigens. However, the factors that control successful tumor rejection are not well understood. Here we identify a subpopulation of CD8+ T cells that are tumor-antigen-specific and can be identified by KIR expression but paradoxically impair anti-tumor immunity in patients with melanoma. These tumor-antigen-specific KIR+CD8+ regulatory T cells target other tumor-antigen-specific CD8+ T cells, can be detected in both the tumor and the blood, have a conserved transcriptional program and are associated with a poor overall survival. These findings broaden our understanding of the transcriptional and functional heterogeneity of human CD8+ T cells and implicate KIR+CD8+ regulatory T cells as a cellular mediator of immune evasion in human cancer.

Negative binomial mixture model for identification of noise in antibody-antigen specificity predictions from single-cell data

Motivation

LIBRA-seq (linking B cell receptor to antigen specificity by sequencing) provides a powerful tool for interrogating the antigen-specific B cell compartment and identifying antibodies against antigen targets of interest. Identification of noise in single-cell B cell receptor sequencing data, such as LIBRA-seq, is critical for improving antigen binding predictions for downstream applications including antibody discovery and machine learning technologies.

Results

In this study, we present a method for denoising LIBRA-seq data by clustering antigen counts into signal and noise components with a negative binomial mixture model. This approach leverages single-cell sequencing reads from a large, multi-donor dataset described in a recent LIBRA-seq study to develop a data-driven means for identification of technical noise. We apply this method to nine donors representing separate LIBRA-seq experiments and show that our approach provides improved predictions for in vitro antibody-antigen binding when compared to the standard scoring method, despite variance in data size and noise structure across samples. This development will improve the ability of LIBRA-seq to identify antigen-specific B cells and contribute to providing more reliable datasets for machine learning based approaches as the corpus of single-cell B cell sequencing data continues to grow.

Availability and implementation

All data and code are available at https://github.com/IGlab-VUMC/mixture_model_denoising.

CD4+CD8αlow T Cell Clonal Expansion Dependent on Costimulation in Patients With Rheumatoid Arthritis

OBJECTIVE

CD4+CD8+ T cells are increased in patients with rheumatoid arthritis (RA). They are not only associated with joint erosions in established disease but are also present in the preclinical stages of RA. This study aims to further investigate their expansion in the context of T cell clonality in patients with RA, as well as their responsiveness to T cell-targeted treatment.

METHODS

Single-cell RNA (scRNA) and single-cell T cell receptor (TCR) sequencing data were used to determine coreceptor expression and TCR sequences to assess the clonality of CD4+CD8+ T cells in patients with RA (n = 3) and healthy controls (n = 2). Peripheral CD4+CD8+ T cells and their subpopulations were measured in patients with RA (n = 53), patients with psoriatic arthritis (PsA; n = 52), and healthy donors (n = 50) using flow cytometry. In addition, changes in CD4+CD8+ T cell frequency were prospectively observed in patients with RA receiving therapy with abatacept for 12 weeks.

RESULTS

We observed an increase of CD4+ T cells expressing CD8α in patients with RA, both in comparison to patients with PsA and healthy controls. Clonality analysis revealed that these CD4+CD8αlow T cells are part of large T cell clones, which cluster separately from CD4+CD8- T cell clones in the scRNA sequencing (scRNA-seq) gene expression analysis. Treatment with abatacept significantly reduced the frequency of peripheral CD4+CD8αlow T cells, and this was linked to reduction in disease activity.

CONCLUSION

In patients with RA, clonal expansion of CD4+ T cell culminates in the emergence of peripheral CD4+CD8αlow T cells, which are associated with disease activity and diminished upon abatacept treatment and could contribute to disease pathogenesis.

IL-12 drives the expression of the inhibitory receptor NKG2A on human tumor-reactive CD8 T cells

Blockade of NKG2A/HLA-E interaction is a promising strategy to unleash the anti-tumor response. Yet the role of NKG2A+ CD8 T cells in the anti-tumor response and the regulation of NKG2A expression on human tumor-infiltrating T cells are still poorly understood. Here, by performing CITE-seq on T cells derived from head and neck squamous cell carcinoma and colorectal cancer, we show that NKG2A expression is induced on CD8 T cells differentiating into cytotoxic, CD39+CD103+ double positive (DP) cells, a phenotype associated with tumor-reactive T cells. This developmental trajectory leads to TCR repertoire overlap between the NKG2A- and NKG2A+ DP CD8 T cells, suggesting shared antigen specificities. Mechanistically, IL-12 is essential for the expression of NKG2A on CD8 T cells in a CD40/CD40L- dependent manner, in conjunction with TCR stimulation. Our study thus reveals that NKG2A is induced by IL-12 on human tumor-reactive CD8 T cells exposed to a TGF-β-rich environment, highlighting an underappreciated immuno-regulatory feedback loop dependent on IL-12 stimulation.

Concepts and new developments in droplet-based single cell multi-omics

Single cell sequencing technologies have become a fixture in the molecular profiling of cells due to their ease, flexibility, and commercial availability. In particular, partitioning individual cells inside oil droplets via microfluidic reactions enables transcriptomic or multi-omic measurements for thousands of cells in parallel. Complementing the multitude of biological discoveries from genomics analyses, the past decade has brought new capabilities from assay baselines to enable a deeper understanding of the complex data from single cell multi-omics. Here, we highlight four innovations that have improved the reliability and understanding of droplet microfluidic assays. We emphasize new developments that further orient principles of technology development and guidelines for the design, benchmarking, and implementation of new droplet-based methodologies.

ADTGP: correcting single-cell antibody sequencing data using Gaussian process regression

SUMMARY

We present ADTGP, an R package that uses Gaussian process regression to correct droplet-specific technical noise in single-cell protein sequencing data. ADTGP improves the interpretability of the data by modeling the distribution of protein expression, conditioned on equal isotype control counts across cells. ADTGP is written in R and needs only the protein raw counts, isotype control raw counts, and a design matrix to run.

AVAILABILITY AND IMPLEMENTATION

ADTGP can be installed from https://github.com/northNomad/ADTGP. It depends on Stan and the R package 'cmdstanr'.

Targeting immune-fibroblast cell communication in heart failure

Inflammation and tissue fibrosis co-exist and are causally linked to organ dysfunction1,2. However, the molecular mechanisms driving immune-fibroblast cell communication in human cardiac disease remain unexplored and there are at present no approved treatments that directly target cardiac fibrosis3,4. Here we performed multiomic single-cell gene expression, epitope mapping and chromatin accessibility profiling in 45 healthy donor, acutely infarcted and chronically failing human hearts. We identified a disease-associated fibroblast trajectory that diverged into distinct populations reminiscent of myofibroblasts and matrifibrocytes, the latter expressing fibroblast activator protein (FAP) and periostin (POSTN). Genetic lineage tracing of FAP+ fibroblasts in vivo showed that they contribute to the POSTN lineage but not the myofibroblast lineage. We assessed the applicability of experimental systems to model cardiac fibroblasts and demonstrated that three different in vivo mouse models of cardiac injury were superior compared with cultured human heart and dermal fibroblasts in recapitulating the human disease phenotype. Ligand-receptor analysis and spatial transcriptomics predicted that interactions between C-C chemokine receptor type 2 (CCR2) macrophages and fibroblasts mediated by interleukin-1β (IL-1β) signalling drove the emergence of FAP/POSTN fibroblasts within spatially defined niches. In vivo, we deleted the IL-1 receptor on fibroblasts and the IL-1β ligand in CCR2+ monocytes and macrophages, and inhibited IL-1β signalling using a monoclonal antibody, and showed reduced FAP/POSTN fibroblasts, diminished myocardial fibrosis and improved cardiac function. These findings highlight the broader therapeutic potential of targeting inflammation to treat tissue fibrosis and preserve organ function.

A spatial human thymus cell atlas mapped to a continuous tissue axis

T cells develop from circulating precursor cells, which enter the thymus and migrate through specialized subcompartments that support their maturation and selection1. In humans, this process starts in early fetal development and is highly active until thymic involution in adolescence. To map the microanatomical underpinnings of this process in pre- and early postnatal stages, we established a quantitative morphological framework for the thymus-the Cortico-Medullary Axis-and used it to perform a spatially resolved analysis. Here, by applying this framework to a curated multimodal single-cell atlas, spatial transcriptomics and high-resolution multiplex imaging data, we demonstrate establishment of the lobular cytokine network, canonical thymocyte trajectories and thymic epithelial cell distributions by the beginning of the the second trimester of fetal development. We pinpoint tissue niches of thymic epithelial cell progenitors and distinct subtypes associated with Hassall's corpuscles and identify divergence in the timing of medullary entry between CD4 and CD8 T cell lineages. These findings provide a basis for a detailed understanding of T lymphocyte development and are complemented with a holistic toolkit for cross-platform imaging data analysis, annotation and OrganAxis construction (TissueTag), which can be applied to any tissue.

CD4+ T cells reactive to a hybrid peptide from insulin-chromogranin A adopt a distinct effector fate and are pathogenic in autoimmune diabetes

T cell-mediated islet destruction is a hallmark of autoimmune diabetes. Here, we examined the dynamics and pathogenicity of CD4+ T cell responses to four different insulin-derived epitopes during diabetes initiation in non-obese diabetic (NOD) mice. Single-cell RNA sequencing of tetramer-sorted CD4+ T cells from the pancreas revealed that islet-antigen-specific T cells adopted a wide variety of fates and required XCR1+ dendritic cells for their activation. Hybrid-insulin C-chromogranin A (InsC-ChgA)-specific CD4+ T cells skewed toward a distinct T helper type 1 (Th1) effector phenotype, whereas the majority of insulin B chain and hybrid-insulin C-islet amyloid polypeptide-specific CD4+ T cells exhibited a regulatory phenotype and early or weak Th1 phenotype, respectively. InsC-ChgA-specific CD4+ T cells were uniquely pathogenic upon transfer, and an anti-InsC-ChgA:IAg7 antibody prevented spontaneous diabetes. Our findings highlight the heterogeneity of T cell responses to insulin-derived epitopes in diabetes and argue for the feasibility of antigen-specific therapies that blunts the response of pathogenic CD4+ T cells causing autoimmunity.

Use of 3M-052-AF with Alum adjuvant in HIV trimer vaccine induces human autologous neutralizing antibodies

Stabilized trimers preserving the native-like HIV envelope structure may be key components of a preventive HIV vaccine regimen to induce broadly neutralizing antibodies (bnAbs). We evaluated trimeric BG505 SOSIP.664 gp140 formulated with a novel TLR7/8 signaling adjuvant, 3M-052-AF/Alum, for safety, adjuvant dose-finding, and immunogenicity in a first-in-healthy adult (n = 17), randomized, and placebo-controlled trial (HVTN 137A). The vaccine regimen appeared safe. Robust, trimer-specific antibody, and B cell and CD4+ T cell responses emerged after vaccination. Five vaccinees developed serum autologous tier 2 nAbs (ID50 titer, 1:28-1:8647) after two to three doses targeting C3/V5 and/or V1/V2/V3 Env regions by electron microscopy and mutated pseudovirus-based neutralization analyses. Trimer-specific, B cell-derived monoclonal antibody activities confirmed these results and showed weak heterologous neutralization in the strongest responder. Our findings demonstrate the clinical utility of the 3M-052-AF/Alum adjuvant and support further improvements of trimer-based Env immunogens to focus responses on multiple broad nAb epitopes.

Acute and persistent responses after H5N1 vaccination in humans

To gain insight into how an adjuvant impacts vaccination responses, we use systems immunology to study human H5N1 influenza vaccination with or without the adjuvant AS03, longitudinally assessing 14 time points including multiple time points within the first day after prime and boost. We develop an unsupervised computational framework to discover high-dimensional response patterns, which uncover adjuvant- and immunogenicity-associated early response dynamics, including some that differ post prime versus boost. With or without adjuvant, some vaccine-induced transcriptional patterns persist to at least 100 days after initial vaccination. Single-cell profiling of surface proteins, transcriptomes, and chromatin accessibility implicates transcription factors in the erythroblast-transformation-specific (ETS) family as shaping these long-lasting signatures, primarily in classical monocytes but also in CD8+ naive-like T cells. These cell-type-specific signatures are elevated at baseline in high-antibody responders in an independent vaccination cohort, suggesting that antigen-agnostic baseline immune states can be modulated by vaccine antigens alone to enhance future responses.

PTPN11 Mutation Clonal Hierarchy in Acute Myeloid Leukemia

Mutations in protein tyrosine phosphatase non-receptor type 11 ( PTPN11 ) have been considered late acquired mutations in acute myeloid leukemia (AML) development. To interrogate the ontogeny of PTPN11 mutations, we utilized single-cell DNA sequencing and identified that PTPN11 mutations can occur as initiating events in some AML patients when accompanied by strong oncogenic drivers, commonly NPM1 mutations. The co-driver role of PTPN11 mutations was confirmed in a novel murine model that exhibits an AML phenotype with early expansion of a diverse set of variably differentiated myeloid cells that engrafted into immunodeficient and immunocompetent mice. This immune diversity was reconstituted from early precursor cells when engrafted into immunodeficient mice. Moreover, immune diversity was also observed in the blast component of patient samples with NPM1 and PTPN11 mutations, providing novel antigen targets for immune based approaches in this subset of AML that is resistant to multiple targeted therapies.

Multiomic single cell sequencing identifies stemlike nature of mixed phenotype acute leukemia

Despite recent work linking mixed phenotype acute leukemia (MPAL) to certain genetic lesions, specific driver mutations remain undefined for a significant proportion of patients and no genetic subtype is predictive of clinical outcomes. Moreover, therapeutic strategy for MPAL remains unclear, and prognosis is overall poor. We performed multiomic single cell profiling of 14 newly diagnosed adult MPAL patients to characterize the inter- and intra-tumoral transcriptional, immunophenotypic, and genetic landscapes of MPAL. We show that neither genetic profile nor transcriptome reliably correlate with specific MPAL immunophenotypes. Despite this, we find that MPAL blasts express a shared stem cell-like transcriptional profile indicative of high differentiation potential. Patients with the highest differentiation potential demonstrate inferior survival in our dataset. A gene set score, MPAL95, derived from genes highly enriched in the most stem-like MPAL cells, is applicable to bulk RNA sequencing data and is predictive of survival in an independent patient cohort, suggesting a potential strategy for clinical risk stratification.

CAR T-cells targeting FGFR4 and CD276 simultaneously show potent antitumor effect against childhood rhabdomyosarcoma

Chimeric antigen receptor (CAR) T-cells targeting Fibroblast Growth Factor Receptor 4 (FGFR4), a highly expressed surface tyrosine receptor in rhabdomyosarcoma (RMS), are already in the clinical phase of development, but tumour heterogeneity and suboptimal activation might hamper their potency. Here we report an optimization strategy of the co-stimulatory and targeting properties of a FGFR4 CAR. We replace the CD8 hinge and transmembrane domain and the 4-1BB co-stimulatory domain with those of CD28. The resulting CARs display enhanced anti-tumor activity in several RMS xenograft models except for an aggressive tumour cell line, RMS559. By searching for a direct target of the RMS core-regulatory transcription factor MYOD1, we identify another surface protein, CD276, as a potential target. Bicistronic CARs (BiCisCAR) targeting both FGFR4 and CD276, containing two distinct co-stimulatory domains, have superior prolonged persistent and invigorated anti-tumor activities compared to the optimized FGFR4-specific CAR and the other BiCisCAR with the same 4-1BB co-stimulatory domain. Our study thus lays down the proof-of-principle for a CAR T-cell therapy targeting both FGFR4 and CD276 in RMS.

Inhibition of CD226 Co-Stimulation Suppresses Diabetes Development in the NOD Mouse by Augmenting Tregs and Diminishing Effector T Cell Function

Aims/hypothesis

Immunotherapeutics targeting T cells are crucial for inhibiting autoimmune disease progression proximal to disease onset in type 1 diabetes. A growing number of T cell-directed therapeutics have demonstrated partial therapeutic efficacy, with anti-CD3 (α-CD3) representing the only regulatory agency-approved drug capable of slowing disease progression through a mechanism involving the induction of partial T cell exhaustion. There is an outstanding need to augment the durability and effectiveness of T cell targeting by directly restraining proinflammatory T helper type 1 (Th1) and type 1 cytotoxic CD8+ T cell (Tc1) subsets, while simultaneously augmenting regulatory T cell (Treg) activity. Here, we present a novel strategy for reducing diabetes incidence in the NOD mouse model using a blocking monoclonal antibody targeting the type 1 diabetes-risk associated T cell co-stimulatory receptor, CD226.

Methods

Female NOD mice were treated with anti-CD226 between 7-8 weeks of age and then monitored for diabetes incidence and therapeutic mechanism of action.

Results

Compared to isotype-treated controls, anti-CD226 treated NOD mice showed reduced insulitis severity at 12 weeks and decreased disease incidence at 30 weeks. Flow cytometric analysis performed five weeks post-treatment demonstrated reduced proliferation of CD4+ and CD8+ effector memory T cells in spleens of anti-CD226 treated mice. Phenotyping of pancreatic Tregs revealed increased CD25 expression and STAT5 phosphorylation following anti-CD226, with splenic Tregs displaying augmented suppression of CD4+ T cell responders in vitro. Anti-CD226 treated mice exhibited reduced frequencies of islet-specific glucose-6-phosphatase catalytic subunit related protein (IGRP)-reactive CD8+ T cells in the pancreas, using both ex vivo tetramer staining and single-cell T cell receptor sequencing (scTCR-seq) approaches. 51Cr-release assays demonstrated reduced cell-mediated lysis of beta-cells by anti-CD226-treated autoreactive cytotoxic T lymphocytes.

Conclusions/interpretation

CD226 blockade reduces T cell cytotoxicity and improves Treg function, representing a targeted and rational approach for restoring immune regulation in type 1 diabetes.

ADTnorm: Robust Integration of Single-cell Protein Measurement across CITE-seq Datasets

CITE-seq enables paired measurement of surface protein and mRNA expression in single cells using antibodies conjugated to oligonucleotide tags. Due to the high copy number of surface protein molecules, sequencing antibody-derived tags (ADTs) allows for robust protein detection, improving cell-type identification. However, variability in antibody staining leads to batch effects in the ADT expression, obscuring biological variation, reducing interpretability, and obstructing cross-study analyses. Here, we present ADTnorm (https://github.com/yezhengSTAT/ADTnorm), a normalization and integration method designed explicitly for ADT abundance. Benchmarking against 14 existing scaling and normalization methods, we show that ADTnorm accurately aligns populations with negative- and positive-expression of surface protein markers across 13 public datasets, effectively removing technical variation across batches and improving cell-type separation. ADTnorm enables efficient integration of public CITE-seq datasets, each with unique experimental designs, paving the way for atlas-level analyses. Beyond normalization, ADTnorm includes built-in utilities to aid in automated threshold-gating as well as assessment of antibody staining quality for titration optimization and antibody panel selection. Applying ADTnorm to a published COVID-19 CITE-seq dataset allowed for identifying previously undetected disease-associated markers, illustrating a broad utility in biological applications.

Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis

Single-cell multiomic analysis of the epigenome, transcriptome, and proteome allows for comprehensive characterization of the molecular circuitry that underpins cell identity and state. However, the holistic interpretation of such datasets presents a challenge given a paucity of approaches for systematic, joint evaluation of different modalities. Here, we present Panpipes, a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customizable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.

Cytokines drive the formation of memory-like NK cell subsets via epigenetic rewiring and transcriptional regulation

Activation of natural killer (NK) cells with the cytokines interleukin-12 (IL-12), IL-15, and IL-18 induces their differentiation into memory-like (ML) NK cells; however, the underlying epigenetic and transcriptional mechanisms are unclear. By combining ATAC-seq, CITE-seq, and functional analyses, we discovered that IL-12/15/18 activation results in two main human NK fates: reprogramming into enriched memory-like (eML) NK cells or priming into effector conventional NK (effcNK) cells. eML NK cells had distinct transcriptional and epigenetic profiles and enhanced function, whereas effcNK cells resembled cytokine-primed cNK cells. Two transcriptionally discrete subsets of eML NK cells were also identified, eML-1 and eML-2, primarily arising from CD56bright or CD56dim mature NK cell subsets, respectively. Furthermore, these eML subsets were evident weeks after transfer of IL-12/15/18-activated NK cells into patients with cancer. Our findings demonstrate that NK cell activation with IL-12/15/18 results in previously unappreciated diverse cellular fates and identifies new strategies to enhance NK therapies.

scCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data

In droplet-based single-cell and single-nucleus RNA-seq assays, systematic contamination of ambient RNA molecules biases the quantification of gene expression levels. Existing methods correct the contamination for all genes globally. However, there lacks specific evaluation of correction efficacy for varying contamination levels. Here, we show that DecontX and CellBender under-correct highly contaminating genes, while SoupX and scAR over-correct lowly/non-contaminating genes. Here, we develop scCDC as the first method to detect the contamination-causing genes and only correct expression levels of these genes, some of which are cell-type markers. Compared with existing decontamination methods, scCDC excels in decontaminating highly contaminating genes while avoiding over-correction of other genes.

Coordinated immune dysregulation in juvenile dermatomyositis revealed by single-cell genomics

Juvenile dermatomyositis (JDM) is one of several childhood-onset autoimmune disorders characterized by a type I IFN response and autoantibodies. Treatment options are limited due to an incomplete understanding of how the disease emerges from dysregulated cell states across the immune system. We therefore investigated the blood of patients with JDM at different stages of disease activity using single-cell transcriptomics paired with surface protein expression. By immunophenotyping peripheral blood mononuclear cells, we observed skewing of the B cell compartment toward an immature naive state as a hallmark of JDM at diagnosis. Furthermore, we find that these changes in B cells are paralleled by T cell signatures suggestive of Th2-mediated inflammation that persist despite disease quiescence. We applied network analysis to reveal that hyperactivation of the type I IFN response in all immune populations is coordinated with previously masked cell states including dysfunctional protein processing in CD4+ T cells and regulation of cell death programming in NK cells, CD8+ T cells, and γδ T cells. Together, these findings unveil the coordinated immune dysregulation underpinning JDM and provide insight into strategies for restoring balance in immune function.

Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint

Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.

A single cell framework identifies functionally and molecularly distinct multipotent progenitors in adult human hematopoiesis

Hematopoietic multipotent progenitors (MPPs) regulate blood cell production to appropriately meet the biological demands of the human body. Human MPPs remain ill-defined whereas mouse MPPs have been well characterized with distinct immunophenotypes and lineage potencies. Using multiomic single cell analyses and complementary functional assays, we identified new human MPPs and oligopotent progenitor populations within Lin-CD34+CD38dim/lo adult bone marrow with distinct biomolecular and functional properties. These populations were prospectively isolated based on expression of CD69, CLL1, and CD2 in addition to classical markers like CD90 and CD45RA. We show that within the canonical Lin-CD34+CD38dim/loCD90CD45RA-MPP population, there is a CD69+ MPP with long-term engraftment and multilineage differentiation potential, a CLL1+ myeloid-biased MPP, and a CLL1-CD69-erythroid-biased MPP. We also show that the canonical Lin-CD34+CD38dim/loCD90-CD45RA+ LMPP population can be separated into a CD2+ LMPP with lymphoid and myeloid potential, a CD2-LMPP with high lymphoid potential, and a CLL1+ GMP with minimal lymphoid potential. We used these new HSPC profiles to study human and mouse bone marrow cells and observe limited cell type specific homology between humans and mice and cell type specific changes associated with aging. By identifying and functionally characterizing new adult MPP sub-populations, we provide an updated reference and framework for future studies in human hematopoiesis.

HIV BG505 SOSIP.664 trimer with 3M-052-AF/alum induces human autologous tier-2 neutralizing antibodies

Stabilized trimers preserving the native-like HIV envelope structure may be key components of a preventive HIV vaccine regimen to induce broadly neutralizing antibodies (bnAbs). We evaluated trimeric BG505 SOSIP.664 gp140, formulated with a novel TLR7/8 signaling adjuvant, 3M-052-AF/Alum, for safety, adjuvant dose-finding and immunogenicity in a first-in-healthy adult (n=17), randomized, placebo-controlled trial (HVTN 137A). The vaccine regimen appeared safe. Robust, trimer-specific antibody, B-cell and CD4+ T-cell responses emerged post-vaccination. Five vaccinees developed serum autologous tier-2 nAbs (ID50 titer, 1:28-1:8647) after 2-3 doses targeting C3/V5 and/or V1/V2/V3 Env regions by electron microscopy and mutated pseudovirus-based neutralization analyses. Trimer-specific, B-cell-derived monoclonal antibody activities confirmed these results and showed weak heterologous neutralization in the strongest responder. Our findings demonstrate the clinical utility of the 3M-052-AF/alum adjuvant and support further improvements of trimer-based Env immunogens to focus responses on multiple broad nAb epitopes.

KEY TAKEAWAY/TAKE-HOME MESSAGES

HIV BG505 SOSIP.664 trimer with novel 3M-052-AF/alum adjuvant in humans appears safe and induces serum neutralizing antibodies to matched clade A, tier 2 virus, that map to diverse Env epitopes with relatively high titers. The novel adjuvant may be an important mediator of vaccine response.

A phase 2 randomized trial with autologous polyclonal expanded regulatory T cells in children with new-onset type 1 diabetes

CD4+CD25hiCD127lo/-FOXP3+ regulatory T cells (Tregs) play a key role in preventing autoimmunity. In autoimmune type 1 diabetes (T1D), adoptive transfer of autologous polyclonal Tregs has been shown to be safe in adults in phase 1 clinical trials. We explored factors contributing to efficacy of autologous polyclonal expanded Tregs (expTregs) in a randomized phase 2 multi-center, double-blind, clinical trial (Sanford/Lisata Therapeutics T-Rex phase 2 trial, ClinicalTrials.gov NCT02691247). One hundred ten treated children and adolescents with new-onset T1D were randomized 1:1:1 to high-dose (20 × 106 cells/kilogram) or low-dose (1 × 106 cells/kilogram) treatments or to matching placebo. Cytometry as well as bulk and single-cell RNA sequencing were performed on selected expTregs and peripheral blood samples from participants. The single doses of expTregs were safe but did not prevent decline in residual β cell function over 1 year compared to placebo (P = 0.94 low dose, P = 0.21 high dose), regardless of age or baseline C-peptide. ExpTregs were highly activated and suppressive in vitro. A transient increase of activated memory Tregs was detectable 1 week after infusion in the high-dose cohort, suggesting effective transfer of expTregs. However, the in vitro fold expansion of expTregs varied across participants, even when accounting for age, and lower fold expansion and its associated gene signature were linked with better C-peptide preservation regardless of Treg dose. These results suggest that a single dose of polyclonal expTregs does not alter progression in T1D; instead, Treg quality may be an important factor.

Mapping genotypes to chromatin accessibility profiles in single cells

In somatic tissue differentiation, chromatin accessibility changes govern priming and precursor commitment towards cellular fates1-3. Therefore, somatic mutations are likely to alter chromatin accessibility patterns, as they disrupt differentiation topologies leading to abnormal clonal outgrowth. However, defining the impact of somatic mutations on the epigenome in human samples is challenging due to admixed mutated and wild-type cells. Here, to chart how somatic mutations disrupt epigenetic landscapes in human clonal outgrowths, we developed genotyping of targeted loci with single-cell chromatin accessibility (GoT-ChA). This high-throughput platform links genotypes to chromatin accessibility at single-cell resolution across thousands of cells within a single assay. We applied GoT-ChA to CD34+ cells from patients with myeloproliferative neoplasms with JAK2V617F-mutated haematopoiesis. Differential accessibility analysis between wild-type and JAK2V617F-mutant progenitors revealed both cell-intrinsic and cell-state-specific shifts within mutant haematopoietic precursors, including cell-intrinsic pro-inflammatory signatures in haematopoietic stem cells, and a distinct profibrotic inflammatory chromatin landscape in megakaryocytic progenitors. Integration of mitochondrial genome profiling and cell-surface protein expression measurement allowed expansion of genotyping onto DOGMA-seq through imputation, enabling single-cell capture of genotypes, chromatin accessibility, RNA expression and cell-surface protein expression. Collectively, we show that the JAK2V617F mutation leads to epigenetic rewiring in a cell-intrinsic and cell type-specific manner, influencing inflammation states and differentiation trajectories. We envision that GoT-ChA will empower broad future investigations of the critical link between somatic mutations and epigenetic alterations across clonal populations in malignant and non-malignant contexts.

scButterfly: a versatile single-cell cross-modality translation method via dual-aligned variational autoencoders

Recent advancements for simultaneously profiling multi-omics modalities within individual cells have enabled the interrogation of cellular heterogeneity and molecular hierarchy. However, technical limitations lead to highly noisy multi-modal data and substantial costs. Although computational methods have been proposed to translate single-cell data across modalities, broad applications of the methods still remain impeded by formidable challenges. Here, we propose scButterfly, a versatile single-cell cross-modality translation method based on dual-aligned variational autoencoders and data augmentation schemes. With comprehensive experiments on multiple datasets, we provide compelling evidence of scButterfly's superiority over baseline methods in preserving cellular heterogeneity while translating datasets of various contexts and in revealing cell type-specific biological insights. Besides, we demonstrate the extensive applications of scButterfly for integrative multi-omics analysis of single-modality data, data enhancement of poor-quality single-cell multi-omics, and automatic cell type annotation of scATAC-seq data. Moreover, scButterfly can be generalized to unpaired data training, perturbation-response analysis, and consecutive translation.

CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny

BACKGROUND

The rapid advancement of new genomic sequencing technology has enabled the development of multi-omic single-cell sequencing assays. These assays profile multiple modalities in the same cell and can often yield new insights not revealed with a single modality. For example, Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) simultaneously profiles the RNA transcriptome and the surface protein expression. The surface protein markers in CITE-Seq can be used to identify cell populations similar to the iterative filtration process in flow cytometry, also called "gating", and is an essential step for downstream analyses and data interpretation. While several packages allow users to interactively gate cells, they often do not process multi-omic sequencing datasets and may require writing redundant code to specify gate boundaries. To streamline the gating process, we developed CITEViz which allows users to interactively gate cells in Seurat-processed CITE-Seq data. CITEViz can also visualize basic quality control (QC) metrics allowing for a rapid and holistic evaluation of CITE-Seq data.

RESULTS

We applied CITEViz to a peripheral blood mononuclear cell CITE-Seq dataset and gated for several major blood cell populations (CD14 monocytes, CD4 T cells, CD8 T cells, NK cells, B cells, and platelets) using canonical surface protein markers. The visualization features of CITEViz were used to investigate cellular heterogeneity in CD14 and CD16-expressing monocytes and to detect differential numbers of detected antibodies per patient donor. These results highlight the utility of CITEViz to enable the robust classification of single cell populations.

CONCLUSIONS

CITEViz is an R-Shiny app that standardizes the gating workflow in CITE-Seq data for efficient classification of cell populations. Its secondary function is to generate basic feature plots and QC figures specific to multi-omic data. The user interface and internal workflow of CITEViz uniquely work together to produce an organized workflow and sensible data structures for easy data retrieval. This package leverages the strengths of biologists and computational scientists to assess and analyze multi-omic single-cell datasets. In conclusion, CITEViz streamlines the flow cytometry gating workflow in CITE-Seq data to help facilitate novel hypothesis generation.

Molecular assessment of intratumoral immune cell subsets and potential mechanisms of resistance to odronextamab, a CD20×CD3 bispecific antibody, in patients with relapsed/refractory B-cell non-Hodgkin lymphoma

BACKGROUND

Patients with relapsed/refractory B-cell non-Hodgkin lymphoma (R/R B-NHL) have a significant need for effective treatment options. Odronextamab is an Fc-silenced, human, CD20×CD3 bispecific antibody that targets CD20-expressing cells via T-cell-mediated cytotoxicity independent of T-cell/major histocompatibility complex interaction. Phase I results in patients with R/R B-NHL demonstrated that odronextamab monotherapy could achieve deep and durable responses with a generally manageable safety profile (ELM-1; NCT02290951). As part of a biomarker analysis of the same study, we investigated potential biomarkers and mechanisms of resistance to odronextamab.

METHODS

Patients with R/R B-NHL enrolled in ELM-1 received one time per week doses of intravenous odronextamab for 4×21 day cycles, then doses every 2 weeks thereafter. Patient tumor biopsies were obtained at baseline, on-treatment, and at progression. Immune cell markers were analyzed by immunohistochemistry, flow cytometry, single-cell RNA sequencing, and whole genome sequencing.

RESULTS

Baseline tumor biopsies showed that almost all patients had high proportions of B cells that expressed the CD20 target antigen, whereas expression of other B-cell surface antigens (CD19, CD22, CD79b) was more variable. Responses to odronextamab in patients with diffuse large B-cell lymphoma were not related to the relative level of baseline CD20 expression, cell of origin, or high-risk molecular subtype. A potential link was observed between greater tumor programmed cell death-ligand 1 expression and increased likelihood of response to odronextamab. Similarly, a trend was observed between clinical response and increased levels of CD8 T cells and regulatory T cells at baseline. We also identified an on-treatment pharmacodynamic shift in intratumoral immune cell subsets. Finally, loss of CD20 expression through inactivating gene mutations was identified as a potential mechanism of resistance in patients who were treated with odronextamab until progression, as highlighted in two detailed patient cases reported here.

CONCLUSIONS

This biomarker analysis expands on clinical findings of odronextamab in patients with R/R B-NHL, providing verification of the suitability of CD20 as a therapeutic target, as well as evidence for potential mechanisms of action and resistance.

Iron dysregulation and inflammatory stress erythropoiesis associates with long-term outcome of COVID-19

Persistent symptoms following SARS-CoV-2 infection are increasingly reported, although the drivers of post-acute sequelae (PASC) of COVID-19 are unclear. Here we assessed 214 individuals infected with SARS-CoV-2, with varying disease severity, for one year from COVID-19 symptom onset to determine the early correlates of PASC. A multivariate signature detected beyond two weeks of disease, encompassing unresolving inflammation, anemia, low serum iron, altered iron-homeostasis gene expression and emerging stress erythropoiesis; differentiated those who reported PASC months later, irrespective of COVID-19 severity. A whole-blood heme-metabolism signature, enriched in hospitalized patients at month 1-3 post onset, coincided with pronounced iron-deficient reticulocytosis. Lymphopenia and low numbers of dendritic cells persisted in those with PASC, and single-cell analysis reported iron maldistribution, suggesting monocyte iron loading and increased iron demand in proliferating lymphocytes. Thus, defects in iron homeostasis, dysregulated erythropoiesis and immune dysfunction due to COVID-19 possibly contribute to inefficient oxygen transport, inflammatory disequilibrium and persisting symptomatology, and may be therapeutically tractable.

Circulating Tumor Reactive KIR+CD8+ T cells Suppress Anti-Tumor Immunity in Patients with Melanoma

Effective anti-tumor immunity is largely driven by cytotoxic CD8+ T cells that can specifically recognize tumor antigens. However, the factors which ultimately dictate successful tumor rejection remain poorly understood. Here we identify a subpopulation of CD8+ T cells which are tumor antigen-specific in patients with melanoma but resemble KIR+CD8+ T cells with a regulatory function (Tregs). These tumor antigen-specific KIR+CD8+ T cells are detectable in both the tumor and the blood, and higher levels of this population are associated with worse overall survival. Our findings therefore suggest that KIR+CD8+ Tregs are tumor antigen-specific but uniquely suppress anti-tumor immunity in patients with melanoma.

Single-cell Multiomics Analysis of Myelodysplastic Syndromes and Clinical Response to Hypomethylating Therapy

Alterations in epigenetic marks, such as DNA methylation, represent a hallmark of cancer that has been successfully exploited for therapy in myeloid malignancies. Hypomethylating agents (HMA), such as azacitidine, have become standard-of-care therapy to treat myelodysplastic syndromes (MDS), myeloid neoplasms that can evolve into acute myeloid leukemia. However, our capacity to identify who will respond to HMAs, and the duration of response, remains limited. To shed light on this question, we have leveraged the unprecedented analytic power of single-cell technologies to simultaneously map the genome and immunoproteome of MDS samples throughout clinical evolution. We were able to chart the architecture and evolution of molecular clones in precious paired bone marrow MDS samples at diagnosis and posttreatment to show that a combined imbalance of specific cell lineages with diverse mutational profiles is associated with the clinical response of patients with MDS to hypomethylating therapy.

SIGNIFICANCE

MDS are myeloid clonal hemopathies with a low 5-year survival rate, and approximately half of the cases do not respond to standard HMA therapy. Our innovative single-cell multiomics approach offers valuable biological insights and potential biomarkers associated with the demethylating agent efficacy. It also identifies vulnerabilities that can be targeted using personalized combinations of small drugs and antibodies.

Single Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting (SNACS): A tool for demultiplexing single-cell DNA sequencing data

Motivation

Recently, single-cell DNA sequencing (scDNA-seq) and multi-modal profiling with the addition of cell-surface antibodies (scDAb-seq) have provided key insights into cancer heterogeneity. Scaling these technologies across large patient cohorts, however, is cost and time prohibitive. Multiplexing, in which cells from unique patients are pooled into a single experiment, offers a possible solution. While multiplexing methods exist for scRNAseq, accurate demultiplexing in scDNAseq remains an unmet need.

Results

Here, we introduce SNACS: Single-Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting. SNACS relies on a combination of patient-level cell-surface identifiers and natural variation in genetic polymorphisms to demultiplex scDNAseq data. We demonstrated the performance of SNACS on a dataset consisting of multi-sample experiments from patients with leukemia where we knew truth from single-sample experiments from the same patients. Using SNACS, accuracy ranged from 0.948 - 0.991 vs 0.552 - 0.934 using demultiplexing methods from the single-cell literature.

Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro

Assays such as CITE-seq can measure the abundance of cell surface proteins on individual cells using antibody derived tags (ADTs). However, many ADTs have high levels of background noise that can obfuscate down-stream analyses. In an exploratory analysis of PBMC datasets, we find that some droplets that were originally called 'empty' due to low levels of RNA contained high levels of ADTs and likely corresponded to neutrophils. We identified a novel type of artifact in the empty droplets called a 'spongelet' which has medium levels of ADT expression and is distinct from ambient noise. ADT expression levels in the spongelets correlate to ADT expression levels in the background peak of true cells in several datasets suggesting that they can contribute to background noise along with ambient ADTs. We then developed DecontPro, a novel Bayesian hierarchical model that can decontaminate ADT data by estimating and removing contamination from these sources. DecontPro outperforms other decontamination tools in removing aberrantly expressed ADTs while retaining native ADTs and in improving clustering specificity. Overall, these results suggest that identification of empty drops should be performed separately for RNA and ADT data and that DecontPro can be incorporated into CITE-seq workflows to improve the quality of downstream analyses.