Integration, exploration, and analysis of high-dimensional single-cell cytometry data using Spectre

A unique human cord blood CD8+CD45RA+CD27+CD161+ T-cell subset identified by flow cytometric data analysis using Seurat

Advances in single-cell level analytical techniques, especially cytometric approaches, have led to profound innovation in biomedical research, particularly in the field of clinical immunology. This has resulted in an expansion of high-dimensional data, posing great challenges for comprehensive and unbiased analysis. Conventional manual analysis is thus becoming untenable to handle these challenges. Furthermore, most newly developed computational methods lack flexibility and interoperability, hampering their accessibility and usability. Here, we adapted Seurat, an R package originally developed for single-cell RNA sequencing (scRNA-seq) analysis, for high-dimensional flow cytometric data analysis. Based on a 20-marker antibody panel and analyses of T-cell profiles in both adult blood and cord blood (CB), we showcased the robust capacity of Seurat in flow cytometric data analysis, which was further validated by Spectre, another high-dimensional cytometric data analysis package, and conventional manual analysis. Importantly, we identified a unique CD8+ T-cell population defined as CD8+CD45RA+CD27+CD161+ T cell that was predominantly present in CB. We characterised its IFN-γ-producing and potential cytotoxic properties using flow cytometry experiments and scRNA-seq analysis from a published dataset. Collectively, we identified a unique human CB CD8+CD45RA+CD27+CD161+ T-cell subset and demonstrated that Seurat, a widely used package for scRNA-seq analysis, possesses great potential to be repurposed for cytometric data analysis. This facilitates an unbiased and thorough interpretation of complicated high-dimensional data using a single analytical pipeline and opens a novel avenue for data-driven investigation in clinical immunology.

Identification of cells of leukemic stem cell origin with non-canonical regenerative properties

Despite most acute myeloid leukemia (AML) patients entering remission following chemotherapy, outcomes remain poor due to surviving leukemic cells that contribute to relapse. The nature of these enduring cells is poorly understood. Here, through temporal single-cell transcriptomic characterization of AML hierarchical regeneration in response to chemotherapy, we reveal a cell population: AML regeneration enriched cells (RECs). RECs are defined by CD74/CD68 expression, and although derived from leukemic stem cells (LSCs), are devoid of stem/progenitor capacity. Based on REC in situ proximity to CD34-expressing cells identified using spatial transcriptomics on AML patient bone marrow samples, RECs demonstrate the ability to augment or reduce leukemic regeneration in vivo based on transfusion or depletion, respectively. Furthermore, RECs are prognostic for patient survival as well as predictive of treatment failure in AML cohorts. Our study reveals RECs as a previously unknown functional catalyst of LSC-driven regeneration contributing to the non-canonical framework of AML regeneration.

SuperCellCyto: enabling efficient analysis of large scale cytometry datasets

Advancements in cytometry technologies have enabled quantification of up to 50 proteins across millions of cells at single cell resolution. Analysis of cytometry data routinely involves tasks such as data integration, clustering, and dimensionality reduction. While numerous tools exist, many require extensive run times when processing large cytometry data containing millions of cells. Existing solutions, such as random subsampling, are inadequate as they risk excluding rare cell subsets. To address this, we propose SuperCellCyto, an R package that builds on the SuperCell tool which groups highly similar cells into supercells. SuperCellCyto is available on GitHub ( https://github.com/phipsonlab/SuperCellCyto ) and Zenodo ( https://doi.org/10.5281/zenodo.10521294 ).

Spectral flow cytometry: Fundamentals and future impact

Spectral flow cytometry has emerged as a significant player in the cytometry marketplace, with the potential for rapid growth. Despite a slow start, the technology has made significant strides in advancing various areas of single-cell analysis utilized by the scientific community. The integration of spectral cytometry into clinical laboratories and diagnostic processes is currently underway and is expected to garner a significant level of widespread acceptance in the near future. However, incorporating a new methodological approach into existing research programs can lead to misunderstandings or even misuse. This chapter offers an introductory yet comprehensive explanation of the scientific principles that form the foundation of spectral cytometry. Specifically, it delves into the unmixing processes that are utilized for data analysis. This overview is designed for those who are new to the field and seeking an informative guide to this exciting emerging technology.

CD200+ fibroblasts form a pro-resolving mesenchymal network in arthritis

Fibroblasts are important regulators of inflammation, but whether fibroblasts change phenotype during resolution of inflammation is not clear. Here we use positron emission tomography to detect fibroblast activation protein (FAP) as a means to visualize fibroblast activation in vivo during inflammation in humans. While tracer accumulation is high in active arthritis, it decreases after tumor necrosis factor and interleukin-17A inhibition. Biopsy-based single-cell RNA-sequencing analyses in experimental arthritis show that FAP signal reduction reflects a phenotypic switch from pro-inflammatory MMP3+/IL6+ fibroblasts (high FAP internalization) to pro-resolving CD200+DKK3+ fibroblasts (low FAP internalization). Spatial transcriptomics of human joints indicates that pro-resolving niches of CD200+DKK3+ fibroblasts cluster with type 2 innate lymphoid cells, whereas MMP3+/IL6+ fibroblasts colocalize with inflammatory immune cells. CD200+DKK3+ fibroblasts stabilized the type 2 innate lymphoid cell phenotype and induced resolution of arthritis via CD200-CD200R1 signaling. Taken together, these data suggest a dynamic molecular regulation of the mesenchymal compartment during resolution of inflammation.

Differential anti-viral response to respiratory syncytial virus A in preterm and term infants

BACKGROUND

Preterm infants are more likely to experience severe respiratory syncytial virus (RSV) disease compared to term infants. The reasons for this are multi-factorial, however their immature immune system is believed to be a major contributing factor.

METHODS

We collected cord blood from 25 preterm (gestational age 30.4-34.1 weeks) and 25 term infants (gestation age 37-40 weeks) and compared the response of cord blood mononuclear cells (CBMCs) to RSVA and RSVB stimulation using neutralising assays, high-dimensional flow cytometry, multiplex cytokine assays and RNA-sequencing.

FINDINGS

We found that preterm and term infants had similar maternally derived neutralising antibody titres to RSVA and RSVB. Preterm infants had significantly higher myeloid dendritic cells (mDC) RSV infection compared to term infants. Differential gene expression analysis of RSVA stimulated CBMCs revealed enrichment of genes involved in cytokine production and immune regulatory pathways involving IL-10, IL-36γ, CXCL1, CXCL2, SOCS1 and SOCS3 in term infants, while differentially expressed genes (DEGs) in preterm infants were related to cell cycle (CDK1, TTK, ESCO2, KNL1, CDC25A, MAD2L1) without associated expression of immune response genes. Furthermore, enriched genes in term infants were highly correlated suggesting an increased co-ordination of their immune response to RSVA. When comparing DEGs in preterm and term infants following RSVB stimulation, no differences in immune response genes were identified.

INTERPRETATION

Overall, our data suggests that preterm infants have a more restricted immunological response to RSVA compared with term infants. While further studies are required, these findings may help to explain why preterm infants are more susceptible to severe RSV disease and identify potential therapeutic targets to protect these vulnerable infants.

FUNDING

Murdoch Children's Research Institute Infection and Immunity theme grant.

Depleting myeloid-biased haematopoietic stem cells rejuvenates aged immunity

Ageing of the immune system is characterized by decreased lymphopoiesis and adaptive immunity, and increased inflammation and myeloid pathologies1,2. Age-related changes in populations of self-renewing haematopoietic stem cells (HSCs) are thought to underlie these phenomena3. During youth, HSCs with balanced output of lymphoid and myeloid cells (bal-HSCs) predominate over HSCs with myeloid-biased output (my-HSCs), thereby promoting the lymphopoiesis required for initiating adaptive immune responses, while limiting the production of myeloid cells, which can be pro-inflammatory4. Ageing is associated with increased proportions of my-HSCs, resulting in decreased lymphopoiesis and increased myelopoiesis3,5,6. Transfer of bal-HSCs results in abundant lymphoid and myeloid cells, a stable phenotype that is retained after secondary transfer; my-HSCs also retain their patterns of production after secondary transfer5. The origin and potential interconversion of these two subsets is still unclear. If they are separate subsets postnatally, it might be possible to reverse the ageing phenotype by eliminating my-HSCs in aged mice. Here we demonstrate that antibody-mediated depletion of my-HSCs in aged mice restores characteristic features of a more youthful immune system, including increasing common lymphocyte progenitors, naive T cells and B cells, while decreasing age-related markers of immune decline. Depletion of my-HSCs in aged mice improves primary and secondary adaptive immune responses to viral infection. These findings may have relevance to the understanding and intervention of diseases exacerbated or caused by dominance of the haematopoietic system by my-HSCs.

NK cell profiling in West Nile virus encephalitis reveals potential metabolic basis for functional inhibition

Natural killer (NK) cells are cytotoxic lymphocytes important for viral defense. West Nile virus (WNV) infection of the central nervous system (CNS) causes marked recruitment of bone marrow (BM)-derived monocytes, T cells and NK cells, resulting in severe neuroinflammation and brain damage. Despite substantial numbers of NK cells in the CNS, their function and phenotype remain largely unexplored. Here, we demonstrate that NK cells mature from the BM to the brain, upregulate inhibitory receptors and show reduced cytokine production and degranulation, likely due to the increased expression of the inhibitory NK cell molecule, MHC-I. Intriguingly, this correlated with a reduction in metabolism associated with cytotoxicity in brain-infiltrating NK cells. Importantly, the degranulation and killing capability were restored in NK cells isolated from WNV-infected tissue, suggesting that WNV-induced NK cell inhibition occurs in the CNS. Overall, this work identifies a potential link between MHC-I inhibition of NK cells and metabolic reduction of their cytotoxicity during infection.

Characterization of Vascular Niche in Systemic Sclerosis by Spatial Proteomics

BACKGROUND

Systemic sclerosis (SSc) is a connective tissue disease that can serve as a model to study vascular changes in response to inflammation, autoimmunity, and fibrotic remodeling. Although microvascular changes are the earliest histopathologic manifestation of SSc, the vascular pathophysiology remains poorly understood.

METHODS

We applied spatial proteomic approaches to deconvolute the heterogeneity of vascular cells at the single-cell level in situ and characterize cellular alterations of the vascular niches of patients with SSc. Skin biopsies of patients with SSc and control individuals were analyzed by imaging mass cytometry, yielding a total of 90 755 cells including 2987 endothelial cells and 4096 immune cells.

RESULTS

We identified 7 different subpopulations of blood vascular endothelial cells (VECs), 2 subpopulations of lymphatic endothelial cells, and 3 subpopulations of pericytes. A novel population of CD34+;αSMA+ (α-smooth muscle actin);CD31+ VECs was more common in SSc, whereas endothelial precursor cells were decreased. Co-detection by indexing and tyramide signal amplification confirmed these findings. The microenvironment of CD34+;αSMA+;CD31+ VECs was enriched for immune cells and myofibroblasts, and CD34+;αSMA+;CD31+ VECs expressed markers of endothelial-to-mesenchymal transition. The density of CD34+;αSMA+;CD31+ VECs was associated with clinical progression of fibrosis in SSc.

CONCLUSIONS

Using spatial proteomics, we unraveled the heterogeneity of vascular cells in control individuals and patients with SSc. We identified CD34+;αSMA+;CD31+ VECs as a novel endothelial cell population that is increased in patients with SSc, expresses markers for endothelial-to-mesenchymal transition, and is located in close proximity to immune cells and myofibroblasts. CD34+;αSMA+;CD31+ VEC counts were associated with clinical outcomes of progressive fibrotic remodeling, thus providing a novel cellular correlate for the crosstalk of vasculopathy and fibrosis.

Differentiation marker-negative CD4+ T cells persist after yellow fever virus vaccination and contribute to durable memory

Factors that contribute to durable immunological memory remain incompletely understood. In our longitudinal analyses of CD4+ T cell responses to the yellow fever virus (YFV) vaccine by peptide-MHC tetramers, we unexpectedly found naïve phenotype virus-specific CD4+ T cells that persisted months to years after immunization. These Marker negative T cells (TMN) lacked CD95, CXCR3, CD11a, and CD49d surface protein expression, distinguishing them from previously discovered stem-cell memory T cells. Functionally, they resembled genuine naïve T cells upon in vitro stimulation. Single-cell TCR sequencing detected expanded clonotypes within the TMN subset and identified a shared repertoire with memory and effector T cells. T cells expressing TMN-associated TCRs were rare before vaccination, suggesting their expansion following vaccination. Longitudinal tracking of YFV-specific responses over the subsequent years revealed superior stability of the TMN subset and their association with the longevity of the overall population. The identification of these long-lived, antigen-experienced T cells may inform the design of durable T cell-based vaccines and engineered T cell therapies.

Immunophenotyping challenging tissue types using high-dimensional full spectrum flow cytometry

Technological advancements in fluorescence flow cytometry and an ever-expanding understanding of the complexity of the immune system, have led to the development of large flow cytometry panels, reaching up to 40 markers at the single-cell level. Full spectrum flow cytometry, that measures the full emission range of all the fluorophores present in the panel instead of only the emission peaks is now routinely used in many laboratories internationally, and the demand for this technology is rapidly increasing. With the capacity to use larger and more complex staining panels, optimized protocols are required for the best panel design, panel validation and high-dimensional data analysis outcomes. In addition, for ex vivo experiments, tissue preparation methods for single-cell analysis should also be optimized to ensure that samples are of the highest quality and are truly representative of tissues in situ. Here we provide optimized step-by-step protocols for full spectrum flow cytometry panel design, tissue digestion and panel optimization to facilitate the analysis of challenging tissue types.

Decidual leukocytes respond to African lineage Zika virus infection with mild anti-inflammatory changes during acute infection in rhesus macaques

Zika virus (ZIKV) can be vertically transmitted during pregnancy resulting in a range of adverse pregnancy outcomes. The decidua is commonly found to be infected by ZIKV, yet the acute immune response to infection remains understudied in vivo. We hypothesized that in vivo African-lineage ZIKV infection induces a pro-inflammatory response in the decidua. To test this hypothesis, we evaluated the decidua in pregnant rhesus macaques within the first two weeks following infection with an African-lineage ZIKV and compared our findings to gestationally aged-matched controls. Decidual leukocytes were phenotypically evaluated using spectral flow cytometry, and cytokines and chemokines were measured in tissue homogenates from the decidua, placenta, and fetal membranes. The results of this study did not support our hypothesis. Although ZIKV RNA was detected in the decidual tissue samples from all ZIKV infected dams, phenotypic changes in decidual leukocytes and differences in cytokine profiles suggest that the decidua undergoes mild anti-inflammatory changes in response to that infection. Our findings emphasize the immunological state of the gravid uterus as a relatively immune privileged site that prioritizes tolerance of the fetus over mounting a pro-inflammatory response to clear infection.

High-Dimensional Methods of Single-Cell Microglial Profiling to Enhance Understanding of Neuropathological Disease

Microglia are the innate myeloid cells of the central nervous system (CNS) parenchyma, functionally implicated in almost every defined neuroinflammatory and neurodegenerative disorder. Current understanding of disease pathogenesis for many neuropathologies is limited and/or lacks reliable diagnostic markers, vaccines, and treatments. With the increasing aging of society and rise in neurogenerative diseases, improving our understanding of their pathogenesis is essential. Analysis of microglia from murine disease models provides an investigative tool to unravel disease processes. In many neuropathologies, bone-marrow-derived monocytes are recruited to the CNS, adopting a phenotype similar to that of microglia. This significantly confounds the accurate identification of cell-type-specific functions and downstream therapeutic targeting. The increased capacity to analyze more phenotypic markers using spectral-cytometry-based technologies allows improved separation of microglia from monocyte-derived cells. Full-spectrum profiling enables enhanced marker resolution, time-efficient analysis of >40 fluorescence parameters, and extraction of cellular autofluorescence parameters. Coupling this system with additional cytometric technologies, including cell sorting and high-parameter imaging, can improve the understanding of microglial phenotypes in disease. To this end, we provide detailed, step-by-step protocols for the analysis of murine brain tissue by high-parameter ex vivo cytometric analysis using the Aurora spectral cytometer (Cytek), including best practices for unmixing and autofluorescence extraction, cell sorting for single-cell RNA analysis, and imaging mass cytometry. Together, this provides a toolkit for researchers to comprehensively investigate microglial disease processes at protein, RNA, and spatial levels for the identification of therapeutic targets in neuropathology. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Processing the mouse brain into a single-cell suspension for microglia isolation Basic Protocol 2: Staining single-cell mouse brain suspensions for microglial phenotyping by spectral cytometry Basic Protocol 3: Flow cytometric sorting of mouse microglia for ex vivo analysis Basic Protocol 4: Processing the mouse brain for imaging mass cytometry for spatial microglia analysis.

CD8+ T Cells Mediate Lethal Lung Pathology in the Absence of PD-L1 and Type I Interferon Signalling following LCMV Infection

CD8+ T cells are critical to the adaptive immune response against viral pathogens. However, overwhelming antigen exposure can result in their exhaustion, characterised by reduced effector function, failure to clear virus, and the upregulation of inhibitory receptors, including programmed cell death 1 (PD-1). However, exhausted T cell responses can be "re-invigorated" by inhibiting PD-1 or the primary ligand of PD-1: PD-L1. Further, the absence of the type I interferon receptor IFNAR1 also results in T cell exhaustion and virus persistence in lymphocytic choriomeningitis virus Armstrong (LCMV-Arm)-infected mice. In this study, utilizing single- and double-knockout mice, we aimed to determine whether ablation of PD-1 could restore T cell functionality in the absence of IFNAR1 signalling in LCMV-Arm-infected mice. Surprisingly, this did not re-invigorate the T cell response and instead, it converted chronic LCMV-Arm infection into a lethal disease characterized by severe lung inflammation with an infiltration of neutrophils and T cells. Depletion of CD8+ T cells, but not neutrophils, rescued mice from lethal disease, demonstrating that IFNAR1 is required to prevent T cell exhaustion and virus persistence in LCMV-Arm infection, and in the absence of IFNAR1, PD-L1 is required for survival. This reveals an important interplay between IFNAR1 and PD-L1 with implications for therapeutics targeting these pathways.

CytoPipeline and CytoPipelineGUI: a Bioconductor R package suite for building and visualizing automated pre-processing pipelines for flow cytometry data

BACKGROUND

With the increase of the dimensionality in flow cytometry data over the past years, there is a growing need to replace or complement traditional manual analysis (i.e. iterative 2D gating) with automated data analysis pipelines. A crucial part of these pipelines consists of pre-processing and applying quality control filtering to the raw data, in order to use high quality events in the downstream analyses. This part can in turn be split into a number of elementary steps: signal compensation or unmixing, scale transformation, debris, doublets and dead cells removal, batch effect correction, etc. However, assembling and assessing the pre-processing part can be challenging for a number of reasons. First, each of the involved elementary steps can be implemented using various methods and R packages. Second, the order of the steps can have an impact on the downstream analysis results. Finally, each method typically comes with its specific, non standardized diagnostic and visualizations, making objective comparison difficult for the end user.

RESULTS

Here, we present CytoPipeline and CytoPipelineGUI, two R packages to build, compare and assess pre-processing pipelines for flow cytometry data. To exemplify these new tools, we present the steps involved in designing a pre-processing pipeline on a real life dataset and demonstrate different visual assessment use cases. We also set up a benchmarking comparing two pre-processing pipelines differing by their quality control methods, and show how the package visualization utilities can provide crucial user insight into the obtained benchmark metrics.

CONCLUSION

CytoPipeline and CytoPipelineGUI are two Bioconductor R packages that help building, visualizing and assessing pre-processing pipelines for flow cytometry data. They increase productivity during pipeline development and testing, and complement benchmarking tools, by providing user intuitive insight into benchmarking results.

OMIP-100: A flow cytometry panel to investigate human neutrophil subsets

This 14-color, 13-antibody optimized multicolor immunofluorescence panel (OMIP) was designed for deep profiling of neutrophil subsets in various types of human samples to contextualize neutrophil plasticity in a range of healthy and diseased states. Markers present in the OMIP allow the profiling of neutrophil subsets associated with ontogeny, migration, phagocytosis capacity, granule release, and immune modulation. For panel design, we ensured that the commonly available fluorophores FITC/AF488, PE, and APC were assigned to the intracellular subset marker Olfactomedin 4, the maturity and activation marker CD10, and whole blood subset marker CD177, respectively. These markers can be easily replaced without affecting the core identification of neutrophils, enabling antibodies to new neutrophil antigens of interest or for fluorescent substrates to assess different neutrophil functions to be easily explored. Panel optimization was performed on whole blood and purified neutrophils. We demonstrate applications on clinical samples (whole blood and saliva) and experimental endpoints (purified neutrophils stimulated through an in vitro transmigration assay). We hope that providing a uniform platform to analyze neutrophil plasticity in various sample types will facilitate the future understanding of neutrophil subsets in health and disease.

PD1+TIGIT+2B4+KLRG1+ Cells Might Underlie T Cell Dysfunction in Patients Treated with BCMA-Directed Chimeric Antigen Receptor T Cell Therapy

Chimeric antigen receptor T cell (CAR-T) therapy has shown rapid, frequent, and deep responses in patients with relapsed/refractory multiple myeloma (RRMM). However, relapse frequently occurs following CAR-T therapy, and the cause of this resistance is not well defined. Among the potential mechanisms of resistance, T cell intrinsic factors may be an important source of failure. Here we used spectral flow cytometry to identify the changes in T cell phenotypes in bone marrow aspirates at different stages of multiple myeloma progression, including cases that relapsed after anti-BCMA CAR-T therapy. We identified completely different T cell phenotypes in RRMM and post CAR-T relapse cases compared to healthy donors and earlier stages of multiple myeloma, novel double-negative CD3+ T cells in RRMM and CAR-T relapsed cases, and differences in CD8 T cell phenotype at the baseline between peripheral blood and bone marrow from healthy donors. We found that the majority of T cells in RRMM patients and significant T cell subsets in post-CAR-T relapsed patients expressed multiple coinhibitory markers, including PD1, TIGIT, 2B4, and KLRG1.

Loss of NAT10 disrupts enhancer organization via p300 mislocalization and suppresses transcription of genes necessary for metastasis progression

Acetylation of protein and RNA represent a critical event for development and cancer progression. NAT10 is the only known RNA acetylase that catalyzes the N4-actylcytidine (ac4C) modification of RNAs. Here, we show that the loss of NAT10 significantly decreases lung metastasis in allograft and genetically engineered mouse models of breast cancer. NAT10 interacts with a mechanosensitive, metastasis susceptibility protein complex at the nuclear pore. In addition to its canonical role in RNA acetylation, we find that NAT10 interacts with p300 at gene enhancers. NAT10 loss is associated with p300 mislocalization into heterochromatin regions. NAT10 depletion disrupts enhancer organization, leading to alteration of gene transcription necessary for metastatic progression, including reduced myeloid cell-recruiting chemokines that results in a less metastasis-prone tumor microenvironment. Our study uncovers a distinct role of NAT10 in enhancer organization of metastatic tumor cells and suggests its involvement in the tumor-immune crosstalk dictating metastatic outcomes.

Panel Design and Optimization for Full Spectrum Flow Cytometry

Technological advancements in fluorescence flow cytometry and an ever-expanding understanding of the complexity of the immune system have led to the development of large flow cytometry panels, reaching up to 40 markers at the single-cell level. Full spectrum flow cytometry, which measures the full emission range of all the fluorophores present in the panel instead of only the emission peaks, is now routinely used in laboratories around the world, and the demand for this technology is rapidly increasing. With the ability to use larger and more complex staining panels, optimized protocols are vital for achieving the best panel design, panel optimization, and high-dimensional data analysis outcomes. In addition, a better understanding of how to fully characterize the autofluorescence of the sample, coupled with an intelligent panel design approach, allows improved marker resolution on highly autofluorescent tissues or cells. Here, we provide optimized step-by-step protocols for full spectrum flow cytometry, covering panel design and optimization, autofluorescence evaluation and strategy selection, and methods for performing longitudinal studies.

OPTIMAL: An OPTimized Imaging Mass cytometry AnaLysis framework for benchmarking segmentation and data exploration

Analysis of imaging mass cytometry (IMC) data and other low-resolution multiplexed tissue imaging technologies is often confounded by poor single-cell segmentation and suboptimal approaches for data visualization and exploration. This can lead to inaccurate identification of cell phenotypes, states, or spatial relationships compared to reference data from single-cell suspension technologies. To this end we have developed the "OPTimized Imaging Mass cytometry AnaLysis (OPTIMAL)" framework to benchmark any approaches for cell segmentation, parameter transformation, batch effect correction, data visualization/clustering, and spatial neighborhood analysis. Using a panel of 27 metal-tagged antibodies recognizing well-characterized phenotypic and functional markers to stain the same Formalin-Fixed Paraffin Embedded (FFPE) human tonsil sample tissue microarray over 12 temporally distinct batches we tested several cell segmentation models, a range of different arcsinh cofactor parameter transformation values, 5 different dimensionality reduction algorithms, and 2 clustering methods. Finally, we assessed the optimal approach for performing neighborhood analysis. We found that single-cell segmentation was improved by the use of an Ilastik-derived probability map but that issues with poor segmentation were only really evident after clustering and cell type/state identification and not always evident when using "classical" bivariate data display techniques. The optimal arcsinh cofactor for parameter transformation was 1 as it maximized the statistical separation between negative and positive signal distributions and a simple Z-score normalization step after arcsinh transformation eliminated batch effects. Of the five different dimensionality reduction approaches tested, PacMap gave the best data structure with FLOWSOM clustering out-performing phenograph in terms of cell type identification. We also found that neighborhood analysis was influenced by the method used for finding neighboring cells with a "disc" pixel expansion outperforming a "bounding box" approach combined with the need for filtering objects based on size and image-edge location. Importantly, OPTIMAL can be used to assess and integrate with any existing approach to IMC data analysis and, as it creates .FCS files from the segmentation output and allows for single-cell exploration to be conducted using a wide variety of accessible software and algorithms familiar to conventional flow cytometrists.

Aged intestinal stem cells propagate cell-intrinsic sources of inflammaging in mice

Low-grade chronic inflammation is a hallmark of ageing, associated with impaired tissue function and disease development. However, how cell-intrinsic and -extrinsic factors collectively establish this phenotype, termed inflammaging, remains poorly understood. We addressed this question in the mouse intestinal epithelium, using mouse organoid cultures to dissect stem cell-intrinsic and -extrinsic sources of inflammaging. At the single-cell level, we found that inflammaging is established differently along the crypt-villus axis, with aged intestinal stem cells (ISCs) strongly upregulating major histocompatibility complex class II (MHC-II) genes. Importantly, the inflammaging phenotype was stably propagated by aged ISCs in organoid cultures and associated with increased chromatin accessibility at inflammation-associated loci in vivo and ex vivo, indicating cell-intrinsic inflammatory memory. Mechanistically, we show that the expression of inflammatory genes is dependent on STAT1 signaling. Together, our data identify that intestinal inflammaging in mice is promoted by a cell-intrinsic mechanism, stably propagated by ISCs, and associated with a disbalance in immune homeostasis.

LOCATOR: feature extraction and spatial analysis of the cancer tissue microenvironment using mass cytometry imaging technologies

Motivation

Recent advances in highly multiplexed imaging have provided unprecedented insights into the complex cellular organization of tissues, with many applications in translational medicine. However, downstream analyses of multiplexed imaging data face several technical limitations, and although some computational methods and bioinformatics tools are available, deciphering the complex spatial organization of cellular ecosystems remains a challenging problem.

Results

To mitigate this problem, we develop a novel computational tool, LOCATOR (anaLysis Of CAncer Tissue micrOenviRonment), for spatial analysis of cancer tissue microenvironments using data acquired from mass cytometry imaging technologies. LOCATOR introduces a graph-based representation of tissue images to describe features of the cellular organization and deploys downstream analysis and visualization utilities that can be used for data-driven patient-risk stratification. Our case studies using mass cytometry imaging data from two well-annotated breast cancer cohorts re-confirmed that the spatial organization of the tumour-immune microenvironment is strongly associated with the clinical outcome in breast cancer. In addition, we report interesting potential associations between the spatial organization of macrophages and patients' survival. Our work introduces an automated and versatile analysis tool for mass cytometry imaging data with many applications in future cancer research projects.

Availability and implementation

Datasets and codes of LOCATOR are publicly available at https://github.com/RezvanEhsani/LOCATOR.

An introduction to representation learning for single-cell data analysis

Single-cell-resolved systems biology methods, including omics- and imaging-based measurement modalities, generate a wealth of high-dimensional data characterizing the heterogeneity of cell populations. Representation learning methods are routinely used to analyze these complex, high-dimensional data by projecting them into lower-dimensional embeddings. This facilitates the interpretation and interrogation of the structures, dynamics, and regulation of cell heterogeneity. Reflecting their central role in analyzing diverse single-cell data types, a myriad of representation learning methods exist, with new approaches continually emerging. Here, we contrast general features of representation learning methods spanning statistical, manifold learning, and neural network approaches. We consider key steps involved in representation learning with single-cell data, including data pre-processing, hyperparameter optimization, downstream analysis, and biological validation. Interdependencies and contingencies linking these steps are also highlighted. This overview is intended to guide researchers in the selection, application, and optimization of representation learning strategies for current and future single-cell research applications.

A unique cytotoxic CD4+ T cell-signature defines critical COVID-19

Objectives

SARS-CoV-2 infection causes a spectrum of clinical disease presentation, ranging from asymptomatic to fatal. While neutralising antibody (NAb) responses correlate with protection against symptomatic and severe infection, the contribution of the T-cell response to disease resolution or progression is still unclear. As newly emerging variants of concern have the capacity to partially escape NAb responses, defining the contribution of individual T-cell subsets to disease outcome is imperative to inform the development of next-generation COVID-19 vaccines.

Methods

Immunophenotyping of T-cell responses in unvaccinated individuals was performed, representing the full spectrum of COVID-19 clinical presentation. Computational and manual analyses were used to identify T-cell populations associated with distinct disease states.

Results

Critical SARS-CoV-2 infection was characterised by an increase in activated and cytotoxic CD4+ lymphocytes (CTL). These CD4+ CTLs were largely absent in asymptomatic to severe disease states. In contrast, non-critical COVID-19 was associated with high frequencies of naïve T cells and lack of activation marker expression.

Conclusion

Highly activated and cytotoxic CD4+ T-cell responses may contribute to cell-mediated host tissue damage and progression of COVID-19. Induction of these potentially detrimental T-cell responses should be considered when developing and implementing effective COVID-19 control strategies.

AliGater: a framework for the development of bioinformatic pipelines for large-scale, high-dimensional cytometry data

Motivation

AliGater is an open-source framework to accelerate the development of bioinformatic pipelines for the analysis of large-scale, high-dimensional flow cytometry data. AliGater provides a Python package for automatic feature extraction workflows, as well as building blocks to construct analysis pipelines.

Results

We illustrate the use of AliGater in a high-resolution flow cytometry-based genome-wide association study on 46 immune cell populations in 14 288 individuals.

Availability and implementation

Source code and documentation at https://github.com/LudvigEk/aligater and https://aligater.readthedocs.io.

Treatment of adult ALL patients with third-generation CD19-directed CAR T cells: results of a pivotal trial

BACKGROUND

Third-generation chimeric antigen receptor (CAR)-engineered T cells (CARTs) might improve clinical outcome of patients with B cell malignancies. This is the first report on a third-generation CART dose-escalating, phase-1/2 investigator-initiated trial treating adult patients with refractory and/or relapsed (r/r) acute lymphoblastic leukemia (ALL).

METHODS

Thirteen patients were treated with escalating doses of CD19-directed CARTs between 1 × 10⁶ and 50 × 10⁶ CARTs/m². Leukapheresis, manufacturing and administration of CARTs were performed in-house.

RESULTS

For all patients, CART manufacturing was feasible. None of the patients developed any grade of Immune effector cell-associated neurotoxicity syndrome (ICANS) or a higher-grade (≥ grade III) catokine release syndrome (CRS). CART expansion and long-term CART persistence were evident in the peripheral blood (PB) of evaluable patients. At end of study on day 90 after CARTs, ten patients were evaluable for response: Eight patients (80%) achieved a complete remission (CR), including five patients (50%) with minimal residual disease (MRD)-negative CR. Response and outcome were associated with the administered CART dose. At 1-year follow-up, median overall survival was not reached and progression-free survival (PFS) was 38%. Median PFS was reached on day 120. Lack of CD39-expression on memory-like T cells was more frequent in CART products of responders when compared to CART products of non-responders. After CART administration, higher CD8 + and γδ-T cell frequencies, a physiological pattern of immune cells and lower monocyte counts in the PB were associated with response.

CONCLUSION

In conclusion, third-generation CARTs were associated with promising clinical efficacy and remarkably low procedure-specific toxicity, thereby opening new therapeutic perspectives for patients with r/r ALL. Trial registration This trial was registered at www.

CLINICALTRIALS

gov as NCT03676504.

CD11c+ and IRF8+ cell densities in rectal cancer biopsies predict outcomes of neoadjuvant chemoradiotherapy

Approximately 20% of locally advanced rectal cancer (LARC) patients treated preoperatively with chemoradiotherapy (CRT) achieve pathologically confirmed complete regression. However, there are no clinically implemented biomarkers measurable in biopsies that are predictive of tumor regression. Here, we conducted multiplexed immunophenotyping of rectal cancer diagnostic biopsies from 16 LARC patients treated preoperatively with CRT. We identified that patients with greater tumor regression had higher tumor infiltration of pan-T cells and IRF8+HLA-DR+ cells prior to CRT. High IRF8+HLA-DR+ cell density was further associated with prolonged disease-specific survival with 83% survival at 5 y compared to 28% in patients with low infiltration. Contrastingly, low CD11c+ myeloid cell infiltration prior to CRT was a putative biomarker associated with longer 3- and 5-y disease-free survival. The results demonstrate the potential use of rectal cancer diagnostic biopsies to measure IRF8+ HLA-DR+ cells as predictors of CRT-induced tumor regression and CD11c+ myeloid cells as predictors of LARC patient survival.

Flow Cytometry: The Next Revolution

Unmasking the subtleties of the immune system requires both a comprehensive knowledge base and the ability to interrogate that system with intimate sensitivity. That task, to a considerable extent, has been handled by an iterative expansion in flow cytometry methods, both in technological capability and also in accompanying advances in informatics. As the field of fluorescence-based cytomics matured, it reached a technological barrier at around 30 parameter analyses, which stalled the field until spectral flow cytometry created a fundamental transformation that will likely lead to the potential of 100 simultaneous parameter analyses within a few years. The simultaneous advance in informatics has now become a watershed moment for the field as it competes with mature systematic approaches such as genomics and proteomics, allowing cytomics to take a seat at the multi-omics table. In addition, recent technological advances try to combine the speed of flow systems with other detection methods, in addition to fluorescence alone, which will make flow-based instruments even more indispensable in any biological laboratory. This paper outlines current approaches in cell analysis and detection methods, discusses traditional and microfluidic sorting approaches as well as next-generation instruments, and provides an early look at future opportunities that are likely to arise.

tidytof: a user-friendly framework for scalable and reproducible high-dimensional cytometry data analysis

Summary

While many algorithms for analyzing high-dimensional cytometry data have now been developed, the software implementations of these algorithms remain highly customized-this means that exploring a dataset requires users to learn unique, often poorly interoperable package syntaxes for each step of data processing. To solve this problem, we developed {tidytof}, an open-source R package for analyzing high-dimensional cytometry data using the increasingly popular 'tidy data' interface.

Availability and implementation

{tidytof} is available at https://github.com/keyes-timothy/tidytof and is released under the MIT license. It is supported on Linux, MS Windows and MacOS. Additional documentation is available at the package website (https://keyes-timothy.github.io/tidytof/).

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Influence of bariatric surgery on the peripheral blood immune system of female patients with morbid obesity revealed by high-dimensional mass cytometry

Introduction

Obesity is associated with low-grade chronic inflammation, altered levels of adipocytokines, and impaired regulation of gastrointestinal hormones. Secreted, these factors exert immunostimulatory functions directly influencing peripheral immune cells.

Methods

In the realm of this study, we aimed to investigate the composition and activation status of peripheral blood immune cells in female patients with morbid obesity compared to lean controls using high-dimensional mass cytometry. Besides, we also assessed the influence of bariatric surgery with respect to its ability to reverse obesity-associated alterations within the first-year post-surgery.

Results

Patients with morbid obesity showed typical signs of chronic inflammation characterized by increased levels of CRP and fibrinogen. Apart from that, metabolic alterations were characterized by increased levels of leptin and resistin as well as decreased levels of adiponectin and ghrelin compared to the healthy control population. All these however, except for ghrelin levels, rapidly normalized after surgery with regard to control levels. Furthermore, we found an increased population of monocytic CD14⁺, HLA-DR^-, CD11b⁺, CXCR3⁺ cells in patients with morbid obesity and an overall reduction of the HLA-DR monocytic expression compared to the control population. Although CD14⁺, HLA-DR^-, CD11b⁺, CXCR3⁺ decreased after surgery, HLA-DR expression did not recover within 9 - 11 months post-surgery. Moreover, compared to the control population, patients with morbid obesity showed a perturbed CD4+ T cell compartment, characterized by a strongly elevated CD127⁺ memory T cell subset and decreased naïve T cells, which was not recovered within 9 - 11 months post-surgery. Although NK cells showed an activated phenotype, they were numerically lower in patients with morbid obesity when compared to healthy controls. The NK cell population further decreased after surgery and did not recover quantitatively within the study period.

Conclusions

Our results clearly demonstrate that the rapid adaptions in inflammatory parameters and adipocytokine levels that occur within the first year post-surgery do not translate to the peripheral immune cells. Apart from that, we described highly affected, distinct immune cell subsets, defined as CD127⁺ memory T cells and monocytic CD14⁺, HLA-DR, CD11b⁺, CXCR3⁺ cells, that might play a significant role in understanding and further decoding the etiopathogenesis of morbid obesity.

High-throughput interrogation of immune responses using the Human Immune Profiling Pipeline

The current abundance of immunotherapy clinical trials presents an opportunity to learn about the underlying mechanisms and pharmacodynamic effects of novel drugs on the human immune system. Here, we present a protocol to study how these immune responses impact clinical outcomes using large-scale high-throughput immune profiling of clinical cohorts. We describe the Human Immune Profiling Pipeline, which comprises an end-to-end solution from flow cytometry results to computational approaches and unsupervised patient clustering based on lymphocyte landscape. For complete details on the use and execution of this protocol, please refer to Lyudovyk et al. (2022).1.

Integrating transcriptomic datasets across neurological disease identifies unique myeloid subpopulations driving disease-specific signatures

Microglia and bone marrow-derived monocytes are key elements of central nervous system (CNS) inflammation, both capable of enhancing and dampening immune-mediated pathology. However, the study-specific focus on individual cell types, disease models or experimental approaches has limited our ability to infer common and disease-specific responses. This meta-analysis integrates bulk and single-cell transcriptomic datasets of microglia and monocytes from disease models of autoimmunity, neurodegeneration, sterile injury, and infection to build a comprehensive resource connecting myeloid responses across CNS disease. We demonstrate that the bulk microglial and monocyte program is highly contingent on the disease environment, challenging the notion of a universal microglial disease signature. Integration of six single-cell RNA-sequencing datasets revealed that these disease-specific signatures are likely driven by differing proportions of unique myeloid subpopulations that were individually expanded in different disease settings. These subsets were functionally-defined as neurodegeneration-associated, inflammatory, interferon-responsive, phagocytic, antigen-presenting, and lipopolysaccharide-responsive cellular states, revealing a core set of myeloid responses at the single-cell level that are conserved across CNS pathology. Showcasing the predictive and practical value of this resource, we performed differential expression analysis on microglia and monocytes across disease and identified Cd81 as a new neuroinflammatory-stable gene that accurately identified microglia and distinguished them from monocyte-derived cells across all experimental models at both the bulk and single-cell level. Together, this resource dissects the influence of disease environment on shared immune response programmes to build a unified perspective of myeloid behavior across CNS pathology.

Early microglial response, myelin deterioration and lethality in mice deficient for very long chain ceramide synthesis in oligodendrocytes

The sphingolipids galactosylceramide (GalCer), sulfatide (ST) and sphingomyelin (SM) are essential for myelin stability and function. GalCer and ST are synthesized mostly from C22-C24 ceramides, generated by Ceramide Synthase 2 (CerS2). To clarify the requirement for C22-C24 sphingolipid synthesis in myelin biosynthesis and stability, we generated mice lacking CerS2 specifically in myelinating cells (CerS2ΔO/ΔO ). At 6 weeks of age, normal-appearing myelin had formed in CerS2ΔO/ΔO mice, however there was a reduction in myelin thickness and the percentage of myelinated axons. Pronounced loss of C22-C24 sphingolipids in myelin of CerS2ΔO/ΔO mice was compensated by greatly increased levels of C18 sphingolipids. A distinct microglial population expressing high levels of activation and phagocytic markers such as CD64, CD11c, MHC class II, and CD68 was apparent at 6 weeks of age in CerS2ΔO/ΔO mice, and had increased by 10 weeks. Increased staining for denatured myelin basic protein was also apparent in 6-week-old CerS2ΔO/ΔO mice. By 16 weeks, CerS2ΔO/ΔO mice showed pronounced myelin atrophy, motor deficits, and axon beading, a hallmark of axon stress. 90% of CerS2ΔO/ΔO mice died between 16 and 26 weeks of age. This study highlights the importance of sphingolipid acyl chain length for the structural integrity of myelin, demonstrating how a modest reduction in lipid chain length causes exposure of a denatured myelin protein epitope and expansion of phagocytic microglia, followed by axon pathology, myelin degeneration, and motor deficits. Understanding the molecular trigger for microglial activation should aid the development of therapeutics for demyelinating and neurodegenerative diseases.

A systems immunology study comparing innate and adaptive immune responses in adults to COVID-19 mRNA and adenovirus vectored vaccines

Identifying the molecular mechanisms that promote optimal immune responses to coronavirus disease 2019 (COVID-19) vaccination is critical for future rational vaccine design. Here, we longitudinally profile innate and adaptive immune responses in 102 adults after the first, second, and third doses of mRNA or adenovirus-vectored COVID-19 vaccines. Using a multi-omics approach, we identify key differences in the immune responses induced by ChAdOx1-S and BNT162b2 that correlate with antigen-specific antibody and T cell responses or vaccine reactogenicity. Unexpectedly, we observe that vaccination with ChAdOx1-S, but not BNT162b2, induces an adenoviral vector-specific memory response after the first dose, which correlates with the expression of proteins with roles in thrombosis with potential implications for thrombosis with thrombocytopenia syndrome (TTS), a rare but serious adverse event linked to adenovirus-vectored vaccines. The COVID-19 Vaccine Immune Responses Study thus represents a major resource that can be used to understand the immunogenicity and reactogenicity of these COVID-19 vaccines.

Intestinal location- and age-specific variation of intraepithelial T lymphocytes and mucosal microbiota in pigs

Intraepithelial T lymphocytes (T-IELs) are T cells located within the epithelium that provide a critical line of immune defense in the intestinal tract. In pigs, T-IEL abundances and phenotypes are used to infer putative T-IEL functions and vary by intestinal location and age, though investigations regarding porcine T-IELs are relatively limited. In this study, we expand on analyses of porcine intestinal T-IELs to include additional phenotypic designations not previously recognized in pigs. We describe non-conventional CD8α⁺CD8β^- αβ T-IELs that were most prevalent in the distal intestinal tract and primarily CD16⁺CD27^-, a phenotype suggestive of innate-like activation and an activated cell state. Additional T-IEL populations included CD8α⁺CD8β⁺ αβ, CD2⁺CD8α⁺ γδ, and CD2⁺CD8α^- γδ T-IELs, with increasing proportions of CD16⁺CD27^- phenotype in the distal intestine. Thus, putative non-conventional, activated T-IELs were most abundant in the distal intestine within multiple γδ and αβ T-IEL populations. A comparison of T-IEL and respective mucosal microbial community structures across jejunum, ileum, and cecum of 5- and 7-week-old pigs revealed largest community differences were tissue-dependent for both T-IELs and the microbiota. Between 5 and 7 weeks of age, the largest shifts in microbial community compositions occurred in the large intestine, while the largest shifts in T-IEL communities were in the small intestine. Therefore, results indicate different rates of community maturation and stabilization for porcine T-IELs and the mucosal microbiota for proximal versus distal intestinal locations between 5 and 7 weeks of age. Collectively, data emphasize the intestinal tract as a site of location- and age-specific T-IEL and microbial communities that have important implications for understanding intestinal health in pigs.

Ensuring Full Spectrum Flow Cytometry Data Quality for High-Dimensional Data Analysis

Full spectrum flow cytometry (FSFC) allows for the analysis of more than 40 parameters at the single-cell level. Compared to the practice of manual gating, high-dimensional data analysis can be used to fully explore single-cell datasets and reduce analysis time. As panel size and complexity increases so too does the detail and time required to prepare and validate the quality of the resulting data for use in downstream high-dimensional data analyses. To ensure data analysis algorithms can be used efficiently and to avoid artifacts, some important steps should be considered. These include data cleaning (such as eliminating variable signal change over time, removing cell doublets, and antibody aggregates), proper unmixing of full spectrum data, ensuring correct scale transformation, and correcting for batch effects. We have developed a methodical step-by-step protocol to prepare full spectrum high-dimensional data for use with high-dimensional data analyses, with a focus on visualizing the impact of each step of data preparation using dimensionality reduction algorithms. Application of our workflow will aid FSFC users in their efforts to apply quality control methods to their datasets for use in high-dimensional analysis, and help them to obtain valid and reproducible results. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Data cleaning Basic Protocol 2: Validating the quality of unmixing Basic Protocol 3: Data scaling Basic Protocol 4: Batch-to-batch normalization.

Circulating effector γδ T cell populations are associated with acute coronavirus disease 19 in unvaccinated individuals

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes severe coronavirus disease 2019 (COVID-19) in a small proportion of infected individuals. The immune system plays an important role in the defense against SARS-CoV-2, but our understanding of the cellular immune parameters that contribute to severe COVID-19 disease is incomplete. Here, we show that populations of effector γδ T cells are associated with COVID-19 in unvaccinated patients with acute disease. We found that circulating CD27^neg CD45RA⁺ CX3CR1⁺ Vδ1_effector cells expressing Granzymes (Gzms) were enriched in COVID-19 patients with acute disease. Moreover, higher frequencies of GzmB⁺ Vδ2⁺ T cells were observed in acute COVID-19 patients. SARS-CoV-2 infection did not alter the γδ T cell receptor repertoire of either Vδ1⁺ or Vδ2⁺ subsets. Our work demonstrates an association between effector populations of γδ T cells and acute COVID-19 in unvaccinated individuals.

TrackSOM: Mapping immune response dynamics through clustering of time-course cytometry data

Mapping the dynamics of immune cell populations over time or disease-course is key to understanding immunopathogenesis and devising putative interventions. We present TrackSOM, a novel method for delineating cellular populations and tracking their development over a time- or disease-course cytometry datasets. We demonstrate TrackSOM-enabled elucidation of the immune response to West Nile Virus infection in mice, uncovering heterogeneous subpopulations of immune cells and relating their functional evolution to disease severity. TrackSOM is easy to use, encompasses few parameters, is quick to execute, and enables an integrative and dynamic overview of the immune system kinetics that underlie disease progression and/or resolution.

Cross-platform immunophenotyping of human peripheral blood mononuclear cells with four high-dimensional flow cytometry panels

Immunophenotyping using high dimensional flow cytometry is a central component of human immune system multi-omic studies. We present four high parameter flow cytometry panels for deep immunophenotyping of human peripheral blood mononuclear cells (PBMC). This set of four 25+ color panels include 64 cell surface markers to resolve broad immune compartment populations, as well as activation and memory of specific T, B, natural killer (NK), and myeloid lineages. Common lineage bridging markers are integrated into each panel to allow for inter-panel quality control through major lineage frequency verification. These panels were developed using a five laser BD Symphony A5 conventional cytometer and successfully transferred to a five laser Cytek Aurora spectral cytometer capable of acquiring the panels. Nine representative PBMC samples were stained with the four phenotyping panels and acquired on both instruments to evaluate population frequency and visual staining patterns for gating between the systems. Both instruments produced comparable high quality flow cytometry data and supported our decision to acquire samples on the spectral cytometer moving forward. This modular set of panels and instrument performance metrics provide guidelines for designing flow cytometry experiments suitable for longitudinal or cross-sectional immune profiling.

Circulating CCR6+ILC proportions are lower in multiple sclerosis patients

Objectives

The role of innate lymphoid cells (ILC), particularly helper ILC, in the pathogenesis of multiple sclerosis (MS) is not well understood. Here, we present a comprehensive analysis of peripheral ILC subsets in MS patients prior and after alemtuzumab administration using mass cytometry.

Methods

Circulating ILC were analysed by mass cytometry in MS patients before and after alemtuzumab. These were compared with non-MS controls. MS-related shifts among ILC immunophenotypes were further elucidated by fast interpolation-based t-SNE (Flt-SNE) dimensionality reduction.

Results

Neither natural killer (NK) cells nor helper ILC (ILC1, ILC2 and ILC3) levels were altered following alemtuzumab treatment. However, CD56^bright NK cell expansions were observed in relapsing patients. MS patients prior to alemtuzumab further displayed proportional shifts from ILC1 to ILC2, with MS-associated decreases in CCR6⁺ helper ILC proportions.

Conclusion

CD56^bright NK cells during relapse indicate an immediate response to disease reactivation, while CCR6-related shifts among helper ILC suggest altered ILC migration to the CNS during MS.

Mass cytometry reveals cladribine-induced resets among innate lymphoid cells in multiple sclerosis

Here we present a comprehensive mass cytometry analysis of peripheral innate lymphoid cell (ILC) subsets in relapsing/remitting MS (RRMS) patients prior to and after onset of cladribine tablets (CladT). ILC analysis was conducted on CyTOF data from peripheral blood mononuclear cells (PBMC) of MS patients before, 2 and 6 months after onset of CladT, and non-MS controls. Dimensionality reduction was used for immunophenotyping ILC subsets. CladT reduced all ILC subsets, except for CD56bright NK cells and ILC2. Furthermore, CD38+ NK cell and CCR6+ ILC3 were excluded from CladT-induced immune cell reductions. Post-CladT replenishment by immature ILC was noted by increased CD5+ ILC1 proportions at 2 months, and boosted CD38-CD56bright NK cell numbers at 6 months. CladT induce immune cell depletion among ILC but exclude CD56bright NK cells and ILC2 subsets, as well as CD38+ NK cell and CCR6+ ILC3 immunophenotypes. Post-CladT ILC expansions indicate ILC reconstitution towards a more tolerant immune system phenotype.

Mucosal TLR2-activating protein-based vaccination induces potent pulmonary immunity and protection against SARS-CoV-2 in mice

Current vaccines against SARS-CoV-2 substantially reduce mortality, but protection against infection is less effective. Enhancing immunity in the respiratory tract, via mucosal vaccination, may provide protection against infection and minimise viral spread. Here, we report testing of a subunit vaccine in mice, consisting of SARS-CoV-2 Spike protein with a TLR2-stimulating adjuvant (Pam₂Cys), delivered to mice parenterally or mucosally. Both routes of vaccination induce substantial neutralising antibody (nAb) titres, however, mucosal vaccination uniquely generates anti-Spike IgA, increases nAb in the serum and airways, and increases lung CD4⁺ T-cell responses. TLR2 is expressed by respiratory epithelia and immune cells. Using TLR2 deficient chimeric mice, we determine that TLR2 expression in either compartment facilitates early innate responses to mucosal vaccination. By contrast, TLR2 on hematopoietic cells is essential for optimal lung-localised, antigen-specific responses. In K18-hACE2 mice, vaccination provides complete protection against disease and sterilising lung immunity against SARS-CoV-2, with a short-term non-specific protective effect from mucosal Pam₂Cys alone. These data support mucosal vaccination as a strategy to improve protection in the respiratory tract against SARS-CoV-2 and other respiratory viruses.

Distinct pretreatment innate immune landscape and posttreatment T cell responses underlie immunotherapy-induced colitis

Immune-related adverse events represent a major hurdle to the success of immunotherapy. The immunological mechanisms underlying their development and relation to antitumor responses are poorly understood. By examining both systemic and tissue-specific immune changes induced by combination anti-CTLA-4 and anti-PD-1 immunotherapy, we found distinct repertoire changes in patients who developed moderate-severe colitis, irrespective of their antitumor response to therapy. The proportion of circulating monocytes were significantly increased at baseline in patients who subsequently developed colitis compared with patients who did not develop colitis, and biopsies from patients with colitis showed monocytic infiltration of both endoscopically and histopathologically normal and inflamed regions of colon. The magnitude of systemic expansion of T cells following commencement of immunotherapy was also greater in patients who developed colitis. Importantly, we show expansion of specific T cell subsets within inflamed regions of the colon, including tissue-resident memory CD8+ T cells and Th1 CD4+ T cells in patients who developed colitis. Our data also suggest that CD8+ T cell expansion was locally induced, while Th1 cell expansion was systemic. Together, our data show that exaggerated innate and T cell responses to combination immunotherapy synergize to propel colitis in susceptible patients.

Approaches to spatially resolving the tumour immune microenvironment of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common and deadly cancer worldwide. Many factors contribute to mortality and place an individual at high risk of developing HCC, including viral infection, alcohol intake, metabolic-associated disease, autoimmunity and genetic liver disorders. Although there are many therapeutics available, much about this disease remains to be understood. This is most evident when investigating the tumour microenvironment (TME). Both innate and adaptive immune cells have been associated with carcinogenesis within the TME of HCC patients. The ability to interrogate the TME more thoroughly with spatial technologies continues to improve, both at the experimental and analytical stages. This review provides insight into technologies available to investigate the TME, and how such technologies are beneficial for improving our understanding of HCC carcinogenesis.

Immune dynamics in SARS-CoV-2 experienced immunosuppressed rheumatoid arthritis or multiple sclerosis patients vaccinated with mRNA-1273

Background

Patients affected by different types of autoimmune diseases, including common conditions such as multiple sclerosis (MS) and rheumatoid arthritis (RA), are often treated with immunosuppressants to suppress disease activity. It is not fully understood how the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific humoral and cellular immunity induced by infection and/or upon vaccination is affected by immunosuppressants.

Methods

The dynamics of cellular immune reactivation upon vaccination of SARS-CoV-2 experienced MS patients treated with the humanized anti-CD20 monoclonal antibody ocrelizumab (OCR) and RA patients treated with methotrexate (MTX) monotherapy were analyzed at great depth via high-dimensional flow cytometry of whole blood samples upon vaccination with the SARS-CoV-2 mRNA-1273 (Moderna) vaccine. Longitudinal B and T cell immune responses were compared to SARS-CoV-2 experienced healthy controls (HCs) before and 7 days after the first and second vaccination.

Results

OCR-treated MS patients exhibit a preserved recall response of CD8+ T central memory cells following first vaccination compared to HCs and a similar CD4+ circulating T follicular helper 1 and T helper 1 dynamics, whereas humoral and B cell responses were strongly impaired resulting in absence of SARS-CoV-2-specific humoral immunity. MTX treatment significantly delayed antibody levels and B reactivation following the first vaccination, including sustained inhibition of overall reactivation marker dynamics of the responding CD4+ and CD8+ T cells.

Conclusions

Together, these findings indicate that SARS-CoV-2 experienced MS-OCR patients may still benefit from vaccination by inducing a broad CD8+ T cell response which has been associated with milder disease outcome. The delayed vaccine-induced IgG kinetics in RA-MTX patients indicate an increased risk after the first vaccination, which might require additional shielding or alternative strategies such as treatment interruptions in vulnerable patients.

Funding

This research project was supported by ZonMw (The Netherlands Organization for Health Research and Development, #10430072010007), the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement (#792532 and #860003), the European Commission (SUPPORT-E, #101015756) and by PPOC (#20_21 L2506), the NHMRC Leadership Investigator Grant (#1173871).

Peripheral B-cell dysregulation is associated with relapse after long-term quiescence in patients with multiple sclerosis

B cells play a major role in multiple sclerosis (MS), with many successful therapeutics capable of removing them from circulation. One such therapy, alemtuzumab, is thought to reset the immune system without the need for ongoing therapy in a proportion of patients. The exact cells contributing to disease pathogenesis and quiescence remain to be identified. We utilized mass cytometry to analyze B cells from the blood of patients with relapse-remitting MS (RRMS) before and after alemtuzumab treatment, and during relapse. A complementary RRMS cohort was analyzed by single-cell RNA sequencing. The R package "Spectre" was used to analyze these data, incorporating FlowSOM clustering, sparse partial least squares-discriminant analysis and permutational multivariate analysis of variance. Immunoglobulin (Ig)A+ and IgG1 + B-cell numbers were altered, including higher IgG1 + B cells during relapse. B-cell linker protein (BLNK), CD40 and CD210 expression by B cells was lower in patients with RRMS compared with non-MS controls, with similar results at the transcriptomic level. Finally, alemtuzumab restored BLNK, CD40 and CD210 expression by IgA+ and IgG1 + B cells, which was altered again during relapse. These data suggest that impairment of IgA+ and IgG1 + B cells may contribute to MS pathogenesis, which can be restored by alemtuzumab.

TGF-β and CIS inhibition overcomes NK cell suppression to restore anti-tumor immunity

Antibodies targeting "immune checkpoints" have revolutionized cancer therapy by reactivating tumor-resident cytotoxic lymphocytes, primarily CD8+ T cells. Interest in targeting analogous pathways in other cytotoxic lymphocytes is growing. Natural killer (NK) cells are key to cancer immunosurveillance by eradicating metastases and driving solid tumor inflammation. NK cell anti-tumor function is dependent on the cytokine interleukin (IL)-15. Ablation of the IL-15 signaling inhibitor CIS (Cish) enhances NK cell anti-tumor immunity by increasing NK cell metabolism and persistence within the tumor microenvironment (TME). The TME has also been shown to impair NK cell fitness via the production of immunosuppressive TGF-β, a suppression which occurs even in the presence of high IL-15 signaling. Here, we identified an unexpected interaction between CIS and the TGF-β signaling pathway in NK cells. Independently, Cish- and Tgfbr2-deficient NK cells are both hyper-responsive to IL-15 and hypo-responsive to TGF-β, with dramatically enhanced anti-tumor immunity. Remarkably, when both these immunosuppressive genes are simultaneously deleted in NK cells, mice are largely resistant to tumor development, suggesting that combining suppression of these two pathways might represent a novel therapeutic strategy to enhance innate anti-cancer immunity.

Deconvolution of the hematopoietic stem cell microenvironment reveals a high degree of specialization and conservation

Understanding the regulation of normal and malignant human hematopoiesis requires comprehensive cell atlas of the hematopoietic stem cell (HSC) regulatory microenvironment. Here, we develop a tailored bioinformatic pipeline to integrate public and proprietary single-cell RNA sequencing (scRNA-seq) datasets. As a result, we robustly identify for the first time 14 intermediate cell states and 11 stages of differentiation in the endothelial and mesenchymal BM compartments, respectively. Our data provide the most comprehensive description to date of the murine HSC-regulatory microenvironment and suggest a higher level of specialization of the cellular circuits than previously anticipated. Furthermore, this deep characterization allows inferring conserved features in human, suggesting that the layers of microenvironmental regulation of hematopoiesis may also be shared between species. Our resource and methodology is a stepping-stone toward a comprehensive cell atlas of the BM microenvironment.

SARS-CoV-2 infection results in immune responses in the respiratory tract and peripheral blood that suggest mechanisms of disease severity

Respiratory tract infection with SARS-CoV-2 results in varying immunopathology underlying COVID-19. We examine cellular, humoral and cytokine responses covering 382 immune components in longitudinal blood and respiratory samples from hospitalized COVID-19 patients. SARS-CoV-2-specific IgM, IgG, IgA are detected in respiratory tract and blood, however, receptor-binding domain (RBD)-specific IgM and IgG seroconversion is enhanced in respiratory specimens. SARS-CoV-2 neutralization activity in respiratory samples correlates with RBD-specific IgM and IgG levels. Cytokines/chemokines vary between respiratory samples and plasma, indicating that inflammation should be assessed in respiratory specimens to understand immunopathology. IFN-α2 and IL-12p70 in endotracheal aspirate and neutralization in sputum negatively correlate with duration of hospital stay. Diverse immune subsets are detected in respiratory samples, dominated by neutrophils. Importantly, dexamethasone treatment does not affect humoral responses in blood of COVID-19 patients. Our study unveils differential immune responses between respiratory samples and blood, and shows how drug therapy affects immune responses during COVID-19.