Differential IRF8 Transcription Factor Requirement Defines Two Pathways of Dendritic Cell Development in Humans.

The formation of mammalian dendritic cells (DCs) is controlled by multiple hematopoietic transcription factors, including IRF8. Loss of IRF8 exerts a differential effect on DC subsets, including plasmacytoid DCs (pDCs) and the classical DC lineages cDC1 and cDC2. In humans, cDC2-related subsets have been described including AXL+SIGLEC6+ pre-DC, DC2 and DC3. The origin of this heterogeneity is unknown. Using high-dimensional analysis, in vitro differentiation, and an allelic series of human IRF8 deficiency, we demonstrated that cDC2 (CD1c+DC) heterogeneity originates from two distinct pathways of development. The lymphoid-primed IRF8hi pathway, marked by CD123 and BTLA, carried pDC, cDC1, and DC2 trajectories, while the common myeloid IRF8lo pathway, expressing SIRPA, formed DC3s and monocytes. We traced distinct trajectories through the granulocyte-macrophage progenitor (GMP) compartment showing that AXL+SIGLEC6+ pre-DCs mapped exclusively to the DC2 pathway. In keeping with their lower requirement for IRF8, DC3s expand to replace DC2s in human partial IRF8 deficiency.

Genetic tracing via DNGR-1 expression history defines dendritic cells as a hematopoietic lineage.

Mononuclear phagocytes are classified as macrophages or dendritic cells (DCs) based on cell morphology, phenotype, or select functional properties. However, these attributes are not absolute and often overlap, leading to difficulties in cell-type identification. To circumvent this issue, we describe a mouse model to define DCs based on their ontogenetic descendence from a committed precursor. We show that precursors of mouse conventional DCs, but not other leukocytes, are marked by expression of DNGR-1. Genetic tracing of DNGR-1 expression history specifically marks cells traditionally ascribed to the DC lineage, and this restriction is maintained after inflammation. Notably, in some tissues, cells previously thought to be monocytes/macrophages are in fact descendants from DC precursors. These studies provide an in vivo model for fate mapping of DCs, distinguishing them from other leukocyte lineages, and thus help to unravel the functional complexity of the mononuclear phagocyte system.

Blood and immune development in human fetal bone marrow and Down syndrome.

Haematopoiesis in the bone marrow (BM) maintains blood and immune cell production throughout postnatal life. Haematopoiesis first emerges in human BM at 11-12 weeks after conception1,2, yet almost nothing is known about how fetal BM (FBM) evolves to meet the highly specialized needs of the fetus and newborn. Here we detail the development of FBM, including stroma, using multi-omic assessment of mRNA and multiplexed protein epitope expression. We find that the full blood and immune cell repertoire is established in FBM in a short time window of 6-7 weeks early in the second trimester. FBM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell subsets emerging for the first time. The substantial expansion of B lymphocytes in FBM contrasts with fetal liver at the same gestational age. Haematopoietic progenitors from fetal liver, FBM and cord blood exhibit transcriptional and functional differences that contribute to tissue-specific identity and cellular diversification. Endothelial cell types form distinct vascular structures that we show are regionally compartmentalized within FBM. Finally, we reveal selective disruption of B lymphocyte, erythroid and myeloid development owing to a cell-intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in Down syndrome (trisomy 21).

Programmed cell death-1 receptor-mediated regulation of Tbet+NK1.1- innate lymphoid cells within the tumor microenvironment.

Innate lymphoid cells (ILCs) play a key role in tissue-mediated immunity and can be controlled by coreceptor signaling. Here, we define a subset of ILCs that are Tbet+NK1.1- and are present within the tumor microenvironment (TME). We show programmed death-1 receptor (PD-1) expression on ILCs within TME is found in Tbet+NK1.1- ILCs. PD-1 significantly controlled the proliferation and function of Tbet+NK1.1- ILCs in multiple murine and human tumors. We found tumor-derived lactate enhanced PD-1 expression on Tbet+NK1.1- ILCs within the TME, which resulted in dampened the mammalian target of rapamycin (mTOR) signaling along with increased fatty acid uptake. In line with these metabolic changes, PD-1-deficient Tbet+NK1.1- ILCs expressed significantly increased IFNγ and granzyme B and K. Furthermore, PD-1-deficient Tbet+NK1.1- ILCs contributed toward diminished tumor growth in an experimental murine model of melanoma. These data demonstrate that PD-1 can regulate antitumor responses of Tbet+NK1.1- ILCs within the TME.

Decoding human fetal liver haematopoiesis.

Definitive haematopoiesis in the fetal liver supports self-renewal and differentiation of haematopoietic stem cells and multipotent progenitors (HSC/MPPs) but remains poorly defined in humans. Here, using single-cell transcriptome profiling of approximately 140,000 liver and 74,000 skin, kidney and yolk sac cells, we identify the repertoire of human blood and immune cells during development. We infer differentiation trajectories from HSC/MPPs and evaluate the influence of the tissue microenvironment on blood and immune cell development. We reveal physiological erythropoiesis in fetal skin and the presence of mast cells, natural killer and innate lymphoid cell precursors in the yolk sac. We demonstrate a shift in the haemopoietic composition of fetal liver during gestation away from being predominantly erythroid, accompanied by a parallel change in differentiation potential of HSC/MPPs, which we functionally validate. Our integrated map of fetal liver haematopoiesis provides a blueprint for the study of paediatric blood and immune disorders, and a reference for harnessing the therapeutic potential of HSC/MPPs.

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.

Guidelines for establishing a cytometry laboratory.

The purpose of this document is to provide guidance for establishing and maintaining growth and development of flow cytometry shared resource laboratories. While the best practices offered in this manuscript are not intended to be universal or exhaustive, they do outline key goals that should be prioritized to achieve operational excellence and meet the needs of the scientific community. Additionally, this document provides information on available technologies and software relevant to shared resource laboratories. This manuscript builds on the work of Barsky et al. 2016 published in Cytometry Part A and incorporates recent advancements in cytometric technology. A flow cytometer is a specialized piece of technology that require special care and consideration in its housing and operations. As with any scientific equipment, a thorough evaluation of the location, space requirements, auxiliary resources, and support is crucial for successful operation. This comprehensive resource has been written by past and present members of the International Society for Advancement of Cytometry (ISAC) Shared Resource Laboratory (SRL) Emerging Leaders Program https://isac-net.org/general/custom.asp?page=SRL-Emerging-Leaders with extensive expertise in managing flow cytometry SRLs from around the world in different settings including academia and industry. It is intended to assist in establishing a new flow cytometry SRL, re-purposing an existing space into such a facility, or adding a flow cytometer to an individual lab in academia or industry. This resource reviews the available cytometry technologies, the operational requirements, and best practices in SRL staffing and management.

Single-cell reconstruction of the early maternal-fetal interface in humans.

During early human pregnancy the uterine mucosa transforms into the decidua, into which the fetal placenta implants and where placental trophoblast cells intermingle and communicate with maternal cells. Trophoblast-decidual interactions underlie common diseases of pregnancy, including pre-eclampsia and stillbirth. Here we profile the transcriptomes of about 70,000 single cells from first-trimester placentas with matched maternal blood and decidual cells. The cellular composition of human decidua reveals subsets of perivascular and stromal cells that are located in distinct decidual layers. There are three major subsets of decidual natural killer cells that have distinctive immunomodulatory and chemokine profiles. We develop a repository of ligand-receptor complexes and a statistical tool to predict the cell-type specificity of cell-cell communication via these molecular interactions. Our data identify many regulatory interactions that prevent harmful innate or adaptive immune responses in this environment. Our single-cell atlas of the maternal-fetal interface reveals the cellular organization of the decidua and placenta, and the interactions that are critical for placentation and reproductive success.

Downregulation of MALAT1 is a hallmark of tissue and peripheral proliferative T cells in COVID-19.

T cells play key protective but also pathogenic roles in COVID-19. We studied the expression of long non-coding RNAs (lncRNAs) in COVID-19 T-cell transcriptomes by integrating previously published single-cell RNA sequencing datasets. The long intergenic non-coding RNA MALAT1 was the most highly transcribed lncRNA in T cells, with Th1 cells demonstrating the lowest and CD8+ resident memory cells the highest MALAT1 expression, amongst CD4+ and CD8+ T-cells populations, respectively. We then identified gene signatures that covaried with MALAT1 in single T cells. A significantly higher number of transcripts correlated negatively with MALAT1 than those that correlated. Enriched functional annotations of the MALAT1- anti-correlating gene signature included processes associated with T-cell activation such as cell division, oxidative phosphorylation, and response to cytokine. The MALAT1 anti-correlating gene signature shared by both CD4+ and CD8+ T-cells marked dividing T cells in both the lung and blood of COVID-19 patients. Focussing on the tissue, we used an independent patient cohort of post-mortem COVID-19 lung samples and demonstrated that MALAT1 suppression was indeed a marker of MKI67+ proliferating CD8+ T cells. Our results reveal MALAT1 suppression and its associated gene signature are a hallmark of human proliferating T cells.

Hyperactive CREB subpopulations increase during therapy in pediatric B-lineage acute lymphoblastic leukemia.

Persistence of residual disease in acute lymphoblastic leukemia (ALL) during the initial stages of chemotherapy is associated with inferior survival. To better understand clonal evolution and mechanisms of chemoresistance, we used multiparameter mass cytometry, at single-cell resolution, to functionally characterize pediatric B-ALL cells at disease presentation and those persisting during induction therapy. Analysis of ALL cells from presentation samples (n=42) showed that the most abundant phosphosignals were pCREB, pH2AX and pHH3 and we identified JAK-STAT and RAS pathway activation in five of six patients with JAK or RAS genetic aberrations. The clonal composition of ALL was heterogeneous and dynamic during treatment but all viable cell clusters showed pCREB activation. Levels of pCREB in ALL cells were increased or maintained during therapy and high dimensional analysis revealed a subpopulation of ALL cells at presentation that was positive for pCREB/pHH3/pS6 which increased during treatment in some patients, implicating this signaling node in conferring a survival advantage to multi-agent induction therapy. The small molecule CREB inhibitor, 666-15, was shown to reduce CREB transcriptional activity and induce apoptosis in ALL patient-derived xenograft cells of varying cytogenetic subtypes in vitro, both in the presence and absence of stromal support. Together, these data suggest that the cAMP signaling pathway may provide an opportunity for minimal residual disease-directed therapy for many patients at high risk of relapse.

Regulation and Role of αE Integrin and Gut Homing Integrins in Migration and Retention of Intestinal Lymphocytes during Inflammatory Bowel Disease.

Targeting interactions between α4ß7 integrin and endothelial adhesion molecule MAdCAM-1 to inhibit lymphocyte migration to the gastrointestinal tract is an effective therapy in inflammatory bowel disease (IBD). Following lymphocyte entry into the mucosa, a subset of these cells expresses αEß7 integrin, which is expressed on proinflammatory lymphocytes, to increase cell retention. The factors governing lymphocyte migration into the intestinal mucosa and αE integrin expression in healthy subjects and IBD patients remain incompletely understood. We evaluated changes in factors involved in lymphocyte migration and differentiation within tissues. Both ileal and colonic tissue from active IBD patients showed upregulation of ICAM-1, VCAM-1, and MAdCAM-1 at the gene and protein levels compared with healthy subjects and/or inactive IBD patients. ß1 and ß7 integrin expression on circulating lymphocytes was similar across groups. TGF-ß1 treatment induced expression of αE on both ß7+ and ß7- T cells, suggesting that cells entering the mucosa independently of MAdCAM-1/α4ß7 can become αEß7+ ITGAE gene polymorphisms did not alter protein induction following TGF-ß1 stimulation. Increased phospho-SMAD3, which is directly downstream of TGF-ß, and increased TGF-ß-responsive gene expression were observed in the colonic mucosa of IBD patients. Finally, in vitro stimulation experiments showed that baseline ß7 expression had little effect on cytokine, chemokine, transcription factor, and effector molecule gene expression in αE+ and αE- T cells. These findings suggest cell migration to the gut mucosa may be altered in IBD and α4ß7-, and α4ß7+ T cells may upregulate αEß7 in response to TGF-ß once within the gut mucosa.

CXCR2 inhibition enables NASH-HCC immunotherapy.

OBJECTIVE: Hepatocellular carcinoma (HCC) is increasingly associated with non-alcoholic steatohepatitis (NASH). HCC immunotherapy offers great promise; however, recent data suggests NASH-HCC may be less sensitive to conventional immune checkpoint inhibition (ICI). We hypothesised that targeting neutrophils using a CXCR2 small molecule inhibitor may sensitise NASH-HCC to ICI therapy. DESIGN: Neutrophil infiltration was characterised in human HCC and mouse models of HCC. Late-stage intervention with anti-PD1 and/or a CXCR2 inhibitor was performed in murine models of NASH-HCC. The tumour immune microenvironment was characterised by imaging mass cytometry, RNA-seq and flow cytometry. RESULTS: Neutrophils expressing CXCR2, a receptor crucial to neutrophil recruitment in acute-injury, are highly represented in human NASH-HCC. In models of NASH-HCC lacking response to ICI, the combination of a CXCR2 antagonist with anti-PD1 suppressed tumour burden and extended survival. Combination therapy increased intratumoural XCR1+ dendritic cell activation and CD8+ T cell numbers which are associated with anti-tumoural immunity, this was confirmed by loss of therapeutic effect on genetic impairment of myeloid cell recruitment, neutralisation of the XCR1-ligand XCL1 or depletion of CD8+ T cells. Therapeutic benefit was accompanied by an unexpected increase in tumour-associated neutrophils (TANs) which switched from a protumour to anti-tumour progenitor-like neutrophil phenotype. Reprogrammed TANs were found in direct contact with CD8+ T cells in clusters that were enriched for the cytotoxic anti-tumoural protease granzyme B. Neutrophil reprogramming was not observed in the circulation indicative of the combination therapy selectively influencing TANs. CONCLUSION: CXCR2-inhibition induces reprogramming of the tumour immune microenvironment that promotes ICI in NASH-HCC.

Effector immune cells in chronic lung allograft dysfunction: A systematic review.

Chronic lung allograft dysfunction (CLAD) remains the major barrier to long-term survival after lung transplantation and improved insight into its underlying immunological mechanisms is critical to better understand the disease and to identify treatment targets. We systematically searched the electronic databases of PubMed and EMBASE for original research publications, published between January 2000 and April 2021, to comprehensively assess current evidence on effector immune cells in lung tissue and bronchoalveolar lavage fluid from lung transplant recipients with CLAD. Literature search revealed 1351 articles, 76 of which met the criteria for inclusion in our analysis. Our results illustrate significant complexity in both innate and adaptive immune cell responses in CLAD, along with presence of numerous immune cell products, including cytokines, chemokines and proteases associated with tissue remodelling. A clear link between neutrophils and eosinophils and CLAD incidence has been seen, in which eosinophils more specifically predisposed to restrictive allograft syndrome. The presence of cytotoxic and T-helper cells in CLAD pathogenesis is well-documented, although it is challenging to draw conclusions about their role in tissue processes from predominantly bronchoalveolar lavage data. In restrictive allograft syndrome, a more prominent humoral immune involvement with increased B cells, immunoglobulins and complement deposition is seen. Our evaluation of published studies over the last 20 years summarizes the complex multifactorial immunopathology of CLAD onset and progression. It highlights the phenotype of several key effector immune cells involved in CLAD pathogenesis, as well as the paucity of single cell resolution spatial studies in lung tissue from patients with CLAD.

Astrocytic Changes in Mitochondrial Oxidative Phosphorylation Protein Levels in Parkinson's Disease.

BACKGROUND: Mitochondrial dysfunction within neurons, particularly those of the substantia nigra, has been well characterized in Parkinson's disease and is considered to be related to the pathogenesis of this disorder. Dysfunction within this important organelle has been suggested to impair neuronal communication and survival; however, the reliance of astrocytes on mitochondria and the impact of their dysfunction on this essential cell type are less well characterized. OBJECTIVE: This study aimed to uncover whether astrocytes harbor oxidative phosphorylation (OXPHOS) deficiencies in Parkinson's disease and whether these deficiencies are more likely to occur in astrocytes closely associated with neurons or those more distant from them. METHODS: Postmortem human brain sections from patients with Parkinson's disease were subjected to imaging mass cytometry for individual astrocyte analysis of key OXPHOS proteins across all five complexes. RESULTS: We show the variability in the astrocytic expression of mitochondrial proteins between individuals. In addition, we found that there is evidence of deficiencies in respiratory chain subunit expression within these important glia and changes, particularly in mitochondrial mass, associated with Parkinson's disease and that are not simply a consequence of advancing age. CONCLUSION: Our data show that astrocytes, like neurons, are susceptible to mitochondrial defects and that these could have an impact on their reactivity and ability to support neurons in Parkinson's disease.

A Cytometrist's Guide to Coordinating and Performing Effective COVID-19 Research.

Cytometry is playing a crucial role in addressing the COVID-19 pandemic. In this commentary-written by a variety of stakeholders in the cytometry, immunology, and infectious disease communities-we review cytometry's role in the COVID-19 response and discuss workflow issues critical to planning and executing effective research in this emerging field. We discuss sample procurement and processing, biosafety, technology options, data sharing, and the translation of research findings into clinical environments. © 2020 International Society for Advancement of Cytometry.

Biosafety during a pandemic: shared resource laboratories rise to the challenge.

Biosafety has always been an important aspect of daily work in any research institution, particularly for cytometry Shared Resources Laboratories (SRLs). SRLs are common-use spaces that facilitate the sharing of knowledge, expertise, and ideas. This sharing inescapably involves contact and interaction of all those within this working environment on a daily basis. The current pandemic caused by SARS-CoV-2 has prompted the re-evaluation of many policies governing the operations of SRLs. Here we identify and review the unique challenges SRLs face in maintaining biosafety standards, highlighting the potential risks associated with not only cytometry instrumentation and samples, but also the people working with them. We propose possible solutions to safety issues raised by the COVID-19 pandemic and provide tools for facilities to adapt to evolving guidelines and future challenges.

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning.

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25-5.0 µg/mL) and/or carbendazim (0.8-1.6 µg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the "DeepFlow" neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for 'mononucleates', 'binucleates', 'mononucleates with MN' and 'binucleates with MN', respectively. Successful classifications of 'trinucleates' (90%) and 'tetranucleates' (88%) in addition to 'other or unscorable' phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.

Multiple Immunostainings with Different Epitope Retrievals-The FOLGAS Protocol.

We describe a sequential multistaining protocol for immunohistochemistry, immunofluorescence and CyTOF imaging for formalin-fixed, paraffin-embedded specimens (FFPE) in the formalin gas-phase (FOLGAS), enabling sequential multistaining, independent from the primary and secondary antibodies and retrieval. Histomorphologic details are preserved, and crossreactivity and loss of signal intensity are not detectable. Combined with a DAB-based hydrophobic masking of metal-labeled primary antibodies, FOLGAS allows the extended use of CyTOF imaging in FFPE sections.

Classification of Human White Blood Cells Using Machine Learning for Stain-Free Imaging Flow Cytometry.

Imaging flow cytometry (IFC) produces up to 12 spectrally distinct, information-rich images of single cells at a throughput of 5,000 cells per second. Yet often, cell populations are still studied using manual gating, a technique that has several drawbacks, hence it would be advantageous to replace manual gating with an automated process. Ideally, this automated process would be based on stain-free measurements, as the currently used staining techniques are expensive and potentially confounding. These stain-free measurements originate from the brightfield and darkfield image channels, which capture transmitted and scattered light, respectively. To realize this automated, stain-free approach, advanced machine learning (ML) methods are required. Previous works have successfully tested this approach on cell cycle phase classification with both a classical ML approach based on manually engineered features, and a deep learning (DL) approach. In this work, we compare both approaches extensively on the problem of white blood cell classification. Four human whole blood samples were assayed on an ImageStream-X MK II imaging flow cytometer. Two samples were stained for the identification of eight white blood cell types, while two other sample sets were stained for the identification of resting and active eosinophils. For both data sets, four ML classifiers were evaluated on stain-free imagery with stratified 5-fold cross-validation. On the white blood cell data set, the best obtained results were 0.778 and 0.703 balanced accuracy for classical ML and DL, respectively. On the eosinophil data set, this was 0.871 and 0.856 balanced accuracy. We conclude that classifying cell types based on only stain-free images is possible with all four classifiers. Noteworthy, we also find that the DL approaches tested in this work do not outperform the approaches based on manually engineered features. © 2019 International Society for Advancement of Cytometry.