Tissue biology involves an intricate balance between cell-intrinsic processes and interactions between cells organized in specific spatial patterns, which can be respectively captured by single-cell profiling methods, such as single-cell RNA-seq (scRNA-seq), and histology imaging data, such as Hematoxylin-and-Eosin (H&E) stains. While single-cell profiles provide rich molecular information, they can be challenging to collect routinely and do not have spatial resolution. Conversely, histological H&E assays have been a cornerstone of tissue pathology for decades, but do not directly report on molecular details, although the observed structure they capture arises from molecules and cells. Here, we leverage adversarial machine learning to develop SCHAF (Single-Cell omics from Histology Analysis Framework), to generate a tissue sample’s spatially-resolved single-cell omics dataset from its H&E histology image. We demonstrate SCHAF on two types of human tumors—from lung and metastatic breast cancer—training with matched samples analyzed by both sc/snRNA-seq and by H&E staining. SCHAF generated appropriate single-cell profiles from histology images in test data, related them spatially, and compared well to ground-truth scRNA-Seq, expert pathologist annotations, or direct MERFISH measurements. SCHAF opens the way to next-generation H&E2.0 analyses and an integrated understanding of cell and tissue biology in health and disease.

BACKGROUND & AIMS:Chronic viral infections present serious public health challenges; however, direct-acting antivirals (DAAs) are now able to cure nearly all patients infected with hepatitis C virus (HCV), representing the only cure of a human chronic viral infection to date. DAAs provide a valuable opportunity to study immune pathways in the reversal of chronic immune failures in an in vivo human system. METHODS:To leverage this opportunity, we used plate-based single-cell RNA-seq to deeply profile myeloid cells from liver fine needle aspirates in patients with HCV before and after DAA treatment. We comprehensively characterised liver neutrophils, eosinophils, mast cells, conventional dendritic cells, plasmacytoid dendritic cells, classical monocytes, non-classical monocytes, and macrophages, and defined fine-grained subpopulations of several cell types. RESULTS:We discovered cell type-specific changes post-cure, including an increase in MCM7+STMN1+ proliferating CD1C+ conventional dendritic cells, which may support restoration from chronic exhaustion. We observed an expected downregulation of interferon-stimulated genes (ISGs) post-cure as well as an unexpected inverse relationship between pre-treatment viral load and post-cure ISG expression in each cell type, revealing a link between viral loads and sustained modifications of the host's immune system. We found an upregulation of PD-L1/L2 gene expression in ISG-high neutrophils and IDO1 expression in eosinophils, pinpointing cell subpopulations crucial for immune regulation. We identified three recurring gene programmes shared by multiple cell types, distilling core functions of the myeloid compartment. CONCLUSIONS:This comprehensive single-cell RNA-seq atlas of human liver myeloid cells in response to cure of chronic viral infections reveals principles of liver immunity and provides immunotherapeutic insights. CLINICAL TRIAL REGISTRATION:This study is registered at ClinicalTrials.gov (NCT02476617). IMPACT AND IMPLICATIONS:Chronic viral liver infections continue to be a major public health problem. Single-cell characterisation of liver immune cells during hepatitis C and post-cure provides unique insights into the architecture of liver immunity contributing to the resolution of the first curable chronic viral infection of humans. Multiple layers of innate immune regulation during chronic infections and persistent immune modifications after cure are revealed. Researchers and clinicians may leverage these findings to develop methods to optimise the post-cure environment for HCV and develop novel therapeutic approaches for other chronic viral infections.

Abstract Background/Aims Chronic viral infections present serious public health challenges. Direct-acting antivirals (DAAs) are now able to cure nearly all patients infected with the hepatitis C virus (HCV), representing the only cure of a human chronic viral infection to date. DAAs provide a valuable opportunity to study immune pathways in the reversal of chronic immune failures in humans. Methods To leverage this opportunity, we used plate-based single-cell RNA-seq (scRNA-seq) to deeply profile myeloid cells from liver fine needle aspirates in HCV patients before and after DAA treatment. We characterized liver neutrophils, eosinophils, mast cells, conventional dendritic cells (cDCs), plasmacytoid DCs, classical/non-classical monocytes, and macrophages, and defined fine-grained subpopulations of several cell types. Results We discovered cell-type-specific changes post-cure, including an increase in MCM7+STMN1+ proliferating CD1C+ cDCs, which may support restoration from chronic exhaustion. We observed an unexpected inverse relationship between pre-treatment viral load and post-cure ISG expression in each cell type, revealing a link between viral loads and sustained modifications of the host’s immune system. We found an upregulation of PD-L1 expression in ISG-high neutrophils, pinpointing cell subpopulations crucial for immune regulation. We identified three recurring gene programs shared by multiple cell types, distilling core functions of the myeloid compartment. Conclusion This comprehensive scRNA-seq atlas of human liver myeloid cells in response to a cure of chronic viral infections reveals principles of liver immunity and provides immunotherapeutic insights. The single-cell sorting was done at the MGH Flow and Mass Cytometry Research Core, which was supported by NIH Shared Instrumentation program grants 1S10OD012027-01A1, 1S10OD016372-01, 1S10RR020936-01, and 1S10RR023440-01A1. Additional sorting was done at the Immunology Core Facility of the Ragon Institute, which is part of the Harvard University Center for AIDS Research (CFAR), an NIH funded program (P30 AI060354).

BACKGROUND:Quality control (QC) of cells, a critical first step in single-cell RNA sequencing data analysis, has largely relied on arbitrarily fixed data-agnostic thresholds applied to QC metrics such as gene complexity and fraction of reads mapping to mitochondrial genes. The few existing data-driven approaches perform QC at the level of samples or studies without accounting for biological variation. RESULTS:We first demonstrate that QC metrics vary with both tissue and cell types across technologies, study conditions, and species. We then propose data-driven QC (ddqc), an unsupervised adaptive QC framework to perform flexible and data-driven QC at the level of cell types while retaining critical biological insights and improved power for downstream analysis. ddqc applies an adaptive threshold based on the median absolute deviation on four QC metrics (gene and UMI complexity, fraction of reads mapping to mitochondrial and ribosomal genes). ddqc retains over a third more cells when compared to conventional data-agnostic QC filters. Finally, we show that ddqc recovers biologically meaningful trends in gradation of gene complexity among cell types that can help answer questions of biological interest such as which cell types express the least and most number of transcripts overall, and ribosomal transcripts specifically. CONCLUSIONS:ddqc retains cell types such as metabolically active parenchymal cells and specialized cells such as neutrophils which are often lost by conventional QC. Taken together, our work proposes a revised paradigm to quality filtering best practices-iterative QC, providing a data-driven QC framework compatible with observed biological diversity.

MAOIs, a well-established class of antidepressant that operate through the inhibition of monoamine oxidase to increase available serotonin, have recently been identified as a surprisingly effective candidate for the circumvention of tumor-induced immune suppression due to their abilities to enhance antitumor T cell activity through autocrine serotonin signaling and depolarize alternatively activated tumor-associated macrophages through a reduction in reactive oxygen species production. However, this impressive class of antidepressants-turned-cancer-drugs can induce aggressive behavioral side effects when administered in immunotherapeutic doses. In this study, we investigated the possibility of avoiding these neurological side effects while simultaneously improving antitumor activity by establishing crosslinked multilamellar liposomal vesicles (cMLVs) containing the MAOI phenelzine (PLZ). Our results showed that cMLV-PLZ treatment increases antitumor efficacy in a B16-OVA mouse melanoma model compared to treatment with free phenelzine. We also found that nanoformulation resulted in the complete elimination of MAOI-related aggression. These findings suggest a promising direction for the future of MAOIs repurposed for cancer immunotherapies.

Throughout postnatal life, haematopoiesis in the bone marrow (BM) maintains blood and immune cell production. Haematopoiesis first emerges in human BM at 12 post conception weeks while fetal liver (FL) haematopoiesis is still expanding. Yet, almost nothing is known about how fetal BM evolves to meet the highly specialised needs of the fetus and newborn infant. Here, we detail the development of fetal BM including stroma using single cell RNA-sequencing. We find that the full blood and immune cell repertoire is established in fetal BM in a short time window of 6-7 weeks early in the second trimester. Fetal BM promotes rapid and extensive diversification of myeloid cells, with granulocytes, eosinophils and dendritic cell (DC) subsets emerging for the first time. B-lymphocyte expansion occurs, in contrast with erythroid predominance in FL at the same gestational age. We identify transcriptional and functional differences that underlie tissue-specific identity and cellular diversification in fetal BM and FL. Finally, we reveal selective disruption of B-lymphocyte, erythroid and myeloid development due to cell intrinsic differentiation bias as well as extrinsic regulation through an altered microenvironment in the fetal BM from constitutional chromosome anomaly Down syndrome during this crucial developmental time window.

Tumor-associated epitopes presented on MHC-I that can activate the immune system against cancer cells are typically identified from annotated protein-coding regions of the genome, but whether peptides originating from novel or unannotated open reading frames (nuORFs) can contribute to antitumor immune responses remains unclear. Here we show that peptides originating from nuORFs detected by ribosome profiling of malignant and healthy samples can be displayed on MHC-I of cancer cells, acting as additional sources of cancer antigens. We constructed a high-confidence database of translated nuORFs across tissues (nuORFdb) and used it to detect 3,555 translated nuORFs from MHC-I immunopeptidome mass spectrometry analysis, including peptides that result from somatic mutations in nuORFs of cancer samples as well as tumor-specific nuORFs translated in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs are an unexplored pool of MHC-I-presented, tumor-specific peptides with potential as immunotherapy targets.

COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure1–4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63+ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments. Single-cell analysis of lung, heart, kidney and liver autopsy samples shows the molecular and cellular changes and immune response resulting from severe COVID-19 infection.

Coccidioidomycosis, otherwise known as Valley Fever, is caused by the dimorphic fungi Coccidioides immitis and C. posadasii. While most clinical cases present with self-limiting pulmonary infection, dissemination of Coccidioides spp. results in prolonged treatment and portends higher mortality rates. While the structure, genome, and niches for Coccidioides have provided some insight into the pathogenesis of disease, the underlying immunological mechanisms of clearance or inability to contain the infection in the lung are poorly understood. This review focuses on the known innate and adaptive immune responses to Coccidioides and highlights three important areas of uncertainty and potential approaches to address them. Closing these gaps in knowledge may enable new preventative and therapeutic strategies to be pursued.

Therapeutic blockade of co-inhibitory immune receptors PD-1 and CTLA-4 has revolutionized oncology, but treatments are limited by immune-related adverse events (IRAEs). IRAE Colitis (irColitis) is the most common, severe IRAE affecting up to 25% of patients on dual PD-1 and CTLA-4 inhibition. Here, we present a systems biology approach to define the cell populations and transcriptional programs driving irColitis. We collected paired colon mucosal biopsy and blood specimens from 13 patients with irColitis, 8 healthy individuals, and 8 controls on immune checkpoint inhibitors (ICIs), and analyzed them with single-cell/nuclei RNA sequencing with paired TCR and BCR sequencing, multispectral fluorescence microscopy, and secreted factor analysis (Luminex). We profiled 299,407 cells from tissue and blood and identified 105 cell subsets that revealed significant tissue remodeling in active disease. Colon mucosal immune populations were dominated by tissue-resident memory (T RM ) ITGAE -expressing CD8 T cells representing a phenotypic spectrum defined by gene programs associated with T cell activation, cytotoxicity, cycling, and exhaustion. CD8 T RM and effector CD4 T cells upregulated type 17 immune programs ( IL17A, IL26 ) and Tfh-like programs ( CXCL13, PDCD1 ). We also identified for the first time an increased abundance of two KLRG1 and ITGB2 -expressing CD8 T cell populations with circulatory cell markers, including a GZMK T RM -like population and a CX3CR1 population that is predicted to be intravascular. These two populations were more abundant in irColitis patients treated with dual PD-1/CTLA-4 inhibition than those receiving anti-PD-1 monotherapy. They also had significant TCR sharing with PBMCs, suggesting a circulatory origin. In irColitis we observed significant epithelial turnover marked by fewer LGR5 -expressing stem cells, more transit amplifying cells, and upregulation of apoptotic and DNA-sensing programs such as the cGAS-STING pathway. Mature epithelial cells with top crypt genes upregulated interferon-stimulated pathways, CD274 (PD-L1), anti-microbial genes, and MHC-class II genes, and downregulated aquaporin and solute-carrier gene families, likely contributing to epithelial cell damage and absorptive dysfunction. Mesenchymal remodeling was defined by increased endothelial cells, both in irColitis patients and specifically in patients on dual PD-1/CTLA-4 blockade. Cell-cell communication analysis identified putative receptor-ligand pairs that recruit CD8 T cells from blood to inflamed endothelium and positive feedback loops such as the CXCR3 chemokine system that retain cells in tissue. This study highlights the cellular and molecular drivers underlying irColitis and provides new insights into the role of CTLA-4 and PD-1 signaling in maintaining CD8 T RM homeostasis, regulating CD8 T recruitment from blood, and promoting epithelial-immune crosstalk critical to gastrointestinal immune tolerance and intestinal barrier function.

In this study, we report that the TLR4 ligand, LPS, and TLR3 ligand polyinosinic:polycytidylic acid failed to activate IRF3 or STAT1 in bone marrow–derived macrophages (BMMs) isolated from two independently generated lines of Rosa26-integrated Cas9-expressing C57BL/6J (B6) mice. RNA-sequencing analysis reveals that hundreds to thousands of genes including IFN-stimulated genes were differentially expressed in BMMs from these Cas9 strains compared with B6 upon LPS stimulation. Furthermore, the NF-κB signaling axis and TRIF-mediated necroptosis were also strongly reduced in response to LPS and polyinosinic:polycytidylic acid. In contrast, there were no defects in the responses of BMMs to ligands of the RIG-I, STING, TLR2, TLR9, and IFN receptors. Defects in TLR3 and TLR4 signaling were observed in mice with the B6 but not 129 background, and when Cas9 was integrated at the Rosa26 but not H11 locus. However, integration at the Rosa26 site, CAG promoter–driven Cas9 or eGFP were not individually sufficient to cause the defect. Taken together, the results of this study suggest a putative TRIF-mediated defect in TLR-3/4 signaling in BMMs from commercially available and widely used B6–Cas9–expressing mice.

The SARS-CoV-2 pandemic has caused over 1 million deaths globally, mostly due to acute lung injury and acute respiratory distress syndrome, or direct complications resulting in multiple-organ failures. Little is known about the host tissue immune and cellular responses associated with COVID-19 infection, symptoms, and lethality. To address this, we collected tissues from 11 organs during the clinical autopsy of 17 individuals who succumbed to COVID-19, resulting in a tissue bank of approximately 420 specimens. We generated comprehensive cellular maps capturing COVID-19 biology related to patients' demise through single-cell and single-nucleus RNA-Seq of lung, kidney, liver and heart tissues, and further contextualized our findings through spatial RNA profiling of distinct lung regions. We developed a computational framework that incorporates removal of ambient RNA and automated cell type annotation to facilitate comparison with other healthy and diseased tissue atlases. In the lung, we uncovered significantly altered transcriptional programs within the epithelial, immune, and stromal compartments and cell intrinsic changes in multiple cell types relative to lung tissue from healthy controls. We observed evidence of: alveolar type 2 (AT2) differentiation replacing depleted alveolar type 1 (AT1) lung epithelial cells, as previously seen in fibrosis; a concomitant increase in myofibroblasts reflective of defective tissue repair; and, putative TP63+ intrapulmonary basal-like progenitor (IPBLP) cells, similar to cells identified in H1N1 influenza, that may serve as an emergency cellular reserve for severely damaged alveoli. Together, these findings suggest the activation and failure of multiple avenues for regeneration of the epithelium in these terminal lungs. SARS-CoV-2 RNA reads were enriched in lung mononuclear phagocytic cells and endothelial cells, and these cells expressed distinct host response transcriptional programs. We corroborated the compositional and transcriptional changes in lung tissue through spatial analysis of RNA profiles in situ and distinguished unique tissue host responses between regions with and without viral RNA, and in COVID-19 donor tissues relative to healthy lung. Finally, we analyzed genetic regions implicated in COVID-19 GWAS with transcriptomic data to implicate specific cell types and genes associated with disease severity. Overall, our COVID-19 cell atlas is a foundational dataset to better understand the biological impact of SARS-CoV-2 infection across the human body and empowers the identification of new therapeutic interventions and prevention strategies.

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).

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

During postnatal life, thymopoiesis depends on the continuous colonization of the thymus by bone-marrow-derived hematopoietic progenitors that migrate through the bloodstream. The current understanding of the nature of thymic immigrants is largely based on datafrom pre-clinical models. Here, we employed single-cell RNA sequencing (scRNA-seq) to examine the immature postnatal thymocyte population in humans. Integration of bone marrow and peripheral blood precursor datasets identified two putative thymus seeding progenitors that varied in expression of CD7; CD10; and the homing receptors CCR7, CCR9, and ITGB7. Whereas both precursors supported T cell development, only one contributed to intrathymic dendritic cell (DC) differentiation, predominantly of plasmacytoid dendritic cells. Trajectory inference delineated the transcriptional dynamics underlying early human T lineage development, enabling prediction of transcription factor (TF) modules that drive stage-specific steps of human T cell development. This comprehensive dataset defines the expression signature of immature human thymocytes and provides a resource for the further study of human thymopoiesis.

Massively parallel single-cell and single-nucleus RNA sequencing has opened the way to systematic tissue atlases in health and disease, but as the scale of data generation is growing, so is the need for computational pipelines for scaled analysis. Here we developed Cumulus—a cloud-based framework for analyzing large-scale single-cell and single-nucleus RNA sequencing datasets. Cumulus combines the power of cloud computing with improvements in algorithm and implementation to achieve high scalability, low cost, user-friendliness and integrated support for a comprehensive set of features. We benchmark Cumulus on the Human Cell Atlas Census of Immune Cells dataset of bone marrow cells and show that it substantially improves efficiency over conventional frameworks, while maintaining or improving the quality of results, enabling large-scale studies.

Tumor epitopes – peptides that are presented on surface-bound MHC I proteins - provide targets for cancer immunotherapy and have been identified extensively in the annotated protein-coding regions of the genome. Motivated by the recent discovery of translated novel unannotated open reading frames (nuORFs) using ribosome profiling (Ribo-seq), we hypothesized that cancer-associated processes could generate nuORFs that can serve as a new source of tumor antigens that harbor somatic mutations or show tumor-specific expression. To identify cancer-specific nuORFs, we generated Ribo-seq profiles for 29 malignant and healthy samples, developed a sensitive analytic approach for hierarchical ORF prediction, and constructed a high-confidence database of translated nuORFs across tissues. Peptides from 3,555 unique translated nuORFs were presented on MHC I, based on analysis of an extensive dataset of MHC I-bound peptides detected by mass spectrometry, with >20-fold more nuORF peptides detected in the MHC I immunopeptidomes compared to whole proteomes. We further detected somatic mutations in nuORFs of cancer samples and identified nuORFs with tumor-specific translation in melanoma, chronic lymphocytic leukemia and glioblastoma. NuORFs thus expand the pool of MHC I-presented, tumor-specific peptides, targetable by immunotherapies.