Tracking rare single donor and recipient immune and leukemia cells after allogeneic hematopoietic cell transplantation using mitochondrial DNA mutations.

Combined tracking of clonal evolution and chimeric cell phenotypes could enable detection of the key cellular populations associated with response following therapy, including after allogeneic hematopoietic stem cell transplantation (HSCT). We demonstrate that mitochondrial DNA (mtDNA) mutations co-evolve with somatic nuclear DNA mutations at relapse post-HSCT and provide a sensitive means to monitor these cellular populations. Further, detection of mtDNA mutations via single-cell ATAC with select antigen profiling by sequencing (ASAP-seq) simultaneously determines not only donor and recipient cells, but also their phenotype, at frequencies of 0.1-1%. Finally, integration of mtDNA mutations, surface markers, and chromatin accessibility profiles enables the phenotypic resolution of leukemic populations from normal immune cells, thereby providing fresh insights into residual donor-derived engraftment and short-term clonal evolution following therapy for post-transplant leukemia relapse. As throughput evolves, we envision future development of single-cell sequencing-based post-transplant monitoring as a powerful approach for guiding clinical decision making.

Mitochondrial genetics through the lens of single-cell multi-omics.

Mitochondria carry their own genetic information encoding for a subset of protein-coding genes and translational machinery essential for cellular respiration and metabolism. Despite its small size, the mitochondrial genome, its natural genetic variation and molecular phenotypes have been challenging to study using bulk sequencing approaches, due to its variation in cellular copy number, non-Mendelian modes of inheritance and propensity for mutations. Here we highlight emerging strategies designed to capture mitochondrial genetic variation across individual cells for lineage tracing and studying mitochondrial genetics in primary human cells and clinical specimens. We review recent advances surrounding single-cell mitochondrial genome sequencing and its integration with functional genomic readouts, including leveraging somatic mitochondrial DNA mutations as clonal markers that can resolve cellular population dynamics in complex human tissues. Finally, we discuss how single-cell whole mitochondrial genome sequencing approaches can be utilized to investigate mitochondrial genetics and its contribution to cellular heterogeneity and disease.

Single-cell genomics-based immune and disease monitoring in blood malignancies.

Achieving long-term disease control using therapeutic immunomodulation is a long-standing concept with a strong tradition in blood malignancies. Besides allogeneic hematopoietic stem cell transplantation that continues to provide potentially curative treatment for otherwise challenging diagnoses, recent years have seen impressive progress in immunotherapies for leukemias and lymphomas with immune checkpoint blockade, bispecific monoclonal antibodies, and CAR T cell therapies. Despite their success, non-response, relapse, and immune toxicities remain frequent, thus prioritizing the elucidation of the underlying mechanisms and identifying predictive biomarkers. The increasing availability of single-cell genomic tools now provides a system's immunology view to resolve the molecular and cellular mechanisms of immunotherapies at unprecedented resolution. Here, we review recent studies that leverage these technological advancements for tracking immune responses, the emergence of immune resistance, and toxicities. As single-cell immune monitoring tools evolve and become more accessible, we expect their wide adoption for routine clinical applications to catalyze more precise therapeutic steering of personal immune responses.

Transcript-specific enrichment enables profiling rare cell states via scRNA-seq.

Single-cell genomics technologies have accelerated our understanding of cell-state heterogeneity in diverse contexts. Although single-cell RNA sequencing (scRNA-seq) identifies many rare populations of interest that express specific marker transcript combinations, traditional flow sorting limits our ability to enrich these populations for further profiling, including requiring cell surface markers with high-fidelity antibodies. Additionally, many single-cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. To address these limitations, we describe Programmable Enrichment via RNA Flow-FISH by sequencing (PERFF-seq), a scalable assay that enables scRNA-seq profiling of subpopulations from complex cellular mixtures defined by the presence or absence of specific RNA transcripts. Across immune populations (n = 141,227 cells) and fresh-frozen and formalin-fixed paraffin-embedded brain tissue (n = 29,522 nuclei), we demonstrate the sorting logic that can be used to enrich for cell populations via RNA-based cytometry followed by high-throughput scRNA-seq. Our approach provides a rational, programmable method for studying rare populations identified by one or more marker transcripts.

Latent human herpesvirus 6 is reactivated in CAR T cells.

Cell therapies have yielded durable clinical benefits for patients with cancer, but the risks associated with the development of therapies from manipulated human cells are understudied. For example, we lack a comprehensive understanding of the mechanisms of toxicities observed in patients receiving T cell therapies, including recent reports of encephalitis caused by reactivation of human herpesvirus 6 (HHV-6)1. Here, through petabase-scale viral genomics mining, we examine the landscape of human latent viral reactivation and demonstrate that HHV-6B can become reactivated in cultures of human CD4+ T cells. Using single-cell sequencing, we identify a rare population of HHV-6 'super-expressors' (about 1 in 300-10,000 cells) that possess high viral transcriptional activity, among research-grade allogeneic chimeric antigen receptor (CAR) T cells. By analysing single-cell sequencing data from patients receiving cell therapy products that are approved by the US Food and Drug Administration2 or are in clinical studies3-5, we identify the presence of HHV-6-super-expressor CAR T cells in patients in vivo. Together, the findings of our study demonstrate the utility of comprehensive genomics analyses in implicating cell therapy products as a potential source contributing to the lytic HHV-6 infection that has been reported in clinical trials1,6-8 and may influence the design and production of autologous and allogeneic cell therapies.

Systematic benchmarking of single-cell ATAC-sequencing protocols.

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.

Single-cell multi-omics of mitochondrial DNA disorders reveals dynamics of purifying selection across human immune cells.

Pathogenic mutations in mitochondrial DNA (mtDNA) compromise cellular metabolism, contributing to cellular heterogeneity and disease. Diverse mutations are associated with diverse clinical phenotypes, suggesting distinct organ- and cell-type-specific metabolic vulnerabilities. Here we establish a multi-omics approach to quantify deletions in mtDNA alongside cell state features in single cells derived from six patients across the phenotypic spectrum of single large-scale mtDNA deletions (SLSMDs). By profiling 206,663 cells, we reveal the dynamics of pathogenic mtDNA deletion heteroplasmy consistent with purifying selection and distinct metabolic vulnerabilities across T-cell states in vivo and validate these observations in vitro. By extending analyses to hematopoietic and erythroid progenitors, we reveal mtDNA dynamics and cell-type-specific gene regulatory adaptations, demonstrating the context-dependence of perturbing mitochondrial genomic integrity. Collectively, we report pathogenic mtDNA heteroplasmy dynamics of individual blood and immune cells across lineages, demonstrating the power of single-cell multi-omics for revealing fundamental properties of mitochondrial genetics.

Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility.

Natural sequence variation within mitochondrial DNA (mtDNA) contributes to human phenotypes and may serve as natural genetic markers in human cells for clonal and lineage tracing. We recently developed a single-cell multi-omic approach, called 'mitochondrial single-cell assay for transposase-accessible chromatin with sequencing' (mtscATAC-seq), enabling concomitant high-throughput mtDNA genotyping and accessible chromatin profiling. Specifically, our technique allows the mitochondrial genome-wide inference of mtDNA variant heteroplasmy along with information on cell state and accessible chromatin variation in individual cells. Leveraging somatic mtDNA mutations, our method further enables inference of clonal relationships among native ex vivo-derived human cells not amenable to genetic engineering-based clonal tracing approaches. Here, we provide a step-by-step protocol for the use of mtscATAC-seq, including various cell-processing and flow cytometry workflows, by using primary hematopoietic cells, subsequent single-cell genomic library preparation and sequencing that collectively take ~3-4 days to complete. We discuss experimental and computational data quality control metrics and considerations for the extension to other mammalian tissues. Overall, mtscATAC-seq provides a broadly applicable platform to map clonal relationships between cells in human tissues, investigate fundamental aspects of mitochondrial genetics and enable additional modes of multi-omic discovery.

Concomitant Sequencing of Accessible Chromatin and Mitochondrial Genomes in Single Cells Using mtscATAC-Seq.

Mitochondria are unique organelles of eukaryotic cells that carry their own multicopy number and circular genome. In most mammals, including humans and mice, the size of the chromosome is ~16,000 base pairs and unlike nuclear DNA, mitochondrial DNA (mtDNA) is not densely compacted. This results in mtDNA to be highly accessible for enzymes such as the Tn5 transposase, commonly used for accessible chromatin profiling of nuclear chromatinized DNA. Here, we describe a method for the concomitant sequencing of mtDNA and accessible chromatin in thousands of individual cells via the mitochondrial single-cell assay for transposase accessible chromatin by sequencing (mtscATAC-seq). Our approach extends the utility of existing scATAC-seq products and protocols as we (Nam et al, Nat Rev Genet 22:3-18, 2021) fix cells using formaldehyde to retain mitochondria and its mtDNA within its originating cell, (Buenrostro et al, Nat Methods 10:1213-1218, 2013) modify lysis conditions to permeabilize cells and mitochondria, and (Corces et al, Nat Methods 14:959-962, 2017) optimize bioinformatic processing protocols to collectively increase mitochondrial genome coverage for downstream analysis. Here, we discuss the essentials for the experimental and computational methodologies to generate and analyze thousands of multiomic profiles of single cells over the course of a few days, enabling the profiling of accessible chromatin and mtDNA genotypes to reconstruct clonal relationships and studies of mitochondrial genetics and disease.

Single-cell multi-omics and lineage tracing to dissect cell fate decision-making.

The concept of cell fate relates to the future identity of a cell, and its daughters, which is obtained via cell differentiation and division. Understanding, predicting, and manipulating cell fate has been a long-sought goal of developmental and regenerative biology. Recent insights obtained from single-cell genomic and integrative lineage-tracing approaches have further aided to identify molecular features predictive of cell fate. In this perspective, we discuss these approaches with a focus on theoretical concepts and future directions of the field to dissect molecular mechanisms underlying cell fate.

Mitochondrial DNA Mutations as Natural Barcodes for Lineage Tracing of Murine Tumor Models.

Murine models are indispensable tools for functional genomic studies and preclinical testing of novel therapeutic approaches. Mitochondrial single-cell assay for transposase-accessible chromatin using sequencing (mtscATAC-seq) enables the dissection of cellular heterogeneity and clonal dynamics by capturing chromatin accessibility, copy-number variations (CNV), and mitochondrial DNA (mtDNA) mutations, yet its applicability to murine studies remains unexplored. By leveraging mtscATAC-seq in novel chronic lymphocytic leukemia and Richter syndrome mouse models, we report the detection of mtDNA mutations, particularly in highly proliferative murine cells, alongside CNV and chromatin state changes indicative of clonal evolution upon secondary transplant. This study thus demonstrates the feasibility and utility of multi-modal single-cell and natural barcoding approaches to characterize murine cancer models. SIGNIFICANCE: mtDNA mutations can serve as natural barcodes to enable lineage tracing in murine cancer models, which can be used to provide new insights into disease biology and to identify therapeutic vulnerabilities.

Clonal expansion and epigenetic inheritance of long-lasting NK cell memory.

Clonal expansion of cells with somatically diversified receptors and their long-term maintenance as memory cells is a hallmark of adaptive immunity. Here, we studied pathogen-specific adaptation within the innate immune system, tracking natural killer (NK) cell memory to human cytomegalovirus (HCMV) infection. Leveraging single-cell multiomic maps of ex vivo NK cells and somatic mitochondrial DNA mutations as endogenous barcodes, we reveal substantial clonal expansion of adaptive NK cells in HCMV+ individuals. NK cell clonotypes were characterized by a convergent inflammatory memory signature enriched for AP1 motifs superimposed on a private set of clone-specific accessible chromatin regions. NK cell clones were stably maintained in specific epigenetic states over time, revealing that clonal inheritance of chromatin accessibility shapes the epigenetic memory repertoire. Together, we identify clonal expansion and persistence within the human innate immune system, suggesting that these mechanisms have evolved independent of antigen-receptor diversification.

JAK inhibition in a patient with a STAT1 gain-of-function variant reveals STAT1 dysregulation as a common feature of aplastic anemia.

BACKGROUND: Idiopathic aplastic anemia is a potentially lethal disease, characterized by T cell-mediated autoimmune attack of bone marrow hematopoietic stem cells. Standard of care therapies (stem cell transplantation or immunosuppression) are effective but associated with a risk of serious toxicities. METHODS: An 18-year-old man presented with aplastic anemia in the context of a germline gain-of-function variant in STAT1. Treatment with the JAK1 inhibitor itacitinib resulted in a rapid resolution of aplastic anemia and a sustained recovery of hematopoiesis. Peripheral blood and bone marrow samples were compared before and after JAK1 inhibitor therapy. FINDINGS: Following therapy, samples showed a decrease in the plasma concentration of interferon-γ, a decrease in PD1-positive exhausted CD8+ T cell population, and a decrease in an interferon responsive myeloid population. Single-cell analysis of chromatin accessibility showed decreased accessibility of STAT1 across CD4+ and CD8+ T cells, as well as CD14+ monocytes. To query whether other cases of aplastic anemia share a similar STAT1-mediated pathophysiology, we examined a cohort of 9 patients with idiopathic aplastic anemia. Bone marrow from six of nine patients also displayed abnormal STAT1 hyper-activation. CONCLUSIONS: These findings raise the possibility that STAT1 hyperactivition defines a subset of idiopathic aplastic anemia patients for whom JAK inhibition may be an efficacious therapy. FUNDING: Funding was provided by the Massachusetts General Hospital Department of Medicine Pathways Program and NIH T32 AI007387. A trial registration is at https://clinicaltrials.gov/ct2/show/NCT03906318.

Mitochondrial variant enrichment from high-throughput single-cell RNA sequencing resolves clonal populations.

The combination of single-cell transcriptomics with mitochondrial DNA variant detection can be used to establish lineage relationships in primary human cells, but current methods are not scalable to interrogate complex tissues. Here, we combine common 3' single-cell RNA-sequencing protocols with mitochondrial transcriptome enrichment to increase coverage by more than 50-fold, enabling high-confidence mutation detection. The method successfully identifies skewed immune-cell expansions in primary human clonal hematopoiesis.

Congenital anemia reveals distinct targeting mechanisms for master transcription factor GATA1.

Master regulators, such as the hematopoietic transcription factor (TF) GATA1, play an essential role in orchestrating lineage commitment and differentiation. However, the precise mechanisms by which such TFs regulate transcription through interactions with specific cis-regulatory elements remain incompletely understood. Here, we describe a form of congenital hemolytic anemia caused by missense mutations in an intrinsically disordered region of GATA1, with a poorly understood role in transcriptional regulation. Through integrative functional approaches, we demonstrate that these mutations perturb GATA1 transcriptional activity by partially impairing nuclear localization and selectively altering precise chromatin occupancy by GATA1. These alterations in chromatin occupancy and concordant chromatin accessibility changes alter faithful gene expression, with failure to both effectively silence and activate select genes necessary for effective terminal red cell production. We demonstrate how disease-causing mutations can reveal regulatory mechanisms that enable the faithful genomic targeting of master TFs during cellular differentiation.

Single-cell profiling of proteins and chromatin accessibility using PHAGE-ATAC.

Multimodal measurements of single-cell profiles are proving increasingly useful for characterizing cell states and regulatory mechanisms. In the present study, we developed PHAGE-ATAC (Assay for Transposase-Accessible Chromatin), a massively parallel droplet-based method that uses phage displaying, engineered, camelid single-domain antibodies ('nanobodies') for simultaneous single-cell measurements of protein levels and chromatin accessibility profiles, and mitochondrial DNA-based clonal tracing. We use PHAGE-ATAC for multimodal analysis in primary human immune cells, sample multiplexing, intracellular protein analysis and the detection of SARS-CoV-2 spike protein in human cell populations. Finally, we construct a synthetic high-complexity phage library for selection of antigen-specific nanobodies that bind cells of particular molecular profiles, opening an avenue for protein detection, cell characterization and screening with single-cell genomics.

cDNA-detector: detection and removal of cDNA contamination in DNA sequencing libraries.

BACKGROUND: Exogenous cDNA introduced into an experimental system, either intentionally or accidentally, can appear as added read coverage over that gene in next-generation sequencing libraries derived from this system. If not properly recognized and managed, this cross-contamination with exogenous signal can lead to incorrect interpretation of research results. Yet, this problem is not routinely addressed in current sequence processing pipelines. RESULTS: We present cDNA-detector, a computational tool to identify and remove exogenous cDNA contamination in DNA sequencing experiments. We demonstrate that cDNA-detector can identify cDNAs quickly and accurately from alignment files. A source inference step attempts to separate endogenous cDNAs (retrocopied genes) from potential cloned, exogenous cDNAs. cDNA-detector provides a mechanism to decontaminate the alignment from detected cDNAs. Simulation studies show that cDNA-detector is highly sensitive and specific, outperforming existing tools. We apply cDNA-detector to several highly-cited public databases (TCGA, ENCODE, NCBI SRA) and show that contaminant genes appear in sequencing experiments where they lead to incorrect coverage peak calls. CONCLUSIONS: cDNA-detector is a user-friendly and accurate tool to detect and remove cDNA detection in NGS libraries. This two-step design reduces the risk of true variant removal since it allows for manual review of candidates. We find that contamination with intentionally and accidentally introduced cDNAs is an underappreciated problem even in widely-used consortium datasets, where it can lead to spurious results. Our findings highlight the importance of sensitive detection and removal of contaminant cDNA from NGS libraries before downstream analysis.

Induction of antigen-specific tolerance by nanobody-antigen adducts that target class-II major histocompatibility complexes.

The association of autoimmune diseases with particular allellic products of the class-II major histocompatibility complex (MHCII) region implicates the presentation of the offending self-antigens to T cells. Because antigen-presenting cells are tolerogenic when they encounter an antigen under non-inflammatory conditions, the manipulation of antigen presentation may induce antigen-specific tolerance. Here, we show that, in mouse models of experimental autoimmune encephalomyelitis, type 1 diabetes and rheumatoid arthritis, the systemic administration of a single dose of nanobodies that recognize MHCII molecules and conjugated to the relevant self-antigen under non-inflammatory conditions confers long-lasting protection against these diseases. Moreover, co-administration of a nanobody-antigen adduct and the glucocorticoid dexamethasone, conjugated to the nanobody via a cleavable linker, halted the progression of established experimental autoimmune encephalomyelitis in symptomatic mice and alleviated their symptoms. This approach may represent a means of treating autoimmune conditions.