A mouse model with high clonal barcode diversity for joint lineage, transcriptomic, and epigenomic profiling in single cells.

Cellular lineage histories and their molecular states encode fundamental principles of tissue development and homeostasis. Current lineage-recording mouse models have insufficient barcode diversity and single-cell lineage coverage for profiling tissues composed of millions of cells. Here, we developed DARLIN, an inducible Cas9 barcoding mouse line that utilizes terminal deoxynucleotidyl transferase (TdT) and 30 CRISPR target sites. DARLIN is inducible, generates massive lineage barcodes across tissues, and enables the detection of edited barcodes in ∼70% of profiled single cells. Using DARLIN, we examined fate bias within developing hematopoietic stem cells (HSCs) and revealed unique features of HSC migration. Additionally, we established a protocol for joint transcriptomic and epigenomic single-cell measurements with DARLIN and found that cellular clonal memory is associated with genome-wide DNA methylation rather than gene expression or chromatin accessibility. DARLIN will enable the high-resolution study of lineage relationships and their molecular signatures in diverse tissues and physiological contexts.

Linking chromatin acylation mark-defined proteome and genome in living cells.

A generalizable strategy with programmable site specificity for in situ profiling of histone modifications on unperturbed chromatin remains highly desirable but challenging. We herein developed a single-site-resolved multi-omics (SiTomics) strategy for systematic mapping of dynamic modifications and subsequent profiling of chromatinized proteome and genome defined by specific chromatin acylations in living cells. By leveraging the genetic code expansion strategy, our SiTomics toolkit revealed distinct crotonylation (e.g., H3K56cr) and ß-hydroxybutyrylation (e.g., H3K56bhb) upon short chain fatty acids stimulation and established linkages for chromatin acylation mark-defined proteome, genome, and functions. This led to the identification of GLYR1 as a distinct interacting protein in modulating H3K56cr's gene body localization as well as the discovery of an elevated super-enhancer repertoire underlying bhb-mediated chromatin modulations. SiTomics offers a platform technology for elucidating the "metabolites-modification-regulation" axis, which is widely applicable for multi-omics profiling and functional dissection of modifications beyond acylations and proteins beyond histones.

Multi-omics analysis of mucosal and systemic immunity to SARS-CoV-2 after birth.

The dynamics of immunity to infection in infants remain obscure. Here, we used a multi-omics approach to perform a longitudinal analysis of immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in infants and young children by analyzing blood samples and weekly nasal swabs collected before, during, and after infection with Omicron and non-Omicron variants. Infection stimulated robust antibody titers that, unlike in adults, showed no sign of decay for up to 300 days. Infants mounted a robust mucosal immune response characterized by inflammatory cytokines, interferon (IFN) α, and T helper (Th) 17 and neutrophil markers (interleukin [IL]-17, IL-8, and CXCL1). The immune response in blood was characterized by upregulation of activation markers on innate cells, no inflammatory cytokines, but several chemokines and IFNα. The latter correlated with viral load and expression of interferon-stimulated genes (ISGs) in myeloid cells measured by single-cell multi-omics. Together, these data provide a snapshot of immunity to infection during the initial weeks and months of life.

Neurulation of the cynomolgus monkey embryo achieved from 3D blastocyst culture.

Neural tube (NT) defects arise from abnormal neurulation and result in the most common birth defects worldwide. Yet, mechanisms of primate neurulation remain largely unknown due to prohibitions on human embryo research and limitations of available model systems. Here, we establish a three-dimensional (3D) prolonged in vitro culture (pIVC) system supporting cynomolgus monkey embryo development from 7 to 25 days post-fertilization. Through single-cell multi-omics analyses, we demonstrate that pIVC embryos form three germ layers, including primordial germ cells, and establish proper DNA methylation and chromatin accessibility through advanced gastrulation stages. In addition, pIVC embryo immunofluorescence confirms neural crest formation, NT closure, and neural progenitor regionalization. Finally, we demonstrate that the transcriptional profiles and morphogenetics of pIVC embryos resemble key features of similarly staged in vivo cynomolgus and human embryos. This work therefore describes a system to study non-human primate embryogenesis through advanced gastrulation and early neurulation.

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19.

Proper acquisition of cell class identity in organoids allows definition of fate specification programs of the human cerebral cortex.

Realizing the full utility of brain organoids to study human development requires understanding whether organoids precisely replicate endogenous cellular and molecular events, particularly since acquisition of cell identity in organoids can be impaired by abnormal metabolic states. We present a comprehensive single-cell transcriptomic, epigenetic, and spatial atlas of human cortical organoid development, comprising over 610,000 cells, from generation of neural progenitors through production of differentiated neuronal and glial subtypes. We show that processes of cellular diversification correlate closely to endogenous ones, irrespective of metabolic state, empowering the use of this atlas to study human fate specification. We define longitudinal molecular trajectories of cortical cell types during organoid development, identify genes with predicted human-specific roles in lineage establishment, and uncover early transcriptional diversity of human callosal neurons. The findings validate this comprehensive atlas of human corticogenesis in vitro as a resource to prime investigation into the mechanisms of human cortical development.

Engineered cell entry links receptor biology with single-cell genomics.

Cells communicate with each other via receptor-ligand interactions. Here, we describe lentiviral-mediated cell entry by engineered receptor-ligand interaction (ENTER) to display ligand proteins, deliver payloads, and record receptor specificity. We optimize ENTER to decode interactions between T cell receptor (TCR)-MHC peptides, antibody-antigen, and other receptor-ligand pairs. A viral presentation strategy allows ENTER to capture interactions between B cell receptor and any antigen. We engineer ENTER to deliver genetic payloads to antigen-specific T or B cells to selectively modulate cellular behavior in mixed populations. Single-cell readout of ENTER by RNA sequencing (ENTER-seq) enables multiplexed enumeration of antigen specificities, TCR clonality, cell type, and states of individual T cells. ENTER-seq of CMV-seropositive patient blood samples reveals the viral epitopes that drive effector memory T cell differentiation and inter-clonal vs. intra-clonal phenotypic diversity targeting the same epitope. ENTER technology enables systematic discovery of receptor specificity, linkage to cell fates, and antigen-specific cargo delivery.

Multiple early factors anticipate post-acute COVID-19 sequelae.

Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific auto-antibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes, exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time, leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

Time-resolved systems immunology reveals a late juncture linked to fatal COVID-19.

COVID-19 exhibits extensive patient-to-patient heterogeneity. To link immune response variation to disease severity and outcome over time, we longitudinally assessed circulating proteins as well as 188 surface protein markers, transcriptome, and T cell receptor sequence simultaneously in single peripheral immune cells from COVID-19 patients. Conditional-independence network analysis revealed primary correlates of disease severity, including gene expression signatures of apoptosis in plasmacytoid dendritic cells and attenuated inflammation but increased fatty acid metabolism in CD56dimCD16hi NK cells linked positively to circulating interleukin (IL)-15. CD8+ T cell activation was apparent without signs of exhaustion. Although cellular inflammation was depressed in severe patients early after hospitalization, it became elevated by days 17-23 post symptom onset, suggestive of a late wave of inflammatory responses. Furthermore, circulating protein trajectories at this time were divergent between and predictive of recovery versus fatal outcomes. Our findings stress the importance of timing in the analysis, clinical monitoring, and therapeutic intervention of COVID-19.

A modular master regulator landscape controls cancer transcriptional identity.

Despite considerable efforts, the mechanisms linking genomic alterations to the transcriptional identity of cancer cells remain elusive. Integrative genomic analysis, using a network-based approach, identified 407 master regulator (MR) proteins responsible for canalizing the genetics of individual samples from 20 cohorts in The Cancer Genome Atlas (TCGA) into 112 transcriptionally distinct tumor subtypes. MR proteins could be further organized into 24 pan-cancer, master regulator block modules (MRBs), each regulating key cancer hallmarks and predictive of patient outcome in multiple cohorts. Of all somatic alterations detected in each individual sample, >50% were predicted to induce aberrant MR activity, yielding insight into mechanisms linking tumor genetics and transcriptional identity and establishing non-oncogene dependencies. Genetic and pharmacological validation assays confirmed the predicted effect of upstream mutations and MR activity on downstream cellular identity and phenotype. Thus, co-analysis of mutational and gene expression profiles identified elusive subtypes and provided testable hypothesis for mechanisms mediating the effect of genetic alterations.

High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue.

We present deterministic barcoding in tissue for spatial omics sequencing (DBiT-seq) for co-mapping of mRNAs and proteins in a formaldehyde-fixed tissue slide via next-generation sequencing (NGS). Parallel microfluidic channels were used to deliver DNA barcodes to the surface of a tissue slide, and crossflow of two sets of barcodes, A1-50 and B1-50, followed by ligation in situ, yielded a 2D mosaic of tissue pixels, each containing a unique full barcode AB. Application to mouse embryos revealed major tissue types in early organogenesis as well as fine features like microvasculature in a brain and pigmented epithelium in an eye field. Gene expression profiles in 10-µm pixels conformed into the clusters of single-cell transcriptomes, allowing for rapid identification of cell types and spatial distributions. DBiT-seq can be adopted by researchers with no experience in microfluidics and may find applications in a range of fields including developmental biology, cancer biology, neuroscience, and clinical pathology.

Fundamental Biological Features of Spaceflight: Advancing the Field to Enable Deep-Space Exploration.

Research on astronaut health and model organisms have revealed six features of spaceflight biology that guide our current understanding of fundamental molecular changes that occur during space travel. The features include oxidative stress, DNA damage, mitochondrial dysregulation, epigenetic changes (including gene regulation), telomere length alterations, and microbiome shifts. Here we review the known hazards of human spaceflight, how spaceflight affects living systems through these six fundamental features, and the associated health risks of space exploration. We also discuss the essential issues related to the health and safety of astronauts involved in future missions, especially planned long-duration and Martian missions.

Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate COVID-19.

We present an integrated analysis of the clinical measurements, immune cells, and plasma multi-omics of 139 COVID-19 patients representing all levels of disease severity, from serial blood draws collected during the first week of infection following diagnosis. We identify a major shift between mild and moderate disease, at which point elevated inflammatory signaling is accompanied by the loss of specific classes of metabolites and metabolic processes. Within this stressed plasma environment at moderate disease, multiple unusual immune cell phenotypes emerge and amplify with increasing disease severity. We condensed over 120,000 immune features into a single axis to capture how different immune cell classes coordinate in response to SARS-CoV-2. This immune-response axis independently aligns with the major plasma composition changes, with clinical metrics of blood clotting, and with the sharp transition between mild and moderate disease. This study suggests that moderate disease may provide the most effective setting for therapeutic intervention.

An Organoid Biobank of Neuroendocrine Neoplasms Enables Genotype-Phenotype Mapping.

Gastroenteropancreatic (GEP) neuroendocrine neoplasm (NEN) that consists of neuroendocrine tumor and neuroendocrine carcinoma (NEC) is a lethal but under-investigated disease owing to its rarity. To fill the scarcity of clinically relevant models of GEP-NEN, we here established 25 lines of NEN organoids and performed their comprehensive molecular characterization. GEP-NEN organoids recapitulated pathohistological and functional phenotypes of the original tumors. Whole-genome sequencing revealed frequent genetic alterations in TP53 and RB1 in GEP-NECs, and characteristic chromosome-wide loss of heterozygosity in GEP-NENs. Transcriptome analysis identified molecular subtypes that are distinguished by the expression of distinct transcription factors. GEP-NEN organoids gained independence from the stem cell niche irrespective of genetic mutations. Compound knockout of TP53 and RB1, together with overexpression of key transcription factors, conferred on the normal colonic epithelium phenotypes that are compatible with GEP-NEN biology. Altogether, our study not only provides genetic understanding of GEP-NEN, but also connects its genetics and biological phenotypes.

Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma.

To define the cellular composition and architecture of cutaneous squamous cell carcinoma (cSCC), we combined single-cell RNA sequencing with spatial transcriptomics and multiplexed ion beam imaging from a series of human cSCCs and matched normal skin. cSCC exhibited four tumor subpopulations, three recapitulating normal epidermal states, and a tumor-specific keratinocyte (TSK) population unique to cancer, which localized to a fibrovascular niche. Integration of single-cell and spatial data mapped ligand-receptor networks to specific cell types, revealing TSK cells as a hub for intercellular communication. Multiple features of potential immunosuppression were observed, including T regulatory cell (Treg) co-localization with CD8 T cells in compartmentalized tumor stroma. Finally, single-cell characterization of human tumor xenografts and in vivo CRISPR screens identified essential roles for specific tumor subpopulation-enriched gene networks in tumorigenesis. These data define cSCC tumor and stromal cell subpopulations, the spatial niches where they interact, and the communicating gene networks that they engage in cancer.

Molecular Choreography of Acute Exercise.

Acute physical activity leads to several changes in metabolic, cardiovascular, and immune pathways. Although studies have examined selected changes in these pathways, the system-wide molecular response to an acute bout of exercise has not been fully characterized. We performed longitudinal multi-omic profiling of plasma and peripheral blood mononuclear cells including metabolome, lipidome, immunome, proteome, and transcriptome from 36 well-characterized volunteers, before and after a controlled bout of symptom-limited exercise. Time-series analysis revealed thousands of molecular changes and an orchestrated choreography of biological processes involving energy metabolism, oxidative stress, inflammation, tissue repair, and growth factor response, as well as regulatory pathways. Most of these processes were dampened and some were reversed in insulin-resistant participants. Finally, we discovered biological pathways involved in cardiopulmonary exercise response and developed prediction models revealing potential resting blood-based biomarkers of peak oxygen consumption.

Rewiring of the Fruit Metabolome in Tomato Breeding.

Humans heavily rely on dozens of domesticated plant species that have been further improved through intensive breeding. To evaluate how breeding changed the tomato fruit metabolome, we have generated and analyzed a dataset encompassing genomes, transcriptomes, and metabolomes from hundreds of tomato genotypes. The combined results illustrate how breeding globally altered fruit metabolite content. Selection for alleles of genes associated with larger fruits altered metabolite profiles as a consequence of linkage with nearby genes. Selection of five major loci reduced the accumulation of anti-nutritional steroidal glycoalkaloids in ripened fruits, rendering the fruit more edible. Breeding for pink tomatoes modified the content of over 100 metabolites. The introgression of resistance genes from wild relatives in cultivars also resulted in major and unexpected metabolic changes. The study reveals a multi-omics view of the metabolic breeding history of tomato, as well as provides insights into metabolome-assisted breeding and plant biology.

Combined protein and nucleic acid imaging reveals virus-dependent B cell and macrophage immunosuppression of tissue microenvironments.

Understanding the mechanisms of HIV tissue persistence necessitates the ability to visualize tissue microenvironments where infected cells reside; however, technological barriers limit our ability to dissect the cellular components of these HIV reservoirs. Here, we developed protein and nucleic acid in situ imaging (PANINI) to simultaneously quantify DNA, RNA, and protein levels within these tissue compartments. By coupling PANINI with multiplexed ion beam imaging (MIBI), we measured over 30 parameters simultaneously across archival lymphoid tissues from healthy or simian immunodeficiency virus (SIV)-infected nonhuman primates. PANINI enabled the spatial dissection of cellular phenotypes, functional markers, and viral events resulting from infection. SIV infection induced IL-10 expression in lymphoid B cells, which correlated with local macrophage M2 polarization. This highlights a potential viral mechanism for conditioning an immunosuppressive tissue environment for virion production. The spatial multimodal framework here can be extended to decipher tissue responses in other infectious diseases and tumor biology.

The use of machine learning to discover regulatory networks controlling biological systems.

Biological systems are composed of a vast web of multiscale molecular interactors and interactions. High-throughput technologies, both bulk and single cell, now allow for investigation of the properties and quantities of these interactors. Computational algorithms and machine learning methods then provide the tools to derive meaningful insights from the resulting data sets. One such approach is graphical network modeling, which provides a computational framework to explicitly model the molecular interactions within and between the cells comprising biological systems. These graphical networks aim to describe a putative chain of cause and effect between interacting molecules. This feature allows for determination of key molecules in a biological process, accelerated generation of mechanistic hypotheses, and simulation of experimental outcomes. We review the computational concepts and applications of graphical network models across molecular scales for both intracellular and intercellular regulatory biology, examples of successful applications, and the future directions needed to overcome current limitations.

New horizons in the stormy sea of multimodal single-cell data integration.

While measurements of RNA expression have dominated the world of single-cell analyses, new single-cell techniques increasingly allow collection of different data modalities, measuring different molecules, structural connections, and intermolecular interactions. Integrating the resulting multimodal single-cell datasets is a new bioinformatics challenge. Equally important, it is a new experimental design challenge for the bench scientist, who is not only choosing from a myriad of techniques for each data modality but also faces new challenges in experimental design. The ultimate goal is to design, execute, and analyze multimodal single-cell experiments that are more than just descriptive but enable the learning of new causal and mechanistic biology. This objective requires strict consideration of the goals behind the analysis, which might range from mapping the heterogeneity of a cellular population to assembling system-wide causal networks that can further our understanding of cellular functions and eventually lead to models of tissues and organs. We review steps and challenges toward this goal. Single-cell transcriptomics is now a mature technology, and methods to measure proteins, lipids, small-molecule metabolites, and other molecular phenotypes at the single-cell level are rapidly developing. Integrating these single-cell readouts so that each cell has measurements of multiple types of data, e.g., transcriptomes, proteomes, and metabolomes, is expected to allow identification of highly specific cellular subpopulations and to provide the basis for inferring causal biological mechanisms.