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Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and treatment-refractory cancer. Molecular stratification in pancreatic cancer remains rudimentary and does not yet inform clinical management or therapeutic development. Here, we construct a high-resolution molecular landscape of the cellular subtypes and spatial communities that compose PDAC using single-nucleus RNA sequencing and whole-transcriptome digital spatial profiling (DSP) of 43 primary PDAC tumor specimens that either received neoadjuvant therapy or were treatment naive. We uncovered recurrent expression programs across malignant cells and fibroblasts, including a newly identified neural-like progenitor malignant cell program that was enriched after chemotherapy and radiotherapy and associated with poor prognosis in independent cohorts. Integrating spatial and cellular profiles revealed three multicellular communities with distinct contributions from malignant, fibroblast and immune subtypes: classical, squamoid-basaloid and treatment enriched. Our refined molecular and cellular taxonomy can provide a framework for stratification in clinical trials and serve as a roadmap for therapeutic targeting of specific cellular phenotypes and multicellular interactions.

T cells engineered to express chimeric antigen receptors (CARs) targeting CD19 have produced impressive outcomes for the treatment of B cell malignancies, but different products vary in kinetics, persistence, and toxicity profiles based on the co-stimulatory domains included in the CAR. In this study, we performed transcriptional profiling of bulk CAR T cell populations and single cells to characterize the transcriptional states of human T cells transduced with CD3ζ, 4-1BB-CD3ζ (BBζ), or CD28-CD3ζ (28ζ) co-stimulatory domains at rest and after activation by triggering their CAR or their endogenous T cell receptor (TCR). We identified a transcriptional signature common across CARs with the CD3ζ signaling domain, as well as a distinct program associated with the 4-1BB co-stimulatory domain at rest and after activation. CAR T cells bearing BBζ had increased expression of human leukocyte antigen (HLA) class II genes, ENPP2, and interleukin (IL)-21 axis genes, and decreased PD1 compared to 28ζ CAR T cells. Similar to previous studies, we also found BBζ CAR CD8 T cells to be enriched in a central memory cell phenotype and fatty acid metabolism genes. Our data uncovered transcriptional signatures related to costimulatory domains and demonstrated that signaling domains included in CARs uniquely shape the transcriptional programs of T cells.

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases., A set of ready-to-use tools for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq facilitates the implementation of single-cell technologies in clinical settings and the construction of single-cell tumor atlases.

Tissue-resident innate lymphoid cells (ILCs) help sustain barrier function and respond to local signals. ILCs are traditionally classified as ILC1, ILC2 or ILC3 on the basis of their expression of specific transcription factors and cytokines1. In the skin, disease-specific production of ILC3-associated cytokines interleukin (IL)-17 and IL-22 in response to IL-23 signalling contributes to dermal inflammation in psoriasis. However, it is not known whether this response is initiated by pre-committed ILCs or by cell-state transitions. Here we show that the induction of psoriasis in mice by IL-23 or imiquimod reconfigures a spectrum of skin ILCs, which converge on a pathogenic ILC3-like state. Tissue-resident ILCs were necessary and sufficient, in the absence of circulatory ILCs, to drive pathology. Single-cell RNA-sequencing (scRNA-seq) profiles of skin ILCs along a time course of psoriatic inflammation formed a dense transcriptional continuum—even at steady state—reflecting fluid ILC states, including a naive or quiescent-like state and an ILC2 effector state. Upon disease induction, the continuum shifted rapidly to span a mixed, ILC3-like subset also expressing cytokines characteristic of ILC2s, which we inferred as arising through multiple trajectories. We confirmed the transition potential of quiescent-like and ILC2 states using in vitro experiments, single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) and in vivo fate mapping. Our results highlight the range and flexibility of skin ILC responses, suggesting that immune activities primed in healthy tissues dynamically adapt to provocations and, left unchecked, drive pathological remodelling. In studies using mouse models of psoriasis, a spectrum of innate lymphoid cell types is reconfigured and converges via multiple trajectories on a type 3-like state, demonstrating the range and flexibility of innate lymphoid cell responses in the skin.

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.

Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease. Characterizing PDAC by mRNA profiling remains particularly challenging. Previously identified bulk expression subtypes were influenced by contaminating stroma and have not yet informed clinical management, whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors and those that received neoadjuvant chemotherapy and radiotherapy (CRT). Gene expression programs learned across untreated malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Moreover, in the increasingly-adopted neoadjuvant treatment context, there was a depletion of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. Spatially-resolved transcriptomics revealed an association between malignant cells expressing these basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to susceptibility to distinct therapeutic strategies. Our refined molecular taxonomy and spatial resolution can help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system.

Tumor evolution from a single cell into a malignant, heterogeneous tissue remains poorly understood. Here, we profile single-cell transcriptomes of genetically engineered mouse lung tumors at seven stages, from pre-neoplastic hyperplasia to adenocarcinoma. The diversity of transcriptional states increases over time and is reproducible across tumors and mice. Cancer cells progressively adopt alternate lineage identities, computationally predicted to be mediated through a common transitional, high-plasticity cell state (HPCS). Accordingly, HPCS cells prospectively isolated from mouse tumors and human patient-derived xenografts display high capacity for differentiation and proliferation. The HPCS program is associated with poor survival across human cancers and demonstrates chemoresistance in mice. Our study reveals a central principle underpinning intra-tumoral heterogeneity and motivates therapeutic targeting of the HPCS. Cellular states capable of promoting tumor progression and resisting therapies exist in heterogeneous tumors. Marjanovic et al. discover that a high-plasticity cell state common to mouse and human lung tumors drives cellular heterogeneity, is highly tumorigenic and drug resistant, and associates with poor patient prognosis.

Malignant abdominal fluid (ascites) frequently develops in women with advanced high-grade serous ovarian cancer (HGSOC) and is associated with drug resistance and a poor prognosis1. To comprehensively characterize the HGSOC ascites ecosystem, we used single-cell RNA sequencing to profile ~11,000 cells from 22 ascites specimens from 11 patients with HGSOC. We found significant inter-patient variability in the composition and functional programs of ascites cells, including immunomodulatory fibroblast sub-populations and dichotomous macrophage populations. We found that the previously described immunoreactive and mesenchymal subtypes of HGSOC, which have prognostic implications, reflect the abundance of immune infiltrates and fibroblasts rather than distinct subsets of malignant cells2. Malignant cell variability was partly explained by heterogeneous copy number alteration patterns or expression of a stemness program. Malignant cells shared expression of inflammatory programs that were largely recapitulated in single-cell RNA sequencing of ~35,000 cells from additionally collected samples, including three ascites, two primary HGSOC tumors and three patient ascites-derived xenograft models. Inhibition of the JAK/STAT pathway, which was expressed in both malignant cells and cancer-associated fibroblasts, had potent anti-tumor activity in primary short-term cultures and patient-derived xenograft models. Our work contributes to resolving the HSGOC landscape3-5 and provides a resource for the development of novel therapeutic approaches.

Candida albicans is the leading cause of fungal infections; yet, complex genetic interaction analysis remains cumbersome in this diploid pathogen. Here, we developed a CRISPR-Cas9-based ‘gene drive array’ (GDA) platform to facilitate efficient genetic analysis in C. albicans. In our system, a modified DNA donor molecule acts as a selfish genetic element, replaces the targeted site, and propagates to replace additional wild-type loci. Using mating-competent C. albicans haploids, each carrying a different gene drive disabling a gene of interest, we are able to create diploid strains that are homozygous double-deletion mutants. We generate double-gene deletion libraries to demonstrate this technology, targeting antifungal efflux and biofilm adhesion factors. We screen these libraries to identify virulence regulators and determine how genetic networks shift under diverse conditions. This platform transforms our ability to perform genetic interaction analysis in C. albicans and is readily extended to other fungal pathogens.

Metabolically dormant bacteria present a critical challenge to effective antimicrobial therapy because these bacteria are genetically susceptible to antibiotic treatment but phenotypically tolerant. Such tolerance has been attributed to impaired drug uptake, which can be reversed by metabolic stimulation. Here, we evaluate the effects of central carbon metabolite stimulations on aminoglycoside sensitivity in the pathogen Pseudomonas aeruginosa. We identify fumarate as a tobramycin potentiator that activates cellular respiration and generates a proton motive force by stimulating the tricarboxylic acid (TCA) cycle. In contrast, we find that glyoxylate induces phenotypic tolerance by inhibiting cellular respiration with acetyl-coenzyme A diversion through the glyoxylate shunt, despite drug import. Collectively, this work demonstrates that TCA cycle activity is important for both aminoglycoside uptake and downstream lethality and identifies a potential strategy for potentiating aminoglycoside treatment of P. aeruginosa infections. Keyword: aminoglycoside susceptibility; Pseudomonas aeruginosa; TCA cycle; respiration; electron transport chain; fumarate; glyoxylate; biochemical persistence; LC-MS metabolomics, Defense Threat Reduction Agency (DTRA) (Grant HDTRA1-15-1-0051), National Institutes of Health (U.S.) (Grant NIH K99GM118907)

Single cell genomics is essential to chart the complex tumor ecosystem. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumor tissues, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each strategy requires modifications to fit the unique characteristics of different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We tested eight tumor types of varying tissue and sample characteristics (resection, biopsy, ascites, and orthotopic patient-derived xenograft): lung cancer, metastatic breast cancer, ovarian cancer, melanoma, neuroblastoma, pediatric sarcoma, glioblastoma, pediatric high-grade glioma, and chronic lymphocytic leukemia. Analyzing 212,498 cells and nuclei from 39 clinical samples, we evaluated protocols by cell quality, recovery rate, and cellular composition. We optimized protocols for fresh tissue dissociation for different tumor types using a decision tree to account for the technical and biological variation between clinical samples. We established methods for nucleus isolation from OCT embedded and fresh-frozen tissues, with an optimization matrix varying mechanical force, buffer, and detergent. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types and intrinsic expression profiles, but at different proportions. Our work provides direct guidance across a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

Summary Signaling abnormalities in immune responses in the small intestine can trigger chronic type 2 inflammation involving interaction of multiple immune cell types. To systematically characterize this response, we analyzed 58,067 immune cells from the mouse small intestine by single-cell RNA sequencing (scRNA-seq) at steady state and after induction of a type 2 inflammatory reaction to ovalbumin (OVA). Computational analysis revealed broad shifts in both cell-type composition and cell programs in response to the inflammation, especially in group 2 innate lymphoid cells (ILC2s). Inflammation induced the expression of exon 5 of Calca, which encodes the alpha-calcitonin gene-related peptide (α-CGRP), in intestinal KLRG1+ ILC2s. α-CGRP antagonized KLRG1+ ILC2s proliferation but promoted IL-5 expression. Genetic perturbation of α-CGRP increased the proportion of intestinal KLRG1+ ILC2s. Our work highlights a model where α-CGRP-mediated neuronal signaling is critical for suppressing ILC2 expansion and maintaining homeostasis of the type 2 immune machinery.

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

Psoriasis pathology is driven by the type 3 cytokines IL-17 and Il-22, but little is understood about the dynamics that initiate alterations in tissue homeostasis. Here, we use mouse models, single-cell RNA-seq (scRNA-seq), computational inference and cell lineage mapping to show that psoriasis induction reconfigures the functionality of skin-resident ILCs to initiate disease. Tissue-resident ILCs amplified an initial IL-23 trigger and were sufficient, without circulatory ILCs, to drive pathology, indicating that ILC tissue remodeling initiates psoriasis. Skin ILCs expressed type 2 cytokines IL-5 and IL-13 in steady state, but were epigenetically poised to become ILC3-like cells. ScRNA-seq profiles of ILCs from psoriatic and naïve skin of wild type (WT) and Rag1-/- mice form a dense continuum, consistent with this model of fluid ILC states. We inferred biological “topics” underlying these states and their relative importance in each cell with a generative model of latent Dirichlet allocation, showing that ILCs from untreated skin span a spectrum of states, including a naïve/quiescent-like state and one expressing the Cd74 and Il13 but little Il5. Upon disease induction, this spectrum shifts, giving rise to a greater proportion of classical Il5- and Il13- expressing “ILC2s” and a new, mixed ILC2/ILC3-like subset, expressing Il13, Il17, and Il22. Using these key topics, we related the cells through transitions, revealing a quiescence-ILC2-ILC3s state trajectory. We demonstrated this plasticity in vivo, combining an IL-5 fate mouse with IL-17A and IL-22 reporters, validating the transition of IL-5–producing ILC2s to IL-22– and IL-17A–producing cells during disease initiation. Thus, steady-state skin ILCs are actively repressed and cued for a plastic, type 2 response, which, upon induction, morphs into a type 3 response that drives psoriasis. This suggests a general model where specific immune activities are primed in healthy tissue, dynamically adapt to provocations, and left unchecked, drive pathological remodeling.

Understanding how antibiotics impact bacterial metabolism may provide insight into their mechanisms of action and could lead to enhanced therapeutic methodologies. Here, we profiled the metabolome of Escherichia coli after treatment with three different classes of bactericidal antibiotics (β-lactams, aminoglycosides, quinolones). These treatments induced a similar set of metabolic changes after 30 min that then diverged into more distinct profiles at later time points. The most striking changes corresponded to elevated concentrations of central carbon metabolites, active breakdown of the nucleotide pool, reduced lipid levels, and evidence of an elevated redox state. We examined potential end-target consequences of these metabolic perturbations and found that antibiotic-treated cells exhibited cytotoxic changes indicative of oxidative stress, including higher levels of protein carbonylation, malondialdehyde adducts, nucleotide oxidation, and double-strand DNA breaks. This work shows that bactericidal antibiotics induce a complex set of metabolic changes that are correlated with the buildup of toxic metabolic by-products., National Institutes of Health (U.S.) (Director's Pioneer Award), Howard Hughes Medical Institute, Wyss Institute for Biologically Inspired Engineering, United States. Defense Threat Reduction Agency (Grant HDTRA1-15-1-0051), National Institutes of Health (U.S.) (Grant R01 CA021615)

The version of this paper originally published contained reference errors. The sentence "To dissect complex genetic interactions in C. albicans, a CRISPR-Cas9-based Gene Drive Array (GDA) was developed" incorrectly cited ref. 13, and should have cited ref. 14. In addition, the reference included as ref. 13 in the original paper was incorrect, and should have been the following: Shapiro, R. S., Chavez, A. & Collins, J. J. CRISPR-based genomic tools for the manipulation of genetically intractable microorganisms. Nat. Rev. Microbiol. 16, 333-339 (2018). This reference should have been cited after the sentence "Recent innovations in CRISPR-Cas9-based genome editing have facilitated such genetic interaction analyses." The original reference 13 (Gerami-Nejad, M., Zacchi, L. F., McClellan, M., Matter, K. & Berman, J. Shuttle vectors for facile gap repair cloning and integration into a neutral locus in Candida albicans. Microbiology 159, 565-579 (2013)) should have been cited later in the paper, and is now in the reference list as ref. 27. As a result, original references 27-33 have been renumbered in the reference list and in the text. These changes have been made in the PDF and HTML versions of the protocol.

Bacteriostatic and bactericidal antibiotic treatments result in two fundamentally different phenotypic outcomes—the inhibition of bacterial growth or, alternatively, cell death. Most antibiotics inhibit processes that are major consumers of cellular energy output, suggesting that antibiotic treatment may have important downstream consequences on bacterial metabolism. We hypothesized that the specific metabolic effects of bacteriostatic and bactericidal antibiotics contribute to their overall efficacy. We leveraged the opposing phenotypes of bacteriostatic and bactericidal drugs in combination to investigate their activity. Growth inhibition from bacteriostatic antibiotics was associated with suppressed cellular respiration whereas cell death from most bactericidal antibiotics was associated with accelerated respiration. In combination, suppression of cellular respiration by the bacteriostatic antibiotic was the dominant effect, blocking bactericidal killing. Global metabolic profiling of bacteriostatic antibiotic treatment revealed that accumulation of metabolites involved in specific drug target activity was linked to the buildup of energy metabolites that feed the electron transport chain. Inhibition of cellular respiration by knockout of the cytochrome oxidases was sufficient to attenuate bactericidal lethality whereas acceleration of basal respiration by genetically uncoupling ATP synthesis from electron transport resulted in potentiation of the killing effect of bactericidal antibiotics. This work identifies a link between antibiotic-induced cellular respiration and bactericidal lethality and demonstrates that bactericidal activity can be arrested by attenuated respiration and potentiated by accelerated respiration. Our data collectively show that antibiotics perturb the metabolic state of bacteria and that the metabolic state of bacteria impacts antibiotic efficacy.