Defined Cell Types Research Articles

Abstract B068: Inferring enhancer activity from cell-free DNA fragmentation patterns

Abstract We present a framework for inferring enhancer activity from cell-free DNA (cfDNA) fragmentation patterns, offering a novel feature set for cfDNA analysis that reflects gene regulation. Enhancers are promoter-distal regulatory elements that regulate gene expression programs that define cell types and cellular states. Despite advances in inferring gene regulation in cancer using liquid biopsy, it remains challenging to identify signals of enhancer activity from cell-free DNA (cfDNA). Active enhancers are characterized by transcription of short enhancer RNAs (eRNAs). Recent studies demonstrated that cfDNA from promoters of transcribed genes demonstrates high variation in DNA fragment length, or “fragmentation entropy”. We tested whether eRNA transcription can be inferred based on cfDNA fragmentation entropy. We quantified “enhancer fragmentation entropy” (EFE) to profile enhancer activity in plasma by measuring Shannon entropy of cfDNA fragments around enhancer transcription start sites (TSS). Using PRO-cap data from lymphoblastoid cell lines, we analyzed EFE signals at 70,000 transcribed enhancers and observed distinct patterns between active (expressed) and inactive enhancers in cfDNA from healthy individuals. cfDNA from patients with prostate cancer showed elevated EFE at enhancers activated in prostate cancer. EFE at these sites correlated with circulating tumor DNA (ctDNA) levels in a published cfDNA dataset of 41 prostate cancer plasma samples. Lower-dimensional projections of the entropy signals across 300 “modules” of co-regulated enhancers revealed tighter clustering of samples within the same cancer type, suggesting that these entropy patterns capture cell-type specific enhancer activity. Our findings suggest that enhancer fragmentation entropy captures cell-type specific signals and, when measured at cancer-specific enhancers in cfDNA, could serve as a promising biomarker for cancer detection and monitoring. Ongoing work is focused on validating these findings in larger cohorts and applying EFE to cancer monitoring and clinical subtyping. Citation Format: Alexis Yang. Inferring enhancer activity from cell-free DNA fragmentation patterns [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B068.

Clinical functional proteomics of intercellular signalling in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) has an atypical, highly stromal tumour microenvironment (TME) that profoundly contributes to its poor prognosis1. Here, to better understand the intercellular signalling between cancer and stromal cells directly in PDAC tumours, we developed a multidimensional proteomic strategy called TMEPro. We appliedTMEPro to profile the glycosylated secreted and plasma membrane proteome of 100 human pancreatic tissue samples to a great depth, define cell type origins and identify potential paracrine cross-talk, especially that mediated through tyrosine phosphorylation. Temporal dynamics during pancreatic tumour progression were investigated in a genetically engineered PDAC mouse model. Functionally, we revealed reciprocal signalling between stromal cells and cancer cells mediated by the stromal PDGFR-PTPN11-FOS signalling axis. Furthermore, we examined the generic shedding mechanism of plasma membrane proteins in PDAC tumours and revealed that matrix-metalloprotease-mediated shedding of the AXL receptor tyrosine kinase ectodomain provides an additional dimension of intercellular signalling regulation in the PDAC TME. Importantly, the level of shed AXL has a potential correlation with lymph node metastasis, and inhibition of AXL shedding and its kinase activity showed a substantial synergistic effect in inhibiting cancer cell growth. In summary, we provide TMEPro, a generically applicable clinical functional proteomic strategy, and a comprehensive resource for better understanding the PDAC TME and facilitating the discovery of new diagnostic and therapeutic targets.

Abstract 4142799: Central role of LIM domain binding 3 (LDB3) protein in Tetralogy of Fallot assessed by single-nuclei multiome profiling of paediatric right ventricular samples

Background and aims: Tetralogy of Fallot (TOF; EC: 1565/2019) is the most common cyanotic congenital heart defect with a world-wide incidence of 0.02–0.04%. The pathophysiological mechanisms driven by variable genetic background are poorly understood. We applied the single-nuclei multiome profiling, composed of ATAC and RNA-seq from the same nuclei, of right ventricular samples of children with TOF. The final aim was to define cell types and characterize gene regulation states in different cell clusters including activation and maturation. Methods: Right ventricular samples were prospectively gathered during routinely performed cardiac surgery for TOF correction (EC: 1565/2019). In total, six paediatric patient samples were processed, and on average ~1,500 nuclei were sequenced per sample. Data was analysed using Scanpy to cluster and annotate cells, pycisTopic to identify cell stats and cis-regulatory topics, and SCENIC+ for enhancer-driven gene Regulatory network (eRegulon) construction. Results: Through manual annotation, using published markers, we identified cell types including cardiomyocyte, fibroblast, endothelial, pericyte, immune and neuronal cells. From this, we observed cell type specific expression, with overexpression of decorin in fibroblasts, PTPRC in immune cells, and neurexin genes in neuronal cells found. Differential expression analysis highlighted patient specific patterns of expression, of which gene set enrichment showed enrichment for genes associated with actomyosin structure organisation, dilated cardiomyopathy and cardiac muscle contraction. Integration of the gene expression data with the ATAC-seq data, across all patients, allowed for the construction of eRegulons networks. In detail, in the cardiomyocyte-annotated clusters, we identified enrichment of MEF2, MEIS2 and EPAS1 family enhancers with a central role of LIM domain binding 3 protein (LDB3, associated with cytoskeletal actin and muscle alpha-actin binding) (Fig. 1). Conclusion: Single nuclei multiome profiling of paediatric right ventricular TOF samples identified several patient specific patterns of expression and regulatory networks, related to the development of cyanotic congenital heart disease, and sheds light to the potential drivers of TOF.

Disease models of Leigh syndrome: From yeast to organoids.

Leigh syndrome (LS) is a severe mitochondrial disease that results from mutations in the nuclear or mitochondrial DNA that impairs cellular respiration and ATP production. Mutations in more than 100 genes have been demonstrated to cause LS. The disease most commonly affects brain development and function, resulting in cognitive and motor impairment. The underlying pathogenesis is challenging to ascertain due to the diverse range of symptoms exhibited by affected individuals and the variability in prognosis. To understand the disease mechanisms of different LS-causing mutations and to find a suitable treatment, several different model systems have been developed over the last 30 years. This review summarizes the established disease models of LS and their key findings. Smaller organisms such as yeast have been used to study the biochemical properties of causative mutations. Drosophila melanogaster, Danio rerio, and Caenorhabditis elegans have been used to dissect the pathophysiology of the neurological and motor symptoms of LS. Mammalian models, including the widely used Ndufs4 knockout mouse model of complex I deficiency, have been used to study the developmental, cognitive, and motor functions associated with the disease. Finally, cellular models of LS range from immortalized cell lines and trans-mitochondrial cybrids to more recent model systems such as patient-derived induced pluripotent stem cells (iPSCs). In particular, iPSCs now allow studying the effects of LS mutations in specialized human cells, including neurons, cardiomyocytes, and even three-dimensional organoids. These latter models open the possibility of developing high-throughput drug screens and personalized treatments based on defined disease characteristics captured in the context of a defined cell type. By analyzing all these different model systems, this review aims to provide an overview of past and present means to elucidate the complex pathology of LS. We conclude that each approach is valid for answering specific research questions regarding LS, and that their complementary use could be instrumental in finding treatment solutions for this severe and currently untreatable disease.

Neuromodulator and neuropeptide sensors and probes for precise circuit interrogation in vivo.

To determine how neuronal circuits encode and drive behavior, it is often necessary to measure and manipulate different aspects of neurochemical signaling in awake animals. Optogenetics and calcium sensors have paved the way for these types of studies, allowing for the perturbation and readout of spiking activity within genetically defined cell types. However, these methods lack the ability to further disentangle the roles of individual neuromodulator and neuropeptides on circuits and behavior. We review recent advances in chemical biology tools that enable precise spatiotemporal monitoring and control over individual neuroeffectors and their receptors in vivo. We also highlight discoveries enabled by such tools, revealing how these molecules signal across different timescales to drive learning, orchestrate behavioral changes, and modulate circuit activity.

An integrated single-cell reference atlas of the human endometrium

The complex and dynamic cellular composition of the human endometrium remains poorly understood. Previous endometrial single-cell atlases profiled few donors and lacked consensus in defining cell types. We introduce the Human Endometrial Cell Atlas (HECA), a high-resolution single-cell reference atlas (313,527 cells) combining published and new endometrial single-cell transcriptomics datasets of 63 women with and without endometriosis. HECA assigns consensus and identifies previously unreported cell types, mapped in situ using spatial transcriptomics and validated using a new independent single-nuclei dataset (312,246 nuclei, 63 donors). In the functionalis, we identify intricate stromal–epithelial cell coordination via transforming growth factor beta (TGFβ) signaling. In the basalis, we define signaling between fibroblasts and an epithelial population expressing progenitor markers. Integration of HECA with large-scale endometriosis genome-wide association study data pinpoints decidualized stromal cells and macrophages as most likely dysregulated in endometriosis. The HECA is a valuable resource for studying endometrial physiology and disorders, and for guiding microphysiological in vitro systems development.

High-throughput analysis of dendrite and axonal arbors reveals transcriptomic correlates of neuroanatomy

Neuronal anatomy is central to the organization and function of brain cell types. However, anatomical variability within apparently homogeneous populations of cells can obscure such insights. Here, we report large-scale automation of neuronal morphology reconstruction and analysis on a dataset of 813 inhibitory neurons characterized using the Patch-seq method, which enables measurement of multiple properties from individual neurons, including local morphology and transcriptional signature. We demonstrate that these automated reconstructions can be used in the same manner as manual reconstructions to understand the relationship between some, but not all, cellular properties used to define cell types. We uncover gene expression correlates of laminar innervation on multiple transcriptomically defined neuronal subclasses and types. In particular, our results reveal correlates of the variability in Layer 1 (L1) axonal innervation in a transcriptomically defined subpopulation of Martinotti cells in the adult mouse neocortex.

Soybean symbiotic-nodule zonation and cell differentiation are defined by NIN2 signaling and GH3-dependent auxin homeostasis

Symbiotic nodules comprise two classes, indeterminate and determinate, defined by the presence/absence of apical meristem and developmental zonation. Why meristem and zonation are absent from determinate nodules remains unclear. Here, we define cell types in developing soybean nodules, highlighting the undifferentiated infection zones and differentiated nitrogen-fixation zones. Auxin governs infection zone maintenance. GRETCHEN HAGEN 3 (GH3) enzymes deactivate auxin by conjugation and promote cell differentiation. gh3 mutants increased undifferentiated cells and enlarged infection zones. The central symbiosis-transcription factor NIN2a activates GH3.1 to reduce auxin levels and facilitates cell differentiation. High auxin promotes NIN2a protein accumulation and enhances signaling, further deactivating auxin and depleting infection zones. Our findings shed light on the NIN2a-GH3-auxin module that drives soybean nodule cell differentiation. This study challenges our understanding of determinate nodule development and proposes that the regulation of nodule zonation offers valuable insights into broader mechanisms of cell differentiation across plant species.

Cellular and circuit architecture of the lateral septum for reward processing

The lateral septum (LS) is composed of heterogeneous cell types that are important for various motivated behaviors. However, the transcriptional profiles, spatial arrangement, function, and connectivity of these cell types have not been systematically studied. Using single-nucleus RNA sequencing, we delineated diverse genetically defined cell types in the LS that play distinct roles in reward processing. Notably, we found that estrogen receptor 1 (Esr1)-expressing neurons in the ventral LS (LSEsr1) are key drivers of reward seeking via projections to the ventral tegmental area, and these neurons play an essential role in methamphetamine (METH) reward and METH-seeking behavior. Extended exposure to METH increases the excitability of LSEsr1 neurons by upregulating hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, thereby contributing to METH-induced locomotor sensitization. These insights not only elucidate the intricate molecular, circuit, and functional architecture of the septal region in reward processing but also reveal a neural pathway critical for METH reward and behavioral sensitization.

A Cocaine-Activated Ensemble Exerts Increased Control Over Behavior While Decreasing in Size

BackgroundSubstance use disorder is characterized by long-lasting changes in reward-related brain regions, such as the nucleus accumbens. Previous work has shown that cocaine exposure induces plasticity in broad, genetically defined cell types in the nucleus accumbens; however, in response to a stimulus, only a small percentage of neurons are transcriptionally active—termed an ensemble. Here, we identify an Arc-expressing neuronal ensemble that has a unique trajectory of recruitment and causally controls drug self-administration after repeated, but not acute, cocaine exposure. MethodsUsing Arc-CreERT2 transgenic mice, we expressed transgenes in Arc+ ensembles activated by cocaine exposure (either acute [1 × 10 mg/kg intraperitoneally] or repeated [10 × 10 mg/kg intraperitoneally]). Using genetic, optical, and physiological recording and manipulation strategies, we assessed the contribution of these ensembles to behaviors associated with substance use disorder. ResultsRepeated cocaine exposure reduced the size of the ensemble while simultaneously increasing its control over behavior. Neurons within the repeated cocaine ensemble were hyperexcitable, and their optogenetic excitation was sufficient for reinforcement. Finally, lesioning the repeated cocaine, but not the acute cocaine, ensemble blunted cocaine self-administration. Thus, repeated cocaine exposure reduced the size of the ensemble while simultaneously increasing its contributions to drug reinforcement. ConclusionsWe showed that repeated, but not acute, cocaine exposure induced a physiologically distinct ensemble characterized by the expression of the immediate early gene Arc, which was uniquely capable of modulating reinforcement behavior.

Single‐cell RNA sequencing in pediatric research: Focusing on differentiation trajectories and immune microenvironment of neuroblastoma

AbstractRecently, single‐cell RNA sequencing (scRNA‐seq) has emerged as a novel and high‐resolution technique for identifying cell types, states, and subpopulations. This technique enables researchers to uncover cellular heterogeneity and detect rare cell populations that might be indistinguishable in bulk RNA‐seq data. The primary aim of scRNA‐seq analysis is to investigate cellular heterogeneity and distinguish distinct cell types or states. scRNA‐seq provides a detailed understanding of intercellular differences and diversity by obtaining gene expression data for each individual cell. Moreover, clustering methods in scRNA‐seq can be used to group cells bring into subpopulations based on their gene expression patterns, thereby uncovering similarities and differences that assist in identifying and defining cell types. Newly discovered cell types can be validated and named by labeling known cell marker genes. Additionally, scRNA‐seq helps in identifying genes specifically expressed at different developmental stages, in various tissue types, or under various disease states. Recently, there has been a growing trend in using single‐cell transcriptome sequencing technology for neuroblastoma (NB) research. Through conducting a comprehensive review of relevant articles published thus far, our understanding of NB has been significantly enriched from three critical perspectives: differentiation trajectory, tumor heterogeneity, and immune microenvironment. Firstly, in exploring the differentiation trajectory of NB, we have summarized the tumor's origin and subsequent directions of differentiation. By elucidating a complete tumor differentiation pathway, we can enhance our understanding of the mechanisms underlying spontaneous tumor regression. Secondly, we have summarized the heterogeneity of tumors, which encompasses different states, cell morphologies, and characteristic genes of NB identified through single‐cell sequencing technology. This consolidation of knowledge enhances our understanding of the heterogeneity of NB. Lastly, we have employed single‐cell sequencing technology to analyze the immune microenvironment, focusing on the cellular components within the tumor's surrounding environment and the diverse states of immune cells. This valuable information contributes to the advancement of NB diagnosis, treatment, and prognosis. In conclusion, the application of single‐cell sequencing technology in NB research has significantly advanced our understanding of the disease and carries great significance.

A spatial transcriptome map of the developing maize ear.

A comprehensive understanding of inflorescence development is crucial for crop genetic improvement, as inflorescence meristems give rise to reproductive organs and determine grain yield. However, dissecting inflorescence development at the cellular level has been challenging owing to a lack of specific marker genes to distinguish among cell types, particularly in different types of meristems that are vital for organ formation. In this study, we used spatial enhanced resolution omics-sequencing (Stereo-seq) to construct a precise spatial transcriptome map of the developing maize ear primordium, identifying 12 cell types, including 4 newly defined cell types found mainly in the inflorescence meristem. By extracting the meristem components for detailed clustering, we identified three subtypes of meristem and validated two MADS-box genes that were specifically expressed at the apex of determinate meristems and involved in stem cell determinacy. Furthermore, by integrating single-cell RNA transcriptomes, we identified a series of spatially specific networks and hub genes that may provide new insights into the formation of different tissues. In summary, this study provides a valuable resource for research on cereal inflorescence development, offering new clues for yield improvement.

Age-related upregulation of dense core vesicles in the central inferior colliculus.

Presbycusis is one of the most prevalent disabilities in aged populations of industrialized countries. As we age less excitation reaches the central auditory system from the periphery. To compensate, the central auditory system [e.g., the inferior colliculus (IC)], downregulates GABAergic inhibition to maintain homeostatic balance. However, the continued downregulation of GABA in the IC causes a disruption in temporal precision related to presbycusis. Many studies of age-related changes to neurotransmission in the IC have therefore focused on GABAergic systems. However, we have discovered that dense core vesicles (DCVs) are significantly upregulated with age in the IC. DCVs can carry neuropeptides, co-transmitters, neurotrophic factors, and proteins destined for the presynaptic zone to participate in synaptogenesis. We used immuno transmission electron microscopy across four age groups (3-month; 19-month; 24-month; and 28-month) of Fisher Brown Norway rats to examine the ultrastructure of DCVs in the IC. Tissue was stained post-embedding for GABA immunoreactivity. DCVs were characterized by diameter and by the neurochemical profile (GABAergic/non-GABAergic) of their location (bouton, axon, soma, and dendrite). Our data was collected across the dorsolateral to ventromedial axis of the central IC. After quantification, we had three primary findings. First, the age-related increase of DCVs occurred most robustly in non-GABAergic dendrites in the middle and low frequency regions of the central IC during middle age. Second, the likelihood of a bouton having more than one DCV increased with age. Lastly, although there was an age-related loss of terminals throughout the IC, the proportion of terminals that contained at least one DCV did not decline. We interpret this finding to mean that terminals carrying proteins packaged in DCVs are spared with age. Several recent studies have demonstrated a role for neuropeptides in the IC in defining cell types and regulating inhibitory and excitatory neurotransmission. Given the age-related increase of DCVs in the IC, it will be critical that future studies determine whether (1) specific neuropeptides are altered with age in the IC and (2) if these neuropeptides contribute to the loss of inhibition and/or increase of excitability that occurs during presbycusis and tinnitus.

Abstract 4946: ssTimiGP: Equip the TimiGP system with a single-sample module, facilitating the cell-cell interaction inference of the tumor microenvironment in any sample

Abstract Understanding the tumor microenvironment (TME) is essential in cancer treatment and risk assessment. While single-cell RNA-seq (scRNA-seq) offers in-depth insights into the TME, its expensive cost results in limited data sets and size. In contrast, microarray and RNA-seq provide rich datasets from larger cohorts, but they yield bulk data with lower resolution. To leverage the strengths of both approaches and comprehensively study the TME, we developed the computational framework TimiGP (Tumor Immune Microenvironment Illustration through Gene Pairs). It is inspired by the dynamic balance of the immune system and extended to the entire TME. TimiGP utilizes scRNA-seq to define cell type of interest, and bulk transcriptomic profiles to deduce clinically relevant cell-cell interaction networks and cell functions. Our recent release includes both prognosis and response modules to study the association between TME and the corresponding clinical outcomes. However, their applicability is constrained by the necessity for paired clinical information. In response to this limitation, we present a significant enhancement, a single sample module slightly modified from the TimiGP framework (ssTimiGP). This upgraded version enables TME analysis in any individual sample, requiring only bulk RNA-seq data and cell-type markers. It exports a cell-cell interaction network representing the relative expression of functional markers and the abundance of cells. This optimization expands the utility of TimiGP, making it more accessible across diverse samples and species. We have further expanded the application of ssTimiGP from solid tumors to liquid samples (e.g., peripheral blood). To validate its performance, we conducted a comparative analysis between the interactions of eight immune cell types observed in experimental results using FACS and the computational results derived from ssTimiGP based on paired RNA-seq data. As a result, ssTimiGP not only successfully identified interactions between different cell types that exhibited a significant correlation with experimental findings (e.g., CD4+ naïve T cells → Monocyte, R=0.75, p< 0.001, accuracy = 0.8), but also demonstrated its capability to achieve higher resolution in capturing interactions between immune cell subpopulations (e.g., CD4 naïve T cells → activated CD4+ memory T cells, R=0.57, p=0.008, accuracy = 1.0). In our benchmark analysis, ssTimiGP demonstrated superior performance compared to CIBERSORTx (e.g., CD4+ naïve T cells → Monocyte, R=0, Accuracy=0.3). In summary, ssTimiGP signifies an expansion of the TimiGP system, enabling the inference of the TME in individual solid tumors and liquid samples at various resolutions by integrating the strengths of both scRNA-seq and bulk RNA-seq. This approach offers substantial potential for advancing personalized cancer treatment. Citation Format: Chenyang Li, Jianjun Zhang, Chao Cheng. ssTimiGP: Equip the TimiGP system with a single-sample module, facilitating the cell-cell interaction inference of the tumor microenvironment in any sample [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4946.

Dopamine Receptor-Expressing Neurons Are Differently Distributed throughout Layers of the Motor Cortex to Control Dexterity.

The motor cortex comprises the primary descending circuits for flexible control of voluntary movements and is critically involved in motor skill learning. Motor skill learning is impaired in patients with Parkinson's disease, but the precise mechanisms of motor control and skill learning are still not well understood. Here we have used transgenic mice, electrophysiology, in situ hybridization, and neural tract-tracing methods to target genetically defined cell types expressing D1 and D2 dopamine receptors in the motor cortex. We observed that putative D1 and D2 dopamine receptor-expressing neurons (D1+ and D2+, respectively) are organized in highly segregated, nonoverlapping populations. Moreover, based on ex vivo patch-clamp recordings, we showed that D1+ and D2+ cells have distinct morphological and electrophysiological properties. Finally, we observed that chemogenetic inhibition of D2+, but not D1+, neurons disrupts skilled forelimb reaching in adult mice. Overall, these results demonstrate that dopamine receptor-expressing cells in the motor cortex are highly segregated and play a specialized role in manual dexterity.

A transfer learning framework to elucidate the clinical relevance of altered proximal tubule cell states in kidney disease

The application of single-cell technologies in clinical nephrology remains elusive. We generated an atlas of transcriptionally defined cell types and cell states of human kidney disease by integrating single-cell signatures reported in the literature with newly generated signatures obtained from 5 patients with acute kidney injury. We used this information to develop kidney-specific cell-level information ExtractoR (K-CLIER), a transfer learning approach specifically tailored to evaluate the role of cell types/states on bulk RNAseq data. We validated the K-CLIER as a reliable computational framework to obtain a dimensionality reduction and to link clinical data with single-cell signatures. By applying K-CLIER on cohorts of patients with different kidney diseases, we identified the most relevant cell types associated with fibrosis and disease progression. This analysis highlighted the central role of altered proximal tubule cells in chronic kidney disease. Our study introduces a new strategy to exploit the power of single-cell technologies toward clinical applications.

Molecular diversity and functional dynamics in the central amygdala.

The central amygdala (CeA) is crucial in integrating sensory and associative information to mediate adaptive responses to emotional stimuli. Recent advances in genetic techniques like optogenetics and chemogenetics have deepened our understanding of distinct neuronal populations within the CeA, particularly those involved in fear learning and memory consolidation. However, challenges remain due to overlapping genetic markers complicating neuron identification. Furthermore, a comprehensive understanding of molecularly defined cell types and their projection patterns, which are essential for elucidating functional roles, is still developing. Recent advancements in transcriptomics are starting to bridge these gaps, offering new insights into the functional dynamics of CeA neurons. In this review, we provide an overview of the expanding genetic markers for amygdala research, encompassing recent developments and current trends. We also discuss how novel transcriptomic approaches are redefining cell types in the CeA and setting the stage for comprehensive functional studies.

Neuropeptidomics of Genetically Defined Cell Types in Mouse Brain.

Peptidomic techniques are powerful tools to identify peptides in a biological sample. In the case of brain, which contains a complex mixture of cell types, standard peptidomics procedures reveal the major peptides in a dissected brain region. It is difficult to obtain information on peptides within a specific cell type using standard approaches, unless that cell type can be isolated. This protocol describes a targeted peptidomic approach that uses affinity chromatography to purify peptides that are substrates of carboxypeptidase E (CPE), an enzyme present in the secretory pathway of neuroendocrine cells. Many CPE products function as neuropeptides and/or peptide hormones, and therefore represent an important subset of the peptidome. Because CPE removes C-terminal Lys and Arg residues from peptide processing intermediates, organisms lacking CPE show a large decrease in the levels of the mature forms of most neuropeptides and peptide hormones, and a very large increase in the levels of the processing intermediates that contain C-terminal Lys and/or Arg (i.e., the CPE substrates). These CPE substrates can be purified on an anhydrotrypsin-agarose affinity resin, which specifically binds peptides with C-terminal basic residues. When this method is used with mice lacking CPE activity in genetically defined cell types, it allows the detection of peptides specifically produced in that cell type.

Molecularly defined and spatially resolved cell atlas of the whole mouse brain

In mammalian brains, millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells have impeded our understanding of the molecular and cellular basis of brain function. Recent advances in spatially resolved single-cell transcriptomics have enabled systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1–3, including several brain regions (for example, refs. 1–11). However, a comprehensive cell atlas of the whole brain is still missing. Here we imaged a panel of more than 1,100 genes in approximately 10 million cells across the entire adult mouse brains using multiplexed error-robust fluorescence in situ hybridization12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating multiplexed error-robust fluorescence in situ hybridization and single-cell RNA sequencing data. Using this approach, we generated a comprehensive cell atlas of more than 5,000 transcriptionally distinct cell clusters, belonging to more than 300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of this atlas to the mouse brain common coordinate framework allowed systematic quantifications of the cell-type composition and organization in individual brain regions. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes of cells. Finally, this high-resolution spatial map of cells, each with a transcriptome-wide expression profile, allowed us to infer cell-type-specific interactions between hundreds of cell-type pairs and predict molecular (ligand–receptor) basis and functional implications of these cell–cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a foundation for functional investigations of neural circuits and their dysfunction in health and disease.

N/KRAS-Mutant AML LSCs Originate from Committed Myelomonocytic Progenitors and Drive Clinical Resistance to Venetoclax

Driver mutations in acute myeloid leukemia (AML) often exhibit distinct temporal acquisition patterns, but the biological basis for this, if any, remains unknown. RAS mutations occur invariably late in AML, upon progression or relapsed/refractory disease, in contrast to their function as early drivers in solid tumors. We developed synthetic leukemogenesis models in human induced pluripotent stem cell (iPSC)- and primary cord blood (CB)-derived human hematopoietic stem/progenitor cells (HSPCs) by introducing the prototypical NRAS G12D mutation alone or with other mutational combinations, using CRISPR, and engraftment of a transplantable leukemia into NSG mice as the readout. RAS mutations alone were not sufficient for leukemogenesis, but required specific cooperating mutations. Subsequently, by creating temporally controlled engineered models, we found that RAS mutations are obligatory late events that can only drive leukemic transformation when acquired after, but not before, cooperating mutations. We provide the mechanistic explanation for this in a requirement for mutant RAS to specifically transform committed granulocyte-monocyte progenitors (GMPs) harboring previously acquired driver mutations, through sorting and transplantation and multi-omics experiments. In contrast, acquisition of RAS mutations in earlier progenitors (common myeloid progenitors, CMP), with or without cooperating mutations, blocked the emergence of GMPs and abolished engraftment or gave rise to a myeloproliferative neoplasm. These results indicate that advanced RAS-mutant (MT) leukemic clones have a different cell type of origin from the ancestral clone. Next, using single-cell transcriptomics in cells isolated from xenografts of two AML-iPSC lines generated from an AML patient with a subclonal KRAS G12D mutation, one capturing the RAS WT major clone and one the KRAS G12D subclone, we show that KRAS G12D leukemia stem cells (LSCs) give rise to leukemia with a more monocytic immunophenotype, while the ancestral clone within the same patient generates more leukemic cells with primitive and neutrophil markers. These results were corroborated by Genotyping of Transcriptomes (GoT) in another AML patient with subclonal NRAS G12D mutation. Recent studies have linked monocytic AML and, independently, RAS pathway mutations to poor responses to Venetoclax (VEN)-containing regiments. In view of the causal link we found between RAS mutations and monocytic disease, we evaluated the associations between monocytic AML, RAS mutations and response to VEN. We reanalyzed data from a cohort of 118 older/unfit newly diagnosed AML patients treated on a prospective clinical trial with VEN and decitabine (DEC) (NCT03404193). All outcomes were comparable between monocytic and non-monocytic groups, including overall response rate, duration of response (DOR) and overall survival. On the other hand, patients with N/KRAS mutations had significantly shorter DOR. These results support the presence of N/KRAS mutations and not the monocytic stage as predictors of inferior responses to VEN regimens. To definitely test this, we treated defined cell types generated from RAS WT and RAS MT iPSC lines - CD34+ LSC-like and CD11b+/CD68+/CD14+ monocytic cells - with VEN. In agreement with previous studies, monocytes were resistant and RAS WT LSCs were sensitive to VEN. However, strikingly RAS MT LSCs were VEN-resistant. Consistent with these, single-cell transcriptomics in patient-derived AML-iPSC cells in vivo, GoT in primary AML cells and bulk transcriptomics in synthetic iPSC-AML cells showed downregulation of BCL2 and upregulation of MCL1 in the RAS MT LSCs. This study provides the first example of a mechanistic explanation of why the timing of mutational acquisition in AML is so strongly biased. It shows for the first time that interaction between an oncogenic driver and the non-genetic developmental hematopoietic hierarchy imposes a specific LSC cell-of-origin restriction and in turn shapes the hierarchical structure of the resulting AML and critically determines therapeutic outcomes in patients. Importantly, our results have direct implications for clinical practice, as they support that RAS MT LSCs drive clinical resistance to VEN and that treatment with VEN in patients with RAS mutations can accelerate disease progression by selection of RAS MT LSCs (Figure).