Single-cell, single-nucleus, and spatial transcriptomics characterization of the immunological landscape in the healthy and PSC human liver

BACKGROUND & AIMS

Primary sclerosing cholangitis (PSC) is an immune-mediated cholestatic liver disease for which there is an unmet need to understand the cellular composition of the affected liver and how it underlies disease pathogenesis. We aimed to generate a comprehensive atlas of the PSC liver using multi-omic modalities and protein-based functional validation.

METHODS

We employed single-cell and single-nucleus RNA sequencing (47,156 cells and 23,000 nuclei) and spatial transcriptomics (one sample by 10x Visium and five samples with Nanostring GeoMx DSP) to profile the cellular ecosystem in 10 PSC livers. Transcriptomic profiles were compared to 24 neurologically deceased donor livers (107,542 cells) and spatial transcriptomics controls, as well as 18,240 cells and 20,202 nuclei from three PBC livers. Flow cytometry was performed to validate PSC-specific differences in immune cell phenotype and function.

RESULTS

PSC explants with parenchymal cirrhosis and prominent periductal fibrosis contained a population of cholangiocyte-like hepatocytes that were surrounded by diverse immune cell populations. PSC-associated biliary, mesenchymal, and endothelial populations expressed chemokine and cytokine transcripts involved in immune cell recruitment. Additionally, expanded CD4+ T cells and recruited myeloid populations in the PSC liver expressed the corresponding receptors to these chemokines and cytokines, suggesting potential recruitment. Tissue-resident macrophages, by contrast, were reduced in number and exhibited a dysfunctional and downregulated inflammatory response to lipopolysaccharide and interferon-γ stimulation.

CONCLUSIONS

We present a comprehensive atlas of the PSC liver and demonstrate an exhaustion-like phenotype of myeloid cells and markers of chronic cytokine expression in late-stage PSC lesions. This atlas expands our understanding of the cellular complexity of PSC and has potential to guide the development of novel treatments.

IMPACT AND IMPLICATIONS

Primary sclerosing cholangitis (PSC) is a rare liver disease characterized by chronic inflammation and irreparable damage to the bile ducts, which eventually results in liver failure. Due to a limited understanding of the underlying pathogenesis of disease, treatment options are limited. To address this, we sequenced healthy and diseased livers to compare the activity, interactions, and localization of immune and non-immune cells. This revealed that hepatocytes lining PSC scar regions co-express cholangiocyte markers, whereas immune cells infiltrate the scar lesions. Of these cells, macrophages, which typically contribute to tissue repair, were enriched in immunoregulatory genes and demonstrated a lack of responsiveness to stimulation. These cells may be involved in maintaining hepatic inflammation and could be a target for novel therapies.

The multimodality cell segmentation challenge: toward universal solutions

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multimodality cell segmentation benchmark, comprising more than 1,500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging.

Integrated transcriptomics uncovers an enhanced association between the prion protein gene expression and vesicle dynamics signatures in glioblastomas

BACKGROUND

Glioblastoma (GBM) is an aggressive brain tumor that exhibits resistance to current treatment, making the identification of novel therapeutic targets essential. In this context, cellular prion protein (PrPC) stands out as a potential candidate for new therapies. Encoded by the PRNP gene, PrPC can present increased expression levels in GBM, impacting cell proliferation, growth, migration, invasion and stemness. Nevertheless, the exact molecular mechanisms through which PRNP/PrPC modulates key aspects of GBM biology remain elusive.

METHODS

To elucidate the implications of PRNP/PrPC in the biology of this cancer, we analyzed publicly available RNA sequencing (RNA-seq) data of patient-derived GBMs from four independent studies. First, we ranked samples profiled by bulk RNA-seq as PRNPhigh and PRNPlow and compared their transcriptomic landscape. Then, we analyzed PRNP+ and PRNP- GBM cells profiled by single-cell RNA-seq to further understand the molecular context within which PRNP/PrPC might function in this tumor. We explored an additional proteomics dataset, applying similar comparative approaches, to corroborate our findings.

RESULTS

Functional profiling revealed that vesicular dynamics signatures are strongly correlated with PRNP/PrPC levels in GBM. We found a panel of 73 genes, enriched in vesicle-related pathways, whose expression levels are increased in PRNPhigh/PRNP+ cells across all RNA-seq datasets. Vesicle-associated genes, ANXA1, RAB31, DSTN and SYPL1, were found to be upregulated in vitro in an in-house collection of patient-derived GBM. Moreover, proteome analysis of patient-derived samples reinforces the findings of enhanced vesicle biogenesis, processing and trafficking in PRNPhigh/PRNP+ GBM cells.

CONCLUSIONS

Together, our findings shed light on a novel role for PrPC as a potential modulator of vesicle biology in GBM, which is pivotal for intercellular communication and cancer maintenance. We also introduce GBMdiscovery, a novel user-friendly tool that allows the investigation of specific genes in GBM biology.

Metformin reduces the clonal fitness of Dnmt3aR878H hematopoietic stem and progenitor cells by reversing their aberrant metabolic and epigenetic state

Clonal hematopoiesis (CH) arises when a hematopoietic stem cell (HSC) acquires a mutation that confers a competitive advantage over wild-type (WT) HSCs, resulting in its clonal expansion. Individuals with CH are at an increased risk of developing hematologic neoplasms and a range of age-related inflammatory illnesses1-3. Therapeutic interventions that suppress the expansion of mutant HSCs have the potential to prevent these CH-related illnesses; however, such interventions have not yet been identified. The most common CH driver mutations are in the DNA methyltransferase 3 alpha (DNMT3A) gene with arginine 882 (R882) being a mutation hotspot. Here we show that murine hematopoietic stem and progenitor cells (HSPCs) carrying the Dnmt3aR878H/+ mutation, which is equivalent to human DNMT3AR882H/+, have increased mitochondrial respiration compared with WT cells and are dependent on this metabolic reprogramming for their competitive advantage. Importantly, treatment with metformin, an oral anti-diabetic drug with inhibitory activity against complex I in the electron transport chain (ETC), reduced the fitness of Dnmt3aR878H/+ HSCs. Through a multi-omics approach, we discovered that metformin acts by enhancing the methylation potential in Dnmt3aR878H/+ HSPCs and reversing their aberrant DNA CpG methylation and histone H3K27 trimethylation (H3K27me3) profiles. Metformin also reduced the fitness of human DNMT3AR882H HSPCs generated by prime editing. Our findings provide preclinical rationale for investigating metformin as a preventive intervention against illnesses associated with DNMT3AR882 mutation-driven CH in humans.

Single-nucleus multiomic atlas of frontal cortex in amyotrophic lateral sclerosis with a deep learning-based decoding of alternative polyadenylation mechanisms

The understanding of how different cell types contribute to amyotrophic lateral sclerosis (ALS) pathogenesis is limited. Here we generated a single-nucleus transcriptomic and epigenomic atlas of the frontal cortex of ALS cases with C9orf72 (C9) hexanucleotide repeat expansions and sporadic ALS (sALS). Our findings reveal shared pathways in C9-ALS and sALS, characterized by synaptic dysfunction in excitatory neurons and a disease-associated state in microglia. The disease subtypes diverge with loss of astrocyte homeostasis in C9-ALS, and a more substantial disturbance of inhibitory neurons in sALS. Leveraging high depth 3'-end sequencing, we found a widespread switch towards distal polyadenylation (PA) site usage across ALS subtypes relative to controls. To explore this differential alternative PA (APA), we developed APA-Net, a deep neural network model that uses transcript sequence and expression levels of RNA-binding proteins (RBPs) to predict cell-type specific APA usage and RBP interactions likely to regulate APA across disease subtypes.

Adversarial training improves model interpretability in single-cell RNA-seq analysis

Motivation

Predictive computational models must be accurate, robust, and interpretable to be considered reliable in important areas such as biology and medicine. A sufficiently robust model should not have its output affected significantly by a slight change in the input. Also, these models should be able to explain how a decision is made to support user trust in the results. Efforts have been made to improve the robustness and interpretability of predictive computational models independently; however, the interaction of robustness and interpretability is poorly understood.

Results

As an example task, we explore the computational prediction of cell type based on single-cell RNA-seq data and show that it can be made more robust by adversarially training a deep learning model. Surprisingly, we find this also leads to improved model interpretability, as measured by identifying genes important for classification using a range of standard interpretability methods. Our results suggest that adversarial training may be generally useful to improve deep learning robustness and interpretability and that it should be evaluated on a range of tasks.

Availability and implementation

Our Python implementation of all analysis in this publication can be found at: https://github.com/MehrshadSD/robustness-interpretability. The analysis was conducted using numPy 0.2.5, pandas 2.0.3, scanpy 1.9.3, tensorflow 2.10.0, matplotlib 3.7.1, seaborn 0.12.2, sklearn 1.1.1, shap 0.42.0, lime 0.2.0.1, matplotlib_venn 0.11.9.

A rat liver cell atlas reveals intrahepatic myeloid heterogeneity

The large size and vascular accessibility of the laboratory rat (Rattus norvegicus) make it an ideal hepatic animal model for diseases that require surgical manipulation. Often, the disease susceptibility and outcomes of inflammatory pathologies vary significantly between strains. This study uses single-cell transcriptomics to better understand the complex cellular network of the rat liver, as well as to unravel the cellular and molecular sources of inter-strain hepatic variation. We generated single-cell and single-nucleus transcriptomic maps of the livers of healthy Dark Agouti and Lewis rat strains and developed a factor analysis-based bioinformatics analysis pipeline to study data covariates, such as strain and batch. Using this approach, we discovered transcriptomic variation within the hepatocyte and myeloid populations that underlie distinct cell states between rat strains. This finding will help provide a reference for future investigations on strain-dependent outcomes of surgical experiment models.

Fate Specification of GFAP-Negative Primitive Neural Stem Cells and Their Progeny at Clonal Resolution

The mature brain contains an incredible number and diversity of cells that are produced and maintained by heterogeneous pools of neural stem cells (NSCs). Two distinct types of NSCs exist in the developing and adult mouse brain: Glial Fibrillary Acidic Protein (GFAP)-negative primitive (p)NSCs and downstream GFAP-positive definitive (d)NSCs. To better understand the embryonic functions of NSCs, we performed clonal lineage tracing within neurospheres grown from either pNSCs or dNSCs to enrich for their most immediate downstream neural progenitor cells (NPCs). These clonal progenitor lineage tracing data allowed us to construct a hierarchy of progenitor subtypes downstream of pNSCs and dNSCs that were then validated using single-cell transcriptomics. Further, we identify Nexn as required for neuronal specification from neuron/astrocyte progenitor cells downstream of rare pNSCs. Combined, these data provide single-cell resolution of NPC lineages downstream of rare pNSCs that likely would be missed from population-level analyses in vivo.

Cell networks in the mouse liver during partial hepatectomy

In solid tissues homeostasis and regeneration after injury involve a complex interplay between many different cell types. The mammalian liver harbors numerous epithelial and non-epithelial cells and little is known about the global signaling networks that govern their interactions. To better understand the hepatic cell network, we isolated and purified 10 different cell populations from normal and regenerative mouse livers. Their transcriptomes were analyzed by bulk RNA-seq and a computational platform was used to analyze the cell-cell and ligand-receptor interactions among the 10 populations. Over 50,000 potential cell-cell interactions were found in both the ground state and after partial hepatectomy. Importantly, about half of these differed between the two states, indicating massive changes in the cell network during regeneration. Our study provides the first comprehensive database of potential cell-cell interactions in mammalian liver cell homeostasis and regeneration. With the help of this prediction model, we identified and validated two previously unknown signaling interactions involved in accelerating and delaying liver regeneration. Overall, we provide a novel platform for investigating autocrine/paracrine pathways in tissue regeneration, which can be adapted to other complex multicellular systems.

Distinct shared and compartment-enriched oncogenic networks drive primary versus metastatic breast cancer

Metastatic breast-cancer is a major cause of death in women worldwide, yet the relationship between oncogenic drivers that promote metastatic versus primary cancer is still contentious. To elucidate this relationship in treatment-naive animals, we hereby describe mammary-specific transposon-mutagenesis screens in female mice together with loss-of-function Rb, which is frequently inactivated in breast-cancer. We report gene-centric common insertion-sites (gCIS) that are enriched in primary-tumors, in metastases or shared by both compartments. Shared-gCIS comprise a major MET-RAS network, whereas metastasis-gCIS form three additional hubs: Rho-signaling, Ubiquitination and RNA-processing. Pathway analysis of four clinical cohorts with paired primary-tumors and metastases reveals similar organization in human breast-cancer with subtype-specific shared-drivers (e.g. RB1-loss, TP53-loss, high MET, RAS, ER), primary-enriched (EGFR, TGFβ and STAT3) and metastasis-enriched (RHO, PI3K) oncogenic signaling. Inhibitors of RB1-deficiency or MET plus RHO-signaling cooperate to block cell migration and drive tumor cell-death. Thus, targeting shared- and metastasis- but not primary-enriched derivers offers a rational avenue to prevent metastatic breast-cancer.

Drugst.One - A plug-and-play solution for online systems medicine and network-based drug repurposing

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.

Multiplatform molecular profiling uncovers two subgroups of malignant peripheral nerve sheath tumors with distinct therapeutic vulnerabilities

Malignant peripheral nerve sheath tumor (MPNST) is a highly aggressive sarcoma, and a lethal neurofibromatosis type 1-related malignancy, with little progress made on treatment strategies. Here, we apply a multiplatform integrated molecular analysis on 108 tumors spanning the spectrum of peripheral nerve sheath tumors to identify candidate drivers of MPNST that can serve as therapeutic targets. Unsupervised analyses of methylome and transcriptome profiles identify two distinct subgroups of MPNSTs with unique targetable oncogenic programs. We establish two subgroups of MPNSTs: SHH pathway activation in MPNST-G1 and WNT/ß-catenin/CCND1 pathway activation in MPNST-G2. Single nuclei RNA sequencing characterizes the complex cellular architecture and demonstrate that malignant cells from MPNST-G1 and MPNST-G2 have neural crest-like and Schwann cell precursor-like cell characteristics, respectively. Further, in pre-clinical models of MPNST we confirm that inhibiting SHH pathway in MPNST-G1 prevent growth and malignant progression, providing the rational for investigating these treatments in clinical trials.

Multi-scale systems genomics analysis predicts pathways, cell types, and drug targets involved in normative variation in peri-adolescent human cognition

An open challenge in human genetics is to better understand the systems-level impact of genotype variation on developmental cognition. To characterize the genetic underpinnings of peri-adolescent cognition, we performed genotype-phenotype and systems analysis for binarized accuracy in nine cognitive tasks from the Philadelphia Neurodevelopmental Cohort (~2,200 individuals of European continental ancestry aged 8-21 years). We report a region of genome-wide significance within the 3' end of the Fibulin-1 gene (P = 4.6 × 10-8), associated with accuracy in nonverbal reasoning, a heritable form of complex reasoning ability. Diffusion tensor imaging data from a subset of these participants identified a significant association of white matter fractional anisotropy with FBLN1 genotypes (P < 0.025); poor performers show an increase in the C and A allele for rs77601382 and rs5765534, respectively, which is associated with increased fractional anisotropy. Integration of published human brain-specific 'omic maps, including single-cell transcriptomes of the developing human brain, shows that FBLN1 demonstrates greatest expression in the fetal brain, as a marker of intermediate progenitor cells, demonstrates negligible expression in the adolescent and adult human brain, and demonstrates increased expression in the brain in schizophrenia. Collectively these findings warrant further study of this gene and genetic locus in cognition, neurodevelopment, and disease. Separately, genotype-pathway analysis identified an enrichment of variants associated with working memory accuracy in pathways related to development and to autonomic nervous system dysfunction. Top-ranking pathway genes include those genetically associated with diseases with working memory deficits, such as schizophrenia and Parkinson's disease. This work advances the "molecules-to-behavior" view of cognition and provides a framework for using systems-level organization of data for other biomedical domains.

Genotyping SARS-CoV-2 Variants Using Ratiometric Nucleic Acid Barcode Panels

Designing diagnostic assays to genotype rapidly mutating viruses remains a challenge despite the overall improvements in nucleic acid detection technologies. RT-PCR and next-generation sequencing are unsuitable for genotyping during outbreaks or in point-of-care detection due to their infrastructure requirements and longer turnaround times. We developed a quantum dot barcode multiplexing system to genotype mutated viruses. We designed multiple quantum dot barcodes to target conserved, wildtype, and mutated regions of SARS-CoV-2. We calculated ratios of the signal output from different barcodes that enabled SARS-CoV-2 detection and identified SARS-CoV-2 variant strains from a sample. We detected different sequence types, including conserved genes, nucleotide deletions, and single nucleotide substitutions. Our system detected SARS-CoV-2 patient specimens with 98% sensitivity and 94% specificity across 91 patient samples. Further, we leveraged our barcoding and ratio system to track the emergence of the N501Y SARS-CoV-2 mutation from December 2020 to May 2021 and demonstrated that the more transmissible N501Y mutation started to dominate infections by April 2021. Our barcoding and signal ratio approach can genotype viruses and track the emergence of viral mutations in a single diagnostic test. This technology can be extended to tracking other viruses. Combined with smartphone detection technologies, this assay can be adapted for point-of-care tracking of viral mutations in real time.

Cytoscape.js 2023 update: a graph theory library for visualization and analysis

SUMMARY

Cytoscape.js is an open-source JavaScript-based graph library. Its most common use case is as a visualization software component, so it can be used to render interactive graphs in a web browser. It also can be used in a headless manner, useful for graph operations on a server, such as Node.js. This update describes new features and enhancements introduced over many new versions from 2015 to 2022.

AVAILABILITY AND IMPLEMENTATION

Cytoscape.js is implemented in JavaScript. Documentation, downloads and source code are available at http://js.cytoscape.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Single-cell profiling of healthy human kidney reveals features of sex-based transcriptional programs and tissue-specific immunity

Knowledge of the transcriptional programs underpinning the functions of human kidney cell populations at homeostasis is limited. We present a single-cell perspective of healthy human kidney from 19 living donors, with equal contribution from males and females, profiling the transcriptome of 27677 cells to map human kidney at high resolution. Sex-based differences in gene expression within proximal tubular cells were observed, specifically, increased anti-oxidant metallothionein genes in females and aerobic metabolism-related genes in males. Functional differences in metabolism were confirmed in proximal tubular cells, with male cells exhibiting higher oxidative phosphorylation and higher levels of energy precursor metabolites. We identified kidney-specific lymphocyte populations with unique transcriptional profiles indicative of kidney-adapted functions. Significant heterogeneity in myeloid cells was observed, with a MRC1⁺LYVE1⁺FOLR2⁺C1QC⁺ population representing a predominant population in healthy kidney. This study provides a detailed cellular map of healthy human kidney, and explores the complexity of parenchymal and kidney-resident immune cells.

Loss of Epigenetic Regulation Disrupts Lineage Integrity, Induces Aberrant Alveogenesis, and Promotes Breast Cancer

Systematically investigating the scores of genes mutated in cancer and discerning disease drivers from inconsequential bystanders is a prerequisite for precision medicine but remains challenging. Here, we developed a somatic CRISPR/Cas9 mutagenesis screen to study 215 recurrent "long-tail" breast cancer genes, which revealed epigenetic regulation as a major tumor-suppressive mechanism. We report that components of the BAP1 and COMPASS-like complexes, including KMT2C/D, KDM6A, BAP1, and ASXL1/2 ("EpiDrivers"), cooperate with PIK3CAH1047R to transform mouse and human breast epithelial cells. Mechanistically, we find that activation of PIK3CAH1047R and concomitant EpiDriver loss triggered an alveolar-like lineage conversion of basal mammary epithelial cells and accelerated formation of luminal-like tumors, suggesting a basal origin for luminal tumors. EpiDriver mutations are found in ∼39% of human breast cancers, and ∼50% of ductal carcinoma in situ express casein, suggesting that lineage infidelity and alveogenic mimicry may significantly contribute to early steps of breast cancer etiology.

SIGNIFICANCE

Infrequently mutated genes comprise most of the mutational burden in breast tumors but are poorly understood. In vivo CRISPR screening identified functional tumor suppressors that converged on epigenetic regulation. Loss of epigenetic regulators accelerated tumorigenesis and revealed lineage infidelity and aberrant expression of alveogenesis genes as potential early events in tumorigenesis. This article is highlighted in the In This Issue feature, p. 2711.

Neurons and glial cells acquire a senescent signature after repeated mild traumatic brain injury in a sex-dependent manner

Mild traumatic brain injury (mTBI) is an important public health issue, as it can lead to long-term neurological symptoms and risk of neurodegenerative disease. The pathophysiological mechanisms driving this remain unclear, and currently there are no effective therapies for mTBI. In this study on repeated mTBI (rmTBI), we have induced three mild closed-skull injuries or sham procedures, separated by 24 h, in C57BL/6 mice. We show that rmTBI mice have prolonged righting reflexes and astrogliosis, with neurological impairment in the Morris water maze (MWM) and the light dark test. Cortical and hippocampal tissue analysis revealed DNA damage in the form of double-strand breaks, oxidative damage, and R-loops, markers of cellular senescence including p16 and p21, and signaling mediated by the cGAS-STING pathway. This study identified novel sex differences after rmTBI in mice. Although these markers were all increased by rmTBI in both sexes, females had higher levels of DNA damage, lower levels of the senescence protein p16, and lower levels of cGAS-STING signaling proteins compared to their male counterparts. Single-cell RNA sequencing of the male rmTBI mouse brain revealed activation of the DNA damage response, evidence of cellular senescence, and pro-inflammatory markers reminiscent of the senescence-associated secretory phenotype (SASP) in neurons and glial cells. Cell-type specific changes were also present with evidence of brain immune activation, neurotransmission alterations in both excitatory and inhibitory neurons, and vascular dysfunction. Treatment of injured mice with the senolytic drug ABT263 significantly reduced markers of senescence only in males, but was not therapeutic in females. The reduction of senescence by ABT263 in male mice was accompanied by significantly improved performance in the MWM. This study provides compelling evidence that senescence contributes to brain dysfunction after rmTBI, but may do so in a sex-dependent manner.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

Modeling human multi-lineage heart field development with pluripotent stem cells

The cardiomyocyte (CM) subtypes in the mammalian heart derive from distinct lineages known as the first heart field (FHF), the anterior second heart field (aSHF), and the posterior second heart field (pSHF) lineages that are specified during gastrulation. We modeled human heart field development from human pluripotent stem cells (hPSCs) by using single-cell RNA-sequencing to delineate lineage specification and progression. Analyses of hPSC-derived and mouse mesoderm transcriptomes enabled the identification of distinct human FHF, aSHF, and pSHF mesoderm subpopulations. Through staged manipulation of signaling pathways identified from transcriptomics, we generated myocyte populations that display molecular characteristics of key CM subtypes. The developmental trajectory of the human cardiac lineages recapitulated that of the mouse, demonstrating conserved cardiovascular programs. These findings establish a comprehensive landscape of human embryonic cardiogenesis that provides access to a broad spectrum of cardiomyocytes for modeling congenital heart diseases and chamber-specific cardiomyopathies as well as for developing new therapies to treat them.

Unraveling the Complexity of Liver Disease One Cell at a Time

The human liver is a complex organ made up of multiple specialized cell types that carry out key physiological functions. An incomplete understanding of liver biology limits our ability to develop therapeutics to prevent chronic liver diseases, liver cancers, and death as a result of organ failure. Recently, single-cell modalities have expanded our understanding of the cellular phenotypic heterogeneity and intercellular cross-talk in liver health and disease. This review summarizes these findings and looks forward to highlighting new avenues for the application of single-cell genomics to unravel unknown pathogenic pathways and disease mechanisms for the development of new therapeutics targeting liver pathology. As these technologies mature, their integration into clinical data analysis will aid in patient stratification and in developing treatment plans for patients suffering from liver disease.

Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry

Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.

Comprehensive multi-cohort transcriptional meta-analysis of muscle diseases identifies a signature of disease severity

Muscle diseases share common pathological features suggesting common underlying mechanisms. We hypothesized there is a common set of genes dysregulated across muscle diseases compared to healthy muscle and that these genes correlate with severity of muscle disease. We performed meta-analysis of transcriptional profiles of muscle biopsies from human muscle diseases and healthy controls. Studies obtained from public microarray repositories fulfilling quality criteria were divided into six categories: (i) immobility, (ii) inflammatory myopathies, (iii) intensive care unit (ICU) acquired weakness (ICUAW), (iv) congenital muscle diseases, (v) chronic systemic diseases, (vi) motor neuron disease. Patient cohorts were separated in discovery and validation cohorts retaining roughly equal proportions of samples for the disease categories. To remove bias towards a specific muscle disease category we repeated the meta-analysis five times by removing data sets corresponding to one muscle disease class at a time in a "leave-one-disease-out" analysis. We used 636 muscle tissue samples from 30 independent cohorts to identify a 52 gene signature (36 up-regulated and 16 down-regulated genes). We validated the discriminatory power of this signature in 657 muscle biopsies from 12 additional patient cohorts encompassing five categories of muscle diseases with an area under the receiver operating characteristic curve of 0.91, 83% sensitivity, and 85.3% specificity. The expression score of the gene signature inversely correlated with quadriceps muscle mass (r = -0.50, p-value = 0.011) in ICUAW and shoulder abduction strength (r = -0.77, p-value = 0.014) in amyotrophic lateral sclerosis (ALS). The signature also positively correlated with histologic assessment of muscle atrophy in ALS (r = 0.88, p-value = 1.62 × 10^-3) and fibrosis in muscular dystrophy (Jonckheere trend test p-value = 4.45 × 10^-9). Our results identify a conserved transcriptional signature associated with clinical and histologic muscle disease severity. Several genes in this conserved signature have not been previously associated with muscle disease severity.

The metabolic enzyme hexokinase 2 localizes to the nucleus in AML and normal haematopoietic stem and progenitor cells to maintain stemness

Mitochondrial metabolites regulate leukaemic and normal stem cells by affecting epigenetic marks. How mitochondrial enzymes localize to the nucleus to control stem cell function is less understood. We discovered that the mitochondrial metabolic enzyme hexokinase 2 (HK2) localizes to the nucleus in leukaemic and normal haematopoietic stem cells. Overexpression of nuclear HK2 increases leukaemic stem cell properties and decreases differentiation, whereas selective nuclear HK2 knockdown promotes differentiation and decreases stem cell function. Nuclear HK2 localization is phosphorylation-dependent, requires active import and export, and regulates differentiation independently of its enzymatic activity. HK2 interacts with nuclear proteins regulating chromatin openness, increasing chromatin accessibilities at leukaemic stem cell-positive signature and DNA-repair sites. Nuclear HK2 overexpression decreases double-strand breaks and confers chemoresistance, which may contribute to the mechanism by which leukaemic stem cells resist DNA-damaging agents. Thus, we describe a non-canonical mechanism by which mitochondrial enzymes influence stem cell function independently of their metabolic function.

Thomas, Egan et al. report that hexokinase 2 localizes to the nucleus of leukaemic and normal haematopoietic cells to maintain stemness by interacting with nuclear proteins and modulating chromatin accessibility independently of its kinase activity.

Identification of the global miR-130a targetome reveals a role for TBL1XR1 in hematopoietic stem cell self-renewal and t(8;21) AML

Gene expression profiling and proteome analysis of normal and malignant hematopoietic stem cells (HSCs) point to shared core stemness properties. However, discordance between mRNA and protein signatures highlights an important role for post-transcriptional regulation by microRNAs (miRNAs) in governing this critical nexus. Here, we identify miR-130a as a regulator of HSC self-renewal and differentiation. Enforced expression of miR-130a impairs B lymphoid differentiation and expands long-term HSCs. Integration of protein mass spectrometry and chimeric AGO2 crosslinking and immunoprecipitation (CLIP) identifies TBL1XR1 as a primary miR-130a target, whose loss of function phenocopies miR-130a overexpression. Moreover, we report that miR-130a is highly expressed in t(8;21) acute myeloid leukemia (AML), where it is critical for maintaining the oncogenic molecular program mediated by the AML1-ETO complex. Our study establishes that identification of the comprehensive miRNA targetome within primary cells enables discovery of genes and molecular networks underpinning stemness properties of normal and leukemic cells.

IPO11 regulates the nuclear import of BZW1/2 and is necessary for AML cells and stem cells

AML cells are arranged in a hierarchy with stem/progenitor cells giving rise to more differentiated bulk cells. Despite the importance of stem/progenitors in the pathogenesis of AML, the determinants of the AML stem/progenitor state are not fully understood. Through a comparison of genes that are significant for growth and viability of AML cells by way of a CRISPR screen, with genes that are differentially expressed in leukemia stem cells (LSC), we identified importin 11 (IPO11) as a novel target in AML. Importin 11 (IPO11) is a member of the importin β family of proteins that mediate transport of proteins across the nuclear membrane. In AML, knockdown of IPO11 decreased growth, reduced engraftment potential of LSC, and induced differentiation. Mechanistically, we identified the transcription factors BZW1 and BZW2 as novel cargo of IPO11. We further show that BZW1/2 mediate a transcriptional signature that promotes stemness and survival of LSC. Thus, we demonstrate for the first time how specific cytoplasmic-nuclear regulation supports stem-like transcriptional signature in relapsed AML.

Hypophosphorylated pRb knock-in mice exhibit hallmarks of aging and vitamin C-preventable diabetes

Despite extensive analysis of pRB phosphorylation in vitro, how this modification influences development and homeostasis in vivo is unclear. Here, we show that homozygous Rb^∆K4 and Rb^∆K7 knock‐in mice, in which either four or all seven phosphorylation sites in the C‐terminal region of pRb, respectively, have been abolished by Ser/Thr‐to‐Ala substitutions, undergo normal embryogenesis and early development, notwithstanding suppressed phosphorylation of additional upstream sites. Whereas Rb^∆K4 mice exhibit telomere attrition but no other abnormalities, Rb^∆K7 mice are smaller and display additional hallmarks of premature aging including infertility, kyphosis, and diabetes, indicating an accumulative effect of blocking pRb phosphorylation. Diabetes in Rb^∆K7 mice is insulin‐sensitive and associated with failure of quiescent pancreatic β‐cells to re‐enter the cell cycle in response to mitogens, resulting in induction of DNA damage response (DDR), senescence‐associated secretory phenotype (SASP), and reduced pancreatic islet mass and circulating insulin level. Pre‐treatment with the epigenetic regulator vitamin C reduces DDR, increases cell cycle re‐entry, improves islet morphology, and attenuates diabetes. These results have direct implications for cell cycle regulation, CDK‐inhibitor therapeutics, diabetes, and longevity.

Temporal profiling of therapy resistance in human medulloblastoma identifies novel targetable drivers of recurrence

Medulloblastoma (MB) remains a leading cause of cancer-related mortality among children. The paucity of MB samples collected at relapse has hindered the functional understanding of molecular mechanisms driving therapy failure. New models capable of accurately recapitulating tumor progression in response to conventional therapeutic interventions are urgently needed. In this study, we developed a therapy-adapted PDX MB model that has a distinct advantage of generating human MB recurrence. The comparative gene expression analysis of MB cells collected throughout therapy led to identification of genes specifically up-regulated after therapy, including one previously undescribed in the setting of brain tumors, bactericidal/permeability-increasing fold-containing family B member 4 (BPIFB4). Subsequent functional validation resulted in a markedly diminished in vitro proliferation, self-renewal, and longevity of MB cells, translating into extended survival and reduced tumor burden in vivo. Targeting endothelial nitric oxide synthase, a downstream substrate of BPIFB4, impeded growth of several patient-derived MB lines at low nanomolar concentrations.

Author-sourced capture of pathway knowledge in computable form using Biofactoid

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a web-based platform that allows scientists to specify networks of interactions between genes, their products, and chemical compounds, and then translates this information into a representation suitable for computational analysis, search and discovery. We also report the results of a pilot study to encourage the wide adoption of Biofactoid by the scientific community.

Single-Cell, Single-Nucleus, and Spatial RNA Sequencing of the Human Liver Identifies Cholangiocyte and Mesenchymal Heterogeneity

The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single-cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation-related cell perturbation can limit the ability to fully capture the human liver's parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the transcriptional landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at a single-cell resolution, revealed the presence of rare subtypes of liver mesenchymal cells, and facilitated the detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and natural killer cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte, and mesenchymal cell populations by an independent spatial transcriptomics data set and immunohistochemistry. Conclusion: Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.

A microfluidic platform enables comprehensive gene expression profiling of mouse retinal stem cells

Loss of photoreceptors due to retinal degeneration is a major cause of untreatable visual impairment and blindness. Cell replacement therapy, using retinal stem cell (RSC)-derived photoreceptors, holds promise for reconstituting damaged cell populations in the retina. One major obstacle preventing translation to the clinic is the lack of validated markers or strategies to prospectively identify these rare cells in the retina and subsequently enrich them. Here, we introduce a microfluidic platform that combines nickel micromagnets, herringbone structures, and a design enabling varying flow velocities among three compartments to facilitate a highly efficient enrichment of RSCs. In addition, we developed an affinity enrichment strategy based on cell-surface markers that was utilized to isolate RSCs from the adult ciliary epithelium. We showed that targeting a panel of three cell surface markers simultaneously facilitates the enrichment of RSCs to 1 : 3 relative to unsorted cells. Combining the microfluidic platform with single-cell whole-transcriptome profiling, we successfully identified four differentially expressed cell surface markers that can be targeted simultaneously to yield an unprecedented 1 : 2 enrichment of RSCs relative to unsorted cells. We also identified transcription factors (TFs) that play functional roles in maintenance, quiescence, and proliferation of RSCs. This level of analysis for the first time identified a spectrum of molecular and functional properties of RSCs.

A clinically applicable integrative molecular classification of meningiomas

Meningiomas are the most common primary intracranial tumour in adults1. Patients with symptoms are generally treated with surgery as there are no effective medical therapies. The World Health Organization histopathological grade of the tumour and the extent of resection at surgery (Simpson grade) are associated with the recurrence of disease; however, they do not accurately reflect the clinical behaviour of all meningiomas2. Molecular classifications of meningioma that reliably reflect tumour behaviour and inform on therapies are required. Here we introduce four consensus molecular groups of meningioma by combining DNA somatic copy-number aberrations, DNA somatic point mutations, DNA methylation and messenger RNA abundance in a unified analysis. These molecular groups more accurately predicted clinical outcomes compared with existing classification schemes. Each molecular group showed distinctive and prototypical biology (immunogenic, benign NF2 wild-type, hypermetabolic and proliferative) that informed therapeutic options. Proteogenomic characterization reinforced the robustness of the newly defined molecular groups and uncovered highly abundant and group-specific protein targets that we validated using immunohistochemistry. Single-cell RNA sequencing revealed inter-individual variations in meningioma as well as variations in intrinsic expression programs in neoplastic cells that mirrored the biology of the molecular groups identified.

Nicotinamide phosphoribosyltransferase inhibitors selectively induce apoptosis of AML stem cells by disrupting lipid homeostasis

Current treatments for acute myeloid leukemia (AML) are often ineffective in eliminating leukemic stem cells (LSCs), which perpetuate the disease. Here, we performed a metabolic drug screen to identify LSC-specific vulnerabilities and found that nicotinamide phosphoribosyltransferase (NAMPT) inhibitors selectively killed LSCs, while sparing normal hematopoietic stem and progenitor cells. Treatment with KPT-9274, a NAMPT inhibitor, suppressed the conversion of saturated fatty acids to monounsaturated fatty acids, a reaction catalyzed by the stearoyl-CoA desaturase (SCD) enzyme, resulting in apoptosis of AML cells. Transcriptomic analysis of LSCs treated with KPT-9274 revealed an upregulation of sterol regulatory-element binding protein (SREBP)-regulated genes, including SCD, which conferred partial protection against NAMPT inhibitors. Inhibition of SREBP signaling with dipyridamole enhanced the cytotoxicity of KPT-9274 on LSCs in vivo. Our work demonstrates that altered lipid homeostasis plays a key role in NAMPT inhibitor-induced apoptosis and identifies NAMPT inhibition as a therapeutic strategy for targeting LSCs in AML.

Control of tissue development and cell diversity by cell cycle-dependent transcriptional filtering

Cell cycle duration changes dramatically during development, starting out fast to generate cells quickly and slowing down over time as the organism matures. The cell cycle can also act as a transcriptional filter to control the expression of long gene transcripts, which are partially transcribed in short cycles. Using mathematical simulations of cell proliferation, we identify an emergent property that this filter can act as a tuning knob to control gene transcript expression, cell diversity, and the number and proportion of different cell types in a tissue. Our predictions are supported by comparison to single-cell RNA-seq data captured over embryonic development. Additionally, evolutionary genome analysis shows that fast-developing organisms have a narrow genomic distribution of gene lengths while slower developers have an expanded number of long genes. Our results support the idea that cell cycle dynamics may be important across multicellular animals for controlling gene transcript expression and cell fate.

The mitochondrial peptidase, neurolysin, regulates respiratory chain supercomplex formation and is necessary for AML viability

Neurolysin (NLN) is a zinc metallopeptidase whose mitochondrial function is unclear. We found that NLN was overexpressed in almost half of patients with acute myeloid leukemia (AML), and inhibition of NLN was selectively cytotoxic to AML cells and stem cells while sparing normal hematopoietic cells. Mechanistically, NLN interacted with the mitochondrial respiratory chain. Genetic and chemical inhibition of NLN impaired oxidative metabolism and disrupted the formation of respiratory chain supercomplexes (RCS). Furthermore, NLN interacted with the known RCS regulator, LETM1, and inhibition of NLN disrupted LETM1 complex formation. RCS were increased in patients with AML and positively correlated with NLN expression. These findings demonstrate that inhibiting RCS formation selectively targets AML cells and stem cells and highlights the therapeutic potential of pharmacologically targeting NLN in AML.

Surveilling and Tracking COVID-19 Patients Using a Portable Quantum Dot Smartphone Device

The ability to rapidly diagnose, track, and disseminate information for SARS-CoV-2 is critical to minimize its spread. Here, we engineered a portable smartphone-based quantum barcode serological assay device for real-time surveillance of patients infected with SARS-CoV-2. Our device achieved a clinical sensitivity of 90% and specificity of 100% for SARS-CoV-2, as compared to 34% and 100%, respectively, for lateral flow assays in a head-to-head comparison. The lateral flow assay misdiagnosed ∼2 out of 3 SARS-CoV-2 positive patients. Our quantum dot barcode device has ∼3 times greater clinical sensitivity because it is ∼140 times more analytically sensitive than lateral flow assays. Our device can diagnose SARS-CoV-2 at different sampling dates and infectious severity. We developed a databasing app to provide instantaneous results to inform patients, physicians, and public health agencies. This assay and device enable real-time surveillance of SARS-CoV-2 seroprevalence and potential immunity.

scNetViz: from single cells to networks using Cytoscape

Single-cell RNA-sequencing (scRNA-seq) has revolutionized molecular biology and medicine by enabling high-throughput studies of cellular heterogeneity in diverse tissues. Applying network biology approaches to scRNA-seq data can provide useful insights into genes driving heterogeneous cell-type compositions of tissues. Here, we present scNetViz-  a Cytoscape app to aid biological interpretation of cell clusters in scRNA-seq data using network analysis. scNetViz calculates the differential expression of each gene across clusters and then creates a cluster-specific gene functional interaction network between the significantly differentially expressed genes for further analysis, such as pathway enrichment analysis. To automate a complete data analysis workflow, scNetViz integrates parts of the Scanpy software, which is a popular Python package for scRNA-seq data analysis, with Cytoscape apps such as stringApp, cyPlot, and enhancedGraphics. We describe our implementation of methods for accessing data from public single cell atlas projects, differential expression analysis, visualization, and automation. scNetViz enables users to analyze data from public atlases or their own experiments, which we illustrate with two use cases. Analysis can be performed via the Cytoscape GUI or CyREST programming interface using R (RCy3) or Python (py4cytoscape).

Single-Cell Profiling Shows Murine Forebrain Neural Stem Cells Reacquire a Developmental State when Activated for Adult Neurogenesis

The transitions from developing to adult quiescent and activated neural stem cells (NSCs) are not well understood. Here, we use single-cell transcriptional profiling and lineage tracing to characterize these transitions in the murine forebrain. We show that the two forebrain NSC parental populations, embryonic cortex and ganglionic eminence radial precursors (RPs), are highly similar even though they make glutamatergic versus gabaergic neurons. Both RP populations progress linearly to transition from a highly active embryonic to a dormant adult stem cell state that still shares many similarities with embryonic RPs. When adult NSCs of either embryonic origin become reactivated to make gabaergic neurons, they acquire a developing ganglionic eminence RP-like identity. Thus, transitions from embryonic RPs to adult NSCs and back to neuronal progenitors do not involve fundamental changes in cell identity, but rather reflect conversions between activated and dormant NSC states that may be determined by the niche environment.

Generation of mature compact ventricular cardiomyocytes from human pluripotent stem cells

Compact cardiomyocytes that make up the ventricular wall of the adult heart represent an important therapeutic target population for modeling and treating cardiovascular diseases. Here, we established a differentiation strategy that promotes the specification, proliferation and maturation of compact ventricular cardiomyocytes from human pluripotent stem cells (hPSCs). The cardiomyocytes generated under these conditions display the ability to use fatty acids as an energy source, a high mitochondrial mass, well-defined sarcomere structures and enhanced contraction force. These ventricular cells undergo metabolic changes indicative of those associated with heart failure when challenged in vitro with pathological stimuli and were found to generate grafts consisting of more mature cells than those derived from immature cardiomyocytes following transplantation into infarcted rat hearts. hPSC-derived atrial cardiomyocytes also responded to the maturation cues identified in this study, indicating that the approach is broadly applicable to different subtypes of the heart. Collectively, these findings highlight the power of recapitulating key aspects of embryonic and postnatal development for generating therapeutically relevant cell types from hPSCs.

Cardiomyocytes of heart ventricles consist of subpopulations of trabecular and compact subtypes. Here the authors describe the generation of structurally, metabolically and functionally mature compact ventricular cardiomyocytes as well as mature atrial cardiomyocytes from human pluripotent stem cells.

Tutorial: guidelines for annotating single-cell transcriptomic maps using automated and manual methods

Single-cell transcriptomics can profile thousands of cells in a single experiment and identify novel cell types, states and dynamics in a wide variety of tissues and organisms. Standard experimental protocols and analysis workflows have been developed to create single-cell transcriptomic maps from tissues. This tutorial focuses on how to interpret these data to identify cell types, states and other biologically relevant patterns with the objective of creating an annotated map of cells. We recommend a three-step workflow including automatic cell annotation (wherever possible), manual cell annotation and verification. Frequently encountered challenges are discussed, as well as strategies to address them. Guiding principles and specific recommendations for software tools and resources that can be used for each step are covered, and an R notebook is included to help run the recommended workflow. Basic familiarity with computer software is assumed, and basic knowledge of programming (e.g., in the R language) is recommended.

SBGN Bricks Ontology as a tool to describe recurring concepts in molecular networks

A comprehensible representation of a molecular network is key to communicating and understanding scientific results in systems biology. The Systems Biology Graphical Notation (SBGN) has emerged as the main standard to represent such networks graphically. It has been implemented by different software tools, and is now largely used to communicate maps in scientific publications. However, learning the standard, and using it to build large maps, can be tedious. Moreover, SBGN maps are not grounded on a formal semantic layer and therefore do not enable formal analysis. Here, we introduce a new set of patterns representing recurring concepts encountered in molecular networks, called SBGN bricks. The bricks are structured in a new ontology, the Bricks Ontology (BKO), to define clear semantics for each of the biological concepts they represent. We show the usefulness of the bricks and BKO for both the template-based construction and the semantic annotation of molecular networks. The SBGN bricks and BKO can be freely explored and downloaded at sbgnbricks.org.

Distinct fibroblast functional states drive clinical outcomes in ovarian cancer and are regulated by TCF21

Recent studies indicate that cancer-associated fibroblasts (CAFs) are phenotypically and functionally heterogeneous. However, little is known about CAF subtypes, the roles they play in cancer progression, and molecular mediators of the CAF “state.” Here, we identify a novel cell surface pan-CAF marker, CD49e, and demonstrate that two distinct CAF states, distinguished by expression of fibroblast activation protein (FAP), coexist within the CD49e⁺ CAF compartment in high-grade serous ovarian cancers. We show for the first time that CAF state influences patient outcomes and that this is mediated by the ability of FAP-high, but not FAP-low, CAFs to aggressively promote proliferation, invasion and therapy resistance of cancer cells. Overexpression of the FAP-low–specific transcription factor TCF21 in FAP-high CAFs decreases their ability to promote invasion, chemoresistance, and in vivo tumor growth, indicating that it acts as a master regulator of the CAF state. Understanding CAF states in more detail could lead to better patient stratification and novel therapeutic strategies.

PRMT5 inhibition disrupts splicing and stemness in glioblastoma

Glioblastoma (GBM) is a deadly cancer in which cancer stem cells (CSCs) sustain tumor growth and contribute to therapeutic resistance. Protein arginine methyltransferase 5 (PRMT5) has recently emerged as a promising target in GBM. Using two orthogonal-acting inhibitors of PRMT5 (GSK591 or LLY-283), we show that pharmacological inhibition of PRMT5 suppresses the growth of a cohort of 46 patient-derived GBM stem cell cultures, with the proneural subtype showing greater sensitivity. We show that PRMT5 inhibition causes widespread disruption of splicing across the transcriptome, particularly affecting cell cycle gene products. We identify a GBM splicing signature that correlates with the degree of response to PRMT5 inhibition. Importantly, we demonstrate that LLY-283 is brain-penetrant and significantly prolongs the survival of mice with orthotopic patient-derived xenografts. Collectively, our findings provide a rationale for the clinical development of brain penetrant PRMT5 inhibitors as treatment for GBM.

Gradient of Developmental and Injury Response transcriptional states defines functional vulnerabilities underpinning glioblastoma heterogeneity

Glioblastomas harbor diverse cell populations, including rare glioblastoma stem cells (GSCs) that drive tumorigenesis. To characterize functional diversity within this population, we performed single-cell RNA sequencing on >69,000 GSCs cultured from the tumors of 26 patients. We observed a high degree of inter- and intra-GSC transcriptional heterogeneity that could not be fully explained by DNA somatic alterations. Instead, we found that GSCs mapped along a transcriptional gradient spanning two cellular states reminiscent of normal neural development and inflammatory wound response. Genome-wide CRISPR-Cas9 dropout screens independently recapitulated this observation, with each state characterized by unique essential genes. Further single-cell RNA sequencing of >56,000 malignant cells from primary tumors found that the majority organize along an orthogonal astrocyte maturation gradient yet retain expression of founder GSC transcriptional programs. We propose that glioblastomas grow out of a fundamental GSC-based neural wound response transcriptional program, which is a promising target for new therapy development.

Sphingosine-1-phosphate receptor 3 potentiates inflammatory programs in normal and leukemia stem cells to promote differentiation

Acute myeloid leukemia (AML) is a caricature of normal hematopoiesis, driven from leukemia stem cells (LSC) that share some hematopoietic stem cell (HSC) programs including responsiveness to inflammatory signaling. Although inflammation dysregulates mature myeloid cells and influences stemness programs and lineage determination in HSC by activating stress myelopoiesis, such roles in LSC are poorly understood. Here, we show that S1PR3, a receptor for the bioactive lipid sphingosine-1-phosphate, is a central regulator which drives myeloid differentiation and activates inflammatory programs in both HSC and LSC. S1PR3-mediated inflammatory signatures varied in a continuum from primitive to mature myeloid states across AML patient cohorts, each with distinct phenotypic and clinical properties. S1PR3 was high in LSC and blasts of mature myeloid samples with linkages to chemosensitivity, while S1PR3 activation in primitive samples promoted LSC differentiation leading to eradication. Our studies open new avenues for therapeutic target identification specific for each AML subset.

Large-scale survey and database of high affinity ligands for peptide recognition modules

Many proteins involved in signal transduction contain peptide recognition modules (PRMs) that recognize short linear motifs (SLiMs) within their interaction partners. Here, we used large-scale peptide-phage display methods to derive optimal ligands for 163 unique PRMs representing 79 distinct structural families. We combined the new data with previous data that we collected for the large SH3, PDZ, and WW domain families to assemble a database containing 7,984 unique peptide ligands for 500 PRMs representing 82 structural families. For 74 PRMs, we acquired enough new data to map the specificity profiles in detail and derived position weight matrices and binding specificity logos based on multiple peptide ligands. These analyses showed that optimal peptide ligands resembled peptides observed in existing structures of PRM-ligand complexes, indicating that a large majority of the phage-derived peptides are likely to target natural peptide-binding sites and could thus act as inhibitors of natural protein-protein interactions. The complete dataset has been assembled in an online database (http://www.prm-db.org) that will enable many structural, functional, and biological studies of PRMs and SLiMs.