Protective role for kidney TREM2high macrophages in obesity- and diabetes-induced kidney injury.

Diabetic kidney disease (DKD), the most common cause of kidney failure, is a frequent complication of diabetes and obesity, and yet to date, treatments to halt its progression are lacking. We analyze kidney single-cell transcriptomic profiles from DKD patients and two DKD mouse models at multiple time points along disease progression-high-fat diet (HFD)-fed mice aged to 90-100 weeks and BTBR ob/ob mice (a genetic model)-and report an expanding population of macrophages with high expression of triggering receptor expressed on myeloid cells 2 (TREM2) in HFD-fed mice. TREM2high macrophages are enriched in obese and diabetic patients, in contrast to hypertensive patients or healthy controls in an independent validation cohort. Trem2 knockout mice on an HFD have worsening kidney filter damage and increased tubular epithelial cell injury, all signs of worsening DKD. Together, our studies suggest that strategies to enhance kidney TREM2high macrophages may provide therapeutic benefits for DKD.

Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations.

The identification of genetic and chemical perturbations with similar impacts on cell morphology can elucidate compounds' mechanisms of action or novel regulators of genetic pathways. Research on methods for identifying such similarities has lagged due to a lack of carefully designed and well-annotated image sets of cells treated with chemical and genetic perturbations. Here we create such a Resource dataset, CPJUMP1, in which each perturbed gene's product is a known target of at least two chemical compounds in the dataset. We systematically explore the directionality of correlations among perturbations that target the same protein encoded by a given gene, and we find that identifying matches between chemical and genetic perturbations is a challenging task. Our dataset and baseline analyses provide a benchmark for evaluating methods that measure perturbation similarities and impact, and more generally, learn effective representations of cellular state from microscopy images. Such advancements would accelerate the applications of image-based profiling of cellular states, such as uncovering drug mode of action or probing functional genomics.

Discovering cellular programs of intrinsic and extrinsic drivers of metabolic traits using LipocyteProfiler.

A primary obstacle in translating genetic associations with disease into therapeutic strategies is elucidating the cellular programs affected by genetic risk variants and effector genes. Here, we introduce LipocyteProfiler, a cardiometabolic-disease-oriented high-content image-based profiling tool that enables evaluation of thousands of morphological and cellular profiles that can be systematically linked to genes and genetic variants relevant to cardiometabolic disease. We show that LipocyteProfiler allows surveillance of diverse cellular programs by generating rich context- and process-specific cellular profiles across hepatocyte and adipocyte cell-state transitions. We use LipocyteProfiler to identify known and novel cellular mechanisms altered by polygenic risk of metabolic disease, including insulin resistance, fat distribution, and the polygenic contribution to lipodystrophy. LipocyteProfiler paves the way for large-scale forward and reverse deep phenotypic profiling in lipocytes and provides a framework for the unbiased identification of causal relationships between genetic variants and cellular programs relevant to human disease.

Optimizing the Cell Painting assay for image-based profiling.

In image-based profiling, software extracts thousands of morphological features of cells from multi-channel fluorescence microscopy images, yielding single-cell profiles that can be used for basic research and drug discovery. Powerful applications have been proven, including clustering chemical and genetic perturbations on the basis of their similar morphological impact, identifying disease phenotypes by observing differences in profiles between healthy and diseased cells and predicting assay outcomes by using machine learning, among many others. Here, we provide an updated protocol for the most popular assay for image-based profiling, Cell Painting. Introduced in 2013, it uses six stains imaged in five channels and labels eight diverse components of the cell: DNA, cytoplasmic RNA, nucleoli, actin, Golgi apparatus, plasma membrane, endoplasmic reticulum and mitochondria. The original protocol was updated in 2016 on the basis of several years' experience running it at two sites, after optimizing it by visual stain quality. Here, we describe the work of the Joint Undertaking for Morphological Profiling Cell Painting Consortium, to improve upon the assay via quantitative optimization by measuring the assay's ability to detect morphological phenotypes and group similar perturbations together. The assay gives very robust outputs despite various changes to the protocol, and two vendors' dyes work equivalently well. We present Cell Painting version 3, in which some steps are simplified and several stain concentrations can be reduced, saving costs. Cell culture and image acquisition take 1-2 weeks for typically sized batches of ≤20 plates; feature extraction and data analysis take an additional 1-2 weeks.This protocol is an update to Nat. Protoc. 11, 1757-1774 (2016): https://doi.org/10.1038/nprot.2016.105.

nELISA: A high-throughput, high-plex platform enables quantitative profiling of the secretome.

We present the nELISA, a high-throughput, high-fidelity, and high-plex protein profiling platform. DNA oligonucleotides are used to pre-assemble antibody pairs on spectrally encoded microparticles and perform displacement-mediated detection. Spatial separation between non-cognate antibodies prevents the rise of reagent-driven cross-reactivity, while read-out is performed cost-efficiently and at high-throughput using flow cytometry. We assembled an inflammatory panel of 191 targets that were multiplexed without cross-reactivity or impact on performance vs 1-plex signals, with sensitivities as low as 0.1pg/mL and measurements spanning 7 orders of magnitude. We then performed a large-scale secretome perturbation screen of peripheral blood mononuclear cells (PBMCs), with cytokines as both perturbagens and read-outs, measuring 7,392 samples and generating ~1.5M protein datapoints in under a week, a significant advance in throughput compared to other highly multiplexed immunoassays. We uncovered 447 significant cytokine responses, including multiple putatively novel ones, that were conserved across donors and stimulation conditions. We also validated the nELISA's use in phenotypic screening, and propose its application to drug discovery.

FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity.

Cellular exposure to free fatty acids (FFAs) is implicated in the pathogenesis of obesity-associated diseases. However, there are no scalable approaches to comprehensively assess the diverse FFAs circulating in human plasma. Furthermore, assessing how FFA-mediated processes interact with genetic risk for disease remains elusive. Here, we report the design and implementation of fatty acid library for comprehensive ontologies (FALCON), an unbiased, scalable, and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids associated with decreased membrane fluidity. Furthermore, we prioritized genes that reflect the combined effects of harmful FFA exposure and genetic risk for type 2 diabetes (T2D). We found that c-MAF-inducing protein (CMIP) protects cells from FFA exposure by modulating Akt signaling. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism.

FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity.

Cellular exposure to free fatty acids (FFA) is implicated in the pathogenesis of obesity-associated diseases. However, studies to date have assumed that a few select FFAs are representative of broad structural categories, and there are no scalable approaches to comprehensively assess the biological processes induced by exposure to diverse FFAs circulating in human plasma. Furthermore, assessing how these FFA- mediated processes interact with genetic risk for disease remains elusive. Here we report the design and implementation of FALCON (Fatty Acid Library for Comprehensive ONtologies) as an unbiased, scalable and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids (MUFAs) with a distinct lipidomic profile associated with decreased membrane fluidity. Furthermore, we developed a new approach to prioritize genes that reflect the combined effects of exposure to harmful FFAs and genetic risk for type 2 diabetes (T2D). Importantly, we found that c-MAF inducing protein (CMIP) protects cells from exposure to FFAs by modulating Akt signaling and we validated the role of CMIP in human pancreatic beta cells. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism. Highlights: FALCON (Fatty Acid Library for Comprehensive ONtologies) enables multimodal profiling of 61 free fatty acids (FFAs) to reveal 5 FFA clusters with distinct biological effectsFALCON is applicable to many and diverse cell typesA subset of monounsaturated FAs (MUFAs) equally or more toxic than canonical lipotoxic saturated FAs (SFAs) leads to decreased membrane fluidityNew approach prioritizes genes that represent the combined effects of environmental (FFA) exposure and genetic risk for diseaseC-Maf inducing protein (CMIP) is identified as a suppressor of FFA-induced lipotoxicity via Akt-mediated signaling.

Morphology and gene expression profiling provide complementary information for mapping cell state.

Morphological and gene expression profiling can cost-effectively capture thousands of features in thousands of samples across perturbations by disease, mutation, or drug treatments, but it is unclear to what extent the two modalities capture overlapping versus complementary information. Here, using both the L1000 and Cell Painting assays to profile gene expression and cell morphology, respectively, we perturb human A549 lung cancer cells with 1,327 small molecules from the Drug Repurposing Hub across six doses, providing a data resource including dose-response data from both assays. The two assays capture both shared and complementary information for mapping cell state. Cell Painting profiles from compound perturbations are more reproducible and show more diversity but measure fewer distinct groups of features. Applying unsupervised and supervised methods to predict compound mechanisms of action (MOAs) and gene targets, we find that the two assays not only provide a partially shared but also a complementary view of drug mechanisms. Given the numerous applications of profiling in biology, our analyses provide guidance for planning experiments that profile cells for detecting distinct cell types, disease phenotypes, and response to chemical or genetic perturbations.

Single-nucleus profiling of human dilated and hypertrophic cardiomyopathy.

Heart failure encompasses a heterogeneous set of clinical features that converge on impaired cardiac contractile function1,2 and presents a growing public health concern. Previous work has highlighted changes in both transcription and protein expression in failing hearts3,4, but may overlook molecular changes in less prevalent cell types. Here we identify extensive molecular alterations in failing hearts at single-cell resolution by performing single-nucleus RNA sequencing of nearly 600,000 nuclei in left ventricle samples from 11 hearts with dilated cardiomyopathy and 15 hearts with hypertrophic cardiomyopathy as well as 16 non-failing hearts. The transcriptional profiles of dilated or hypertrophic cardiomyopathy hearts broadly converged at the tissue and cell-type level. Further, a subset of hearts from patients with cardiomyopathy harbour a unique population of activated fibroblasts that is almost entirely absent from non-failing samples. We performed a CRISPR-knockout screen in primary human cardiac fibroblasts to evaluate this fibrotic cell state transition; knockout of genes associated with fibroblast transition resulted in a reduction of myofibroblast cell-state transition upon TGFß1 stimulation for a subset of genes. Our results provide insights into the transcriptional diversity of the human heart in health and disease as well as new potential therapeutic targets and biomarkers for heart failure.

High-Throughput Assay to Screen Small Molecules for Their Ability to Prevent Sickling of Red Blood Cells.

Sickle cell disease (SCD) is an inherited disorder of hemoglobin (Hb); approximately 300,000 babies are born worldwide with SCD each year. In SCD, fibers of polymerized sickle Hb (HbS) form in red blood cells (RBCs), which cause RBCs to develop their characteristic "sickled" shape, resulting in hemolytic anemia and numerous vascular complications including vaso-occlusive crises. The development of novel antisickling compounds will provide new therapeutic options for patients with SCD. We developed a high-throughput "sickling assay" that is based on an automated high-content imaging system to quantify the effects of hypoxia on the shape and size of RBCs from HbSS SCD patients (SS RBCs). We used this assay to screen thousands of compounds for their ability to inhibit sickling. In the assay, voxelotor (an FDA-approved medication used to treat SCD) prevented sickling with a z'-factor > 0.4, suggesting that the assay is capable of identifying compounds that inhibit sickling. We screened the Broad Repurposing Library of 5393 compounds for their ability to prevent sickling in 4% oxygen/96% nitrogen. We identified two compounds, SNS-314 mesylate and voxelotor itself, that successfully prevented sickling. SNS-314 mesylate prevented sickling in the absence of oxygen, while voxelotor did not, suggesting that SNS-314 mesylate acts by a mechanism that is different from that of voxelotor. The sickling assay described in this study will permit the identification of additional, novel antisickling compounds, which will potentially expand the therapeutic options for SCD.

Phenotypic Screening for Small Molecules that Protect ß-Cells from Glucolipotoxicity.

Type 2 diabetes is marked by progressive ß-cell failure, leading to loss of ß-cell mass. Increased levels of circulating glucose and free fatty acids associated with obesity lead to ß-cell glucolipotoxicity. There are currently no therapeutic options to address this facet of ß-cell loss in obese type 2 diabetes patients. To identify small molecules capable of protecting ß-cells, we performed a high-throughput screen of 20,876 compounds in the rat insulinoma cell line INS-1E in the presence of elevated glucose and palmitate. We found 312 glucolipotoxicity-protective small molecules (1.49% hit rate) capable of restoring INS-1E viability, and we focused on 17 with known biological targets. 16 of the 17 compounds were kinase inhibitors with activity against specific families including but not limited to cyclin-dependent kinases (CDK), PI-3 kinase (PI3K), Janus kinase (JAK), and Rho-associated kinase 2 (ROCK2). 7 of the 16 kinase inhibitors were PI3K inhibitors. Validation studies in dissociated human islets identified 10 of the 17 compounds, namely, KD025, ETP-45658, BMS-536924, AT-9283, PF-03814735, torin-2, AZD5438, CP-640186, ETP-46464, and GSK2126458 that reduced glucolipotoxicity-induced ß-cell death. These 10 compounds decreased markers of glucolipotoxicity including caspase activation, mitochondrial depolarization, and increased calcium flux. Together, these results provide a path forward toward identifying novel treatments to preserve ß-cell viability in the face of glucolipotoxicity.

Control of osteocyte dendrite formation by Sp7 and its target gene osteocrin.

Some osteoblasts embed within bone matrix, change shape, and become dendrite-bearing osteocytes. The circuitry that drives dendrite formation during "osteocytogenesis" is poorly understood. Here we show that deletion of Sp7 in osteoblasts and osteocytes causes defects in osteocyte dendrites. Profiling of Sp7 target genes and binding sites reveals unexpected repurposing of this transcription factor to drive dendrite formation. Osteocrin is a Sp7 target gene that promotes osteocyte dendrite formation and rescues defects in Sp7-deficient mice. Single-cell RNA-sequencing demonstrates defects in osteocyte maturation in the absence of Sp7. Sp7-dependent osteocyte gene networks are associated with human skeletal diseases. Moreover, humans with a SP7R316C mutation show defective osteocyte morphology. Sp7-dependent genes that mark osteocytes are enriched in neurons, highlighting shared features between osteocytic and neuronal connectivity. These findings reveal a role for Sp7 and its target gene Osteocrin in osteocytogenesis, revealing that pathways that control osteocyte development influence human bone diseases.

Predicting cell health phenotypes using image-based morphology profiling.

Genetic and chemical perturbations impact diverse cellular phenotypes, including multiple indicators of cell health. These readouts reveal toxicity and antitumorigenic effects relevant to drug discovery and personalized medicine. We developed two customized microscopy assays, one using four targeted reagents and the other three targeted reagents, to collectively measure 70 specific cell health phenotypes including proliferation, apoptosis, reactive oxygen species, DNA damage, and cell cycle stage. We then tested an approach to predict multiple cell health phenotypes using Cell Painting, an inexpensive and scalable image-based morphology assay. In matched CRISPR perturbations of three cancer cell lines, we collected both Cell Painting and cell health data. We found that simple machine learning algorithms can predict many cell health readouts directly from Cell Painting images, at less than half the cost. We hypothesized that these models can be applied to accurately predict cell health assay outcomes for any future or existing Cell Painting dataset. For Cell Painting images from a set of 1500+ compound perturbations across multiple doses, we validated predictions by orthogonal assay readouts. We provide a web app to browse predictions: http://broad.io/cell-health-app. Our approach can be used to add cell health annotations to Cell Painting datasets.

Targeting a Braf/Mapk pathway rescues podocyte lipid peroxidation in CoQ-deficiency kidney disease.

Mutations affecting mitochondrial coenzyme Q (CoQ) biosynthesis lead to kidney failure due to selective loss of podocytes, essential cells of the kidney filter. Curiously, neighboring tubular epithelial cells are spared early in disease despite higher mitochondrial content. We sought to illuminate noncanonical, cell-specific roles for CoQ, independently of the electron transport chain (ETC). Here, we demonstrate that CoQ depletion caused by Pdss2 enzyme deficiency in podocytes results in perturbations in polyunsaturated fatty acid (PUFA) metabolism and the Braf/Mapk pathway rather than ETC dysfunction. Single-nucleus RNA-Seq from kidneys of Pdss2kd/kd mice with nephrotic syndrome and global CoQ deficiency identified a podocyte-specific perturbation of the Braf/Mapk pathway. Treatment with GDC-0879, a Braf/Mapk-targeting compound, ameliorated kidney disease in Pdss2kd/kd mice. Mechanistic studies in Pdss2-depleted podocytes revealed a previously unknown perturbation in PUFA metabolism that was confirmed in vivo. Gpx4, an enzyme that protects against PUFA-mediated lipid peroxidation, was elevated in disease and restored after GDC-0879 treatment. We demonstrate broader human disease relevance by uncovering patterns of GPX4 and Braf/Mapk pathway gene expression in tissue from patients with kidney diseases. Our studies reveal ETC-independent roles for CoQ in podocytes and point to Braf/Mapk as a candidate pathway for the treatment of kidney diseases.

A High-Content Screen for Mucin-1-Reducing Compounds Identifies Fostamatinib as a Candidate for Rapid Repurposing for Acute Lung Injury.

Drug repurposing has the advantage of identifying potential treatments on a shortened timescale. In response to the pandemic spread of SARS-CoV-2, we took advantage of a high-content screen of 3,713 compounds at different stages of clinical development to identify FDA-approved compounds that reduce mucin-1 (MUC1) protein abundance. Elevated MUC1 levels predict the development of acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) and correlate with poor clinical outcomes. Our screen identifies fostamatinib (R788), an inhibitor of spleen tyrosine kinase (SYK) approved for the treatment of chronic immune thrombocytopenia, as a repurposing candidate for the treatment of ALI. In vivo, fostamatinib reduces MUC1 abundance in lung epithelial cells in a mouse model of ALI. In vitro, SYK inhibition by the active metabolite R406 promotes MUC1 removal from the cell surface. Our work suggests fostamatinib as a repurposing drug candidate for ALI.

TFEB Transcriptional Responses Reveal Negative Feedback by BHLHE40 and BHLHE41.

Transcription factor EB (TFEB) activates lysosomal biogenesis genes in response to environmental cues. Given implications of impaired TFEB signaling and lysosomal dysfunction in metabolic, neurological, and infectious diseases, we aim to systematically identify TFEB-directed circuits by examining transcriptional responses to TFEB subcellular localization and stimulation. We reveal that steady-state nuclear TFEB is sufficient to activate transcription of lysosomal, autophagy, and innate immunity genes, whereas other targets require higher thresholds of stimulation. Furthermore, we identify shared and distinct transcriptional signatures between mTOR inhibition and bacterial autophagy. Using a genome-wide CRISPR library, we find TFEB targets that protect cells from or sensitize cells to lysosomal cell death. BHLHE40 and BHLHE41, genes responsive to high, sustained levels of nuclear TFEB, act in opposition to TFEB upon lysosomal cell death induction. Further investigation identifies genes counter-regulated by TFEB and BHLHE40/41, adding this negative feedback to the current understanding of TFEB regulatory mechanisms.

A High Content Screen for Mucin-1-Reducing Compounds Identifies Fostamatinib as a Candidate for Rapid Repurposing for Acute Lung Injury during the COVID-19 pandemic.

Drug repurposing is the only method capable of delivering treatments on the shortened time-scale required for patients afflicted with lung disease arising from SARS-CoV-2 infection. Mucin-1 (MUC1), a membrane-bound molecule expressed on the apical surfaces of most mucosal epithelial cells, is a biochemical marker whose elevated levels predict the development of acute lung injury (ALI) and respiratory distress syndrome (ARDS), and correlate with poor clinical outcomes. In response to the pandemic spread of SARS-CoV-2, we took advantage of a high content screen of 3,713 compounds at different stages of clinical development to identify FDA-approved compounds that reduce MUC1 protein abundance. Our screen identified Fostamatinib (R788), an inhibitor of spleen tyrosine kinase (SYK) approved for the treatment of chronic immune thrombocytopenia, as a repurposing candidate for the treatment of ALI. In vivo , Fostamatinib reduced MUC1 abundance in lung epithelial cells in a mouse model of ALI. In vitro , SYK inhibition by Fostamatinib promoted MUC1 removal from the cell surface. Our work reveals Fostamatinib as a repurposing drug candidate for ALI and provides the rationale for rapidly standing up clinical trials to test Fostamatinib efficacy in patients with COVID-19 lung injury.

Single cell census of human kidney organoids shows reproducibility and diminished off-target cells after transplantation.

Human iPSC-derived kidney organoids have the potential to revolutionize discovery, but assessing their consistency and reproducibility across iPSC lines, and reducing the generation of off-target cells remain an open challenge. Here, we profile four human iPSC lines for a total of 450,118 single cells to show how organoid composition and development are comparable to human fetal and adult kidneys. Although cell classes are largely reproducible across time points, protocols, and replicates, we detect variability in cell proportions between different iPSC lines, largely due to off-target cells. To address this, we analyze organoids transplanted under the mouse kidney capsule and find diminished off-target cells. Our work shows how single cell RNA-seq (scRNA-seq) can score organoids for reproducibility, faithfulness and quality, that kidney organoids derived from different iPSC lines are comparable surrogates for human kidney, and that transplantation enhances their formation by diminishing off-target cells.

Small Molecule Targets TMED9 and Promotes Lysosomal Degradation to Reverse Proteinopathy.

Intracellular accumulation of misfolded proteins causes toxic proteinopathies, diseases without targeted therapies. Mucin 1 kidney disease (MKD) results from a frameshift mutation in the MUC1 gene (MUC1-fs). Here, we show that MKD is a toxic proteinopathy. Intracellular MUC1-fs accumulation activated the ATF6 unfolded protein response (UPR) branch. We identified BRD4780, a small molecule that clears MUC1-fs from patient cells, from kidneys of knockin mice and from patient kidney organoids. MUC1-fs is trapped in TMED9 cargo receptor-containing vesicles of the early secretory pathway. BRD4780 binds TMED9, releases MUC1-fs, and re-routes it for lysosomal degradation, an effect phenocopied by TMED9 deletion. Our findings reveal BRD4780 as a promising lead for the treatment of MKD and other toxic proteinopathies. Generally, we elucidate a novel mechanism for the entrapment of misfolded proteins by cargo receptors and a strategy for their release and anterograde trafficking to the lysosome.

Discovering metabolic disease gene interactions by correlated effects on cellular morphology.

OBJECTIVE: Impaired expansion of peripheral fat contributes to the pathogenesis of insulin resistance and Type 2 Diabetes (T2D). We aimed to identify novel disease-gene interactions during adipocyte differentiation. METHODS: Genes in disease-associated loci for T2D, adiposity and insulin resistance were ranked according to expression in human adipocytes. The top 125 genes were ablated in human pre-adipocytes via CRISPR/CAS9 and the resulting cellular phenotypes quantified during adipocyte differentiation with high-content microscopy and automated image analysis. Morphometric measurements were extracted from all images and used to construct morphologic profiles for each gene. RESULTS: Over 107 morphometric measurements were obtained. Clustering of the morphologic profiles accross all genes revealed a group of 14 genes characterized by decreased lipid accumulation, and enriched for known lipodystrophy genes. For two lipodystrophy genes, BSCL2 and AGPAT2, sub-clusters with PLIN1 and CEBPA identifed by morphological similarity were validated by independent experiments as novel protein-protein and gene regulatory interactions. CONCLUSIONS: A morphometric approach in adipocytes can resolve multiple cellular mechanisms for metabolic disease loci; this approach enables mechanistic interrogation of the hundreds of metabolic disease loci whose function still remains unknown.