Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution.

Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable "developed" state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.

Convergence of multiple RNA-silencing pathways on GW182/TNRC6.

The RNA-binding protein TRIM71/LIN-41 is a phylogenetically conserved developmental regulator that functions in mammalian stem cell reprogramming, brain development, and cancer. TRIM71 recognizes target mRNAs through hairpin motifs and silences them through molecular mechanisms that await identification. Here, we uncover that TRIM71 represses its targets through RNA-supported interaction with TNRC6/GW182, a core component of the miRNA-induced silencing complex (miRISC). We demonstrate that AGO2, TRIM71, and UPF1 each recruit TNRC6 to specific sets of transcripts to silence them. As cellular TNRC6 levels are limiting, competition occurs among the silencing pathways, such that the loss of AGO proteins or of AGO binding to TNRC6 enhances the activities of the other pathways. We conclude that a miRNA-like silencing activity is shared among different mRNA silencing pathways and that the use of TNRC6 as a central hub provides a means to integrate their activities.

Loss of Hepatic Leucine-Rich Repeat-Containing G-Protein Coupled Receptors 4 and 5 Promotes Nonalcoholic Fatty Liver Disease.

The roof plate-specific spondin-leucine-rich repeat-containing G-protein coupled receptor 4/5 (LGR4/5)-zinc and ring finger 3 (ZNRF3)/ring finger protein 43 (RNF43) module is a master regulator of hepatic Wnt/ß-catenin signaling and metabolic zonation. However, its impact on nonalcoholic fatty liver disease (NAFLD) remains unclear. The current study investigated whether hepatic epithelial cell-specific loss of the Wnt/ß-catenin modulator Lgr4/5 promoted NAFLD. The 3- and 6-month-old mice with hepatic epithelial cell-specific deletion of both receptors Lgr4/5 (Lgr4/5dLKO) were compared with control mice fed with normal diet (ND) or high-fat diet (HFD). Six-month-old HFD-fed Lgr4/5dLKO mice developed hepatic steatosis and fibrosis but the control mice did not. Serum cholesterol-high-density lipoprotein and total cholesterol levels in 3- and 6-month-old HFD-fed Lgr4/5dLKO mice were decreased compared with those in control mice. An ex vivo primary hepatocyte culture assay and a comprehensive bile acid (BA) characterization in liver, plasma, bile, and feces demonstrated that ND-fed Lgr4/5dLKO mice had impaired BA secretion, predisposing them to develop cholestatic characteristics. Lipidome and RNA-sequencing analyses demonstrated severe alterations in several lipid species and pathways controlling lipid metabolism in the livers of Lgr4/5dLKO mice. In conclusion, loss of hepatic Wnt/ß-catenin activity by Lgr4/5 deletion led to loss of BA secretion, cholestatic features, altered lipid homeostasis, and deregulation of lipoprotein pathways. Both BA and intrinsic lipid alterations contributed to the onset of NAFLD.

BET bromodomain inhibitors regulate keratinocyte plasticity.

Although most acute skin wounds heal rapidly, non-healing skin ulcers represent an increasing and substantial unmet medical need that urgently requires effective therapeutics. Keratinocytes resurface wounds to re-establish the epidermal barrier by transitioning to an activated, migratory state, but this ability is lost in dysfunctional chronic wounds. Small-molecule regulators of keratinocyte plasticity with the potential to reverse keratinocyte malfunction in situ could offer a novel therapeutic approach in skin wound healing. Utilizing high-throughput phenotypic screening of primary keratinocytes, we identify such small molecules, including bromodomain and extra-terminal domain (BET) protein family inhibitors (BETi). BETi induce a sustained activated, migratory state in keratinocytes in vitro, increase activation markers in human epidermis ex vivo and enhance skin wound healing in vivo. Our findings suggest potential clinical utility of BETi in promoting keratinocyte re-epithelialization of skin wounds. Importantly, this novel property of BETi is exclusively observed after transient low-dose exposure, revealing new potential for this compound class.

Non-invasive candidate protein signature predicts hepatic venous pressure gradient reduction in cirrhotic patients after sustained virologic response.

BACKGROUND AND AIMS: A reduction in hepatic venous pressure gradient (HVPG) is the most accurate marker for assessing the severity of portal hypertension and the effectiveness of intervention treatments. This study aimed to evaluate the prognostic potential of blood-based proteomic biomarkers in predicting HVPG response amongst cirrhotic patients with portal hypertension due to Hepatitis C virus (HCV) and had achieved sustained virologic response (SVR). METHODS: The study comprised 59 patients from two cohorts. Patients underwent paired HVPG (pretreatment and after SVR), liver stiffness (LSM), and enhanced liver fibrosis scores (ELF) measurements, as well as proteomics-based profiling on serum samples using SomaScan® at baseline (BL) and after SVR (EOS). Machine learning with feature selection (Caret, Random Forest and RPART) methods were performed to determine the proteins capable of classifying HVPG responders. Model performance was evaluated using AUROC (pROC R package). RESULTS: Patients were stratified by a change in HVPG (EOS vs. BL) into responders (greater than 20% decline in HVPG from BL, or <10 mmHg at EOS with >10 mmHg at BL) and non-responders. LSM and ELF decreased markedly after SVR but did not correlate with HVPG response. SomaScan (SomaLogic, Inc., Boulder, CO) analysis revealed a substantial shift in the peripheral proteome composition, reflected by 82 significantly differentially abundant proteins. Twelve proteins accurately distinguished responders from non-responders, with an AUROC of .86, sensitivity of 83%, specificity of 83%, accuracy of 83%, PPV of 83%, and NPV of 83%. CONCLUSIONS: A combined non-invasive soluble protein signature was identified, capable of accurately predicting HVPG response in HCV liver cirrhosis patients after achieving SVR.

Genome-wide CRISPR screen for PARKIN regulators reveals transcriptional repression as a determinant of mitophagy.

PARKIN, an E3 ligase mutated in familial Parkinson's disease, promotes mitophagy by ubiquitinating mitochondrial proteins for efficient engagement of the autophagy machinery. Specifically, PARKIN-synthesized ubiquitin chains represent targets for the PINK1 kinase generating phosphoS65-ubiquitin (pUb), which constitutes the mitophagy signal. Physiological regulation of PARKIN abundance, however, and the impact on pUb accumulation are poorly understood. Using cells designed to discover physiological regulators of PARKIN abundance, we performed a pooled genome-wide CRISPR/Cas9 knockout screen. Testing identified genes individually resulted in a list of 53 positive and negative regulators. A transcriptional repressor network including THAP11 was identified and negatively regulates endogenous PARKIN abundance. RNAseq analysis revealed the PARKIN-encoding locus as a prime THAP11 target, and THAP11 CRISPR knockout in multiple cell types enhanced pUb accumulation. Thus, our work demonstrates the critical role of PARKIN abundance, identifies regulating genes, and reveals a link between transcriptional repression and mitophagy, which is also apparent in human induced pluripotent stem cell-derived neurons, a disease-relevant cell type.

Data-Driven Derivation of an "Informer Compound Set" for Improved Selection of Active Compounds in High-Throughput Screening.

Despite the usefulness of high-throughput screening (HTS) in drug discovery, for some systems, low assay throughput or high screening cost can prohibit the screening of large numbers of compounds. In such cases, iterative cycles of screening involving active learning (AL) are employed, creating the need for smaller "informer sets" that can be routinely screened to build predictive models for selecting compounds from the screening collection for follow-up screens. Here, we present a data-driven derivation of an informer compound set with improved predictivity of active compounds in HTS, and we validate its benefit over randomly selected training sets on 46 PubChem assays comprising at least 300,000 compounds and covering a wide range of assay biology. The informer compound set showed improvement in BEDROC(α = 100), PRAUC, and ROCAUC values averaged over all assays of 0.024, 0.014, and 0.016, respectively, compared to randomly selected training sets, all with paired t-test p-values <10(-15). A per-assay assessment showed that the BEDROC(α = 100), which is of particular relevance for early retrieval of actives, improved for 38 out of 46 assays, increasing the success rate of smaller follow-up screens. Overall, we showed that an informer set derived from historical HTS activity data can be employed for routine small-scale exploratory screening in an assay-agnostic fashion. This approach led to a consistent improvement in hit rates in follow-up screens without compromising scaffold retrieval. The informer set is adjustable in size depending on the number of compounds one intends to screen, as performance gains are realized for sets with more than 3,000 compounds, and this set is therefore applicable to a variety of situations. Finally, our results indicate that random sampling may not adequately cover descriptor space, drawing attention to the importance of the composition of the training set for predicting actives.

Multiple Genes Core to ERAD, Macroautophagy and Lysosomal Degradation Pathways Participate in the Proteostasis Response in α1-Antitrypsin Deficiency.

BACKGROUND & AIMS: In the classic form of α1-antitrypsin deficiency (ATD), the misfolded α1-antitrypsin Z (ATZ) variant accumulates in the endoplasmic reticulum (ER) of liver cells. A gain-of-function proteotoxic mechanism is responsible for chronic liver disease in a subgroup of homozygotes. Proteostatic response pathways, including conventional endoplasmic reticulum-associated degradation and autophagy, have been proposed as the mechanisms that allow cellular adaptation and presumably protection from the liver disease phenotype. Recent studies have concluded that a distinct lysosomal pathway called endoplasmic reticulum-to-lysosome completely supplants the role of the conventional macroautophagy pathway in degradation of ATZ. Here, we used several state-of-the-art approaches to characterize the proteostatic responses more fully in cellular systems that model ATD. METHODS: We used clustered regularly interspaced short palindromic repeats (CRISPR)-mediated genome editing coupled to a cell selection step by fluorescence-activated cell sorter to perform screening for proteostasis genes that regulate ATZ accumulation and combined that with selective genome editing in 2 other model systems. RESULTS: Endoplasmic reticulum-associated degradation genes are key early regulators and multiple autophagy genes, from classic as well as from ER-to-lysosome and other newly described ER-phagy pathways, participate in degradation of ATZ in a manner that is temporally regulated and evolves as ATZ accumulation persists. Time-dependent changes in gene expression are accompanied by specific ultrastructural changes including dilation of the ER, formation of globular inclusions, budding of autophagic vesicles, and alterations in the overall shape and component parts of mitochondria. CONCLUSIONS: Macroautophagy is a critical component of the proteostasis response to cellular ATZ accumulation and it becomes more important over time as ATZ synthesis continues unabated. Multiple subtypes of macroautophagy and nonautophagic lysosomal degradative pathways are needed to respond to the high concentrations of misfolded protein that characterizes ATD and these pathways are attractive candidates for genetic variants that predispose to the hepatic phenotype.

Small molecule induced STING degradation facilitated by the HECT ligase HERC4.

Stimulator of interferon genes (STING) is a central component of the cytosolic nucleic acids sensing pathway and as such master regulator of the type I interferon response. Due to its critical role in physiology and its' involvement in a variety of diseases, STING has been a focus for drug discovery. Targeted protein degradation (TPD) has emerged as a promising pharmacology for targeting previously considered undruggable proteins by hijacking the cellular ubiquitin proteasome system (UPS) with small molecules. Here, we identify AK59 as a STING degrader leveraging HERC4, a HECT-domain E3 ligase. Additionally, our data reveals that AK59 is effective on the common pathological STING mutations, suggesting a potential clinical application of this mechanism. Thus, these findings introduce HERC4 to the fields of TPD and of compound-induced degradation of STING, suggesting potential therapeutic applications.

The transcription factor ZNF469 regulates collagen production in liver fibrosis.

Non-alcoholic fatty liver disease (NAFLD) - characterized by excess accumulation of fat in the liver - now affects one third of the world's population. As NAFLD progresses, extracellular matrix components including collagen accumulate in the liver causing tissue fibrosis, a major determinant of disease severity and mortality. To identify transcriptional regulators of fibrosis, we computationally inferred the activity of transcription factors (TFs) relevant to fibrosis by profiling the matched transcriptomes and epigenomes of 108 human liver biopsies from a deeply-characterized cohort of patients spanning the full histopathologic spectrum of NAFLD. CRISPR-based genetic knockout of the top 100 TFs identified ZNF469 as a regulator of collagen expression in primary human hepatic stellate cells (HSCs). Gain- and loss-of-function studies established that ZNF469 regulates collagen genes and genes involved in matrix homeostasis through direct binding to gene bodies and regulatory elements. By integrating multiomic large-scale profiling of human biopsies with extensive experimental validation we demonstrate that ZNF469 is a transcriptional regulator of collagen in HSCs. Overall, these data nominate ZNF469 as a previously unrecognized determinant of NAFLD-associated liver fibrosis.

Genome-wide screening in human kidney organoids identifies developmental and disease-related aspects of nephrogenesis.

Human organoids allow the study of proliferation, lineage specification, and 3D tissue development. Here we present a genome-wide CRISPR screen in induced pluripotent stem cell (iPSC)-derived kidney organoids. The combination of inducible genome editing, longitudinal sampling, and endpoint sorting of tubular and stromal cells generated a complex, high-quality dataset uncovering a broad spectrum of insightful biology from early development to "adult" epithelial morphogenesis. Our functional dataset allows improving mesoderm induction by ROCK inhibition, contains monogenetic and complex trait kidney disease genes, confirms two additional congenital anomalies of the kidney and urinary tract (CAKUT) genes (CCDC170 and MYH7B), and provides a large candidate list of ciliopathy-related genes. Finally, identification of a cis-inhibitory effect of Jagged1 controlling epithelial proliferation shows how mosaic knockouts in pooled CRISPR screening can reveal ways of communication between heterogeneous cell populations in complex tissues. These data serve as a rich resource for the kidney research community and as a benchmark for future iPSC-derived organoid CRISPR screens.

Activity-aware clustering of high throughput screening data and elucidation of orthogonal structure-activity relationships.

From a medicinal chemistry point of view, one of the primary goals of high throughput screening (HTS) hit list assessment is the identification of chemotypes with an informative structure-activity relationship (SAR). Such chemotypes may enable optimization of the primary potency, as well as selectivity and phamacokinetic properties. A common way to prioritize them is molecular clustering of the hits. Typical clustering techniques, however, rely on a general notion of chemical similarity or standard rules of scaffold decomposition and are thus insensitive to molecular features that are enriched in biologically active compounds. This hinders SAR analysis, because compounds sharing the same pharmacophore might not end up in the same cluster and thus are not directly compared to each other by the medicinal chemist. Similarly, common chemotypes that are not related to activity may contaminate clusters, distracting from important chemical motifs. We combined molecular similarity and Bayesian models and introduce (I) a robust, activity-aware clustering approach and (II) a feature mapping method for the elucidation of distinct SAR determinants in polypharmacologic compounds. We evaluated the method on 462 dose-response assays from the Pubchem Bioassay repository. Activity-aware clustering grouped compounds sharing molecular cores that were specific for the target or pathway at hand, rather than grouping inactive scaffolds commonly found in compound series. Many of these core structures we also found in literature that discussed SARs of the respective targets. A numerical comparison of cores allowed for identification of the structural prerequisites for polypharmacology, i.e., distinct bioactive regions within a single compound, and pointed toward selectivity-conferring medchem strategies. The method presented here is generally applicable to any type of activity data and may help bridge the gap between hit list assessment and designing a medchem strategy.

Classifying large chemical data sets: using a regularized potential function method.

In recent years classifiers generated with kernel-based methods, such as support vector machines (SVM), Gaussian processes (GP), regularization networks (RN), and binary kernel discrimination (BKD) have been very popular in chemoinformatics data analysis. Aizerman et al. were the first to introduce the notion of employing kernel-based classifiers in the area of pattern recognition. Their original scheme, which they termed the potential function method (PFM), can basically be viewed as a kernel-based perceptron procedure and arguably subsumes the modern kernel-based algorithms. PFM can be computationally much cheaper than modern kernel-based classifiers; furthermore, PFM is far simpler conceptually and easier to implement than the SVM, GP, and RN algorithms. Unfortunately, unlike, e.g., SVM, GP, and RN, PFM is not endowed with both theoretical guarantees and practical strategies to safeguard it against generating overfitting classifiers. This is, in our opinion, the reason why this simple and elegant method has not been taken up in chemoinformatics. In this paper we empirically address this drawback: while maintaining its simplicity, we demonstrate that PFM combined with a simple regularization scheme may yield binary classifiers that can be, in practice, as efficient as classifiers obtained by employing state-of-the-art kernel-based methods. Using a realistic classification example, the augmented PFM was used to generate binary classifiers. Using a large chemical data set, the generalization ability of PFM classifiers were then compared with the prediction power of Laplacian-modified naive Bayesian (LmNB), Winnow (WN), and SVM classifiers.

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information.

The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu.

Genome-wide CRISPR-Cas9 screens identify mechanisms of BET bromodomain inhibitor sensitivity.

BET bromodomain inhibitors hold promise as therapeutic agents in diverse indications, but their clinical progression has been challenging and none have received regulatory approval. Early clinical trials in cancer have shown heterogeneous clinical responses, development of resistance, and adverse events. Increased understanding of their mechanism(s) of action and identification of biomarkers are needed to identify appropriate indication(s) and achieve efficacious dosing. Using genome-wide CRISPR-Cas9 screens at different concentrations, we report molecular mechanisms defining cellular responses to BET inhibitors, some of which appear specific to a single compound concentration. We identify multiple transcriptional regulators and mTOR pathway members as key determinants of JQ1 sensitivity and two Ca2+/Mn2+ transporters, ATP2C1 and TMEM165, as key determinants of JQ1 resistance. Our study reveals new molecular mediators of BET bromodomain inhibitor effects, suggests the involvement of manganese, and provides a rich resource for discovery of biomarkers and targets for combination therapies.

Single-cell and bulk transcriptomics of the liver reveals potential targets of NASH with fibrosis.

Fibrosis is characterized by the excessive production of collagen and other extracellular matrix (ECM) components and represents a leading cause of morbidity and mortality worldwide. Previous studies of nonalcoholic steatohepatitis (NASH) with fibrosis were largely restricted to bulk transcriptome profiles. Thus, our understanding of this disease is limited by an incomplete characterization of liver cell types in general and hepatic stellate cells (HSCs) in particular, given that activated HSCs are the major hepatic fibrogenic cell population. To help fill this gap, we profiled 17,810 non-parenchymal cells derived from six healthy human livers. In conjunction with public single-cell data of fibrotic/cirrhotic human livers, these profiles enable the identification of potential intercellular signaling axes (e.g., ITGAV-LAMC1, TNFRSF11B-VWF and NOTCH2-DLL4) and master regulators (e.g., RUNX1 and CREB3L1) responsible for the activation of HSCs during fibrogenesis. Bulk RNA-seq data of NASH patient livers and rodent models for liver fibrosis of diverse etiologies allowed us to evaluate the translatability of candidate therapeutic targets for NASH-related fibrosis. We identified 61 liver fibrosis-associated genes (e.g., AEBP1, PRRX1 and LARP6) that may serve as a repertoire of translatable drug target candidates. Consistent with the above regulon results, gene regulatory network analysis allowed the identification of CREB3L1 as a master regulator of many of the 61 genes. Together, this study highlights potential cell-cell interactions and master regulators that underlie HSC activation and reveals genes that may represent prospective hallmark signatures for liver fibrosis.

Farnesoid X Receptor Agonism, Acetyl-Coenzyme A Carboxylase Inhibition, and Back Translation of Clinically Observed Endpoints of De Novo Lipogenesis in a Murine NASH Model.

A promising approach for the treatment of nonalcoholic steatohepatitis (NASH) is the inhibition of enhanced hepatic de novo lipogenesis (DNL), which is the synthesis of fatty acids from nonlipid sources. This study assesses three approaches to DNL suppression in a newly developed dietary NASH mouse model: i) dietary intervention (switch from NASH-inducing diet to normal diet); ii) inhibition of acetyl-coenzyme A carboxylase (ACC), the enzyme catalyzing the rate-limiting step in DNL; and iii) activation of farnesoid X receptor (FXR), a major transcriptional regulator of DNL. C57BL/6J mice on a high-fat diet combined with ad libitum consumption of a fructose-sucrose solution developed several of the liver histologic features seen in human disease, including steatosis, inflammation, and fibrosis, accompanied by elevated fibrosis biomarkers and liver injury enzymes. Obesity and metabolic impairments were associated with increased intestinal permeability and progression to adenoma and hepatocellular carcinoma. All three approaches led to resolution of established NASH with fibrosis in mice; however, some differences were noted, e.g., with respect to the degree of hepatic steatosis attenuation. While ACC inhibition resulted in elevated blood triglycerides and peripheral obesity, FXR activation prevented peripheral obesity in NASH mice. Comparative transcriptome analysis underlined the translatability of the mouse model to human NASH and revealed novel mechanistic insights into differential regulation of lipid, inflammatory, and extracellular matrix pathways by FXR agonism and ACC inhibition. Conclusion: Novel insights are provided on back translation of clinically observed endpoints of DNL inhibition by targeting ACC or FXR, which are promising therapeutic options for the treatment of NASH, in a newly developed diet-induced NASH mouse model.

Systematic Chemogenetic Library Assembly.

Chemogenetic libraries, collections of well-defined chemical probes, provide tremendous value to biomedical research but require substantial effort to ensure diversity as well as quality of the contents. We have assembled a chemogenetic library by data mining and crowdsourcing institutional expertise. We are sharing our approach, lessons learned, and disclosing our current collection of 4,185 compounds with their primary annotated gene targets (https://github.com/Novartis/MoaBox). This physical collection is regularly updated and used broadly both within Novartis and in collaboration with external partners.

CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data.

We develop CellSIUS (Cell Subtype Identification from Upregulated gene Sets) to fill a methodology gap for rare cell population identification for scRNA-seq data. CellSIUS outperforms existing algorithms for specificity and selectivity for rare cell types and their transcriptomic signature identification in synthetic and complex biological data. Characterization of a human pluripotent cell differentiation protocol recapitulating deep-layer corticogenesis using CellSIUS reveals unrecognized complexity in human stem cell-derived cellular populations. CellSIUS enables identification of novel rare cell populations and their signature genes providing the means to study those populations in vitro in light of their role in health and disease.

IRF2 is a master regulator of human keratinocyte stem cell fate.

Resident adult epithelial stem cells maintain tissue homeostasis by balancing self-renewal and differentiation. The stem cell potential of human epidermal keratinocytes is retained in vitro but lost over time suggesting extrinsic and intrinsic regulation. Transcription factor-controlled regulatory circuitries govern cell identity, are sufficient to induce pluripotency and transdifferentiate cells. We investigate whether transcriptional circuitry also governs phenotypic changes within a given cell type by comparing human primary keratinocytes with intrinsically high versus low stem cell potential. Using integrated chromatin and transcriptional profiling, we implicate IRF2 as antagonistic to stemness and show that it binds and regulates active cis-regulatory elements at interferon response and antigen presentation genes. CRISPR-KD of IRF2 in keratinocytes with low stem cell potential increases self-renewal, migration and epidermis formation. These data demonstrate that transcription factor regulatory circuitries, in addition to maintaining cell identity, control plasticity within cell types and offer potential for therapeutic modulation of cell function.