Yuliang Wang

Reconstruction of genome-scale metabolic models for 126 human tissues using mCADRE

BackgroundHuman tissues perform diverse metabolic functions. Mapping out these tissue-specific functions in genome-scale models will advance our understanding of the metabolic basis of various physiological and pathological processes. The global knowledgebase of metabolic functions categorized for the human genome (Human Recon 1) coupled with abundant high-throughput data now makes possible the reconstruction of tissue-specific metabolic models. However, the number of available tissue-specific models remains incomplete compared with the large diversity of human tissues.ResultsWe developed a method called metabolic Context-specificity Assessed by Deterministic Reaction Evaluation (mCADRE). mCADRE is able to infer a tissue-specific network based on gene expression data and metabolic network topology, along with evaluation of functional capabilities during model building. mCADRE produces models with similar or better functionality and achieves dramatic computational speed up over existing methods. Using our method, we reconstructed draft genome-scale metabolic models for 126 human tissue and cell types. Among these, there are models for 26 tumor tissues along with their normal counterparts, and 30 different brain tissues. We performed pathway-level analyses of this large collection of tissue-specific models and identified the eicosanoid metabolic pathway, especially reactions catalyzing the production of leukotrienes from arachidnoic acid, as potential drug targets that selectively affect tumor tissues.ConclusionsThis large collection of 126 genome-scale draft metabolic models provides a useful resource for studying the metabolic basis for a variety of human diseases across many tissues. The functionality of the resulting models and the fast computational speed of the mCADRE algorithm make it a useful tool to build and update tissue-specific metabolic models.

Molecular signatures from omics data: From chaos to consensus

In the past 15 years, new “omics” technologies have made it possible to obtain high‐resolution molecular snapshots of organisms, tissues, and even individual cells at various disease states and experimental conditions. It is hoped that these developments will usher in a new era of personalized medicine in which an individuals molecular measurements are used to diagnose disease, guide therapy, and perform other tasks more accurately and effectively than is possible using standard approaches. There now exists a vast literature of reported “molecular signatures”. However, despite some notable exceptions, many of these signatures have suffered from limited reproducibility in independent datasets, insufficient sensitivity or specificity to meet clinical needs, or other challenges. In this paper, we discuss the process of molecular signature discovery on the basis of omics data. In particular, we highlight potential pitfalls in the discovery process, as well as strategies that can be used to increase the odds of successful discovery. Despite the difficulties that have plagued the field of molecular signature discovery, we remain optimistic about the potential to harness the vast amounts of available omics data in order to substantially impact clinical practice.

Integrated Genomic Analysis of Diverse Induced Pluripotent Stem Cells from the Progenitor Cell Biology Consortium

Summary The rigorous characterization of distinct induced pluripotent stem cells (iPSC) derived from multiple reprogramming technologies, somatic sources, and donors is required to understand potential sources of variability and downstream potential. To achieve this goal, the Progenitor Cell Biology Consortium performed comprehensive experimental and genomic analyses of 58 iPSC from ten laboratories generated using a variety of reprogramming genes, vectors, and cells. Associated global molecular characterization studies identified functionally informative correlations in gene expression, DNA methylation, and/or copy-number variation among key developmental and oncogenic regulators as a result of donor, sex, line stability, reprogramming technology, and cell of origin. Furthermore, X-chromosome inactivation in PSC produced highly correlated differences in teratoma-lineage staining and regulator expression upon differentiation. All experimental results, and raw, processed, and metadata from these analyses, including powerful tools, are interactively accessible from a new online portal at https://www.synapse.org to serve as a reusable resource for the stem cell community.

Transcriptomic, proteomic, and metabolomic landscape of positional memory in the caudal fin of zebrafish.

Significance In vertebrates, proper patterning during appendage regeneration is regulated by positional memory—a cellular property hypothesized to rely on gradients of molecules present in uninjured limbs. Only one gene, exclusive to salamanders, has been shown to regulate positional memory and be expressed in a gradient in the uninjured limb. To identify new candidate effectors of positional memory, we mapped the abundance of RNAs, proteins, and metabolites along the uninjured zebrafish tail fin. We identified hundreds of molecular gradients and generated a high-confidence list of 32 genes and 42 metabolites that are candidate effectors of positional memory in zebrafish. Furthermore, expression patterns discovered here may help to explain how size-homeostasis and patterning are maintained in a complex adult tissue. Regeneration requires cells to regulate proliferation and patterning according to their spatial position. Positional memory is a property that enables regenerating cells to recall spatial information from the uninjured tissue. Positional memory is hypothesized to rely on gradients of molecules, few of which have been identified. Here, we quantified the global abundance of transcripts, proteins, and metabolites along the proximodistal axis of caudal fins of uninjured and regenerating adult zebrafish. Using this approach, we uncovered complex overlapping expression patterns for hundreds of molecules involved in diverse cellular functions, including development, bioelectric signaling, and amino acid and lipid metabolism. Moreover, 32 genes differentially expressed at the RNA level had concomitant differential expression of the encoded proteins. Thus, the identification of proximodistal differences in levels of RNAs, proteins, and metabolites will facilitate future functional studies of positional memory during appendage regeneration.

Metabolic remodeling in early development and cardiomyocyte maturation

Aberrations in metabolism contribute to a large number of diseases, such as diabetes, obesity, cancer, and cardiovascular diseases, that have a substantial impact on the mortality rates and quality of life worldwide. However, the mechanisms leading to these changes in metabolic state--and whether they are conserved between diseases--is not well understood. Changes in metabolism similar to those seen in pathological conditions are observed during normal development in a number of different cell types. This provides hope that understanding the mechanism of these metabolic switches in normal development may provide useful insight in correcting them in pathological cases. Here, we focus on the metabolic remodeling observed both in early stage embryonic stem cells and during the maturation of cardiomyocytes.

Multi-study Integration of Brain Cancer Transcriptomes Reveals Organ-Level Molecular Signatures

We utilized abundant transcriptomic data for the primary classes of brain cancers to study the feasibility of separating all of these diseases simultaneously based on molecular data alone. These signatures were based on a new method reported herein – Identification of Structured Signatures and Classifiers (ISSAC) – that resulted in a brain cancer marker panel of 44 unique genes. Many of these genes have established relevance to the brain cancers examined herein, with others having known roles in cancer biology. Analyses on large-scale data from multiple sources must deal with significant challenges associated with heterogeneity between different published studies, for it was observed that the variation among individual studies often had a larger effect on the transcriptome than did phenotype differences, as is typical. For this reason, we restricted ourselves to studying only cases where we had at least two independent studies performed for each phenotype, and also reprocessed all the raw data from the studies using a unified pre-processing pipeline. We found that learning signatures across multiple datasets greatly enhanced reproducibility and accuracy in predictive performance on truly independent validation sets, even when keeping the size of the training set the same. This was most likely due to the meta-signature encompassing more of the heterogeneity across different sources and conditions, while amplifying signal from the repeated global characteristics of the phenotype. When molecular signatures of brain cancers were constructed from all currently available microarray data, 90% phenotype prediction accuracy, or the accuracy of identifying a particular brain cancer from the background of all phenotypes, was found. Looking forward, we discuss our approach in the context of the eventual development of organ-specific molecular signatures from peripheral fluids such as the blood.

LSD1 activates a lethal prostate cancer gene network independently of its demethylase function

Significance Medical castration or interference with androgen receptor (AR) function is the principal treatment for advanced prostate cancer. However, progression is universal, and therapies following the emergence of castration resistance do not offer durable control of the disease. Lysine-specific demethylase 1 (LSD1) is an important regulator of gene expression, including in cancer. Here, we show that LSD1 is highly expressed in tumors of patients with lethal castration-resistant prostate cancer (CRPC) and that LSD1 promotes AR-independent survival in CRPC cells in a noncanonical, demethylase-independent manner. We determined that the drug SP-2509 acts as an allosteric inhibitor of LSD1–blocking demethylase-independent functions. Our demonstration of tumor suppression with this inhibitor in CRPC preclinical models provides the rationale for clinical trials with LSD1 inhibitors. Medical castration that interferes with androgen receptor (AR) function is the principal treatment for advanced prostate cancer. However, clinical progression is universal, and tumors with AR-independent resistance mechanisms appear to be increasing in frequency. Consequently, there is an urgent need to develop new treatments targeting molecular pathways enriched in lethal prostate cancer. Lysine-specific demethylase 1 (LSD1) is a histone demethylase and an important regulator of gene expression. Here, we show that LSD1 promotes the survival of prostate cancer cells, including those that are castration-resistant, independently of its demethylase function and of the AR. Importantly, this effect is explained in part by activation of a lethal prostate cancer gene network in collaboration with LSD1’s binding protein, ZNF217. Finally, that a small-molecule LSD1 inhibitor―SP-2509―blocks important demethylase-independent functions and suppresses castration-resistant prostate cancer cell viability demonstrates the potential of LSD1 inhibition in this disease.

Chromatin and Transcriptional Analysis of Mesoderm Progenitor Cells Identifies HOPX as a Regulator of Primitive Hematopoiesis

We analyzed chromatin dynamics and transcriptional activity of human embryonic stem cell (hESC)-derived cardiac progenitor cells (CPCs) and KDR+/CD34+ endothelial cells generated from different mesodermal origins. Using an unbiased algorithm to hierarchically rank genes modulated at the level of chromatin and transcription, we identified candidate regulators of mesodermal lineage determination. HOPX, a non-DNA-binding homeodomain protein, was identified as a candidate regulator of blood-forming endothelial cells. Using HOPX reporter and knockout hESCs, we show that HOPX regulates blood formation. Loss of HOPX does not impact endothelial fate specification but markedly reduces primitive hematopoiesis, acting at least in part through failure to suppress Wnt/β-catenin signaling. Thus, chromatin state analysis permits identification of regulators of mesodermal specification, including a conserved role for HOPX in governing primitive hematopoiesis.

First critical repressive H3K27me3 marks in embryonic stem cells identified using designed protein inhibitor.

Significance We describe an approach to blocking protein–protein interactions in living cells and use it to probe the earliest stages of epigenetic regulation in stem cell differentiation. We describe a computationally designed protein that tightly binds EED and disrupts PRC2 function in both cancer and stem cells. Expression of the binder at different stem cell stages identifies the first critical repressive H3K27me3 mark in embryonic development. The polycomb repressive complex 2 (PRC2) histone methyltransferase plays a central role in epigenetic regulation in development and in cancer, and hence to interrogate its role in a specific developmental transition, methods are needed for disrupting function of the complex with high temporal and spatial precision. The catalytic and substrate recognition functions of PRC2 are coupled by binding of the N-terminal helix of the Ezh2 methylase to an extended groove on the EED trimethyl lysine binding subunit. Disrupting PRC2 function can in principle be achieved by blocking this single interaction, but there are few approaches for blocking specific protein–protein interactions in living cells and organisms. Here, we describe the computational design of proteins that bind to the EZH2 interaction site on EED with subnanomolar affinity in vitro and form tight and specific complexes with EED in living cells. Induction of the EED binding proteins abolishes H3K27 methylation in human embryonic stem cells (hESCs) and at all but the earliest stage blocks self-renewal, pinpointing the first critical repressive H3K27me3 marks in development.

Cardiac differentiation at single cell resolution reveals a requirement of hypertrophic signaling for HOPX transcription

Differentiation into diverse cell lineages requires the orchestration of gene regulatory networks guiding diverse cell fate choices. Utilizing human pluripotent stem cells, we measured expression dynamics of 17,718 genes from 43,168 cells across five-time points over a thirty-day time-course of in vitro cardiac- directed differentiation. Unsupervised clustering and lineage prediction algorithms were used to map fate choices and transcriptional networks underlying cardiac differentiation. We leveraged this resource to identify strategies for controlling in vitro differentiation as it occurs in vivo. HOPX, a non-DNA binding homeodomain protein essential for heart development in vivo was identified as dysregulated in vitro derived cardiomyocytes. Utilizing genetic gain and loss of function approaches, we dissect the transcriptional complexity of the HOPX locus and identify the requirement of hypertrophic signaling for HOPX transcription in hPSC-derived cardiomyocytes. This work provides a single cell dissection of the transcriptional landscape of cardiac differentiation for broad applications of stem cells in cardiovascular biology.Differentiation into diverse cell lineages requires orchestration of gene regulatory networks guiding cell fate choices. Here, we present the dissection of cellular composition and gene networks from transcriptomic data of 43,168 cells across five discrete time points during cardiac-directed differentiation. We utilize unsupervised clustering and implement a lineage trajectory prediction algorithm that integrates transcription factor networks to predict cell fate progression of 15 subpopulations that correlate with germ layer and cardiovascular differentiation in vivo. These data reveal transcriptional networks underlying lineage derivation of mesoderm, definitive endoderm, vascular endothelium, cardiac precursors, and definitive cell types that comprise cardiomyocytes and a previously unrecognized cardiac outflow tract population. Single cell analysis of genetic regulators governing cardiac fate diversification identified the non-DNA binding homeodomain protein, HOPX, as functionally necessary for endothelial specification. Our findings further implicate dysregulation of HOPX during in vitro cardiac-directed differentiation underlying the molecular and physiological immaturity of stem cell-derived cardiomyocytes.