Hock Chuan Yeo

Mechanistic elements and critical factors of cellular reprogramming revealed by stepwise global gene expression analyses

A better understanding of the cellular and molecular mechanisms involved in the reprogramming of somatic cells is essential for further improvement of induced pluripotent stem (iPS) cell technology. In this study, we enriched for cells actively undergoing reprogramming at different time points by sorting the cells stained with a stem cell-selective fluorescent chemical probe CDy1 for their global gene expression analysis. Day-to-day comparison of differentially expressed genes showed highly dynamic and transient gene expressions during reprogramming, which were largely distinct from those of fully-reprogrammed cells. An unbiased analysis of functional regulation indicated robust modulation of concurrent programs at critical junctures. Globally, transcriptional programs involved in cell proliferation, morphology and signal transduction were instantly triggered as early as 3 days-post-infection to prepare the cell for reprogramming but became somewhat muted in the final iPS cells. On the other hand, the highly coordinated metabolic reprogramming process was more gradually activated. Subsequent network analysis of differentially expressed genes indicated PDGF-BB as a core player in reprogramming which was verified by our gain- and loss-of-function experiments. As such, our study has revealed previously-unknown insights into the mechanisms of cellular reprogramming.

Enhanced production of neuroprogenitors, dopaminergic neurons, and identification of target genes by overexpression of sonic hedgehog in human embryonic stem cells.

Molecular and cellular signaling pathways are involved in the process of neural differentiation from human embryonic stem cells (hESC) to terminally differentiated neurons. The Sonic hedgehog (SHH) morphogen is required to direct the differentiation of hESC to several neural subtypes, for example, dopaminergic (DA) or motor neurons. However, the roles of SHH signaling and the pathway target genes that regulate the diversity of cellular responses arising from SHH activation during neurogenesis of hESC have yet to be elucidated. In this study, we report that overexpression of SHH in hESC promotes the derivation of neuroprogenitors (NP), increases proliferation of NP, and subsequently increases the yield of DA neurons. Next, gene expression changes resulting from the overexpression of SHH in hESC-derived NP were examined by genome-wide transcriptional profiling. Categorizing the differentially expressed genes according to the Gene Ontology biological processes showed that they are involved in numerous cellular processes, including neural development, NP proliferation, and neural specification. In silico GLI-binding sites analysis of the differentially expressed genes also identified a set of putative novel direct target genes of SHH in hESC-derived NP, which are involved in nervous system development. Electrophoretic mobility shift assays and promoter-luciferase assays confirmed that GLI1 binds to the promoter region and activates transcription of HEY2, a NOTCH signaling target gene. Taken together, our data provide evidence for the first time that there is cross-talk between the NOTCH and SHH signaling pathways in hESC-derived NP and also provide significant new insights into transcriptional targets in SHH-mediated neural differentiation of hESC.

Integrated Transcriptome and Binding Sites Analysis Implicates E2F in the Regulation of Self-Renewal in Human Pluripotent Stem Cells

Rapid cellular growth and multiplication, limited replicative senescence, calibrated sensitivity to apoptosis, and a capacity to differentiate into almost any cell type are major properties that underline the self-renewal capabilities of human pluripotent stem cells (hPSCs). We developed an integrated bioinformatics pipeline to understand the gene regulation and functions involved in maintaining such self-renewal properties of hPSCs compared to matched fibroblasts. An initial genome-wide screening of transcription factor activity using in silico binding-site and gene expression microarray data newly identified E2F as one of major candidate factors, revealing their significant regulation of the transcriptome. This is underscored by an elevated level of its transcription factor activity and expression in all tested pluripotent stem cell lines. Subsequent analysis of functional gene groups demonstrated the importance of the TFs to self-renewal in the pluripotency-coupled context; E2F directly targets the global signaling (e.g. self-renewal associated WNT and FGF pathways) and metabolic network (e.g. energy generation pathways, molecular transports and fatty acid metabolism) to promote its canonical functions that are driving the self-renewal of hPSCs. In addition, we proposed a core self-renewal module of regulatory interplay between E2F and, WNT and FGF pathways in these cells. Thus, we conclude that E2F plays a significant role in influencing the self-renewal capabilities of hPSCs.

Patterns of cis-element enrichment reveal potential regulatory modules involved in the transcriptional regulation of anoxia response of japonica rice

Unlike other cereal species, rice is able to germinate and elongate under anoxia. The regulatory mechanism that configures the transcriptome of rice during anaerobic germination is yet to be established. In this study, the major regulatory modules among anoxia-responsive genes in rice identified from published microarray data were predicted by ab initio analysis of cis-regulatory information content. Statistically overrepresented sequence motifs were detected from bona fide promoter sequences [-1000 to +200], revealing various patterns of cis-element enrichment that are highly correlated with bZIP, ERF and MYB types of transcription factors. As implied by the cis-element enrichment patterns, combinatorial mechanisms configure the overall changes in gene expression during anoxic germination and coleoptile elongation. High enrichment of cis-elements associated with ARF, bZIP, ERF, MYB and WRKY (SUSIBA2) transcription factors was also detected among the glycolytic and fermentative associated genes that were upregulated during anoxia. The patterns established from the global analysis of cis-element distribution for upregulated and downregulated genes and their associations with potential cognate regulatory transcription factors indicate the significant roles of ethylene and abscisic acid mediated signaling during coleoptile elongation under anoxia. In addition, the regulation of genes encoding enzymes in the glycolytic and fermentative metabolism could be associated with abscisic acid and auxin in rice coleoptiles to maintain sugar and ATP levels for longer survival.

WEbcoli: an interactive and asynchronous web application for in silico design and analysis of genome-scale E.coli model

SUMMARY WEbcoli is a WEb application for in silico designing, analyzing and engineering Escherichia coli metabolism. It is devised and implemented using advanced web technologies, thereby leading to enhanced usability and dynamic web accessibility. As a main feature, the WEbcoli system provides a user-friendly rich web interface, allowing users to virtually design and synthesize mutant strains derived from the genome-scale wild-type E.coli model and to customize pathways of interest through a graph editor. In addition, constraints-based flux analysis can be conducted for quantifying metabolic fluxes and charactering the physiological and metabolic states under various genetic and/or environmental conditions. AVAILABILITY WEbcoli is freely accessible at http://webcoli.org. CONTACT cheld@nus.edu.sg.

Precursor mass prediction by clustering ionization products in LC-MS-based metabolomics

Liquid chromatography-mass spectrometry (LC-MS) is becoming the dominant technology in metabolomics, involving the comprehensive analysis of small molecules in biological systems. However, its use is still limited mainly by challenges in global high-throughput identification of metabolites: LC-MS data is highly complex, particularly due to the formation of multiple ionization products from individual metabolites. To address the limitation in metabolite identification, we developed a principled approach, designed to exploit the multi-dimensional information hidden in the data. The workflow first clusters candidate ionization products of the same metabolite together which typically have similar retention time, then searches for mass relationships among them in order to determine their ion types and metabolite identity. The robustness of our approach was demonstrated by its application to the LC-MS profiles of cell culture supernatant, which accurately predicted most of the known media components in the samples. Compared to conventional methods, our approach was able to generate significantly fewer candidate metabolites without missing out valid ones, thus reducing false-positive matches. Additionally, improved confidence in identification is achieved since each prediction comes with a probable combination of known ion types. Hence, our integrative workflow provides precursor mass predictions with high confidence by identifying various ionization products which account for a large proportion of detected peaks, thus minimizing false positives.

Genome-Wide Transcriptome and Binding Sites Analyses Identify Early FOX Expressions for Enhancing Cardiomyogenesis Efficiency of hESC Cultures

The differentiation efficiency of human embryonic stem cells (hESCs) into heart muscle cells (cardiomyocytes) is highly sensitive to culture conditions. To elucidate the regulatory mechanisms involved, we investigated hESCs grown on three distinct culture platforms: feeder-free Matrigel, mouse embryonic fibroblast feeders, and Matrigel replated on feeders. At the outset, we profiled and quantified their differentiation efficiency, transcriptome, transcription factor binding sites and DNA-methylation. Subsequent genome-wide analyses allowed us to reconstruct the relevant interactome, thereby forming the regulatory basis for implicating the contrasting differentiation efficiency of the culture conditions. We hypothesized that the parental expressions of FOXC1, FOXD1 and FOXQ1 transcription factors (TFs) are correlative with eventual cardiomyogenic outcome. Through WNT induction of the FOX TFs, we observed the co-activation of WNT3 and EOMES which are potent inducers of mesoderm differentiation. The result strengthened our hypothesis on the regulatory role of the FOX TFs in enhancing mesoderm differentiation capacity of hESCs. Importantly, the final proportions of cells expressing cardiac markers were directly correlated to the strength of FOX inductions within 72 hours after initiation of differentiation across different cell lines and protocols. Thus, we affirmed the relationship between early FOX TF expressions and cardiomyogenesis efficiency.

An LC–MS-based lipidomics pre-processing framework underpins rapid hypothesis generation towards CHO systems biotechnology

IntroductionGiven a raw LC–MS dataset, it is often required to rapidly generate initial hypotheses, in conjunction with other ‘omics’ datasets, without time-consuming lipid verifications. Furthermore, for meta-analysis of many datasets, it may be impractical to conduct exhaustive confirmatory analyses. In other cases, samples for validation may be difficult to obtain, replicate or maintain. Thus, it is critical that the computational identification of lipids is of appropriate accuracy, coverage, and unbiased by a researcher’s experience and prior knowledge.ObjectivesWe aim to prescribe a systematic framework for lipid identifications, without usage of their characteristic retention-time by fully exploiting their underlying mass features.ResultsInitially, a hybrid technique, for deducing both common and distinctive daughter ions, is used to infer parent lipids from deconvoluted spectra. This is followed by parent confirmation using basic knowledge of their preferred product ions. Using the framework, we could achieve an accuracy of ~ 80% by correctly identified 101 species from 18 classes in Chinese hamster ovary (CHO) cells. The resulting inferences could explain the recombinant-producing capability of CHO-SH87 cells, compared to non-producing CHO-K1 cells. For comparison, a XCMS-based study of the same dataset, guided by a user’s ad-hoc knowledge, identified less than 60 species of 12 classes from thousands of possibilities.ConclusionWe describe a systematic LC–MS-based framework that identifies lipids for rapid hypothesis generation.