An Algorithm for Cellular Reprogramming

The day we understand the time evolution of subcellular elements at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology, providing data-guided frameworks that allow us to develop better predictions about and methods for control over specific biological processes and system-wide cell behavior. In this paper we describe an approach to optimizing the use of transcription factors in the context of cellular reprogramming. We construct an approximate model for the natural evolution of a synchronized population of fibroblasts, based on data obtained by sampling the expression of some 22,083 genes at several times along the cell cycle. (These data are based on a colony of cells that have been cell cycle synchronized) In order to arrive at a model of moderate complexity, we cluster gene expression based on the division of the genome into topologically associating domains (TADs) and then model the dynamics of the expression levels of the TADs. Based on this dynamical model and known bioinformatics, we develop a methodology for identifying the transcription factors that are the most likely to be effective toward a specific cellular reprogramming task. The approach used is based on a device commonly used in optimal control. From this data-guided methodology, we identify a number of validated transcription factors used in reprogramming and/or natural differentiation. Our findings highlight the immense potential of dynamical models models, mathematics, and data guided methodologies for improving methods for control over biological processes

Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes.

With defined culture protocol, human embryonic stem cells (hESCs) are able to generate cardiomyocytes in vitro, therefore providing a great model for human heart development, and holding great potential for cardiac disease therapies. In this study, we successfully generated a highly pure population of human cardiomyocytes (hCMs) (>95% cTnT(+)) from hESC line, which enabled us to identify and characterize an hCM-specific signature, at both the gene expression and DNA methylation levels. Gene functional association network and gene-disease network analyses of these hCM-enriched genes provide new insights into the mechanisms of hCM transcriptional regulation, and stand as an informative and rich resource for investigating cardiac gene functions and disease mechanisms. Moreover, we show that cardiac-structural genes and cardiac-transcription factors have distinct epigenetic mechanisms to regulate their gene expression, providing a better understanding of how the epigenetic machinery coordinates to regulate gene expression in different cell types

A stochastic model dissects cell states in biological transition processes

Many biological processes, including differentiation, reprogramming, and disease transformations, involve transitions of cells through distinct states. Direct, unbiased investigation of cell states and their transitions is challenging due to several factors, including limitations of single-cell assays. Here we present a stochastic model of cellular transitions that allows underlying single-cell information, including cell-state-specific parameters and rates governing transitions between states, to be estimated from genome-wide, population-averaged time-course data. The key novelty of our approach lies in specifying latent stochastic models at the single-cell level, and then aggregating these models to give a likelihood that links parameters at the single-cell level to observables at the population level. We apply our approach in the context of reprogramming to pluripotency. This yields new insights, including profiles of two intermediate cell states, that are supported by independent single-cell studies. Our model provides a general conceptual framework for the study of cell transitions, including epigenetic transformations

A Network of microRNAs Acts to Promote Cell Cycle Exit and Differentiation of Human Pancreatic Endocrine Cells.

Pancreatic endocrine cell differentiation is orchestrated by the action of transcription factors that operate in a gene regulatory network to activate endocrine lineage genes and repress lineage-inappropriate genes. MicroRNAs (miRNAs) are important modulators of gene expression, yet their role in endocrine cell differentiation has not been systematically explored. Here we characterize miRNA-regulatory networks active in human endocrine cell differentiation by combining small RNA sequencing, miRNA over-expression, and network modeling approaches. Our analysis identified Let-7g, Let-7a, miR-200a, miR-127, and miR-375 as endocrine-enriched miRNAs that drive endocrine cell differentiation-associated gene expression changes. These miRNAs are predicted to target different transcription factors, which converge on genes involved in cell cycle regulation. When expressed in human embryonic stem cell-derived pancreatic progenitors, these miRNAs induce cell cycle exit and promote endocrine cell differentiation. Our study delineates the role of miRNAs in human endocrine cell differentiation and identifies miRNAs that could facilitate endocrine cell reprogramming

Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection

Computationally retrieving biologically relevant cis-regulatory modules (CRMs) is not straightforward. Because of the large number of candidates and the imperfection of the screening methods, many spurious CRMs are detected that are as high scoring as the biologically true ones. Using ChIP-information allows not only to reduce the regions in which the binding sites of the assayed transcription factor (TF) should be located, but also allows restricting the valid CRMs to those that contain the assayed TF (here referred to as applying CRM detection in a query-based mode). In this study, we show that exploiting ChIP-information in a query-based way makes in silico CRM detection a much more feasible endeavor. To be able to handle the large datasets, the query-based setting and other specificities proper to CRM detection on ChIP-Seq based data, we developed a novel powerful CRM detection method 'CPModule'. By applying it on a well-studied ChIP-Seq data set involved in self-renewal of mouse embryonic stem cells, we demonstrate how our tool can recover combinatorial regulation of five known TFs that are key in the self-renewal of mouse embryonic stem cells. Additionally, we make a number of new predictions on combinatorial regulation of these five key TFs with other TFs documented in TRANSFAC

Suv4-20h Histone Methyltransferases Promote Neuroectodermal Differentiation by Silencing the Pluripotency-Associated Oct-25 Gene

Post-translational modifications (PTMs) of histones exert fundamental roles in regulating gene expression. During development, groups of PTMs are constrained by unknown mechanisms into combinatorial patterns, which facilitate transitions from uncommitted embryonic cells into differentiated somatic cell lineages. Repressive histone modifications such as H3K9me3 or H3K27me3 have been investigated in detail, but the role of H4K20me3 in development is currently unknown. Here we show that Xenopus laevis Suv4-20h1 and h2 histone methyltransferases (HMTases) are essential for induction and differentiation of the neuroectoderm. Morpholino-mediated knockdown of the two HMTases leads to a selective and specific downregulation of genes controlling neural induction, thereby effectively blocking differentiation of the neuroectoderm. Global transcriptome analysis supports the notion that these effects arise from the transcriptional deregulation of specific genes rather than widespread, pleiotropic effects. Interestingly, morphant embryos fail to repress the Oct4-related Xenopus gene Oct-25. We validate Oct-25 as a direct target of xSu4-20h enzyme mediated gene repression, showing by chromatin immunoprecipitaton that it is decorated with the H4K20me3 mark downstream of the promoter in normal, but not in double-morphant, embryos. Since knockdown of Oct-25 protein significantly rescues the neural differentiation defect in xSuv4-20h double-morphant embryos, we conclude that the epistatic relationship between Suv4-20h enzymes and Oct-25 controls the transit from pluripotent to differentiation-competent neural cells. Consistent with these results in Xenopus, murine Suv4-20h1/h2 double-knockout embryonic stem (DKO ES) cells exhibit increased Oct4 protein levels before and during EB formation, and reveal a compromised and biased capacity for in vitro differentiation, when compared to normal ES cells. Together, these results suggest a regulatory mechanism, conserved between amphibians and mammals, in which H4K20me3-dependent restriction of specific POU-V genes directs cell fate decisions, when embryonic cells exit the pluripotent state

microRNAs of parasitic helminths – identification, characterization and potential as drug targets

microRNAs (miRNAs) are small non-coding RNAs involved in post-transcriptional gene regulation. They were first identified in the free-living nematode Caenorhabditis elegans, where the miRNAs lin-4 and let-7 were shown to be essential for regulating correct developmental progression. The sequence of let-7 was subsequently found to be conserved in higher organisms and changes in expression of let-7, as well as other miRNAs, are associated with certain cancers, indicating important regulatory roles. Some miRNAs have been shown to have essential functions, but the roles of many are currently unknown. With the increasing availability of genome sequence data, miRNAs have now been identified from a number of parasitic helminths, by deep sequencing of small RNA libraries and bioinformatic approaches. While some miRNAs are widely conserved in a range of organisms, others are helminth-specific and many are novel to each species. Here we review the potential roles of miRNAs in regulating helminth development, in interacting with the host environment and in development of drug resistance. Use of fluorescently-labeled small RNAs demonstrates uptake by parasites, at least in vitro. Therefore delivery of miRNA inhibitors or mimics has potential to alter miRNA activity, providing a useful tool for probing the roles of miRNAs and suggesting novel routes to therapeutics for parasite control

Pax6 interactions with chromatin and identification of its novel direct target genes in lens and forebrain.

Pax6 encodes a specific DNA-binding transcription factor that regulates the development of multiple organs, including the eye, brain and pancreas. Previous studies have shown that Pax6 regulates the entire process of ocular lens development. In the developing forebrain, Pax6 is expressed in ventricular zone precursor cells and in specific populations of neurons; absence of Pax6 results in disrupted cell proliferation and cell fate specification in telencephalon. In the pancreas, Pax6 is essential for the differentiation of α-, β- and δ-islet cells. To elucidate molecular roles of Pax6, chromatin immunoprecipitation experiments combined with high-density oligonucleotide array hybridizations (ChIP-chip) were performed using three distinct sources of chromatin (lens, forebrain and β-cells). ChIP-chip studies, performed as biological triplicates, identified a total of 5,260 promoters occupied by Pax6. 1,001 (133) of these promoter regions were shared between at least two (three) distinct chromatin sources, respectively. In lens chromatin, 2,335 promoters were bound by Pax6. RNA expression profiling from Pax6⁺/⁻ lenses combined with in vivo Pax6-binding data yielded 76 putative Pax6-direct targets, including the Gaa, Isl1, Kif1b, Mtmr2, Pcsk1n, and Snca genes. RNA and ChIP data were validated for all these genes. In lens cells, reporter assays established Kib1b and Snca as Pax6 activated and repressed genes, respectively. In situ hybridization revealed reduced expression of these genes in E14 cerebral cortex. Moreover, we examined differentially expressed transcripts between E9.5 wild type and Pax6⁻/⁻ lens placodes that suggested Efnb2, Fat4, Has2, Nav1, and Trpm3 as novel Pax6-direct targets. Collectively, the present studies, through the identification of Pax6-direct target genes, provide novel insights into the molecular mechanisms of Pax6 gene control during mouse embryonic development. In addition, the present data demonstrate that Pax6 interacts preferentially with promoter regions in a tissue-specific fashion. Nevertheless, nearly 20% of the regions identified are accessible to Pax6 in multiple tissues