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

A pound of flesh: what cachexia is and what it is not

Body weight loss, mostly due to the wasting of skeletal muscle and adipose tissue, is the hallmark of the so-called cachexia syndrome. Cachexia is associated with several acute and chronic disease states such as cancer, chronic obstructive pulmonary disease (COPD), heart and kidney failure, and acquired and autoimmune diseases and also pharmacological treatments such as chemotherapy. The clinical relevance of cachexia and its impact on patients' quality of life has been neglected for decades. Only recently did the international community agree upon a definition of the term cachexia, and we are still awaiting the standardization of markers and tests for the diagnosis and staging of cancer-related cachexia. In this review, we discuss cachexia, considering the evolving use of the term for diagnostic purposes and the implications it has for clinical biomarkers, to provide a comprehensive overview of its biology and clinical management. Advances and tools developed so far for the in vitro testing of cachexia and drug screening will be described. We will also evaluate the nomenclature of different forms of muscle wasting and degeneration and discuss features that distinguish cachexia from other forms of muscle wasting in the context of different conditions

DISCO-SCA and Properly Applied GSVD as Swinging Methods to Find Common and Distinctive Processes

BACKGROUND: In systems biology it is common to obtain for the same set of biological entities information from multiple sources. Examples include expression data for the same set of orthologous genes screened in different organisms and data on the same set of culture samples obtained with different high-throughput techniques. A major challenge is to find the important biological processes underlying the data and to disentangle therein processes common to all data sources and processes distinctive for a specific source. Recently, two promising simultaneous data integration methods have been proposed to attain this goal, namely generalized singular value decomposition (GSVD) and simultaneous component analysis with rotation to common and distinctive components (DISCO-SCA). RESULTS: Both theoretical analyses and applications to biologically relevant data show that: (1) straightforward applications of GSVD yield unsatisfactory results, (2) DISCO-SCA performs well, (3) provided proper pre-processing and algorithmic adaptations, GSVD reaches a performance level similar to that of DISCO-SCA, and (4) DISCO-SCA is directly generalizable to more than two data sources. The biological relevance of DISCO-SCA is illustrated with two applications. First, in a setting of comparative genomics, it is shown that DISCO-SCA recovers a common theme of cell cycle progression and a yeast-specific response to pheromones. The biological annotation was obtained by applying Gene Set Enrichment Analysis in an appropriate way. Second, in an application of DISCO-SCA to metabolomics data for Escherichia coli obtained with two different chemical analysis platforms, it is illustrated that the metabolites involved in some of the biological processes underlying the data are detected by one of the two platforms only; therefore, platforms for microbial metabolomics should be tailored to the biological question. CONCLUSIONS: Both DISCO-SCA and properly applied GSVD are promising integrative methods for finding common and distinctive processes in multisource data. Open source code for both methods is provided

Using Ribosomal Protein Genes as Reference: A Tale of Caution

Background: Housekeeping genes are needed in every tissue as their expression is required for survival, integrity or duplication of every cell. Housekeeping genes commonly have been used as reference genes to normalize gene expression data, the underlying assumption being that they are expressed in every cell type at approximately the same level. Often, the terms "reference genes'' and "housekeeping genes'' are used interchangeably. In this paper, we would like to distinguish between these terms. Consensus is growing that housekeeping genes which have traditionally been used to normalize gene expression data are not good reference genes. Recently, ribosomal protein genes have been suggested as reference genes based on a meta-analysis of publicly available microarray data. Methodology/Principal Findings: We have applied several statistical tools on a dataset of 70 microarrays representing 22 different tissues, to assess and visualize expression stability of ribosomal protein genes. We confirmed the housekeeping status of these genes, but further estimated expression stability across tissues in order to assess their potential as reference genes. One- and two-way ANOVA revealed that all ribosomal protein genes have significant expression variation across tissues and exhibit tissue-dependent expression behavior as a group. Via multidimensional unfolding analysis, we visualized this tissue-dependency. In addition, we explored mechanisms that may cause tissue dependent effects of individual ribosomal protein genes. Conclusions/Significance: Here we provide statistical and biological evidence that ribosomal protein genes exhibit important tissue-dependent variation in mRNA expression. Though these genes are most stably expressed of all investigated genes in a meta-analysis they cannot be considered true reference genes

Network Analysis of Differential Expression for the Identification of Disease-Causing Genes

Genetic studies (in particular linkage and association studies) identify chromosomal regions involved in a disease or phenotype of interest, but those regions often contain many candidate genes, only a few of which can be followed-up for biological validation. Recently, computational methods to identify (prioritize) the most promising candidates within a region have been proposed, but they are usually not applicable to cases where little is known about the phenotype (no or few confirmed disease genes, fragmentary understanding of the biological cascades involved). We seek to overcome this limitation by replacing knowledge about the biological process by experimental data on differential gene expression between affected and healthy individuals. Considering the problem from the perspective of a gene/protein network, we assess a candidate gene by considering the level of differential expression in its neighborhood under the assumption that strong candidates will tend to be surrounded by differentially expressed neighbors. We define a notion of soft neighborhood where each gene is given a contributing weight, which decreases with the distance from the candidate gene on the protein network. To account for multiple paths between genes, we define the distance using the Laplacian exponential diffusion kernel. We score candidates by aggregating the differential expression of neighbors weighted as a function of distance. Through a randomization procedure, we rank candidates by p-values. We illustrate our approach on four monogenic diseases and successfully prioritize the known disease causing genes

The future of induced pluripotent stem cells for cardiac therapy and drug development

The field of stem cell research was revolutionized with the advent of induced pluripotent stem cells. By reprogramming somatic cells to pluripotent stem cells, most ethical concerns associated with the use of embryonic stem cells are overcome, such that many hopes from the stem cell field now seem a step closer to reality. Several methods and cell sources have been described to create induced pluripotent stem cells and we discuss their characteristics in terms of feasibility and efficiency. From these cells, cardiac progenitors and cardiomyocytes can be derived by several protocols and most recent advances as well as remaining limitations are being discussed. However, in the short time period this technology has been around, evidence emerges that induced pluripotent stem cells may be more prone to genetic defects and maintain an epigenetic memory and thus may not be entirely the same as embryonic stem cells. Despite the lack of a complete fundamental understanding of stem cell biology, and even more of ways how to coax them into defined cell types, the technology is quickly adopted by industry. This paper gives an overview of the current applications of induced pluripotent stem cells in cardiovascular drug development and highlights active areas of research towards functional repair of the damaged heart. Adult stem cells have already been taken to clinical trials and we discuss these results in light of potential and hurdles to be taken to move induced pluripotent stem cells to the clinic.status: publishe

Challenges in the quest for 'clean meat'

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Pluripotent stem cell derivation and differentiation toward cardiac muscle: novel techniques and advances in patent literature

Pluripotent stem cells hold unprecedented potential for regenerative medicine, disease modeling and drug screening. Embryonic stem cells (ESCs), standard model for pluripotency studies, have been recently flanked by induced pluripotent stem cells (iPSCs). iPSCs are obtained from somatic cells via epigenetic and transcriptional reprogramming, overcoming ESC-related ethical issues and enabling the possibility of donor-matching pluripotent cell lines. Since the European Court of Justice banned patents involving embryo disaggregation to generate human ESCs, iPSCs can now fuel the willingness of European companies to invest in treatments based on stem cells. Moreover, iPSCs share many unique features of ESCs, such as unlimited self-renewal potential and broad differentiation capability, even though iPSCs seem more susceptible to genomic instability and display epigenetic biases as compared to ESCs. Both ESCs and iPSCs have been intensely investigated for cardiomyocyte production and cardiac muscle regeneration, both in human and animal models. In vitro and in vivo studies are continuously expanding and refining this field via genetic manipulation and cell conditioning, trying to achieve standard and reproducible products, eligible for clinical and biopharmaceutical scopes. This review focuses on the recently growing body of patents, concerning technical advances in production, expansion and cardiac differentiation of ESCs and iPSCs.status: publishe

Disallowed and Allowed Gene Expression: Two Faces of Mature Islet Beta Cells

Glucose homeostasis greatly depends on the match between fluctuating insulin demands and adjusted rates of insulin secretion, which is the function of pancreatic beta cells. Emerging evidence suggests that when neonatal beta cells mature, they acquire two faces of differentiated function: an expected "visible face" that depends on specific beta cell proteins needed for regulated insulin release, but also a "hidden face" that represses ubiquitous proteins to prevent inappropriate beta cell function such as elevated basal hormone secretion or insulin release triggered by exercise. This review highlights this novel concept, and we first propose that hidden faces may also be relevant for other specialized tissue functions, such as ketogenesis in the liver. Next, we discuss three scenarios in which aberrant gene expression causes abnormal glucose-induced insulin release and the epigenetic regulation of the hidden face in beta cells. We conclude with perspectives for new research, including beta cell replacement to cure diabetes.status: publishe

Preclinical gene therapy studies for hemophilia using adenoviral vectors

Hemophilia A and B are hereditary coagulation defects resulting from a deficiency of factor VIII (FVIII) and factor IX (FIX), respectively. Introducing a functional FVIII or FIX gene could potentially provide a cure for these bleeding disorders. Adenoviral vectors have been used as tools to introduce potentially therapeutic genes into mammalian cells and are by far the most efficient vectors for hepatic gene delivery. Long-term expression of both FVIII and FIX has been achieved in preclinical (hemophilic) mouse models using adenoviral vectors. Therapeutic levels of FVIII and FIX also have been achieved in hemophilic dogs using adenoviral vectors and in some cases expression was long-term. The performance of earlier generation adenoviral vectors, which retained residual viral genes, was compromised by potent acute and chronic inflammatory responses that contributed to significant toxicity and morbidity and short-term expression of FVIII and FIX. The development of improved adenoviral vectors devoid of viral genes (gutless or high-capacity adenoviral vectors) was therefore warranted, which led to a significant reduction in acute and chronic toxicity and more prolonged expression of FVIII and FIX. Strategies aimed at making these vectors safer and less immunogenic and their implications for hemophilia gene therapy are discussed in this review.status: publishe