Erroneous attribution of relevant transcription factor binding sites despite successful prediction of cis-regulatory modules

<p>Abstract</p> <p>Background</p> <p><it>Cis</it>-regulatory modules are bound by transcription factors to regulate gene expression. Characterizing these DNA sequences is central to understanding gene regulatory networks and gaining insight into mechanisms of transcriptional regulation, but genome-scale regulatory module discovery remains a challenge. One popular approach is to scan the genome for clusters of transcription factor binding sites, especially those conserved in related species. When such approaches are successful, it is typically assumed that the activity of the modules is mediated by the identified binding sites and their cognate transcription factors. However, the validity of this assumption is often not assessed.</p> <p>Results</p> <p>We successfully predicted five new <it>cis</it>-regulatory modules by combining binding site identification with sequence conservation and compared these to unsuccessful predictions from a related approach not utilizing sequence conservation. Despite greatly improved predictive success, the positive set had similar degrees of sequence and binding site conservation as the negative set. We explored the reasons for this by mutagenizing putative binding sites in three <it>cis</it>-regulatory modules. A large proportion of the tested sites had little or no demonstrable role in mediating regulatory element activity. Examination of loss-of-function mutants also showed that some transcription factors supposedly binding to the modules are not required for their function.</p> <p>Conclusions</p> <p>Our results raise important questions about interpreting regulatory module predictions obtained by finding clusters of conserved binding sites. Attribution of function to these sites and their cognate transcription factors may be incorrect even when modules are successfully identified. Our study underscores the importance of empirical validation of computational results even when these results are in line with expectation.</p

Skeletal Muscle Differentiation Evokes Endogenous XIAP to Restrict the Apoptotic Pathway

Myotube apoptosis occurs normally during muscle development and aging but it can lead to destruction of skeletal muscle in neuromuscular diseases. Therefore, understanding how myotube apoptosis is regulated is important for developing novel strategies for treatment of muscle loss. We investigated the regulation of apoptosis in skeletal muscle and report a striking increase in resistance to apoptosis following differentiation. We find mitotic C2C12 cells (myoblast-like cells) are sensitive to cytosolic cytochrome c microinjection. However, differentiated C2C12 cells (myotube-like cells) and primary myotubes are markedly resistant. This resistance is due to endogenous X-linked inhibitor of apoptotic protein (XIAP). Importantly, the selective difference in the ability of XIAP to block myotube but not myoblast apoptosis is not due to a change in XIAP but rather a decrease in Apaf-1 expression. This decrease in Apaf-1 links XIAP to caspase activation and death. Our findings suggest that in order for myotubes to die, they may degrade XIAP, functionally inactivate XIAP or upregulate Apaf-1. Importantly, we identify a role for endogenous Smac in overcoming XIAP to allow myotube death. However, in postmitotic cardiomyocytes, where XIAP also restricts apoptosis, endogenous Smac was not capable of overcoming XIAP to cause death. These results show that as skeletal muscle differentiate, they become resistant to apoptosis because of the ability of XIAP to regulate caspase activation. The increased restriction of apoptosis in myotubes is presumably important to ensure the long term survival of these postmitotic cells as they play a vital role in the physiology of organisms

Mechanism of the Interaction between the Intrinsically Disordered C-Terminus of the Pro-Apoptotic ARTS Protein and the Bir3 Domain of XIAP

ARTS (Sept4_i2) is a mitochondrial pro-apoptotic protein that functions as a tumor suppressor. Its expression is significantly reduced in leukemia and lymphoma patients. ARTS binds and inhibits XIAP (X-linked Inhibitor of Apoptosis protein) by interacting with its Bir3 domain. ARTS promotes degradation of XIAP through the proteasome pathway. By doing so, ARTS removes XIAP inhibition of caspases and enables apoptosis to proceed. ARTS contains 27 unique residues in its C-terminal domain (CTD, residues 248–274) which are important for XIAP binding. Here we characterized the molecular details of this interaction. Biophysical and computational methods were used to show that the ARTS CTD is intrinsically disordered under physiological conditions. Direct binding of ARTS CTD to Bir3 was demonstrated using NMR and fluorescence spectroscopy. The Bir3 interacting region in ARTS CTD was mapped to ARTS residues 266–274, which are the nine C-terminal residues in the protein. Alanine scan of ARTS 266–274 showed the importance of several residues for Bir3 binding, with His268 and Cys273 contributing the most. Adding a reducing agent prevented binding to Bir3. A dimer of ARTS 266–274 formed by oxidation of the Cys residues into a disulfide bond bound with similar affinity and was probably required for the interaction with Bir3. The detailed analysis of the ARTS – Bir3 interaction provides the basis for setting it as a target for anti cancer drug design: It will enable the development of compounds that mimic ARTS CTD, remove IAPs inhibition of caspases, and thereby induce apoptosis

Assessing Computational Methods of Cis-Regulatory Module Prediction

Computational methods attempting to identify instances of cis-regulatory modules (CRMs) in the genome face a challenging problem of searching for potentially interacting transcription factor binding sites while knowledge of the specific interactions involved remains limited. Without a comprehensive comparison of their performance, the reliability and accuracy of these tools remains unclear. Faced with a large number of different tools that address this problem, we summarized and categorized them based on search strategy and input data requirements. Twelve representative methods were chosen and applied to predict CRMs from the Drosophila CRM database REDfly, and across the human ENCODE regions. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. When discriminating CRMs from non-coding regions, those methods considering evolutionary conservation have a stronger predictive power than methods designed to be run on a single genome. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. For example, some favour homotypical clusters of binding sites, while others perform best on short CRMs. Furthermore, most methods appear to be sensitive to the composition and structure of the genome to which they are applied. We analyze the principal features that distinguish the methods that performed well, identify weaknesses leading to poor performance, and provide a guide for users. We also propose key considerations for the development and evaluation of future CRM-prediction methods

Computational Identification of Transcriptional Regulators in Human Endotoxemia

One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically ‘coregulated’ genes are proposed. Subsequently, statistically significant cis-regulatory modules (CRMs) are identified and decomposed into a list of critical transcription factors (34) that are validated largely on primary literature. Finally, our analysis further allows for the construction of a dynamic representation of the temporal transcriptional regulatory program across the host, deciphering possible combinatorial interactions among factors under which they might be active. Although much remains to be explored, this study has computationally identified key transcription factors and proposed a putative time-dependent transcriptional regulatory program associated with critical transcriptional inflammatory responses. These results provide a solid foundation for future investigations to elucidate the underlying transcriptional regulatory mechanisms under the host inflammatory response. Also, the assumption that coexpressed genes that are functionally relevant are more likely to share some common transcriptional regulatory mechanism seems to be promising, making the proposed framework become essential in unravelling context-specific transcriptional regulatory interactions underlying diverse mammalian biological processes

Angiogenesis in Differentiated Placental Multipotent Mesenchymal Stromal Cells Is Dependent on Integrin α5β1

Human placental multipotent mesenchymal stromal cells (hPMSCs) can be isolated from term placenta, but their angiogenic ability and the regulatory pathways involved are not known. hPMSCs were shown to express integrins αv, α4, α5, β1, β3, and β5 and could be induced to differentiate into cells expressing endothelial markers. Increases in cell surface integrins α5 and β1, but not α4, αvβ3, or αvβ5, accompanied endothelial differentiation. Vascular endothelial growth factor-A augmented the effect of fibronectin in enhancing adhesion and migration of differentiated hPMSC through integrin α5β1, but not αvβ3 or αvβ5. Formation of capillary-like structures in vitro from differentiated cells was inhibited by pre-treatment with function-blocking antibodies to integrins α5 and β1. When hPMSCs were seeded onto chick chorioallantoic membranes (CAM), human von Willebrand factor-positive cells were observed to engraft in the chick endothelium. CAMs transplanted with differentiated hPMSCs had a greater number of vessels containing human cells and more incorporated cells per vessel compared to CAMs transplanted with undifferentiated hPMSCs, and overall angiogenesis was enhanced more by the differentiated cells. Function-blocking antibodies to integrins α5 and β1 inhibited angiogenesis in the CAM assay. These results suggest that differentiated hPMSCs may contribute to blood vessel formation, and this activity depends on integrin α5β1

Data-analysis strategies for image-based cell profiling

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.Peer reviewe

Anisotropic nanomaterials: structure, growth, assembly, and functions

Comprehensive knowledge over the shape of nanomaterials is a critical factor in designing devices with desired functions. Due to this reason, systematic efforts have been made to synthesize materials of diverse shape in the nanoscale regime. Anisotropic nanomaterials are a class of materials in which their properties are direction-dependent and more than one structural parameter is needed to describe them. Their unique and fine-tuned physical and chemical properties make them ideal candidates for devising new applications. In addition, the assembly of ordered one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) arrays of anisotropic nanoparticles brings novel properties into the resulting system, which would be entirely different from the properties of individual nanoparticles. This review presents an overview of current research in the area of anisotropic nanomaterials in general and noble metal nanoparticles in particular. We begin with an introduction to the advancements in this area followed by general aspects of the growth of anisotropic nanoparticles. Then we describe several important synthetic protocols for making anisotropic nanomaterials, followed by a summary of their assemblies, and conclude with major applications