Cardiac remodeling in Drosophila arises from changes in actin gene expression and from a contribution of lymph gland-like cells to the heart musculature

Understanding the basis of normal heart remodeling can provide insight into the plasticity of the cardiac state, and into the potential for treating diseased tissue. In Drosophila, the adult heart arises during metamorphosis from a series of events, that include the remodeling of an existing cardiac tube, the elaboration of new inflow tracts, and the addition of a layer of longitudinal muscle fibers. We have identified genes active in all these three processes, and studied their expression in order to characterize in greater detail normal cardiac remodeling. Using a Transglutaminase-lacZ transgenic line, that is expressed in the inflow tracts of the larval and adult heart, we confirm the existence of five inflow tracts in the adult structure. In addition, expression of the Actin87E actin gene is initiated in the remodeling cardiac tube, but not in the longitudinal fibers, and we have identified an Act87E promoter fragment that recapitulates this switch in expression. We also establish that the longitudinal fibers are multinucleated, characterizing these cells as specialized skeletal muscles. Furthermore, we have defined the origin of the longitudinal fibers, as a subset of lymph gland cells associated with the larval dorsal vessel. These studies underline the myriad contributors to the formation of the adult Drosophila heart, and provide new molecular insights into the development of this complex organ. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Gene Expression Profiling of Preovulatory Follicle in the Buffalo Cow: Effects of Increased IGF-I Concentration on Periovulatory Events

The preovulatory follicle in response to gonadotropin surge undergoes dramatic biochemical, and morphological changes orchestrated by expression changes in hundreds of genes. Employing well characterized bovine preovulatory follicle model, granulosa cells (GCs) and follicle wall were collected from the preovulatory follicle before, 1, 10 and 22 h post peak LH surge. Microarray analysis performed on GCs revealed that 450 and 111 genes were differentially expressed at 1 and 22 h post peak LH surge, respectively. For validation, qPCR and immunocytochemistry analyses were carried out for some of the differentially expressed genes. Expression analysis of many of these genes showed distinct expression patterns in GCs and the follicle wall. To study molecular functions and genetic networks, microarray data was analyzed using Ingenuity Pathway Analysis which revealed majority of the differentially expressed genes to cluster within processes like steroidogenesis, cell survival and cell differentiation. In the ovarian follicle, IGF-I is established to be an important regulator of the above mentioned molecular functions. Thus, further experiments were conducted to verify the effects of increased intrafollicular IGF-I levels on the expression of genes associated with the above mentioned processes. For this purpose, buffalo cows were administered with exogenous bGH to transiently increase circulating and intrafollicular concentrations of IGF-I. The results indicated that increased intrafollicular concentrations of IGF-I caused changes in expression of genes associated with steroidogenesis (StAR, SRF) and apoptosis (BCL-2, FKHR, PAWR). These results taken together suggest that onset of gonadotropin surge triggers activation of various biological pathways and that the effects of growth factors and peptides on gonadotropin actions could be examined during preovulatory follicle development.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

Silencing of toxic gene expression by Fis

Bacteria and bacteriophages have evolved DNA modification as a strategy to protect their genomes. Mom protein of bacteriophage Mu modifies the phage DNA, rendering it refractile to numerous restriction enzymes and in turn enabling the phage to successfully invade a variety of hosts. A strong fortification, a combined activity of the phage and host factors, prevents untimely expression of mom and associated toxic effects. Here, we identify the bacterial chromatin architectural protein Fis as an additional player in this crowded regulatory cascade. Both in vivo and in vitro studies described here indicate that Fis acts as a transcriptional repressor of mom promoter. Further, our data shows that Fis mediates its repressive effect by denying access to RNA polymerase at mom promoter. We propose that a combined repressive effect of Fis and previously characterized negative regulatory factors could be responsible to keep the gene silenced most of the time. We thus present a new facet of Fis function in Mu biology. In addition to bringing about overall downregulation of Mu genome, it also ensures silencing of the advantageous but potentially lethal mom gene.

Silencing of toxic gene expression by Fis

Bacteria and bacteriophages have evolved DNA modification as a strategy to protect their genomes. Mom protein of bacteriophage Mumodifies the phage DNA, rendering it refractile to numerous restriction enzymes and in turn enabling the phage to successfully invade a variety of hosts. A strong fortification, a combined activity of the phage and host factors, prevents untimely expression of mom and associated toxic effects. Here, we identify the bacterial chromatin architectural protein Fis as an additional player in this crowded regulatory cascade. Both in vivo and in vitro studies described here indicate that Fisacts as a transcriptional repressor of mom promoter. Further, our data shows that Fis mediates its repressive effect by denying access to RNA polymerase at mom promoter. We propose that a combined repressive effect of Fis and previously characterized negative regulatory factors could be responsible to keep the gene silenced most of the time. We thus present a new facet of Fis function in Mu biology. In addition to bringing about overall downregulation of Mu genome, it also ensures silencing of the advantageous but potentially lethal mom gene.

Development of a New Generation of Vectors for Gene Expression, Gene Replacement, and Protein-Protein Interaction Studies in Mycobacteria

Escherichia coli-mycobacterium shuttle vectors are important tools for gene expression and gene replacement in mycobacteria. However, most of the currently available vectors are limited in their use because of the lack of extended multiple cloning sites (MCSs) and convenience of appending an epitope tag(s) to the cloned open reading frames (ORFs). Here we report a new series of vectors that allow for the constitutive and regulatable expression of proteins, appended with peptide tag sequences at their N and C termini, respectively. The applicability of these vectors is demonstrated by the constitutive and induced expression of the Mycobacterium tuberculosis pknK gene, coding for protein kinase K, a serine-threonine protein kinase. Furthermore, a suicide plasmid with expanded MCS for creating gene replacements, a plasmid for chromosomal integrations at the commonly used L5 attB site, and a hypoxia-responsive vector, for expression of a gene(s) under hypoxic conditions that mimic latency, have also been created. Additionally, we have created a vector for the coexpression of two proteins controlled by two independent promoters, with each protein being in fusion with a different tag. The shuttle vectors developed in the present study are excellent tools for the analysis of gene function in mycobacteria and are a valuable addition to the existing repertoire of vectors for mycobacterial research.

Gene expression in osteoblast cells treated with submicron to nanometer hydroxyapatite-mullite eluate particles

The present research focused on determining the effect of hydroxyapatite-20 wt% mullite (H20M) particle eluates on apoptosis and differentiation of human fetal osteoblast (hFOB) cells. The H20M particles (257 +/- 37 nm) were prepared, starting with the production of a nanocomposite using a unique route of spark plasma sintering, followed by a repeated grinding-cryo treatment and elution process. Tetrazolium based cytotoxicity assay results showed a time-and dose-dependent effect of H20M particle eluates on hFOB cytotoxicity. In particular, the results revealed statistically reduced cell viability after hFOB were exposed to the above 10% H20M (257 +/- 37 nm) eluates for 48 h. The apoptotic cell death triggered by H20M treatment was proven by the analysis of molecular markers of apoptosis, that is, the Bcl-2 family of genes. hFOB expression of Bcl-xL and Bcl-xS significantly increased 25.6- and 25.2-fold for 50% of H20M concentrations, respectively. The ratio of Bcl-xL/Bax (4.01) decreased 2-fold for hFOB exposed to 100% of H20M eluates than that for 10% H20M eluate (7.94) treated hFOB cells. On the other hand, the Bcl-xS/Bax ratio for the 10% H20M eluate was 4.15-fold, whereas for 100% H20M eluates, it was 11.55-fold. Specifically, the anti-apoptotic effect of the H20M particle eluates was corroborated by the up-regulation of bone cell differentiation marker genes such as, collagen type I, cbfa, and osteocalcin. In summary, the present work clearly demonstrated that H20M submicron to nanometer composite particle eluates have a minimal effect on hFOB apoptosis and can even up-regulate the expression of bone cell markers at the molecular level.

Gene expression programming-fuzzy logic method for crop type classification

Crop type classification using remote sensing data plays a vital role in planning cultivation activities and for optimal usage of the available fertile land. Thus a reliable and precise classification of agricultural crops can help improve agricultural productivity. Hence in this paper a gene expression programming based fuzzy logic approach for multiclass crop classification using Multispectral satellite image is proposed. The purpose of this work is to utilize the optimization capabilities of GEP for tuning the fuzzy membership functions. The capabilities of GEP as a classifier is also studied. The proposed method is compared to Bayesian and Maximum likelihood classifier in terms of performance evaluation. From the results we can conclude that the proposed method is effective for classification.

Reaction dynamics under confinement: an exact path integral treatment of a two-stage model of stochastic gene expression

Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p, r, t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p, r, t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t -> infinity. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.

Role of DNA sequence based structural features of promoters in transcription initiation and gene expression

D Regulatory information for transcription initiation is present in a stretch of genomic DNA, called the promoter region that is located upstream of the transcription start site (TSS) of the gene. The promoter region interacts with different transcription factors and RNA polymerase to initiate transcription and contains short stretches of transcription factor binding sites (TFBSs), as well as structurally unique elements. Recent experimental and computational analyses of promoter sequences show that they often have non-B-DNA structural motifs, as well as some conserved structural properties, such as stability, bendability, nucleosome positioning preference and curvature, across a class of organisms. Here, we briefly describe these structural features, the differences observed in various organisms and their possible role in regulation of gene expression.

Multi-Temporal Satellite Image Analysis Using Gene Expression Programming

This paper discusses an approach for river mapping and flood evaluation to aid multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation to extract water covered region. Analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images is applied in two stages: before flood and during flood. For these images the extraction of water region utilizes spectral information for image classification and spatial information for image segmentation. Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as artificial neural networks and gene expression programming to separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water region. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification and region-based segmentation is an accurate and reliable for the extraction of water-covered region.

Ontology analysis of global gene expression differences of human bone marrow stromal cells cultured on 3D scaffolds or 2D films

Differences in gene expression of human bone marrow stromal cells (hBMSCs) during culture in three-dimensional (3D) nanofiber scaffolds or on two-dimensional (2D) films were investigated via pathway analysis of microarray mRNA expression profiles. Previous work has shown that hBMSC culture in nanofiber scaffolds can induce osteogenic differentiation in the absence of osteogenic supplements (OS). Analysis using ontology databases revealed that nanofibers and OS regulated similar pathways and that both were enriched for TGF-beta and cell-adhesion/ECM-receptor pathways. The most notable difference between the two was that nanofibers had stronger enrichment for cell-adhesion/ECM-receptor pathways. Comparison of nanofibers scaffolds with flat films yielded stronger differences in gene expression than comparison of nanofibers made from different polymers, suggesting that substrate structure had stronger effects on cell function than substrate polymer composition. These results demonstrate that physical (nanofibers) and biochemical (OS) signals regulate similar ontological pathways, suggesting that these cues use similar molecular mechanisms to control hBMSC differentiation. Published by Elsevier Ltd.