Integrative analysis of large scale expression profiles reveals core transcriptional response and coordination between multiple cellular processes in a cyanobacterium

<p>Abstract</p> <p>Background</p> <p>Cyanobacteria are the only known prokaryotes capable of oxygenic photosynthesis. They play significant roles in global biogeochemical cycles and carbon sequestration, and have recently been recognized as potential vehicles for production of renewable biofuels. <it>Synechocystis </it>sp. PCC 6803 has been extensively used as a model organism for cyanobacterial studies. DNA microarray studies in <it>Synechocystis </it>have shown varying degrees of transcriptome reprogramming under altered environmental conditions. However, it is not clear from published work how transcriptome reprogramming affects pre-existing networks of fine-tuned cellular processes.</p> <p>Results</p> <p>We have integrated 163 transcriptome data sets generated in response to numerous environmental and genetic perturbations in <it>Synechocystis</it>. Our analyses show that a large number of genes, defined as the core transcriptional response (CTR), are commonly regulated under most perturbations. The CTR contains nearly 12% of <it>Synechocystis </it>genes found on its chromosome. The majority of genes in the CTR are involved in photosynthesis, translation, energy metabolism and stress protection. Our results indicate that a large number of differentially regulated genes identified in most reported studies in <it>Synechocystis </it>under different perturbations are associated with the general stress response. We also find that a majority of genes in the CTR are coregulated with 25 regulatory genes. Some of these regulatory genes have been implicated in cellular responses to oxidative stress, suggesting that reactive oxygen species are involved in the regulation of the CTR. A Bayesian network, based on the regulation of various KEGG pathways determined from the expression patterns of their associated genes, has revealed new insights into the coordination between different cellular processes.</p> <p>Conclusion</p> <p>We provide here the first integrative analysis of transcriptome data sets generated in a cyanobacterium. This compilation of data sets is a valuable resource to researchers for all cyanobacterial gene expression related queries. Importantly, our analysis provides a global description of transcriptional reprogramming under different perturbations and a basic framework to understand the strategies of cellular adaptations in <it>Synechocystis</it>.</p

Seeded Bayesian Networks: Constructing genetic networks from microarray data

<p>Abstract</p> <p>Background</p> <p>DNA microarrays and other genomics-inspired technologies provide large datasets that often include hidden patterns of correlation between genes reflecting the complex processes that underlie cellular metabolism and physiology. The challenge in analyzing large-scale expression data has been to extract biologically meaningful inferences regarding these processes – often represented as networks – in an environment where the datasets are often imperfect and biological noise can obscure the actual signal. Although many techniques have been developed in an attempt to address these issues, to date their ability to extract meaningful and predictive network relationships has been limited. Here we describe a method that draws on prior information about gene-gene interactions to infer biologically relevant pathways from microarray data. Our approach consists of using preliminary networks derived from the literature and/or protein-protein interaction data as seeds for a Bayesian network analysis of microarray results.</p> <p>Results</p> <p>Through a bootstrap analysis of gene expression data derived from a number of leukemia studies, we demonstrate that seeded Bayesian Networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data.</p> <p>Conclusion</p> <p>The use of network seeds greatly improves the ability of Bayesian Network analysis to learn gene interaction networks from gene expression data. We demonstrate that the use of seeds derived from the biomedical literature or high-throughput protein-protein interaction data, or the combination, provides improvement over a standard Bayesian Network analysis, allowing networks involving dynamic processes to be deduced from the static snapshots of biological systems that represent the most common source of microarray data. Software implementing these methods has been included in the widely used TM4 microarray analysis package.</p

A Day in the Life of Microcystis aeruginosa Strain PCC 7806 as Revealed by a Transcriptomic Analysis

The cyanobacterium, Microcystis aeruginosa, is able to proliferate in a wide range of freshwater ecosystems and to produce many secondary metabolites that are a threat to human and animal health. The dynamic of this production and more globally the metabolism of this species is still poorly known. A DNA microarray based on the genome of M. aeruginosa PCC 7806 was constructed and used to study the dynamics of gene expression in this cyanobacterium during the light/dark cycle, because light is a critical factor for this species, like for other photosynthetic microorganisms. This first application of transcriptomics to a Microcystis species has revealed that more than 25% of the genes displayed significant changes in their transcript abundance during the light/dark cycle and in particular during the dark/light transition. The metabolism of M. aeruginosa is compartmentalized between the light period, during which carbon uptake, photosynthesis and the reductive pentose phosphate pathway lead to the synthesis of glycogen, and the dark period, during which glycogen degradation, the oxidative pentose phosphate pathway, the TCA branched pathway and ammonium uptake promote amino acid biosynthesis. We also show that the biosynthesis of secondary metabolites, such as microcystins, aeruginosin and cyanopeptolin, occur essentially during the light period, suggesting that these metabolites may interact with the diurnal part of the central metabolism

Identifying Alternative Hyper-Splicing Signatures in MG-Thymoma by Exon Arrays

BACKGROUND: The vast majority of human genes (>70%) are alternatively spliced. Although alternative pre-mRNA processing is modified in multiple tumors, alternative hyper-splicing signatures specific to particular tumor types are still lacking. Here, we report the use of Affymetrix Human Exon Arrays to spot hyper-splicing events characteristic of myasthenia gravis (MG)-thymoma, thymic tumors which develop in patients with MG and discriminate them from colon cancer changes. METHODOLOGY/PRINCIPAL FINDINGS: We combined GO term to parent threshold-based and threshold-independent ad-hoc functional statistics with in-depth analysis of key modified transcripts to highlight various exon-specific changes. These denote alternative splicing in MG-thymoma tumors compared to healthy human thymus and to in-house and Affymetrix datasets from colon cancer and healthy tissues. By using both global and specific, term-to-parent Gene Ontology (GO) statistical comparisons, our functional integrative ad-hoc method allowed the detection of disease-relevant splicing events. CONCLUSIONS/SIGNIFICANCE: Hyper-spliced transcripts spanned several categories, including the tumorogenic ERBB4 tyrosine kinase receptor and the connective tissue growth factor CTGF, as well as the immune function-related histocompatibility gene HLA-DRB1 and interleukin (IL)19, two muscle-specific collagens and one myosin heavy chain gene; intriguingly, a putative new exon was discovered in the MG-involved acetylcholinesterase ACHE gene. Corresponding changes in spliceosome composition were indicated by co-decreases in the splicing factors ASF/SF(2) and SC35. Parallel tumor-associated changes occurred in colon cancer as well, but the majority of the apparent hyper-splicing events were particular to MG-thymoma and could be validated by Fluorescent In-Situ Hybridization (FISH), Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and mass spectrometry (MS) followed by peptide sequencing. Our findings demonstrate a particular alternative hyper-splicing signature for transcripts over-expressed in MG-thymoma, supporting the hypothesis that alternative hyper-splicing contributes to shaping the biological functions of these and other specialized tumors and opening new venues for the development of diagnosis and treatment approaches

Evolutionary Diversification of Plant Shikimate Kinase Gene Duplicates

Shikimate kinase (SK; EC 2.7.1.71) catalyzes the fifth reaction of the shikimate pathway, which directs carbon from the central metabolism pool to a broad range of secondary metabolites involved in plant development, growth, and stress responses. In this study, we demonstrate the role of plant SK gene duplicate evolution in the diversification of metabolic regulation and the acquisition of novel and physiologically essential function. Phylogenetic analysis of plant SK homologs resolves an orthologous cluster of plant SKs and two functionally distinct orthologous clusters. These previously undescribed genes, shikimate kinase-like 1 (SKL1) and -2 (SKL2), do not encode SK activity, are present in all major plant lineages, and apparently evolved under positive selection following SK gene duplication over 400 MYA. This is supported by functional assays using recombinant SK, SKL1, and SKL2 from Arabidopsis thaliana (At) and evolutionary analyses of the diversification of SK-catalytic and -substrate binding sites based on theoretical structure models. AtSKL1 mutants yield albino and novel variegated phenotypes, which indicate SKL1 is required for chloroplast biogenesis. Extant SKL2 sequences show a strong genetic signature of positive selection, which is enriched in a protein–protein interaction module not found in other SK homologs. We also report the first kinetic characterization of plant SKs and show that gene expression diversification among the AtSK inparalogs is correlated with developmental processes and stress responses. This study examines the functional diversification of ancient and recent plant SK gene duplicates and highlights the utility of SKs as scaffolds for functional innovation

Transgenic Expression of Walleye Dermal Sarcoma Virus rv-cyclin (orfA) in Zebrafish does not Result in Tissue Proliferation

10.1007/s10126-010-9274-2Marine Biotechnology132142-150MABI

Transgenic Expression of Walleye Dermal Sarcoma Virus rv-cyclin Gene in Zebrafish and Its Suppressive Effect on Liver Tumor Development After Carcinogen Treatment

10.1007/s10126-009-9251-9Marine Biotechnology126640-649MABI