A molecular signature of epithelial host defense: comparative gene expression analysis of cultured bronchial epithelial cells and keratinocytes

BACKGROUND: Epithelia are barrier-forming tissues that protect the organism against external noxious stimuli. Despite the similarity in function of epithelia, only few common protective mechanisms that are employed by these tissues have been systematically studied. Comparative analysis of genome-wide expression profiles generated by means of Serial Analysis of Gene Expression (SAGE) is a powerful approach to yield further insight into epithelial host defense mechanisms. We performed an extensive comparative analysis of previously published SAGE data sets of two types of epithelial cells, namely bronchial epithelial cells and keratinocytes, in which the response to pro-inflammatory cytokines was assessed. These data sets were used to elucidate a common denominator in epithelial host defense. RESULTS: Bronchial epithelial cells and keratinocytes were found to have a high degree of overlap in gene expression. Using an in silico approach, an epithelial-specific molecular signature of gene expression was identified in bronchial epithelial cells and keratinocytes comprising of family members of keratins, small proline-rich proteins and proteinase inhibitors. Whereas some of the identified genes were known to be involved in inflammation, the majority of the signature represented genes that were previously not associated with host defense. Using polymerase chain reaction, presence of expression of selected tissue-specific genes was validated. CONCLUSION: Our comparative analysis of gene transcription reveals that bronchial epithelial cells and keratinocytes both express a subset of genes that is likely to be essential in epithelial barrier formation in these cell types. The expression of these genes is specific for bronchial epithelial cells and keratinocytes and is not seen in non-epithelial cells. We show that bronchial epithelial cells, similar to keratinocytes, express components that are able to form a cross-linked protein envelope that may contribute to an effective barrier against noxious stimuli and pathogens

A Conserved Mito-Cytosolic Translational Balance Links Two Longevity Pathways.

Slowing down translation in either the cytosol or the mitochondria is a conserved longevity mechanism. Here, we found a non-interventional natural correlation of mitochondrial and cytosolic ribosomal proteins (RPs) in mouse population genetics, suggesting a translational balance. Inhibiting mitochondrial translation in C. elegans through mrps-5 RNAi repressed cytosolic translation. Transcriptomics integrated with proteomics revealed that this inhibition specifically reduced translational efficiency of mRNAs required in growth pathways while increasing stress response mRNAs. The repression of cytosolic translation and extension of lifespan from mrps-5 RNAi were dependent on atf-5/ATF4 and independent from metabolic phenotypes. We found the translational balance to be conserved in mammalian cells upon inhibiting mitochondrial translation pharmacologically with doxycycline. Lastly, extending this in vivo, doxycycline repressed cytosolic translation in the livers of germ-free mice. These data demonstrate that inhibiting mitochondrial translation initiates an atf-5/ATF4-dependent cascade leading to coordinated repression of cytosolic translation, which could be targeted to promote longevity

On the spontaneous stochastic dynamics of a single gene: complexity of the molecular interplay at the promoter

International audienceBACKGROUND: Gene promoters can be in various epigenetic states and undergo interactions with many molecules in a highly transient, probabilistic and combinatorial way, resulting in a complex global dynamics as observed experimentally. However, models of stochastic gene expression commonly consider promoter activity as a two-state on/off system. We consider here a model of single-gene stochastic expression that can represent arbitrary prokaryotic or eukaryotic promoters, based on the combinatorial interplay between molecules and epigenetic factors, including energy-dependent remodeling and enzymatic activities. RESULTS: We show that, considering the mere molecular interplay at the promoter, a single-gene can demonstrate an elaborate spontaneous stochastic activity (eg. multi-periodic multi-relaxation dynamics), similar to what is known to occur at the gene-network level. Characterizing this generic model with indicators of dynamic and steady-state properties (including power spectra and distributions), we reveal the potential activity of any promoter and its influence on gene expression. In particular, we can reproduce, based on biologically relevant mechanisms, the strongly periodic patterns of promoter occupancy by transcription factors (TF) and chromatin remodeling as observed experimentally on eukaryotic promoters. Moreover, we link several of its characteristics to properties of the underlying biochemical system. The model can also be used to identify behaviors of interest (eg. stochasticity induced by high TF concentration) on minimal systems and to test their relevance in larger and more realistic systems. We finally show that TF concentrations can regulate many aspects of the stochastic activity with a considerable flexibility and complexity. CONCLUSIONS: This tight promoter-mediated control of stochasticity may constitute a powerful asset for the cell. Remarkably, a strongly periodic activity that demonstrates a complex TF concentration-dependent control is obtained when molecular interactions have typical characteristics observed on eukaryotic promoters (high mobility, functional redundancy, many alternate states/pathways). We also show that this regime results in a direct and indirect energetic cost. Finally, this model can constitute a framework for unifying various experimental approaches. Collectively, our results show that a gene - the basic building block of complex regulatory networks - can itself demonstrate a significantly complex behavior

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust

Using Petri nets for experimental design in a multi-organ elimination pathway

Genistein is a soy metabolite with estrogenic activity that may result in (un)favorable effects on human health. Elucidation of the mechanisms through which food additives such as genistein exert their beneficiary effects is a major challenge for the food industry. A better understanding of the genistein elimination pathway could shed light on such mechanisms. We developed a Petri net model that represents this multi-organ elimination pathway and which assists in the design of future experiments. Using this model we show that metabolic profiles solely measured in venous blood are not sufficient to uniquely parameterize the model. Based on simulations we suggest two solutions that provide better results: parameterize the model using gut epithelium profiles or add additional biological constrains in the mode

Integrated support for neuroscience research: from study design to publication

Computational neuroscience is a new field of research in which neurodegenerative diseases are studied with the aid of new imaging techniques and computation facilities. Researchers with different expertise collaborate in these studies. A study requires scalable computational and storage capacity and information management facilities to succeed. Many virtual laboratories are proposed and developed to facilitate these studies, however most of them cover only the parts related to the computational data processing. In this paper we describe and analyse the phases of the computational neuroscience studies including the actors, the tasks they perform, and the characteristics of each phase. Based on these we identify the required properties and functionalities of a virtual laboratory that supports the actors and their tasks throughout the complete stud

Consensus and conflict cards for metabolic pathway databases

<p>Background: The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial.</p><p>Results: We introduce the concept of Consensus and Conflict Cards (C(2)Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C(2)Cards(Human), as a web application http://www.molgenis.org/c2cards, covering five human pathway databases.</p><p>Conclusions: C(2)Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C(2)Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement.</p>

Looking ultra deep: short identical sequences and transcriptional slippage

Studying transcriptomes by ultra deep sequencing provides an in-depth picture of transcriptional regulation and it facilitates the detection of rare transcriptional events. Using ultra deep sequencing of amplicons we identified known isoforms and also various new low frequency variants. Most of these variants likely involve the splicing machinery except for two events that we named variations affecting multiple exons, which are mainly deletions affecting parts of adjacent exons and intra-exonic deletions. Both events involve short identical sequences of 1 to 8 nucleotides at the junction and canonical splice sites are missing. They were identified in different genes and species at very low frequencies. We excluded that they are an artifact of PCR, sequencing, or reverse transcription. We propose that these variants represent intramolecular slippage events that require short identical sequences for reannealing of dissociated transcript