Molecular Biology

Background: Endothelial tight and adherens junctions control a variety of physiological processes like adhesion, paracellular transport of solutes or trafficking of activated leukocytes. Formation and maintenance of endothelial junctions largely depend on the microenvironment of the specific vascular bed and on interactions of the endothelium with adjacent cell types. Consequently, primary cultures of endothelial cells often lose their specific junctional pattern and fail to establish tight monolayer in vitro. This is also true for endothelial cells isolated from the vein of human umbilical cords (HUVEC) which are widely used as model for endothelial cell-related studies. Results: We here compared the effect of cyclic 3'-5'-adenosine monophosphate (cAMP) and its derivates on formation and stabilization of tight junctions and on alterations in paracellular permeability in HUVEC. We demonstrated by light and confocal laser microscopy that for shorter time periods the sodium salt of 8-bromoadenosine-cAMP (8-Br-cAMP/Na) and for longer incubation periods 8-(4-chlorophenylthio)-cAMP (pCPT-cAMP) exerted the greatest effects of all compounds tested here on formation of continuous tight junction strands in HUVEC. We further demonstrated that although all compounds induced protein kinase A-dependent expression of the tight junction proteins claudin-5 and occludin only pCPT-cAMP slightly enhanced paracellular barrier functions. Moreover, we showed that pCPT-cAMP and 8-Br-cAMP/Na induced expression and membrane translocation of tricellulin. Conclusions: pCPT-cAMP and, to a lesser extend, 8-Br-cAMP/Na improved formation of continuous tight junction strands and decreased paracellular permeability in primary HUVEC. We concluded that under these conditions HUVEC represent a feasible in vitro model to study formation and disassembly of endothelial tight junctions and to characterize tight junction-associated proteins.

Whole-genome sequencing of an Irish person reveals hundreds of thousands of novel genomic variants. Imputation using previous known information improves the accuracy of low-read-depth sequencing.See research article: http://genomebiology.com/2010/11/9/R91

Background: Recent studies generating complete human sequences from Asian, African and European subgroups have revealed population specific variation and disease susceptibility loci. Here, choosing a DNA sample from a population of interest due to its relative geographical isolation and genetic impact on further populations, we extend the above studies through the generation of 11 fold coverage of the first Irish human genome sequence. Results: Using sequence data from a branch of the European ancestral tree as yet unsequenced, we identify variants that may be specific to this population. Through comparisons with HapMap and previous genetic association studies, we identified novel disease associated variants including a novel nonsense variant putatively associated with inflammatory bowel disease. We describe a novel method for improving SNP calling accuracy at low genome coverage using haplotype information. This analysis has implications for future re-sequencing studies and validates the imputation of Irish haplotypes using data from the current Human Genome Diversity Cell Line Panel (HGDP-CEPH). Finally, we identify gene duplication events as constituting significant targets of recent positive selection in the human lineage. Conclusions: Our findings show that there remains utility in generating whole genome sequences to illustrate both general principles and reveal specific instances of human biology. With increasing access to low cost sequencing we would predict that even armed with the resources of a small research group a number of similar initiatives geared towards answering specific biological questions will emerge.

Background: Activated protein C (PC) is a serine protease that regulates blood coagulation by inactivating coagulation factors Va and VIIIa. PC deficiency is an autosomally inherited disorder associated with a high risk of recurrent venous thrombosis. The aim of the study was to explore the mechanisms responsible for severe PC deficiency in a patient with the protein C A267T mutation by in-vitro expression studies. Results: Huh7 and CHO-K1 cells were transiently transfected with expression vectors containing wild-type (WT PC) and mutated PC (A267T PC) cDNAs. PC mRNA levels were assessed by qRT-PCR and the PC protein levels were measured by ELISA. The mRNA levels of WT PC and A267T PC were similar, while the intracellular protein level of A267T PC was moderately decreased compared to WT PC. The secretion of A267T PC into the medium was severely impaired. No differences in molecular weights were observed between WT and A267T PC before and after treatment with endo-beta-N-acetylglucosaminidase. Proteasomal and lysosomal degradations were examined using lactacystin and bafilomycin, respectively, and revealed that A267T PC was slightly more susceptible for proteasomal degradation than WT PC. Intracellular co-localization analysis indicated that A267T PC was mainly located in the endoplasmic reticulum (ER), whereas WT PC was observed in both ER and Golgi. Conclusions: In contrast to what has been reported for other PC mutants, intracellular degradation of A267T PC was not the main/dominant mechanism underlying the reduced intracellular and secretion levels of PC. Our results indicate that the A267T mutation most likely caused misfolding of PC, which might lead to increased retention of the mutated PC in ER.

MirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.

The scientific worldview of someone starting graduate school today is very different from that of previous generations.

A recent study presents a technique allowing one to image transcription from a single gene copy in live cells, and highlights the dynamic nature of transcriptional regulation.

A transcriptomic analysis of early human organogenesis reveals the molecular signature of these processes and provides a valuable resource for identifying and comparing crucial regulators of mammalian embryogenesis.

Background: Burkholderia thailandensis is a non-pathogenic environmental saprophyte closely related to Burkholderia pseudomallei, the causative agent of the often fatal animal and human disease melioidosis. To study B. thailandensis genomic variation, we profiled 50 isolates using a pan-genome microarray comprising genomic elements from 28 Burkholderia strains and species. Of 39 genomic regions variably present across the B. thailandensis strains, 13 regions corresponded to known genomic islands, while 26 regions were novel. Results: Variant B. thailandensis isolates exhibited isolated acquisition of a capsular polysaccharide biosynthesis gene cluster (B. pseudomallei-like capsular polysaccharide) closely resembling a similar cluster in B. pseudomallei that is essential for virulence in mammals; presence of this cluster was confirmed by whole genome sequencing of a representative variant strain (B. thailandensis E555). Both whole-genome microarray and multi-locus sequence typing analysis revealed that the variant strains formed part of a phylogenetic subgroup distinct from the ancestral B. thailandensis population and were associated with atypical isolation sources when compared to the majority of previously-described B. thailandensis strains. In functional assays, B. thailandensis E555 exhibited several B. pseudomallei-like phenotypes, including colony wrinkling, resistance to human complement binding, and intracellular macrophage survival. However, in murine infection assays, B. thailandensis E555 did not exhibit enhanced virulence relative to other B. thailandensis strains, suggesting that additional factors are required to successfully colonize and infect mammals. Conclusions: The discovery of such novel variant strains demonstrates how unbiased genomic surveys of non-pathogenic isolates can reveal insights on the development and emergence of new pathogenic species.

Here we describe the Genome Variation Format (GVF) and the 10Gen dataset. GVF, an extension of Generic Feature Format version 3 (GFF3), is a simple tab-delimited format for DNA variant files, which uses Sequence Ontology to describe genome variation data. The 10Gen dataset, ten human genomes in GVF format, is freely available for community analysis from the Sequence Ontology website and from an Amazon elastic block storage (EBS) snapshot for use in Amazon's EC2 cloud computing environment.

Diploid genomes are exquisitely balanced systems of gene expression. The dosage-compensation systems that evolved along with monosomic sex chromosomes exemplify the intricacies of compensating for differences in gene copy number by transcriptional regulation.

A report on the 18th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and the 7th Special Interest Group meeting on Alternative Splicing, Boston, USA, 9-13 July 2010.

Background: Recent studies in budding yeast have shown that antisense transcription occurs at many loci. However, the functional role of antisense transcripts has been demonstrated only in a few cases and it has been suggested that most antisense transcripts may result from promiscuous bi-directional transcription in a dense genome. Results: Here, we present data from the use of strand specific ribonucleic acid (RNA) sequencing in Saccharomyces cerevisiae. We detect 1103 putative antisense transcripts expressed in mid-log phase growth, ranging from 39 short transcripts covering only the 3'UTR of sense genes to 145 long transcripts covering the entire sense open reading frame. Many of these antisense transcripts overlap sense genes that are repressed in mid-log phase and are important in stationary phase, stress response, or meiosis. We validate the differential regulation of 67 antisense transcripts and their sense targets in relevant conditions, including nutrient limitation and environmental stresses. Moreover, we show that several antisense transcripts and, in some cases, their differential expression have been conserved across five species of yeast spanning 150 million years of evolution. Divergence in the regulation of antisense transcripts to two respiratory genes coincides with the evolution of respiro-fermentation. Conclusions: Our work provides support for a global and conserved role for antisense transcription in yeast gene regulation.

Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy (http://usegalaxy.org), an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.

The Galaxy package empowers regular users to perform rich DNA sequence analysis through a much-needed and user-friendly graphical web interface.See research article http://genomebiology.com/2010/11/8/R86Research highlightWith the advent of affordable and high-throughput DNA sequencing, sequencing is becoming an essential component in nearly every genetics lab. These data are being generated to probe sequence variations, to understand transcribed, regulated or methylated DNA elements, and to explore a host of other biological features across the tree of life and across a range of environments and conditions. Given this deluge of data, novices and experts alike are facing the daunting challenge of trying to analyze the raw sequence data computationally. With so many tools available and so many assays to analyze, how can one be expected to stay current with the state of the art? How can one be expected to learn to use each tool and construct robust end-to-end analysis pipelines, all while ensuring that input formats, command-line options, sequence databases and program libraries are set correctly? Finally, once the analysis is complete, how does one ensure the results are reproducible and transparent for others to scrutinize and study?In an article published in Genome Biology, Jeremy Goecks, Anton Nekrutenko, James Taylor and the rest of the Galaxy Team (Goecks et al. 1 ) make a great advance towards resolving these critical questions with the latest update to their Galaxy Project. The ambitious goal of Galaxy is to empower regular users to carry out their own computational analysis without having to be an expert in computational biology or computer science. Galaxy adds a desperately needed graphical user interface to genomics research, making data analysis universally accessible in a web browser, and freeing users from the minutiae of archaic command-line parameters, data formats and scripting languages. Data inputs and computational steps are selected from dynamic graphical menus, and the results are displayed in intuitive plots and summaries that encourage interactive workflows and the exploration of hypotheses. The underlying data analysis tools can be almost any piece of software, written in any language, but all their complexity is neatly hidden inside of Galaxy, allowing users to focus on scientific rather than technical questions.

Background: Diatoms represent the predominant group of eukaryotic phytoplankton in the oceans and are responsible for around 20% of global photosynthesis. Two whole genome sequences are now available. Notwithstanding, our knowledge of diatom biology remains limited because only around half of their genes can be ascribed a function based on homology-based methods. High throughput tools are needed therefore to associate functions to diatom-specific genes. Results: We have performed a systematic analysis of 130,000 Expressed Sequence Tags (ESTs) derived from Phaeodactylum tricornutum cells grown in sixteen different conditions. These include different sources of nitrogen, different concentrations of carbon dioxide, silicate and iron, and abiotic stresses such as low temperature and low salinity. Based on unbiased statistical methods we have catalogued transcripts with similar expression profiles and identified transcripts differentially expressed in response to specific treatments. Functional annotation of these transcripts provides insights into expression patterns of genes involved in various metabolic and regulatory pathways and into the roles of novel genes with unknown functions. Specific growth conditions could be associated with enhanced gene diversity, known gene product functions, and over-representation of novel transcripts.Comparative analysis of data from the other sequenced diatom, Thalassiosira pseudonana, helped identify several unique diatom genes that are specifically regulated under particular conditions, thus facilitating studies of gene function, genome annotation and the molecular basis of species diversity. Conclusions: The digital gene expression database represents a new resource for identifying candidate diatom-specific genes involved in processes of major ecological relevance.

Background: Ultrasound elasticity imaging provides biomechanical and elastic properties of vascular tissue, with the potential to distinguish between tissue motion and tissue strain. To validate the ability of ultrasound elasticity imaging to predict structurally defined physical changes in tissue, strain measurement patterns during angioplasty in four bovine carotid artery pathology samples were compared to the measured physical characteristics of the tissue specimens. Methods: Using computational image-processing techniques, the circumferences of each bovine artery specimen were obtained from ultrasound and pathologic data. Results: Ultrasound-strain-based and pathology-based arterial circumference measurements were correlated with an R^2 value of 0.94 (p = 0.03). The experimental elasticity imaging results confirmed the onset of deformation of an angioplasty procedure by indicating a consistent inflection point where vessel fibers were fully unfolded and vessel wall strain initiated. Conclusion: These results validate the ability of ultrasound elasticity imaging to measure localized mechanical changes in vascular tissue.

Background: One of the goals of computational immunology is to facilitate the study of infectious diseases. Dynamic modeling is a powerful tool to integrate empirical data from independent sources, make novel predictions, and to foresee the gaps in the current knowledge. Dynamic models constructed to study the interactions between pathogens and hosts' immune responses have revealed key regulatory processes in the infection.Optimum complexity and dynamic modelingWe discuss the usability of various deterministic dynamic modeling approaches to study the progression of infectious diseases. The complexity of these models is dependent on the number of components and the temporal resolution in the model. We comment on the specific use of simple and complex models in the study of the progression of infectious diseases. Conclusions: Models of sub-systems or simplified immune response can be used to hypothesize phenomena of host-pathogen interactions and to estimate rates and parameters. Nevertheless, to study the pathogenesis of an infection we need to develop models describing the dynamics of the immune components involved in the progression of the disease. Incorporation of the large number and variety of immune processes involved in pathogenesis requires tradeoffs in modeling.

Background: Hypoxia plays an important role in vascular remodeling and directly affects vascular smooth muscle cells (VSMC) functions. Macrophage migration inhibitory factor (MIF) is a well known proinflammatory factor, and recent evidence suggests an important role of MIF in the progression of atherosclerosis and restenosis. However, the potential link between hypoxia and MIF in VSMC has not been investigated. The current study was designed to test whether hypoxia could regulate MIF expression in human VSMC. The effect of modulating MIF expression on hypoxia-induced VSMC proliferation and migration was also investigated at the same time. Results: Expression of MIF mRNA and protein was up-regulated as early as 2 hours in cultured human VSMCs after exposed to moderate hypoxia condition (3% O2). The up-regulation of MIF expression appears to be dependent on hypoxia-inducible transcription factor-1 alpha (HIF-1 alpha) since knockdown of HIF-1alpha inhibits the hypoxia induction of MIF gene and protein expression. The hypoxia induced expression of MIF was attenuated by antioxidant treatment as well as by inhibition of extracellular signal-regulated kinase (ERK). Under moderate hypoxia conditions (3% O2), both cell proliferation and cell migration were increased in VSMC cells. Blocking the MIF by specific small interference RNA to MIF (MIF-shRNA) resulted in the suppression of proliferation and migration of VSMCs. Conclusion: Our results demonstrated that in VSMCs, hypoxia increased MIF gene expression and protein production. The hypoxia-induced HIF-1 alpha activation, reactive oxygen species (ROS) generation and ERK activation might be involved in this response. Both MIF and HIF-1alpha mediated the hypoxia response of vascular smooth muscle cells, including cell migration and proliferation.

Background: Serotonin is a neurotransmitter that has been linked to a wide variety of behaviors including feeding and body-weight regulation, social hierarchies, aggression and suicidality, obsessive compulsive disorder, alcoholism, anxiety, and affective disorders. Full understanding of serotonergic systems in the central nervous system involves genomics, neurochemistry, electrophysiology, and behavior. Though associations have been found between functions at these different levels, in most cases the causal mechanisms are unknown. The scientific issues are daunting but important for human health because of the use of selective serotonin reuptake inhibitors and other pharmacological agents to treat disorders in the serotonergic signaling system. Methods: We construct a mathematical model of serotonin synthesis, release, and reuptake in a single serotonergic neuron terminal. The model includes the effects of autoreceptors, the transport of tryptophan into the terminal, and the metabolism of serotonin, as well as the dependence of release on the firing rate. The model is based on real physiology determined experimentally and is compared to experimental data. Results: We compare the variations in serotonin and dopamine synthesis due to meals and find that dopamine synthesis is insensitive to the availability of tyrosine but serotonin synthesis is sensitive to the availability of tryptophan. We conduct in silico experiments on the clearance of extracellular serotonin, normally and in the presence of fluoxetine, and compare to experimental data. We study the effects of various polymorphisms in the genes for the serotonin transporter and for tryptophan hydroxylase on synthesis, release, and reuptake. We find that, because of the homeostatic feedback mechanisms of the autoreceptors, the polymorphisms have smaller effects than one expects. We compute the expected steady concentrations of serotonin transporter knockout mice and compare to experimental data. Finally, we study how the properties of the the serotonin transporter and the autoreceptors give rise to the time courses of extracellular serotonin in various projection regions after a dose of fluoxetine. Conclusions: Serotonergic systems must respond robustly to important biological signals, while at the same time maintaining homeostasis in the face of normal biological fluctuations in inputs, expression levels, and firing rates. This is accomplished through the cooperative effect of many different homeostatic mechanisms including special properties of the serotonin transporters and the serotonin autoreceptors. Many difficult questions remain in order to fully understand how serotonin biochemistry affects serotonin electrophysiology and vice versa, and how both are changed in the presence of selective serotonin reuptake inhibitors. Mathematical models are useful tools for investigating some of these questions.