Mathematical model of excitation-contraction in a uterine smooth muscle cell

Uterine contractility is generated by contractions of myometrial smooth muscle cells (SMCs) that compose most of the myometrial layer of the uterine wall. Calcium ion (Ca²⁺) entry into the cell can be initiated by depolarization of the cell membrane. The increase in the free Ca²⁺ concentration within the cell initiates a chain of reactions, which lead to formation of cross bridges between actin and myosin filaments, and thereby the cell contracts. During contraction the SMC shortens while it exerts forces on neighboring cells. A mathematical model of myometrial SMC contraction has been developed to study this process of excitation and contraction. The model can be used to describe the intracellular Ca²⁺ concentration and stress produced by the cell in response to depolarization of the cell membrane. The model accounts for the operation of three Ca²⁺ control mechanisms: voltage-operated Ca²⁺ channels, Ca²⁺ pumps, and Na⁺/Ca²⁺ exchangers. The processes of myosin light chain (MLC) phosphorylation and stress production are accounted for using the cross-bridge model of Hai and Murphy (Am J Physiol Cell Physiol 254: C99–C106, 1988) and are coupled to the Ca²⁺ concentration through the rate constant of myosin phosphorylation. Measurements of Ca²⁺, MLC phosphorylation, and force in contracting cells were used to set the model parameters and test its ability to predict the cell response to stimulation. The model has been used to reproduce results of voltage-clamp experiments performed in myometrial cells of pregnant rats as well as the results of simultaneous measurements of MLC phosphorylation and force production in human nonpregnant myometrial cells. cellular calcium control mechanisms; myometrial contractions; myosin light chain phosphorylation     

Protein-tyrosine phosphatase sigma is associated with ulcerative colitis

Inflammatory bowel disease (IBD), a relatively common chronic debilitating intestinal illness, is composed of two broadly defined groups, Crohn's disease (CD) and ulcerative colitis (UC). Although several susceptibility genes for CD have been recently described, susceptibility genes exclusive for UC have not been forthcoming. Here, we show that receptor protein-tyrosine phosphatase sigma (PTPRS-encoding PTPsigma) knockout mice spontaneously develop mild colitis that becomes severe when challenged with two known inducers of colitis. We also demonstrate that E-cadherin and beta-catenin, two important adherens junction proteins involved in maintenance of barrier defense in the colon, act as colonic substrates for PTPsigma. Furthermore, we show that three SNPs (rs886936, rs17130, and rs8100586) that flank exon 8 in the human PTPRS gene are associated with UC. The presence of these SNPs is associated with novel splicing that removes the third immunoglobulin-like domain (exon 9) from the extracellular portion of PTPsigma, possibly altering dimerization or ligand recognition. We propose that polymorphisms in the human PTPRS gene lead to ulcerative colitis.     

Medical sequencing at the extremes of human body mass

Body weight is a quantitative trait with significant heritability in humans. To identify potential genetic contributors to this phenotype, we resequenced the coding exons and splice junctions of 58 genes in 379 obese and 378 lean individuals. Our 96-Mb survey included 21 genes associated with monogenic forms of obesity in humans or mice, as well as 37 genes that function in body weight-related pathways. We found that the monogenic obesity-associated gene group was enriched for rare nonsynonymous variants unique to the obese population compared with the lean population. In addition, computational analysis predicted a greater fraction of deleterious variants within the obese cohort. Together, these data suggest that multiple rare alleles contribute to obesity in the population and provide a medical sequencing-based approach to detect them.     

Systematic identification of gene annotation errors in the widely used yeast mutation collections

The baker's yeast mutation collections are extensively used genetic resources that are the basis for many genome-wide screens and new technologies. Anecdotal evidence has previously pointed to the putative existence of a neighboring gene effect (NGE) in these collections. NGE occurs when the phenotype of a strain carrying a particular perturbed gene is due to the lack of proper function of its adjacent gene. Here we performed a large-scale study of NGEs, presenting a network-based algorithm for detecting NGEs and validating software predictions using complementation experiments. We applied our approach to four datasets uncovering a similar magnitude of NGE in each (7-15%). These results have important consequences for systems biology, as the mutation collections are extensively used in almost every aspect of the field, from genetic network analysis to functional gene annotation.     

Structural robustness of metabolic networks with respect to multiple knockouts

We present a generalised framework for analysing structural robustness of metabolic networks, based on the concept of elementary flux modes (EFMs). Extending our earlier study on single knockouts [Wilhelm, T., Behre, J., Schuster, S., 2004. Analysis of structural robustness of metabolic networks. IEE Proc. Syst. Biol. 1(1), 114-120], we are now considering the general case of double and multiple knockouts. The robustness measures are based on the ratio of the number of remaining EFMs after knockout vs. the number of EFMs in the unperturbed situation, averaged over all combinations of knockouts. With the help of simple examples we demonstrate that consideration of multiple knockouts yields additional information going beyond single-knockout results. It is proven that the robustness score decreases as the knockout depth increases.We apply our extended framework to metabolic networks representing amino acid anabolism in Escherichia coli and human hepatocytes, and the central metabolism in human erythrocytes. Moreover, in the E. coli model the two subnetworks synthesising amino acids that are essential and those that are non-essential for humans are studied separately. The results are discussed from an evolutionary viewpoint. We find that E. coli has the most robust metabolism of all the cell types studied here. Considering only the subnetwork of the synthesis of non-essential amino acids, E. coli and the human hepatocyte show about the same robustness.     

Evolutionary rate and gene expression across different brain regions

Background

The evolutionary rate of a protein is a basic measure of evolution at the molecular level. Previous studies have shown that genes expressed in the brain have significantly lower evolutionary rates than those expressed in somatic tissues.

Results

We study the evolutionary rates of genes expressed in 21 different human brain regions. We find that genes highly expressed in the more recent cortical regions of the brain have lower evolutionary rates than genes highly expressed in subcortical regions. This may partially result from the observation that genes that are highly expressed in cortical regions tend to be highly expressed in subcortical regions, and thus their evolution faces a richer set of functional constraints. The frequency of mammal-specific and primate-specific genes is higher in the highly expressed gene sets of subcortical brain regions than in those of cortical brain regions. The basic inverse correlation between evolutionary rate and gene expression is significantly stronger in brain versus nonbrain tissues, and in cortical versus subcortical regions. Extending upon this cortical/subcortical trend, this inverse correlation is generally more marked for tissues that are located higher along the cranial vertical axis during development, giving rise to the possibility that these tissues are also more evolutionarily recent.

Conclusions

We find that cortically expressed genes are more conserved than subcortical ones, and that gene expression levels exert stronger constraints on sequence evolution in cortical versus subcortical regions. Taken together, these findings suggest that cortically expressed genes are under stronger selective pressure than subcortically expressed genes.     

Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species

The evolutionary origins of genetic robustness are still under debate: it may arise as a consequence of requirements imposed by varying environmental conditions, due to intrinsic factors such as metabolic requirements, or directly due to an adaptive selection in favor of genes that allow a species to endure genetic perturbations. Stratifying the individual effects of each origin requires one to study the pertaining evolutionary forces across many species under diverse conditions. Here we conduct the first large-scale computational study charting the level of robustness of metabolic networks of hundreds of bacterial species across many simulated growth environments. We provide evidence that variations among species in their level of robustness reflect ecological adaptations. We decouple metabolic robustness into two components and quantify the extents of each: the first, environmental-dependent, is responsible for at least 20% of the non-essential reactions and its extent is associated with the species'' lifestyle (specialized/generalist); the second, environmental-independent, is associated (correlation = ∼0.6) with the intrinsic metabolic capacities of a species—higher robustness is observed in fast growers or in organisms with an extensive production of secondary metabolites. Finally, we identify reactions that are uniquely susceptible to perturbations in human pathogens, potentially serving as novel drug-targets.