A variational approach to the stochastic aspects of cellular signal transduction

Cellular signaling networks have evolved to cope with intrinsic fluctuations, coming from the small numbers of constituents, and the environmental noise. Stochastic chemical kinetics equations govern the way biochemical networks process noisy signals. The essential difficulty associated with the master equation approach to solving the stochastic chemical kinetics problem is the enormous number of ordinary differential equations involved. In this work, we show how to achieve tremendous reduction in the dimensionality of specific reaction cascade dynamics by solving variationally an equivalent quantum field theoretic formulation of stochastic chemical kinetics. The present formulation avoids cumbersome commutator computations in the derivation of evolution equations, making more transparent the physical significance of the variational method. We propose novel time-dependent basis functions which work well over a wide range of rate parameters. We apply the new basis functions to describe stochastic signaling in several enzymatic cascades and compare the results so obtained with those from alternative solution techniques. The variational ansatz gives probability distributions that agree well with the exact ones, even when fluctuations are large and discreteness and nonlinearity are important. A numerical implementation of our technique is many orders of magnitude more efficient computationally compared with the traditional Monte Carlo simulation algorithms or the Langevin simulations.Comment: 15 pages, 11 figure

Modeling Progressive Fibrosis with Pluripotent Stem Cells Identifies an Anti-fibrotic Small Molecule.

Progressive organ fibrosis accounts for one-third of all deaths worldwide, yet preclinical models that mimic the complex, progressive nature of the disease are lacking, and hence, there are no curative therapies. Progressive fibrosis across organs shares common cellular and molecular pathways involving chronic injury, inflammation, and aberrant repair resulting in deposition of extracellular matrix, organ remodeling, and ultimately organ failure. We describe the generation and characterization of an in vitro progressive fibrosis model that uses cell types derived from induced pluripotent stem cells. Our model produces endogenous activated transforming growth factor β (TGF-β) and contains activated fibroblastic aggregates that progressively increase in size and stiffness with activation of known fibrotic molecular and cellular changes. We used this model as a phenotypic drug discovery platform for modulators of fibrosis. We validated this platform by identifying a compound that promotes resolution of fibrosis in in vivo and ex vivo models of ocular and lung fibrosis

F8 haplotype and inhibitor risk: results from the Hemophilia Inhibitor Genetics Study (HIGS) Combined Cohort.

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.Ancestral background, specifically African descent, confers higher risk for development of inhibitory antibodies to factor VIII (FVIII) in haemophilia A. It has been suggested that differences in the distribution of FVIII gene (F8) haplotypes, and mismatch between endogenous F8 haplotypes and those comprising products used for treatment could contribute to risk. Data from the Hemophilia Inhibitor Genetics Study (HIGS) Combined Cohort were used to determine the association between F8 haplotype 3 (H3) vs. haplotypes 1 and 2 (H1 + H2) and inhibitor risk among individuals of genetically determined African descent. Other variables known to affect inhibitor risk including type of F8 mutation and human leucocyte antigen (HLA) were included in the analysis. A second research question regarding risk related to mismatch in endogenous F8 haplotype and recombinant FVIII products used for treatment was addressed. Haplotype 3 was associated with higher inhibitor risk among those genetically identified (N = 49) as of African ancestry, but the association did not remain significant after adjustment for F8 mutation type and the HLA variables. Among subjects of all racial ancestries enrolled in HIGS who reported early use of recombinant products (N = 223), mismatch in endogenous haplotype and the FVIII proteins constituting the products used did not confer greater risk for inhibitor development. Haplotype 3 was not an independent predictor of inhibitor risk. Furthermore, our findings did not support a higher risk of inhibitors in the presence of a haplotype mismatch between the FVIII molecule infused and that of the individual.Baxter BioScience Frederick National Laboratory for Cancer Research, National Institutes of Health (NIH) HHSN261200800001E Wyeth Research Fund at Malmo University Hospital NIH, National Institute of Child Health and Human Development R01-HD-41224 Bayer Inspiration Biopharmaceuticals, Inc. Grifols, Inc. Baxter Biogen Idec Biotest CSL Behring Grifols Inspiration Biopharmaceuticals NovoNordisk Octapharma Swedish Orphan Biovitrum Wyeth/Pfize

Evolution of Robustness to Noise and Mutation in Gene Expression Dynamics

Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of `genetic robustness' while that of isogenic individuals gives a measure of `developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The condition for evolution of robustness as well as relationship between genetic and developmental robustness is derived through the variance of phenotypic fluctuations, which are measurable experimentally.Comment: 25 page

Rule-based modeling of biochemical systems with BioNetGen

Totowa, NJ. Please cite this article when referencing BioNetGen in future publications. Rule-based modeling involves the representation of molecules as structured objects and molecular interactions as rules for transforming the attributes of these objects. The approach is notable in that it allows one to systematically incorporate site-specific details about proteinprotein interactions into a model for the dynamics of a signal-transduction system, but the method has other applications as well, such as following the fates of individual carbon atoms in metabolic reactions. The consequences of protein-protein interactions are difficult to specify and track with a conventional modeling approach because of the large number of protein phosphoforms and protein complexes that these interactions potentially generate. Here, we focus on how a rule-based model is specified in the BioNetGen language (BNGL) and how a model specification is analyzed using the BioNetGen software tool. We also discuss new developments in rule-based modeling that should enable the construction and analyses of comprehensive models for signal transduction pathways and similarly large-scale models for other biochemical systems. Key Words: Computational systems biology; mathematical modeling; combinatorial complexity; software; formal languages; stochastic simulation; ordinary differential equations; protein-protein interactions; signal transduction; metabolic networks. 1

Lung Epithelial Injury by B. Anthracis Lethal Toxin Is Caused by MKK-Dependent Loss of Cytoskeletal Integrity

Bacillus anthracis lethal toxin (LT) is a key virulence factor of anthrax and contributes significantly to the in vivo pathology. The enzymatically active component is a Zn2+-dependent metalloprotease that cleaves most isoforms of mitogen-activated protein kinase kinases (MKKs). Using ex vivo differentiated human lung epithelium we report that LT destroys lung epithelial barrier function and wound healing responses by immobilizing the actin and microtubule network. Long-term exposure to the toxin generated a unique cellular phenotype characterized by increased actin filament assembly, microtubule stabilization, and changes in junction complexes and focal adhesions. LT-exposed cells displayed randomly oriented, highly dynamic protrusions, polarization defects and impaired cell migration. Reconstitution of MAPK pathways revealed that this LT-induced phenotype was primarily dependent on the coordinated loss of MKK1 and MKK2 signaling. Thus, MKKs control fundamental aspects of cytoskeletal dynamics and cell motility. Even though LT disabled repair mechanisms, agents such as keratinocyte growth factor or dexamethasone improved epithelial barrier integrity by reducing cell death. These results suggest that co-administration of anti-cytotoxic drugs may be of benefit when treating inhalational anthrax

Immunohistochemical detection and regulation of α5 nicotinic acetylcholine receptor (nAChR) subunits by FoxA2 during mouse lung organogenesis

<p>Abstract</p> <p>Background</p> <p>α₅nicotinic acetylcholine receptor (nAChR) subunits structurally stabilize functional nAChRs in many non-neuronal tissue types. The expression of α₅nAChR subunits and cell-specific markers were assessed during lung morphogenesis by co-localizing immunohistochemistry from embryonic day (E) 13.5 to post natal day (PN) 20. Transcriptional control of α₅nAChR expression by FoxA2 and GATA-6 was determined by reporter gene assays.</p> <p>Results</p> <p>Steady expression of α₅nAChR subunits was observed in distal lung epithelial cells during development while proximal lung expression significantly alternates between abundant prenatal expression, absence at PN4 and PN10, and a return to intense expression at PN20. α₅expression was most abundant on luminal edges of alveolar type (AT) I and ATII cells, non-ciliated Clara cells, and ciliated cells in the proximal lung at various periods of lung formation. Expression of α₅nAChR subunits correlated with cell differentiation and reporter gene assays suggest expression of α₅is regulated in part by FoxA2, with possible cooperation by GATA-6.</p> <p>Conclusions</p> <p>Our data reveal a highly regulated temporal-spatial pattern of α₅nAChR subunit expression during important periods of lung morphogenesis. Due to specific regulation by FoxA2 and distinct identification of α₅in alveolar epithelium and Clara cells, future studies may identify possible mechanisms of cell differentiation and lung homeostasis mediated at least in part by α₅-containing nAChRs.</p

OsLIC, a Novel CCCH-Type Zinc Finger Protein with Transcription Activation, Mediates Rice Architecture via Brassinosteroids Signaling

Rice architecture is an important agronomic trait and a major limiting factor for its high productivity. Here we describe a novel CCCH-type zinc finger gene, OsLIC (Oraza sativa leaf and tiller angle increased controller), which is involved in the regulation of rice plant architecture. OsLIC encoded an ancestral and unique CCCH type zinc finge protein. It has many orthologous in other organisms, ranging from yeast to humane. Suppression of endogenous OsLIC expression resulted in drastically increased leaf and tiller angles, shortened shoot height, and consequently reduced grain production in rice. OsLIC is predominantly expressed in rice collar and tiller bud. Genetic analysis suggested that OsLIC is epistatic to d2-1, whereas d61-1 is epistatic to OsLIC. Interestingly, sterols were significantly higher in level in transgenic shoots than in the wild type. Genome-wide expression analysis indicated that brassinosteroids (BRs) signal transduction was activated in transgenic lines. Moreover, transcription of OsLIC was induced by 24-epibrassinolide. OsLIC, with a single CCCH motif, displayed binding activity to double-stranded DNA and single-stranded polyrA, polyrU and polyrG but not polyrC. It contains a novel conserved EELR domain among eukaryotes and displays transcriptional activation activity in yeast. OsLIC may be a transcription activator to control rice plant architecture