Signaling of Human Frizzled Receptors to the Mating Pathway in Yeast

Frizzled receptors have seven membrane-spanning helices and are considered as atypical G protein-coupled receptors (GPCRs). The mating response of the yeast Saccharomyces cerevisiae is mediated by a GPCR signaling system and this model organism has been used extensively in the past to study mammalian GPCR function. We show here that human Frizzled receptors (Fz1 and Fz2) can be properly targeted to the yeast plasma membrane, and that they stimulate the yeast mating pathway in the absence of added Wnt ligands, as evidenced by cell cycle arrest in G1 and reporter gene expression dependent on the mating pathway-activated FUS1 gene. Introducing intracellular portions of Frizzled receptors into the Ste2p backbone resulted in the generation of constitutively active receptor chimeras that retained mating factor responsiveness. Introducing intracellular portions of Ste2p into the Frizzled receptor backbone was found to strongly enhance mating pathway activation as compared to the native Frizzleds, likely by facilitating interaction with the yeast Gα protein Gpa1p. Furthermore, we show reversibility of the highly penetrant G1-phase arrests exerted by the receptor chimeras by deletion of the mating pathway effector FAR1. Our data demonstrate that Frizzled receptors can functionally replace mating factor receptors in yeast and offer an experimental system to study modulators of Frizzled receptors

Breakup Temperature of Target Spectators in Au + Au Collisions at E/A = 1000 MeV

Breakup temperatures were deduced from double ratios of isotope yields for target spectators produced in the reaction Au + Au at 1000 MeV per nucleon. Pairs of $^{3,4}$He and $^{6,7}$Li isotopes and pairs of $^{3,4}$He and H isotopes (p, d and d, t) yield consistent temperatures after feeding corrections, based on the quantum statistical model, are applied. The temperatures rise with decreasing impact parameter from 4 MeV for peripheral to about 10 MeV for the most central collisions. The good agreement with the breakup temperatures measured previously for projectile spectators at an incident energy of 600 MeV per nucleon confirms the observed universality of the spectator decay at relativistic bombarding energies. The measured temperatures also agree with the breakup temperatures predicted by the statistical multifragmentation model. For these calculations a relation between the initial excitation energy and mass was derived which gives good simultaneous agreement for the fragment charge correlations. The energy spectra of light charged particles, measured at $\theta_{lab}$ = 150$^{\circ}$, exhibit Maxwellian shapes with inverse slope parameters much higher than the breakup temperatures. The statistical multifragmentation model, because Coulomb repulsion and sequential decay processes are included, yields light-particle spectra with inverse slope parameters higher than the breakup temperatures but considerably below the measured values. The systematic behavior of the differences suggests that they are caused by light-charged-particle emission prior to the final breakup stage. PACS numbers: 25.70.Mn, 25.70.Pq, 25.75.-qComment: 29 pages, TeX with 11 included figures; Revised version accepted for publication in Z. Phys. A Two additional figure

An N-acetylglucosamine transporter required for arbuscular mycorrhizal symbioses in rice and maize

Most terrestrial plants, including crops, engage in beneficial interactions with arbuscular mycorrhizal fungi. Vital to the association is mutual recognition involving the release of diffusible signals into the rhizosphere. Previously, we identified the maize $\textit{no perception 1}$ ($\textit{nope1}$) mutant to be defective in early signalling. Here, we report cloning of $\textit{ZmNope1}$ on the basis of synteny with rice. $\textit{NOPE1}$ encodes a functional homologue of the $\textit{Candida albicans}$ $N$-acetylglucosamine (GlcNAc) transporter $\textit{NGT1}$, and represents the first plasma membrane GlcNAc transporter identified from plants. In $\textit{C. albicans}$, exposure to GlcNAc activates cell signalling and virulence. Similarly, in $\textit{Rhizophagus irregularis}$ treatment with rice wild-type but not $\textit{nope1}$ root exudates induced transcriptome changes associated with signalling function, suggesting a requirement of NOPE1 function for presymbiotic fungal reprogramming.Research in the U.P. laboratories was supported by the Swiss National Science Foundation grants 3100A0- 104132, PP00A-110874, PP00P3-130704 and by the Gatsby Charitable Foundation grant RG60824. S.N. and J.B.K. were supported by a grant from the National Institutes of Health (R01GM116048)

Overlaps Between Autism and Language Impairment: Phenomimicry or Shared Etiology?

Traditionally, autistic spectrum disorder (ASD) and specific language impairment (SLI) are regarded as distinct conditions with separate etiologies. Yet these disorders co-occur at above chance levels, suggesting shared etiology. Simulations, however, show that additive pleiotropic genes cannot account for observed rates of language impairment in relatives, which are higher for probands with SLI than for those with ASD + language impairment. An alternative account is in terms of ‘phenomimicry’, i.e., language impairment in comorbid cases may be a consequence of ASD risk factors, and different from that seen in SLI. However, this cannot explain why molecular genetic studies have found a common risk genotype for ASD and SLI. This paper explores whether nonadditive genetic influences could account for both family and molecular findings. A modified simulation involving G × G interactions obtained levels of comorbidity and rates of impairment in relatives more consistent with observed values. The simulations further suggest that the shape of distributions of phenotypic trait scores for different genotypes may provide evidence of whether a gene is involved in epistasis

Expression of miRNAs and Their Cooperative Regulation of the Pathophysiology in Traumatic Brain Injury

Traumatic brain injury (TBI) is a leading cause of injury-related death and disability worldwide. Effective treatment for TBI is limited and many TBI patients suffer from neuropsychiatric sequelae. The molecular and cellular mechanisms underlying the neuronal damage and impairment of mental abilities following TBI are largely unknown. Here we used the next generation sequencing platform to delineate miRNA transcriptome changes in the hippocampus at 24 hours and 7 days following TBI in the rat controlled cortical impact injury (CCI) model, and developed a bioinformatic analysis to identify cellular activities that are regulated by miRNAs differentially expressed in the CCI brains. The results of our study indicate that distinct sets of miRNAs are regulated at different post-traumatic times, and suggest that multiple miRNA species cooperatively regulate cellular pathways for the pathological changes and management of brain injury. The distinctive miRNAs expression profiles at different post-CCI times may be used as molecular signatures to assess TBI progression. In addition to known pathophysiological changes, our study identifies many other cellular pathways that are subjected to modification by differentially expressed miRNAs in TBI brains. These pathways can potentially be targeted for development of novel TBI treatment

Synthetic Morphology Using Alternative Inputs

Designing the shape and size of a cell is an interesting challenge for synthetic biology. Prolonged exposure to the mating pheromone α-factor induces an unusual morphology in yeast cells: multiple mating projections. The goal of this work was to reproduce the multiple projections phenotype in the absence of α-factor using a gain-of-function approach termed “Alternative Inputs (AIs)”. An alternative input is defined as any genetic manipulation that can activate the signaling pathway instead of the natural input. Interestingly, none of the alternative inputs were sufficient to produce multiple projections although some produced a single projection. Then, we extended our search by creating all combinations of alternative inputs and deletions that were summarized in an AIs-Deletions matrix. We found a genetic manipulation (AI-Ste5p ste2Δ) that enhanced the formation of multiple projections. Following up this lead, we demonstrated that AI-Ste4p and AI-Ste5p were sufficient to produce multiple projections when combined. Further, we showed that overexpression of a membrane-targeted form of Ste5p alone could also induce multiple projections. Thus, we successfully re-engineered the multiple projections mating morphology using alternative inputs without α-factor

Rationale for combination therapy of chronic myelogenous leukaemia with imatinib and irradiation or alkylating agents: implications for pretransplant conditioning

The tyrosine kinase activity of the BCR–ABL oncoprotein results in reduced apoptosis and thus prolongs survival of chronic myelogenous leukaemia cells. The tyrosine kinase inhibitor imatinib (formerly STI571) was reported to selectively suppress the proliferation of BCR–ABL-positive cells. Assuming that imatinib could be included in pretransplantation conditioning therapies, we tested whether combinations of imatinib and γ-irradiation or alkylating agents such as busulfan or treosulfan would display synergistic activity in BCR–ABL-positive chronic myelogenous leukaemia BV173 and EM-3 cell lines. Further, primary cells of untreated chronic myelogenous leukaemia patients were assayed for colony forming ability under combination therapy with imatinib. Additionally, the cytotoxic effect of these combinations on BCR–ABL-negative cells was investigated. In the cell lines a tetrazolium based MTT assay was used to quantify growth inhibition after exposure to cytotoxic drugs alone or to combinations with imatinib. Irradiation was applied prior to exposure to imatinib. Interaction of drugs was analysed using the median-effect method of Chou and Talalay. The combination index was calculated according to the classic isobologram equation. The combination imatinib + γ-irradiation proved to be significantly synergistic over a broad range of cell growth inhibition levels in both BCR–ABL-positive cell lines and produced the strongest reduction in primary chronic myelogenous leukaemia colony-forming progenitor cells. Combinations of imatinib + busulfan and imatinib + treosulfan showed merely additive to antagonistic effects. Imatinib did not potentiate the effects of irradiation or cytotoxic agents in BCR–ABL-negative cells. Our data provide the basis to further develop imatinib-containing conditioning therapies for stem cell transplantation in chronic myelogenous leukaemia

PathFinder: mining signal transduction pathway segments from protein-protein interaction networks

<p>Abstract</p> <p>Background</p> <p>A Signal transduction pathway is the chain of processes by which a cell converts an extracellular signal into a response. In most unicellular organisms, the number of signal transduction pathways influences the number of ways the cell can react and respond to the environment. Discovering signal transduction pathways is an arduous problem, even with the use of systematic genomic, proteomic and metabolomic technologies. These techniques lead to an enormous amount of data and how to interpret and process this data becomes a challenging computational problem.</p> <p>Results</p> <p>In this study we present a new framework for identifying signaling pathways in protein-protein interaction networks. Our goal is to find biologically significant pathway segments in a given interaction network. Currently, protein-protein interaction data has excessive amount of noise, e.g., false positive and false negative interactions. First, we eliminate false positives in the protein-protein interaction network by integrating the network with microarray expression profiles, protein subcellular localization and sequence information. In addition, protein families are used to repair false negative interactions. Then the characteristics of known signal transduction pathways and their functional annotations are extracted in the form of association rules.</p> <p>Conclusion</p> <p>Given a pair of starting and ending proteins, our methodology returns candidate pathway segments between these two proteins with possible missing links (recovered false negatives). In our study, <it>S. cerevisiae </it>(yeast) data is used to demonstrate the effectiveness of our method.</p

OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models

Biology-driven cancer drug development: back to the future

Most of the significant recent advances in cancer treatment have been based on the great strides that have been made in our understanding of the underlying biology of the disease. Nevertheless, the exploitation of biological insight in the oncology clinic has been haphazard and we believe that this needs to be enhanced and optimized if patients are to receive maximum benefit. Here, we discuss how research has driven cancer drug development in the past and describe how recent advances in biology, technology, our conceptual understanding of cell networks and removal of some roadblocks may facilitate therapeutic advances in the (hopefully) near future