Diversity and Functional Evolution of Terpene Synthases in Dictyostelid Social Amoebae

Dictyostelids, or social amoebae, have a unique life style in forming multicellular fruiting bodies from unicellular amoeboids upon starvation. Recently, dictyostelids were found to contain terpene synthase (TPS) genes, a gene type of secondary metabolism previously known to occur only in plants, fungi and bacteria. Here we report an evolutionary functional study of dictyostelid TPS genes. The number of TPS genes in six species of dictyostelids examined ranges from 1 to 19; and the model species Dictyostelium purpureum contains 12 genes. Using in vitro enzyme assays, the 12 TPS genes from D. purpureum were shown to encode functional enzymes with distinct product profiles. The expression of the 12 TPS genes in D. purpureum is developmentally regulated. During multicellular development, D. purpureum releases a mixture of volatile terpenes dominated by sesquiterpenes that are the in vitro products of a subset of the 12 TPS genes. The quality and quantity of the terpenes released from D. purpureum, however, bear little resemblance to those of D. discoideum, a closely related dictyostelid. Despite these variations, the conserved clade of dictyostelid TPSs, which have an evolutionary distance of more than 600 million years, has the same biochemical function, catalyzing the formation of a sesquiterpene protoillud-7-ene. Taken together, our results indicate that the dynamic evolution of dictyostelid TPS genes includes both purifying selection of an orthologous group and species-specific expansion with functional divergence. Consequently, the terpenes produced by these TPSs most likely have conserved as well as speciesadaptive biological functions as chemical languages in dictyostelids

Differentiation-Inducing Factor-1 and -2 Function also as Modulators for Dictyostelium Chemotaxis

BackgroundIn the early stages of development of the cellular slime mold Dictyostelium discoideum, chemotaxis toward cAMP plays a pivotal role in organizing discrete cells into a multicellular structure. In this process, a series of signaling molecules, such as G-protein-coupled cell surface receptors for cAMP, phosphatidylinositol metabolites, and cyclic nucleotides, function as the signal transducers for controlling dynamics of cytoskeleton. Differentiation-inducing factor-1 and -2 (DIF-1 and DIF-2) were originally identified as the factors (chlorinated alkylphenones) that induce Dictyostelium stalk cell differentiation, but it remained unknown whether the DIFs had any other physiologic functions.Methodology/Principal FindingsTo further elucidate the functions of DIFs, in the present study we investigated their effects on chemotaxis under various conditions. Quite interestingly, in shallow cAMP gradients, DIF-1 suppressed chemotaxis whereas DIF-2 promoted it greatly. Analyses with various mutants revealed that DIF-1 may inhibit chemotaxis, at least in part, via GbpB (a phosphodiesterase) and a decrease in the intracellular cGMP concentration ([cGMP]i). DIF-2, by contrast, may enhance chemotaxis, at least in part, via RegA (another phosphodiesterase) and an increase in [cGMP]i. Using null mutants for DimA and DimB, the transcription factors that are required for DIF-dependent prestalk differentiation, we also showed that the mechanisms for the modulation of chemotaxis by DIFs differ from those for the induction of cell differentiation by DIFs, at least in part.Conclusions/SignificanceOur findings indicate that DIF-1 and DIF-2 function as negative and positive modulators for Dictyostelium chemotaxis, respectively. To our knowledge, this is the first report in any organism of physiologic modulators (small molecules) for chemotaxis having differentiation-inducing activity

Democratized image analytics by visual programming through integration of deep models and small-scale machine learning

Analysis of biomedical images requires computational expertize that are uncommon among biomedical scientists. Deep learning approaches for image analysis provide an opportunity to develop user-friendly tools for exploratory data analysis. Here, we use the visual programming toolbox Orange (http://orange.biolab.si) to simplify image analysis by integrating deep-learning embedding, machine learning procedures, and data visualization. Orange supports the construction of data analysis workflows by assembling components for data preprocessing, visualization, and modeling. We equipped Orange with components that use pre-trained deep convolutional networks to profile images with vectors of features. These vectors are used in image clustering and classification in a framework that enables mining of image sets for both novel and experienced users. We demonstrate the utility of the tool in image analysis of progenitor cells in mouse bone healing, identification of developmental competence in mouse oocytes, subcellular protein localization in yeast, and developmental morphology of social amoebae

From Classical Genetics to Quantitative Genetics to Systems Biology: Modeling Epistasis

Gene expression data has been used in lieu of phenotype in both classical and quantitative genetic settings. These two disciplines have separate approaches to measuring and interpreting epistasis, which is the interaction between alleles at different loci. We propose a framework for estimating and interpreting epistasis from a classical experiment that combines the strengths of each approach. A regression analysis step accommodates the quantitative nature of expression measurements by estimating the effect of gene deletions plus any interaction. Effects are selected by significance such that a reduced model describes each expression trait. We show how the resulting models correspond to specific hierarchical relationships between two regulator genes and a target gene. These relationships are the basic units of genetic pathways and genomic system diagrams. Our approach can be extended to analyze data from a variety of experiments, multiple loci, and multiple environments

The transcription factor Spores Absent A is a PKA dependent inducer of Dictyostelium sporulation

Abstract Sporulation in Dictyostelium fruiting bodies evolved from amoebozoan encystation with both being induced by cAMP acting on PKA, but with downstream components still being unknown. Using tagged mutagenesis to find missing pathway components, we identified a sporeless mutant defective in a nuclear protein, SpaA. Expression of prespore genes was strongly reduced in spaA- cells, while expression of many spore stage genes was absent. Chromatin immunoprecipitation (ChIP) of a SpaA-YFP gene fusion showed that (pre)spore gene promoters bind directly to SpaA, identifying SpaA as a transcriptional regulator. SpaA dependent spore gene expression required PKA in vivo and was stimulated in vitro by the membrane-permeant PKA agonist 8Br-cAMP. The PKA agonist also promoted SpaA binding to (pre)spore promoters, placing SpaA downstream of PKA. Sequencing of SpaA-YFP ChIPed DNA fragments revealed that SpaA binds at least 117 (pre)spore promoters, including those of other transcription factors that activate some spore genes. These factors are not in turn required for spaA expression, identifying SpaA as the major trancriptional inducer of sporulation

Broad targeting of resistance to apoptosis in cancer

Apoptosis or programmed cell death is natural way of removing aged cells from the body. Most of the anti-cancer therapies trigger apoptosis induction and related cell death networks to eliminate malignant cells. However, in cancer, de-regulated apoptotic signaling, particularly the activation of an anti-apoptotic systems, allows cancer cells to escape this program leading to uncontrolled proliferation resulting in tumor survival, therapeutic resistance and recurrence of cancer. This resistance is a complicated phenomenon that emanates from the interactions of various molecules and signaling pathways. In this comprehensive review we discuss the various factors contributing to apoptosis resistance in cancers. The key resistance targets that are discussed include (1) Bcl-2 and Mcl-1 proteins; (2) autophagy processes; (3) necrosis and necroptosis; (4) heat shock protein signaling; (5) the proteasome pathway; (6) epigenetic mechanisms; and (7) aberrant nuclear export signaling. The shortcomings of current therapeutic modalities are highlighted and a broad spectrum strategy using approaches including (a) gossypol; (b) epigallocatechin-3-gallate; (c) UMI-77 (d) triptolide and (e) selinexor that can be used to overcome cell death resistance is presented. This review provides a roadmap for the design of successful anti-cancer strategies that overcome resistance to apoptosis for better therapeutic outcome in patients with cancer

The Putative bZIP Transcripton Factor BzpN Slows Proliferation and Functions in the Regulation of Cell Density by Autocrine Signals in Dictyostelium

The secreted proteins AprA and CfaD function as autocrine signals that inhibit cell proliferation in Dictyostelium discoideum, thereby regulating cell numbers by a negative feedback mechanism. We report here that the putative basic leucine zipper transcription factor BzpN plays a role in the inhibition of proliferation by AprA and CfaD. Cells lacking BzpN proliferate more rapidly than wild-type cells but do not reach a higher stationary density. Recombinant AprA inhibits wild-type cell proliferation but does not inhibit the proliferation of cells lacking BzpN. Recombinant CfaD also inhibits wild-type cell proliferation, but promotes the proliferation of cells lacking BzpN. Overexpression of BzpN results in a reduced cell density at stationary phase, and this phenotype requires AprA, CfaD, and the kinase QkgA. Conditioned media from high-density cells stops the proliferation of wild-type but not bzpN− cells and induces a nuclear localization of a BzpN-GFP fusion protein, though this localization does not require AprA or CfaD. Together, the data suggest that BzpN is necessary for some but not all of the effects of AprA and CfaD, and that BzpN may function downstream of AprA and CfaD in a signal transduction pathway that inhibits proliferation

Experimentally Guided Computational Model Discovers Important Elements for Social Behavior in Myxobacteria

Identifying essential factors in cellular interactions and organized movement of cells is important in predicting behavioral phenotypes exhibited by many bacterial cells. We chose to study Myxococcus xanthus, a soil bacterium whose individual cell behavior changes while in groups, leading to spontaneous formation of aggregation center during the early stage of fruiting body development. In this paper, we develop a cell-based computational model that solely relies on experimentally determined parameters to investigate minimal elements required to produce the observed social behaviors in M. xanthus. The model verifies previously known essential parameters and identifies one novel parameter, the active turning, which we define as the ability and tendency of a cell to turn to a certain angle without the presence of any obvious external factors. The simulation is able to produce both gliding pattern and spontaneous aggregation center formation as observed in experiments. The model is tested against several known M. xanthus mutants and our modification of parameter values relevant for the individual mutants produces good phenotypic agreements. This outcome indicates the strong predictive potential of our model for the social behaviors of uncharacterized mutants and their expected phenotypes during development

The Dictyostelium discoideum acaA Gene Is Transcribed from Alternative Promoters during Aggregation and Multicellular Development

Background: Extracellular cAMP is a key extracellular signaling molecule that regulates aggregation, cell differentiation and morphogenesis during multi-cellular development of the social amoeba Dictyostelium discoideum. This molecule is produced by three different adenylyl cyclases, encoded by the genes acaA, acrA and acgA, expressed at different stages of development and in different structures. Methodology/Principal Findings: This article describes the characterization of the promoter region of the acaA gene, showing that it is transcribed from three different alternative promoters. The distal promoter, promoter 1, is active during the aggregation process while the more proximal promoters are active in tip-organiser and posterior regions of the structures. A DNA fragment containing the three promoters drove expression to these same regions and similar results were obtained by in situ hybridization. Analyses of mRNA expression by quantitative RT-PCR with specific primers for each of the three transcripts also demonstrated their different temporal patterns of expression. Conclusions/Significance: The existence of an aggregation-specific promoter can be associated with the use of cAMP as chemo-attractant molecule, which is specific for some Dictyostelium species. Expression at late developmental stages indicates that adenylyl cyclase A might play a more important role in post-aggregative development than previously considered