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bioRxiv2018

Contingency in the convergent evolution of a regulatory network: Dosage compensation in Drosophila

The repeatability or predictability of evolution is a central question in evolutionary biology, and most often addressed in experimental evolution studies. Here, we infer how genetically heterogeneous natural systems acquire the same molecular changes, to address how genomic background affects adaptation in natural populations. In particular, we take advantage of independently formed neo-sex chromosomes in Drosophila species that have evolved dosage compensation by co-opting the dosage compensation (MSL) complex, to study the mutational paths that have led to the acquisition of 100s of novel binding sites for the MSL complex in different species. This complex recognizes a conserved 21-bp GA-rich sequence motif that is enriched on the X chromosome, and newly formed X chromosomes recruit the MSL complex by de novo acquisition of this binding motif. We identify recently formed sex chromosomes in the Drosophila repleta and robusta species groups by genome sequencing, and generate genomic occupancy maps of the MSL complex to infer the location of novel binding sites. We find that diverse mutational paths were utilized in each species to evolve 100s of de novo binding motifs along the neo-X, including expansions of microsatellites and transposable element insertions. However, the propensity to utilize a particular mutational path differs between independently formed X chromosomes, and appears to be contingent on genomic properties of that species, such as simple repeat or transposable element density. This establishes the \"genomic environment\" as an important determinant in predicting the outcome of evolutionary adaptations.

evolutionary biology↗

bioRxiv2018

Subcellular Time Series Modeling of Heterogeneous Cell Protrusion

In this paper, a new biological modeling approach is proposed for predicting complex heterogeneous subcellular behaviors. Cell protrusion which initiates cell migration has a significant amount of subcellular heterogeneity in micrometer length and minute time scales. It is driven by actin polymerization, e.g., pushing the plasma membrane forward, and then regulated by a multitude of actin regulators. While mathematical modeling is central to system-level understandings of cell protrusion, most of the modeling is based on the ensemble average of actin regulator dynamics at the cellular or population levels, preventing from capturing the heterogeneous cellular activities. With these in mind, a systematic modeling framework is proposed in this paper for predicting velocities of heterogeneous protrusion of migrating cells driven by multiple molecular mechanisms. The modeling framework is developed through the integration of the multiple AutoRegressive eXogenous (ARX) models employing probability density input variables. Unlike conventional ARX models, it provides an effective framework for modeling heterogeneous subcellular behaviors with complex nonlinearities and uncertainties of dynamic systems. To train and validate the proposed model, numerous subcellular time series are extracted from time-lapse movies of migrating PtK1 cells using spinning disk confocal microscope: The current edge velocities and fluorescent intensities of mDia1, actin at the leading edge are used as the input while the future cell edge velocities are selected as an output. It is demonstrated that the proposed approach is highly effective in predicting the future trends of heterogeneous cell protrusion. In particular, by capturing the various multiple activities from the dataset, it is expected that it would improve the understanding of the molecular mechanism underlying cellular and subcellular heterogeneity.

systems biology↗

bioRxiv2018

Periodically driven force protein translocation through a α-hemolysin biological nano-pore

We study the translocation of protein pulled under the action of time periodically external driving force through -hemolysin nano-pore using Langevin molecular dynamical simulation. We observe that time depended external pulling force could enhance to more efficient translocation process as compared to protein translocation driven by constant external pulling force. We characterized the time depended force driven translocation mechanism by studying the gain in translocation as a function of frequency. We also present Golestanian plot which shows the modulated evolutions of number of translocation peptides, and of the probability distribution function with frequency as a results of the transmission of force oscillation to translocation dynamics.

bioinformatics↗

bioRxiv2015

A cell-free framework for biological systems engineering

SUMMARYWhile complex dynamic biological networks control gene expression and metabolism in all living organisms, engineering comparable synthetic networks remains challenging1,2. Conducting extensive, quantitative and rapid characterization during the design and implementation process of synthetic networks is currently severely limited due to cumbersome molecular cloning and the difficulties associated with measuring parts, components and systems in cellular hosts. Engineering gene networks in a cell-free environment promises to be an efficient and effective approach to rapidly develop novel biological systems and understand their operating regimes3-5. However, it remains questionable whether complex synthetic networks behave similarly in cells and a cell-free environment, which is critical for in vitro approaches to be of significance to biological engineering. Here we show that synthetic dynamic networks can be readily implemented, characterized, and engineered in a cell-free framework and consequently transferred to cellular hosts. We implemented and characterized the \"repressilator\"6, a three-node negative feedback oscillator in vitro. We then used our cell-free framework to engineer novel three-node, four-node, and five-node negative feedback architectures going from the characterization of circuit components to the rapid analysis of complete networks. We validated our cell-free approach by transferring these novel three-node and five-node oscillators to Escherichia coli, resulting in robust and synchronized oscillations reflecting the in vitro observation. We demonstrate that comprehensive circuit engineering can be performed in a cell-free system and that the in vitro results have direct applicability in vivo. Cell-free synthetic biology thus has the potential to drastically speed up design-build-test cycles in biological engineering and enable the quantitative characterization of synthetic and natural networks.

Synthetic Biology↗

bioRxiv2017

Sex differences in gene regulation in the dorsal root ganglion after nerve injury

Pain is a subjective experience derived from complex interactions among biological, environmental, and psychosocial pathways. Sex differences in pain sensitivity and chronic pain prevalence are well established. However, the molecular causes underlying these sex dimorphisms are poorly understood particularly with regard to the role of the peripheral nervous system. Here we sought to identify shared and distinct gene networks functioning in the peripheral nervous systems that may contribute to sex differences of pain after nerve injury. We performed RNA-seq on dorsal root ganglia following chronic constriction injury of the sciatic nerve in male and female rats. Analysis from paired naive and injured tissues showed that 1456 genes were differentially expressed between sexes. Appreciating sex-related gene expression differences and similarities in neuropathic pain models may help to improve the translational relevance to clinical populations and efficacy of clinical trials of this major health issue.

neuroscience↗

bioRxiv2017

Effects of mutation and selection on plasticity of TDH3 promoter activity in Saccharomyces cerevisiae

Phenotypic plasticity is an evolvable property of biological systems that can arise from environment-specific regulation of gene expression. To better understand the evolutionary and molecular mechanisms that give rise to plasticity in gene expression, we quantified the effects of 235 single nucleotide mutations in the Saccharomyces cerevisiae TDH3 promoter (PTDH3) on the activity of this promoter in media containing glucose, galactose, or glycerol as a carbon source. We found that the distributions of mutational effects differed among environments because many mutations altered the plastic response exhibited by the wild type allele. Comparing the effects of these mutations to the effects of 30 PTDH3 polymorphisms on expression plasticity in the same environments provided evidence of natural selection acting to prevent the plastic response in PTDH3 activity between glucose and galactose from becoming larger. The largest changes in expression plasticity were observed between fermentable (glucose or galactose) and nonfermentable (glycerol) carbon sources and were caused by mutations located in the RAP1 and GCR1 transcription factor binding sites. Mutations altered expression plasticity most frequently between the two fermentable environments, however, with mutations causing significant changes in plasticity between glucose and galactose distributed throughout the promoter, suggesting they might affect chromatin structure. Taken together, these results provide insight into the molecular mechanisms underlying gene-by-environment interactions affecting gene expression as well as the evolutionary dynamics affecting natural variation in plasticity of gene expression.\n\nSignificance StatementFrom seasonal variation in the color of butterfly wings to trees bending toward the light, organisms often change in response to their environment. These changes, known as phenotypic plasticity, can result from differences in how genes are expressed among environments. Mutations causing environment-specific changes in gene expression provide raw material for phenotypic plasticity, but their frequency, effect size and direction of effects among environments are not well understood. This study shows that mutations in the promoter of a yeast metabolic gene often display environment-dependent effects on gene expression and that these environment-dependent effects have been shaped by selection in natural populations.

genetics↗

bioRxiv2017

The evolutionary history of the current global Ramularia collo-cygni epidemic

Ramularia Leaf Spot (RLS) has emerged as a threat for barley production in many regions of the world. Late appearance of unspecific symptoms caused that Ramularia collo-cygni could only by molecular diagnostics be detected as the causal agent of RLS. Although recent research has shed more light on the biology and genomics of the pathogen, the cause of the recent global spread remains unclear.\n\nTo address urgent questions, especially on the emergence to a major disease, life-cycle, transmission, and quick adaptation to control measures, we de-novo sequenced the genome of R. collo-cygni (urug2 isolate). Additionally, we sequenced fungal RNA from 6 different conditions, which allowed for an improved genome annotation. This resulted in a high quality draft assembly of about 32 Mb, with only 78 scaffolds with an N50 of 2.1 Mb. The overall annotation enabled the prediction of 12.346 high confidence genes. Genomic comparison revealed that R. collo-cygni has significantly diverged from related Dothidiomycetes, including gain and loss of putative effectors, however without obtaining species-specific genome features.\n\nTo evaluate the species-wide genetic diversity, we sequenced the genomes of 19 R. collo-cygni isolates from multiple geographic locations and diverse hosts and mapped sequences to our reference genome. Admixture analyses show that R. collo-cygni is world-wide genetically uniform and that samples do not show a strong clustering on either geographical location or host species. To date, the teleomorph of R. collo-cygni has not been observed. Analysis of linkage disequilibrium shows that in the world-wide sample set there are clear signals of recombination and thus sexual reproduction, however these signals largely disappear when excluding three outliers samples, suggesting that the main global expansion of R. collo-cygni comes from mixed or clonally propagating populations. We further analysed the historic population size (Ne) of R. collo-cygni using Bayesian simulations.\n\nWe discuss how our genomic data and population genetics analysis can help understand the current R. collo-cygni epidemic and provide different hypothesis that are supported by our data. We specifically highlight how recombination, clonal spreading and lack of host-specificity could further support global epidemics of this increasingly recognized plant disease and suggest specific approaches to combat this pathogen.

plant biology↗

bioRxiv2018

Elimination of PCR duplicates in RNA-seq and small RNA-seq using unique molecular identifiers

RNA-seq and small RNA-seq are powerful, quantitative tools to study gene regulation and function. Common high-throughput sequencing methods rely on polymerase chain reaction (PCR) to expand the starting material, but not every molecule amplifies equally, causing some to be overrepresented. Unique molecular identifiers (UMIs) can be used to distinguish undesirable PCR duplicates derived from a single molecule and identical but biologically meaningful reads from different molecules. We have incorporated UMIs into RNA-seq and small RNA-seq protocols and developed tools to analyze the resulting data. Our UMIs contain stretches of random nucleotides whose lengths sufficiently capture diverse molecule species in both RNA-seq and small RNA-seq libraries generated from mouse testis. Our approach yields high-quality data while allowing unique tagging of all molecules in high-depth libraries. Using simulated and real datasets, we demonstrate that our methods increase the reproducibility of RNA-seq and small RNA-seq data. Notably, we find that the amount of starting material and sequencing depth, but not the number of PCR cycles, determine PCR duplicate frequency. Finally, we show that computational removal of PCR duplicates based only on their mapping coordinates introduces substantial bias into data analysis.

genomics↗

bioRxiv2018

Ribo-tag translatomic profiling of Drosophila oenocyte reveals down-regulation of peroxisome and mitochondria biogenesis under aging and oxidative stress

BackgroundAging is accompanied with loss of tissue homeostasis and accumulation of cellular damages. As one of the important metabolic centers, aged liver shows altered lipid metabolism, impaired detoxification pathway, increased inflammation and oxidative stress response. However, the mechanisms for these age-related changes still remain unclear. In fruit flies, Drosophila melanogaster, liver-like functions are controlled by two distinct tissues, fat body and oenocytes. Although the role of fat body in aging regulation has been well studied, little is known about how oenocytes age and what are their roles in aging regulation. To address these questions, we used cell-type-specific ribosome profiling (RiboTag) to study the impacts of aging and oxidative stress on oenocyte translatome in Drosophila.\n\nResultsWe show that aging and oxidant paraquat significantly increased the levels of reactive oxygen species (ROS) in adult oenocytes of Drosophila, and aged oenocytes exhibited reduced sensitivity to paraquat treatment. Through RiboTag sequencing, we identified 3324 and 949 differentially expressed genes in oenocytes under aging and paraquat treatment, respectively. Aging and paraquat exhibit both shared and distinct regulations on oenocyte translatome. Among all age-regulated genes, mitochondrial, proteasome, peroxisome, fatty acid metabolism, and cytochrome P450 pathways were down-regulated, whereas DNA replication and glutathione metabolic pathways were up-regulated. Interestingly, most of the peroxisomal genes were down-regulated in aged oenocytes, including peroxisomal biogenesis factors and beta-oxidation genes. Further analysis of the oenocyte translatome showed that oenocytes highly expressed genes involving in liver-like processes (e.g., ketogenesis). Many age-related transcriptional changes in oenocytes are similar to aging liver, including up-regulation of Ras/MAPK signaling pathway and down-regulation of peroxisome and fatty acid metabolism.\n\nConclusionsOur oenocyte-specific translatome analysis identified many genes and pathways that are shared between Drosophila oenocytes and mammalian liver, highlighting the molecular and functional similarities between the two tissues. Many of these genes are altered in both aged oenocytes and aged liver, suggesting a conserved molecular mechanism underlying oenocyte and liver aging. Thus, our translatome analysis will contribute significantly to the understanding of oenocyte biology, and its role in lipid metabolism, stress response and aging regulation.

genomics↗

bioRxiv2018

Coarse-Grained Model of the SNARE Complex Shows that Quick Zippering Requires Partial Assembly

Neuronal transmitters are released from nerve terminals via the fusion of synaptic vesicles with the presynaptic membrane. Vesicles become attached to the membrane via the SNARE complex. The SNARE complex comprises the vesicle associate protein Synaptobrevin (Syb), the membrane associated protein syntaxin (Syx), and the cytosolic protein SNAP25, which together form a four-helical bundle. The full assembly of Syb onto the core SNARE bundle promotes vesicle fusion. We investigated SNARE assembly using a coarse-grained model of the SNARE complex. The model retains chemical specificity, and was calibrated using single molecule experiments and all-atom molecular dynamics simulations. Steered force-control simulations of SNARE unzippering by peeling off Syb were used to set up initial disassembled states of the SNARE complex. From these states, the assembly process was simulated. We found that if Syb is in helical form, then the SNARE complex assembles rapidly, on a sub-microsecond time-scale. We found that assembly times grow exponentially with separation distance between Syb and Syx C-termni. The formation of helical turns is likely to substantially decelerate the assembly, consistent with single molecule force experiments that show SNARE assembly duration on the time-scale of hundreds of ms. Since synaptic vesicle fusion occurs at a sub-millisecond time-scale, our results indicate that for biologically relevant rapid assembly the SNARE complex needs to be partially zippered and its constituent helices brought into proximity, possibly by means of molecular chaperones.

biophysics↗

bioRxiv2018

Classifying Bladder Cancer Subtypes

Urothelial carcinoma of the bladder is is estimated to have killed over 16,000 people in the United States in 2016. Like breast cancer, bladder cancer is a heterogeneous disease, and characterization of its various subtypes can be useful for forecasting prognosis and treatment efficacy. According to The Cancer Genome Atlas (TCGA) project, the mRNA expression profiles of bladder tumours can be used to cluster the tumors into four different categories: I - Papillary-like, II -Luminal A, III - basal/squamous-like, and IV - other (similar to III). However it is not clear whether these mRNA expression based clusters correlate with other molecular and genetic features of the tumor cells. In other words, do differences in mRNA expression profile contain the same information as differences in protein expression, micro RNA (miRNA) expression, copy number variation and somatic mutation data. We tried to recreate mRNA based bladder tumor clusters from other multi-omic data for 328 bladder cancer tumor samples using a special deep and wide belief network composed of restricted Boltzmann machines and a multilayer perceptron. For 10-fold cross validation, we got 79% average test accuracy which implies that that differences in mRNA expression between bladder tumor cells can be reliably, though not perfectly, inferred from different molecular and genetic features of the tumors.

cancer biology↗

bioRxiv2018

Delving deeper: Relating the behaviour of a metabolic system to the properties of its components using symbolic metabolic control analysis

High-level behaviour of metabolic systems results from the properties of, and interactions between, numerous molecular components. Reaching a complete understanding of metabolic behaviour based on the systems components is therefore a difficult task. This problem can be tackled by constructing and subsequently analysing kinetic models of metabolic pathways since such models aim to capture all the relevant properties of the system components and their interactions.\n\nSymbolic control analysis is a framework for analysing pathway models in order to reach a mechanistic understanding of their behaviour. By providing algebraic expressions for the sensitivities of system properties, such as metabolic fluxor steady-state concentrations, in terms of the properties of individual reactions it allows one to trace the high level behaviour back to these low level components. Here we apply this method to a model of pyruvate branch metabolism in Lactococcus lactis in order to explain a previously observed negative flux response towards an increase in substrate concentration. With this method we are able to show, first, that the sensitivity of flux towards changes in reaction rates (represented by flux control coefficients) is determined by the individual metabolic branches of the pathway, and second, how the sensitivities of individual reaction rates towards their substrates (represented by elasticity coefficients) contribute to this flux control. We also quantify the contributions of enzyme binding and mass-action to enzyme elasticity separately, which allows for an even finer-grained understanding of flux control.\n\nThese analytical tools allow us to analyse the control properties of a metabolic model and to arrive at a mechanistic understanding of the quantitative contributions of each of the enzymes to this control. Our analysis provides an example of the descriptive power of the general principles of symbolic control analysis.\n\nAuthor summaryMetabolic networks are complex systems consisting of numerous individual molecular components. The properties of these components, together with their non-linear interactions, give rise to high-level observed behaviour of the system in which they reside. Therefore, in order to fully understand the behaviour of a metabolic system, one has to consider the properties of all of its components. The analysis of computer models that capture and represent these systems and their components simplifies this task by allowing for an easy way to isolate the effects of each individual component. In this paper we use the framework of symbolic control analysis to investigate the sensitivity of the rate of flow of matter through one of the branches in a particular metabolic pathway towards changes in the rates of individual reactions. Here we are able to quantify how certain chains of reactions, individual reactions, and even thermodynamic and kinetic aspects of individual reactions contribute to the overall sensitivity of the rate of matter-flow. Thus, we are able to trace the behaviour of the system as a whole in a mechanistic way to the properties of the individual molecular components.

systems biology↗

bioRxiv2018

The perils of intralocus recombination for inferences of molecular convergence

Accurate inferences of convergence require that the appropriate tree topology be used. If there is a mismatch between the tree a trait has evolved along and the tree used for analysis, then false inferences of convergence (\"hemiplasy\") can occur. To avoid problems of hemiplasy when there are high levels of gene tree discordance with the species tree, researchers have begun to construct tree topologies from individual loci. However, due to intralocus recombination even locus-specific trees may contain multiple topologies within them. This implies that the use of individual tree topologies discordant with the species tree can still lead to incorrect inferences about molecular convergence. Here we examine the frequency with which single exons and single protein-coding genes contain multiple underlying tree topologies, in primates and Drosophila, and quantify the effects of hemiplasy when using trees inferred from individual loci. In both clades we find that there are most often multiple diagnosable topologies within single exons and whole genes, with 91% of Drosophila protein-coding genes containing multiple topologies. Because of this underlying topological heterogeneity, even using trees inferred from individual protein-coding genes results in 25% and 38% of substitutions falsely labeled as convergent in primates and Drosophila, respectively. While constructing local trees can reduce the problem of hemiplasy, our results suggest that it will be difficult to completely avoid false inferences of convergence. We conclude by suggesting several ways forward in the analysis of convergent evolution, for both molecular and morphological characters.

evolutionary biology↗

bioRxiv2018

Modular co-option of cardiopharyngeal genes during non-embryonic myogenesis

BackgroundIn chordates cardiac and body muscles arise from different embryonic origins. Myogenesis can in addition be triggered in adult organisms, during asexual development or regeneration. In the non-vertebrate ascidians, muscles originate from embryonic precursors regulated by a conserved set of genes that orchestrate cell behavior and dynamics during development. In colonial ascidians, besides embryogenesis and metamorphosis, an adult can propagate asexually via blastogenesis, skipping embryo and larval stages, and form anew the adult body, including the complete body musculature.\n\nResultsTo investigate the cellular origin and mechanisms that trigger non-embryonic myogenesis, we followed the expression of ascidian myogenic genes during Botryllus schlosseri blastogenesis, and reconstructed the dynamics of muscle precursors. Based on the expression dynamics of Tbx1/10, Ebf, Mrf, Myh3 for body wall and of FoxF, Tbx1/10, Nk4, Myh2 for heart development we show that the embryonic factors regulating myogenesis are only partially co-opted in blastogenesis, and propose that the cellular precursors contributing to heart or body muscles have different origins.\n\nConclusionsRegardless of the developmental pathway, non-embryonic myogenesis shares a similar molecular and anatomical setup as embryonic myogenesis, but implements co-option and loss of molecular modules.

developmental biology↗

bioRxiv2018

Codon-dependent noise dictates cell-to-cell variability in nutrient poor environments

Under nutrient-rich conditions, stochasticity of transcription drives protein expression noise. However, by shifting the environment to amino acid-limited conditions, we identified in E. coli a source of noise whose strength is dictated by translational processes. Specifically, we discovered that cell-to-cell variations in fluorescent protein expression depend on codon choice, with codons yielding lower mean expression after amino acid downshift also resulting in greater noise. We propose that ultra-sensitivity in the tRNA charging/discharging cycle shapes the strength of the observed noise by amplifying fluctuations in global intracellular parameters, such as the concentrations of amino acid, synthetase, and tRNA. We hypothesize that this codon-dependent noise may allow bacteria to selectively optimize cell-to-cell variability in poor environments without relying on low molecular numbers.

systems biology↗

bioRxiv2018

Self-organization controls expression more than abundance of molecular components of transcription and translation in confined cell-free gene expression

Cell-free gene expression using purified components or cell extracts has become an important platform for synthetic biology that is finding a growing numBer of practical applications. Unfortunately, at cell-relevant reactor volumes, cell-free expression suffers from excessive variability (noise) such that protein concentrations may vary by more than an order of magnitude across a population of identically constructed reaction chambers. Consensus opinion holds that variability in expression is due to the stochastic distribution of expression resources (DNA, RNAP, ribosomes, etc.) across the population of reaction chambers. In contrast, here we find that chamber-to-chamber variation in the expression efficiency generates the large variability in protein production. Through analysis and modeling, we show that chambers self-organize into expression centers that control expression efficiency. Chambers that organize into many centers, each having relatively few expression resources, exhibit high expression efficiency. Conversely, chambers that organize into just a few centers where each center has an abundance of resources, exhibit low expression efficiency. A particularly surprising finding is that diluting expression resources reduces the chamber-to-chamber variation in protein production. Chambers with dilute pools of expression resources exhibit higher expression efficiency and lower expression noise than those with more concentrated expression resources. In addition to demonstrating the means to tune expression noise, these results demonstrate that in cell-free systems, self-organization may exert even more influence over expression than the abundance of the molecular components of transcription and translation. These observations in cell-free platform may elucidate how self-organized, membrane-less structures emerge and function in cells.

biophysics↗

bioRxiv2017

DNA methylation differences at regulatory elements are associated with the cancer risk factor age in normal breast tissue

BackgroundThe underlying biological mechanisms through which epidemiologically defined breast cancer risk factors contribute to disease risk remain poorly understood. Identification of the molecular changes associated with cancer risk factors in normal tissues may aid in determining the earliest events of carcinogenesis and informing cancer prevention strategies.\n\nResultsHere we investigated the impact cancer risk factors have on the normal breast epigenome by analyzing DNA methylation genome-wide (Infinium 450K array) in cancer-free women from the Susan G. Komen Tissue Bank (n = 100). We tested the relation of established breast cancer risk factors: age, body mass index, parity, and family history of disease with DNA methylation adjusting for potential variation in cell-type proportions. We identified 787 CpG sites that demonstrated significant associations (Q-value < 0.01) with subject age. Notably, DNA methylation was not strongly associated with the other evaluated breast cancer risk factors. Age-related DNA methylation changes are primarily increases in methylation enriched at breast epithelial cell enhancer regions (P = 7.1E-20), and binding sites of chromatin remodelers (MYC and CTCF). We validated the age-related associations in two independent populations of normal breast tissue (n = 18) and normal-adjacent to tumor tissue (n = 97). The genomic regions classified as age-related were more likely to be regions altered in cancer in both pre-invasive (n = 40, P=3.0E-03) and invasive breast tumors (n = 731, P=1.1E-13).\n\nConclusionsDNA methylation changes with age occur at regulatory regions, and are further exacerbated in cancer suggesting that age influences breast cancer risk in part through its contribution to epigenetic dysregulation in normal breast tissue.

epidemiology↗

bioRxiv2017

A model for autonomous and non-autonomous effects of the Hippo pathway in Drosophila

While significant progress has been made toward understanding morphogen-mediated patterning in development from both the experimental and the theoretical side, the control of size and shape of tissues and organs is poorly understood. Both involve adjustment of the scale of gene expression to the size of the system, but how growth and patterning are coupled to produce scale invariance and how molecular-level information is translated into organ- and organism-level functioning is one of the most difficult problems in biology. The Hippo pathway, which controls cell proliferation and apoptosis in Drosophila and mammalian cells, contains a core kinase mechanism that affects control of the cell cycle and growth. Studies involving over- and under-expression of components in the morphogen and Hippo pathways in Drosophila reveal conditions that lead to over- or undergrowth. Herein we develop a mathematical model that incorporates the current understanding of the Hippo signal transduction network and which can explain qualitatively both the observations on whole-disc manipulations and the results arising from mutant clones. We find that a number of non-intuitive experimental results can be explained by subtle changes in the balances between inputs to the Hippo pathway. Since signal transduction and growth control pathways are highly conserved across species, much of what is learned about Drosophila applies in higher organisms, and may have direct relevance to tumor dynamics in mammalian systems.

biophysics↗