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IntroductionIncreasing evidence supports a role of an epithelial to mesenchymal transition (EMT) process in endowing subsets of tumor cells with properties driving malignant tumor progression and resistance to cancer therapy. To advance our understanding of the underlying mechanisms, we sought to generate a transplantable cellular model system that allows defined experimental manipulation and analysis of EMT in vitro and at the same time recapitulates oncogenic EMT in vivo.Methodology/resultsWe have established a stable murine breast cancer cell line (Py2T) from a breast tumor of an MMTV-PyMT transgenic mouse. Py2T cells display a metastable epithelial phenotype characterized by concomitant expression of luminal and basal cytokeratins and sheet migration. Exposure of Py2T cells to transforming growth factor β (TGFβ) in vitro induces reversible EMT accompanied by downregulation of E-cadherin and upregulation of mesenchymal markers, including EMT transcription factors, and a gain in single cell motility and invasiveness. Py2T cells give rise to tumors after orthotopic injection into syngeneic FVB/N mice. Notably, transplantation of epithelial Py2T cells results in the formation of invasive primary tumors with low to absent E-cadherin expression, indicating that the cells undergo EMT-like changes in vivo. This process appears to at least in part depend on TGFβ signaling, since tumors formed by Py2T cells expressing a dominant-negative version of TGFβ receptor widely maintain their epithelial differentiation status.Conclusions/significanceTogether, the data demonstrate that the Py2T cell line represents a versatile model system to study the EMT process in vitro and in vivo. The observation that Py2T cells give rise to tumors and collectively undergo EMT-like changes in vivo highlights the suitability of the Py2T model system as a tool to study tumor-related EMT. In particular, Py2T cells may serve to corroborate recent findings relating EMT to cancer cell stemness, to therapy resistance and to tumor recurrence. more...

Conventional lipid-tube formation is based on either a tube phase of certain lipids or the shape transformation of lamellar structures by applying a point load. In the present study, lipid blocks in inverted hexagonal phase made of 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) were shown to protrude lipid nanotubes upon a fluid-dynamic flow on polyelectrolyte-functionalized surfaces in physiological buffer solution. The outer diameter of the tubes is 19.1 ± 4.5 nm and their lengths are up to several hundred micrometers. The method described enables the alignment and patterning of lipid nanotubes into various (including curvy) shapes with a microfluidic system. more...

A third of the human genome encodes N-glycosylated proteins. These are co-translationally translocated into the lumen/membrane of the endoplasmic reticulum (ER) where they fold and assemble before they are transported to their final destination. Here, we show that calnexin, a major ER chaperone involved in glycoprotein folding is palmitoylated and that this modification is mediated by the ER palmitoyltransferase DHHC6. This modification leads to the preferential localization of calnexin to the perinuclear rough ER, at the expense of ER tubules. Moreover, palmitoylation mediates the association of calnexin with the ribosome-translocon complex (RTC) leading to the formation of a supercomplex that recruits the actin cytoskeleton, leading to further stabilization of the assembly. When formation of the calnexin-RTC supercomplex was affected by DHHC6 silencing, mutation of calnexin palmitoylation sites or actin depolymerization, folding of glycoproteins was impaired. Our findings thus show that calnexin is a stable component of the RTC in a manner that is exquisitely dependent on its palmitoylation status. This association is essential for the chaperone to capture its client proteins as they emerge from the translocon, acquire their N-linked glycans and initiate folding. The EMBO Journal (2012) 31, 1823-1835. doi: 10.1038/emboj.2012.15; Published online 7 February 2012 more...

In order to understand how retinal circuits encode visual scenes, the neural activity of defined populations of retinal ganglion cells (RGCs) has to be investigated. Here we report on a method for stimulating, detecting, and subsequently targeting defined populations of RGCs. The possibility to select a distinct population of RGCs for extracellular recording enables the design of experiments that can increase our understanding of how these neurons extract precise spatio-temporal features from the visual scene, and how the brain interprets retinal signals. We used light stimulation to elicit a response from physiologically distinct types of RGCs and then utilized the dynamic-configurability capabilities of a microelectronics-based high-density microelectrode array (MEA) to record their synchronous action potentials. The layout characteristics of the MEA made it possible to stimulate and record from multiple, highly overlapping RGCs simultaneously without light-induced artifacts. The high-density of electrodes and the high signal-to-noise ratio of the MEA circuitry allowed for recording of the activity of each RGC on 14 ± 7 electrodes. The spatial features of the electrical activity of each RGC greatly facilitated spike sorting. We were thus able to localize, identify and record from defined RGCs within a region of mouse retina. In addition, we stimulated and recorded from genetically modified RGCs to demonstrate the applicability of optogenetic methods, which introduces an additional feature to target a defined cell type. The developed methodologies can likewise be applied to other neuronal preparations including brain slices or cultured neurons. more...

Glycosylphosphatidylinositol (GPI) anchor biosynthesis takes place in the endoplasmic reticulum (ER). After protein attachment, the GPI anchor is transported to the Golgi where it undergoes fatty acid remodeling. The ER exit of GPI-anchored proteins is controlled by glycan remodeling and p24 complexes act as cargo receptors for GPI anchor sorting into COPII vesicles. In this study, we have characterized the lipid profile of mammalian cell lines that have a defect in GPI anchor biosynthesis. Depending on which step of GPI anchor biosynthesis the cells were defective, we observed sphingolipid changes predominantly for very long chain monoglycosylated ceramides (HexCer). We found that the structure of the GPI anchor plays an important role in the control of HexCer levels. GPI anchor-deficient cells that generate short truncated GPI anchor intermediates showed a decrease in very long chain HexCer levels. Cells that synthesize GPI anchors but have a defect in GPI anchor remodeling in the ER have a general increase in HexCer levels. GPI-transamidase-deficient cells that produce no GPI-anchored proteins but generate complete free GPI anchors had unchanged levels of HexCer. In contrast, sphingomyelin levels were mostly unaffected.(jlr) We therefore propose a model in which the transport of very long chain ceramide from the ER to Golgi is regulated by the transport of GPI anchor molecules.-Loizides-Mangold, U., F. P. A. David, V. J. Nesatyy, T. Kinoshita, and H. Riezman. Glycosylphosphatidylinositol anchors regulate glycosphingolipid levels. J. Lipid Res. 2012. 53: 1522-1534. more...

Our interest is to characterize the spline-like integer-shift-invariant bases capable of reproducing exponential polynomial curves. We prove that any compact-support function that reproduces a subspace of the exponential polynomials can be expressed as the convolution of an exponential B-spline with a compact-support distribution. As a direct consequence of this factorization theorem, we show that the minimal-support basis functions of that subspace are linear combinations of derivatives of exponential B-splines. These minimal-support basis functions form a natural multiscale hierarchy, which we utilize to design fast multiresolution algorithms and subdivision schemes for the representation of closed geometric curves. This makes them attractive from a computational point of view. Finally, we illustrate our scheme by constructing minimal-support bases that reproduce ellipses and higher-order harmonic curves. (C) 2011 Elsevier B.V. All rights reserved. more...

Invasive Salmonella infection is an important health problem that is worsening because of rising antimicrobial resistance and changing Salmonella serovar spectrum. Novel vaccines with broad serovar coverage are needed, but suitable protective antigens remain largely unknown. Here, we tested 37 broadly conserved Salmonella antigens in a mouse typhoid fever model, and identified antigen candidates that conferred partial protection against lethal disease. Antigen properties such as high in vivo abundance or immunodominance in convalescent individuals were not required for protectivity, but all promising antigen candidates were associated with the Salmonella surface. Surprisingly, this was not due to superior immunogenicity of surface antigens compared to internal antigens as had been suggested by previous studies and novel findings for CD4 T cell responses to model antigens. Confocal microscopy of infected tissues revealed that many live Salmonella resided alone in infected host macrophages with no damaged Salmonella releasing internal antigens in their vicinity. In the absence of accessible internal antigens, detection of these infected cells might require CD4 T cell recognition of Salmonella surface-associated antigens that could be processed and presented even from intact Salmonella. In conclusion, our findings might pave the way for development of an efficacious Salmonella vaccine with broad serovar coverage, and suggest a similar crucial role of surface antigens for immunity to both extracellular and intracellular pathogens., Author Summary Salmonella infections cause extensive morbidity and mortality worldwide. A vaccine that prevents systemic Salmonella infections is urgently needed but suitable antigens remain largely unknown. In this study we identified several antigen candidates that mediated protective immunity to Salmonella in a mouse typhoid fever model. Interestingly, all these antigens were associated with the Salmonella surface. This suggested that similar antigen properties might be relevant for CD4 T cell dependent immunity to intracellular pathogens like Salmonella, as for antibody-dependent immunity to extracellular pathogens. Detailed analysis revealed that Salmonella surface antigens were not generally more immunogenic compared to internal antigens. However, internal antigens were inaccessible for CD4 T cell recognition of a substantial number of infected host cells that contained exclusively live intact Salmonella. Together, these results might pave the way for development of an efficacious Salmonella vaccine, and provide a basis to facilitate antigen identification for Salmonella and possibly other intracellular pathogens. more...

As a frequent post‐translational modification, protein phosphorylation regulates many cellular processes. Although several hundred phosphorylation sites have been mapped to metabolic enzymes in Saccharomyces cerevisiae, functionality was demonstrated for few of them. Here, we describe a novel approach to identify in vivo functionality of enzyme phosphorylation by combining flux analysis with proteomics and phosphoproteomics. Focusing on the network of 204 enzymes that constitute the yeast central carbon and amino‐acid metabolism, we combined protein and phosphoprotein levels to identify 35 enzymes that change their degree of phosphorylation during growth under five conditions. Correlations between previously determined intracellular fluxes and phosphoprotein abundances provided first functional evidence for five novel phosphoregulated enzymes in this network, adding to nine known phosphoenzymes. For the pyruvate dehydrogenase complex E1 α subunit Pda1 and the newly identified phosphoregulated glycerol‐3‐phosphate dehydrogenase Gpd1 and phosphofructose‐1‐kinase complex β subunit Pfk2, we then validated functionality of specific phosphosites through absolute peptide quantification by targeted mass spectrometry, metabolomics and physiological flux analysis in mutants with genetically removed phosphosites. These results demonstrate the role of phosphorylation in controlling the metabolic flux realised by these three enzymes., Molecular Systems Biology, 8 (1), ISSN:1744-4292 more...

Genome-wide rhythms in RNA polymerase II loading and dynamic chromatin remodeling underlie periodic gene expression during diurnal cycles in the mouse liver., Interactions of cell-autonomous circadian oscillators with diurnal cycles govern the temporal compartmentalization of cell physiology in mammals. To understand the transcriptional and epigenetic basis of diurnal rhythms in mouse liver genome-wide, we generated temporal DNA occupancy profiles by RNA polymerase II (Pol II) as well as profiles of the histone modifications H3K4me3 and H3K36me3. We used these data to quantify the relationships of phases and amplitudes between different marks. We found that rhythmic Pol II recruitment at promoters rather than rhythmic transition from paused to productive elongation underlies diurnal gene transcription, a conclusion further supported by modeling. Moreover, Pol II occupancy preceded mRNA accumulation by 3 hours, consistent with mRNA half-lives. Both methylation marks showed that the epigenetic landscape is highly dynamic and globally remodeled during the 24-hour cycle. While promoters of transcribed genes had tri-methylated H3K4 even at their trough activity times, tri-methylation levels reached their peak, on average, 1 hour after Pol II. Meanwhile, rhythms in tri-methylation of H3K36 lagged transcription by 3 hours. Finally, modeling profiles of Pol II occupancy and mRNA accumulation identified three classes of genes: one showing rhythmicity both in transcriptional and mRNA accumulation, a second class with rhythmic transcription but flat mRNA levels, and a third with constant transcription but rhythmic mRNAs. The latter class emphasizes widespread temporally gated posttranscriptional regulation in the mouse liver., Author Summary In mammalian organs such as the liver, many metabolic and physiological processes occur preferentially at specific times during the 24-hour daily cycle. The timing of these rhythmic functions depends on a complex interplay between the endogenous circadian clock and environmental timing cues relayed through the master circadian clock in the suprachiasmatic nucleus, or via feeding rhythms. These rhythms can be implemented on several regulatory levels, and here we aimed at a better understanding of the transcriptional and epigenetic changes that regulate diurnal rhythms. We performed genome-wide analysis of the locations of RNA polymerase II (Pol II) and the epigenetic histone modifications H3K4me3 and H3K36me3 at specific times of day, relating these data to mRNA expression levels. Our analyses show that Pol II transcriptional rhythms are biphasic in mouse liver, having predominant peak activities in the morning and evening. Moreover, dynamic changes in histone marks lag transcription rhythms genome-wide, indicating that the epigenetic landscape can be remodeled during the 24-hour cycle. Finally, a quantitative analysis of temporal Pol II and mRNA accumulation profiles indicates that posttranscriptional regulation significantly contributes to the amplitude and phase of mRNA accumulation profiles. While many studies have analyzed how transcription and chromatin states are modified during irreversible cell differentiation processes, our work highlights how these states can evolve reversibly in a system exhibiting periodicity in time. more...

In this chapter, we review basic concepts from probability theory and computational statistics that are fundamental to evolutionary genomics. We provide a very basic introduction to statistical modeling and discuss general principles, including maximum likelihood and Bayesian inference. Markov chains, hidden Markov models, and Bayesian network models are introduced in more detail as they occur frequently and in many variations in genomics applications. In particular, we discuss efficient inference algorithms and methods for learning these models from partially observed data. Several simple examples are given throughout the text, some of which point to models that are discussed in more detail in subsequent chapters. more...

We consider the problem of inferring the unknown parameters of a stochastic biochemical network model from a single measured time-course of the concentration of some of the involved species. Such measurements are available, e.g., from live-cell fluorescence microscopy in image-based systems biology. In addition, fluctuation time-courses from, e.g., fluorescence correlation spectroscopy provide additional information about the system dynamics that can be used to more robustly infer parameters than when considering only mean concentrations. Estimating model parameters from a single experimental trajectory enables single-cell measurements and quantification of cell--cell variability. We propose a novel combination of an adaptive Monte Carlo sampler, called Gaussian Adaptation, and efficient exact stochastic simulation algorithms that allows parameter identification from single stochastic trajectories. We benchmark the proposed method on a linear and a non-linear reaction network at steady state and during transient phases. In addition, we demonstrate that the present method also provides an ellipsoidal volume estimate of the viable part of parameter space and is able to estimate the physical volume of the compartment in which the observed reactions take place., Article in print as a book chapter in Springer's "Advances in Systems Biology" more...

The perception of facial affect engages a distributed cortical network. We used functional magnetic resonance imaging and dynamic causal modeling to characterize effective connectivity during explicit (conscious) categorization of affective stimuli in the human brain. Specifically, we examined the modulation of connectivity from posterior regions of the face-processing network to the lateral ventral prefrontal cortex (VPFC) during affective categorization and we tested for a potential role of the amygdala (AMG) in mediating this modulation. We found that explicit processing of facial affect led to prominent modulation (increase) in the effective connectivity from the inferior occipital gyrus (IOG) to the VPFC, while there was less evidence for modulation of the afferent connections from fusiform gyrus and AMG to VPFC. More specifically, the forward connection from IOG to the VPFC exhibited a selective increase under anger (as opposed to fear or sadness). Furthermore, Bayesian model comparison suggested that the modulation of afferent connections to the VPFC was mediated directly by facial affect, as opposed to an indirect modulation mediated by the AMG. Our results thus suggest that affective information is conveyed to the VPFC along multiple parallel pathways and that AMG activity is not sufficient to account for the gating of information transfer to the VPFC during explicit emotional processing. more...

The activity of the Dpp morphogen adapts to tissue size in the growing Drosophila wing imaginal disc, and Pentagone, an important secreted feedback regulator of the Dpp pathway, is required for this adaptation., The wing of the fruit fly, Drosophila melanogaster, with its simple, two-dimensional structure, is a model organ well suited for a systems biology approach. The wing arises from an epithelial sac referred to as the wing imaginal disc, which undergoes a phase of massive growth and concomitant patterning during larval stages. The Decapentaplegic (Dpp) morphogen plays a central role in wing formation with its ability to co-coordinately regulate patterning and growth. Here, we asked whether the Dpp signaling activity scales, i.e. expands proportionally, with the growing wing imaginal disc. Using new methods for spatial and temporal quantification of Dpp activity and its scaling properties, we found that the Dpp response scales with the size of the growing tissue. Notably, scaling is not perfect at all positions in the field and the scaling of target gene domains is ensured specifically where they define vein positions. We also found that the target gene domains are not defined at constant concentration thresholds of the downstream Dpp activity gradients P-Mad and Brinker. Most interestingly, Pentagone, an important secreted feedback regulator of the pathway, plays a central role in scaling and acts as an expander of the Dpp gradient during disc growth., Author Summary Scaling, the fitting of pattern to size, manifests itself in numerous examples around us. During development, individual body parts scale up to fit the overall body size. Starved animals form smaller adults with proportionally smaller parts, and amphibian embryos can form normally proportioned adults after extreme surgical operations. How scaling is achieved is not well understood. Here, we establish the Drosophila wing imaginal disc, the precursor tissue of the adult wing, as a model to study scaling quantitatively during growth. In this model, we define scaling as the preservation of proportions of gene expression domains with tissue size during disc growth. The Decapentaplegic (Dpp) morphogen is known to play a central role in Drosophila wing formation and co-coordinately regulates growth and patterning. We found that as the disc grows, the Dpp response expands and scales with the tissue size. Interestingly, scaling is not perfect at all positions in the field. The scaling of the target gene domains is best where they have a function; Spalt, for example, scales best at the position in the anterior compartment where it helps to form one of the anterior veins of the wing. Analysis of mutants for pentagone, a transcriptional target of Dpp that encodes a secreted feedback regulator of the pathway, indicates that Pentagone plays a key role in scaling the Dpp gradient activity. more...

Silent information regulator proteins Sir2, Sir3, and Sir4 form a heterotrimeric complex that represses transcription at subtelomeric regions and homothallic mating type (HM) loci in budding yeast. We have performed a detailed biochemical and genetic analysis of the largest Sir protein, Sir4. The N-terminal half of Sir4 is dispensable for SIR–mediated repression of HM loci in vivo, except in strains that lack Yku70 or have weak silencer elements. For HM silencing in these cells, the C-terminal domain (Sir4C, residues 747–1,358) must be complemented with an N-terminal domain (Sir4N; residues 1–270), expressed either independently or as a fusion with Sir4C. Nonetheless, recombinant Sir4C can form a complex with Sir2 and Sir3 in vitro, is catalytically active, and has sedimentation properties similar to a full-length Sir4-containing SIR complex. Sir4C-containing SIR complexes bind nucleosomal arrays and protect linker DNA from nucleolytic digestion, but less effectively than wild-type SIR complexes. Consistently, full-length Sir4 is required for the complete repression of subtelomeric genes. Supporting the notion that the Sir4 N-terminus is a regulatory domain, we find it extensively phosphorylated on cyclin-dependent kinase consensus sites, some being hyperphosphorylated during mitosis. Mutation of two major phosphoacceptor sites (S63 and S84) derepresses natural subtelomeric genes when combined with a serendipitous mutation (P2A), which alone can enhance the stability of either the repressed or active state. The triple mutation confers resistance to rapamycin-induced stress and a loss of subtelomeric repression. We conclude that the Sir4 N-terminus plays two roles in SIR–mediated silencing: it contributes to epigenetic repression by stabilizing the SIR–mediated protection of linker DNA; and, as a target of phosphorylation, it can destabilize silencing in a regulated manner., Author Summary Three Silent Information Regulator (SIR) proteins Sir2, Sir3, and Sir4 are involved in the epigenetic gene silencing of the homothallic mating (HM) loci and of telomere-proximal genes in budding yeast. They bind as a heterotrimeric complex to chromatin, repressing the underlying genes. Sir2 has an essential histone deacetylase activity, and Sir3 binds nucleosomes, with a high specificity for unmodified histones. We explored Sir4, whose role had largely remained a mystery. We report here that Sir4 N- and C-terminal domains have distinct functions: The Sir4 C-terminus binds all proteins essential for SIR–mediated silencing and is sufficient to repress HM loci, but surprisingly it is not sufficient to efficiently repress at telomeres. The Sir4 N-terminus binds DNA, which strengthens the SIR–chromatin interaction and helps target Sir4 to telomeric loci. In addition the Sir4 N-terminus binds sequence-specific factors that recruit Sir4 to sites of repression. We find that the Sir4 N-terminus is a target of mitotic phosphorylation. Mutation of the phosphoacceptor sites indicates that they help fine-tune subtelomeric repression. We propose therefore that phosphorylation of the Sir4 N-terminal domain modulates epigenetic repression at telomeres in response to cell cycle and/or stress situations. more...

International audience; The goal of dynamic causal modelling (DCM) of neuroimaging data is to study experimentally induced changes in functional integration among brain regions. This requires (i) biophysically plausible and physiologically interpretable models of neuronal network dynamics that can predict distributed brain responses to experimental stimuli and (ii) efficient statistical methods for parameter estimation and model comparison. These two key components of DCM have been the focus of more than thirty methodological articles since the seminal work of Friston and colleagues published in 2003. In this paper, we provide a critical review of the current state-of-the-art of DCM. We inspect the properties of DCM in relation to the most common neuroimaging modalities (fMRI and EEG/MEG) and the specificity of inference on neural systems that can be made from these data. We then discuss both the plausibility of the underlying biophysical models and the robustness of the statistical inversion techniques. Finally, we discuss potential extensions of the current DCM framework, such as stochastic DCMs, plastic DCMs and field DCMs. more...

The yeast Saccharomyces cerevisiae can show different metabolic phenotypes (e.g. fermentation and respiration). Based on data from the literature, we argue that the substrate uptake rate is the core variable in the system that controls the global metabolic phenotype. Consequently the metabolic phenotype that the cell expresses is not dependent on the type of the sugar or its concentration, but only on the rate at which the sugar enters the cell. As this requires the cells to ‘measure’ metabolic flux, we discuss the existing clues toward a flux-sensing mechanism in this organism and also outline several aspects of the involved flux-dependent regulation system. It becomes clear that the sensing and regulation system that divides the taken up carbon flux into the respiratory or fermentative pathways is complex with many molecular components interacting on multiple levels. To obtain a true understanding about how the global metabolic phenotype of S. cerevisiae is controlled by the glucose uptake rate, different tools and approaches from systems biology will be required. more...

Bacterial type IV secretion systems (T4SS) mediate interbacterial conjugative DNA transfer and transkingdom protein transfer into eukaryotic host cells in bacterial pathogenesis. The sole bacterium known to naturally transfer DNA into eukaryotic host cells via a T4SS is the plant pathogen Agrobacterium tumefaciens . Here we demonstrate T4SS-mediated DNA transfer from a human bacterial pathogen into human cells. We show that the zoonotic pathogen Bartonella henselae can transfer a cryptic plasmid occurring in the bartonellae into the human endothelial cell line EA.hy926 via its T4SS VirB/VirD4. DNA transfer into EA.hy926 cells was demonstrated by using a reporter derivative of this Bartonella -specific mobilizable plasmid generated by insertion of a eukaryotic e gfp -expression cassette. Fusion of the C-terminal secretion signal of the endogenous VirB/VirD4 protein substrate BepD with the plasmid-encoded DNA-transport protein Mob resulted in a 100-fold increased DNA transfer rate. Expression of the delivered e gfp gene in EA.hy926 cells required cell division, suggesting that nuclear envelope breakdown may facilitate passive entry of the transferred ssDNA into the nucleus as prerequisite for complementary strand synthesis and transcription of the e gfp gene. Addition of an eukaryotic neomycin phosphotransferase expression cassette to the reporter plasmid facilitated selection of stable transgenic EA.hy926 cell lines that display chromosomal integration of the transferred plasmid DNA. Our data suggest that T4SS-dependent DNA transfer into host cells may occur naturally during human infection with Bartonella and that these chronically infecting pathogens have potential for the engineering of in vivo gene-delivery vectors with applications in DNA vaccination and therapeutic gene therapy. more...

The EMBO Journal, 30 (17), ISSN:0261-4189, ISSN:1460-2075

Although animal researchers established the role of testosterone as a 'social hormone' decades ago, the investigation of its causal influence on human social behaviors has only recently begun. Here, we review and discuss recent studies showing the causal effects of testosterone on social interactions in animals and humans, and outline the basic neurobiological mechanisms that might underlie these effects. Based on these recent findings, we argue that the role of testosterone in human social behavior might be best understood in terms of the search for, and maintenance of, social status. more...

We use the Dpp morphogen gradient in the Drosophila wing disc as a model to address the fundamental question of how a gradient of a growth factor can produce uniform growth. We first show that proper expression and subcellular localization of components in the Fat tumor-suppressor pathway, which have been argued to depend on Dpp activity differences, are not reliant on the Dpp gradient. We next analyzed cell proliferation in discs with uniformly high Dpp or uniformly low Fat signaling activity and found that these pathways regulate growth in a complementary manner. While the Dpp mediator Brinker inhibits growth in the primordium primarily in the lateral regions, Fat represses growth mostly in the medial region. Together, our results indicate that the activities of both signaling pathways are regulated in a parallel rather than sequential manner and that uniform proliferation is achieved by their complementary action on growth. more...

Several real-world systems, such as gene expression networks in biological cells, contain coupled chemical reactions with a time delay between reaction initiation and completion. The non-Markovian kinetics of such reaction networks can be exactly simulated using the delay stochastic simulation algorithm (dSSA). The computational cost of dSSA scales with the total number of reactions in the network. We reduce this cost to scale at most with the smaller number of species by using the concept of partial reaction propensities. The resulting delay partial-propensity direct method (dPDM) is an exact dSSA formulation for well-stirred systems of coupled chemical reactions with delays. We detail dPDM and present a theoretical analysis of its computational cost. Furthermore, we demonstrate the implications of the theoretical cost analysis in two prototypical benchmark applications. The dPDM formulation is shown to be particularly efficient for strongly coupled reaction networks, where the number of reactions is much larger than the number of species. more...

The protein kinase B (PKB) family encompasses three isoforms; PKBα (AKT1), PKBβ (AKT2) and PKBγ (AKT3). PKBα and PKBβ but not PKBγ, are prominently expressed in classical insulin-sensitive tissues like liver, muscle and fat. Transgenic mice deficient for PKBα, PKBβ or PKBγ have been analysed to study the roles of PKB isoforms in metabolic regulation. Until recently, only loss of PKBβ was reported to result in metabolic disorders, especially insulin resistance, in humans and mice. However, a new study has shown that PKBα-deficient mice can show enhanced glucose tolerance accompanied by improved β-cell function and higher insulin sensitivity in adipocytes. These findings prompted us to review the relevant literature on the regulation of glucose metabolism by PKB isoforms in liver, skeletal muscle, adipocytes and pancreas. more...

Stochastic effects from correlated noise non-trivially modulate the kinetics of non-linear chemical reaction networks. This is especially important in systems where reactions are confined to small volumes and reactants are delivered in bursts. We characterise how the two noise sources confinement and burst modulate the relaxation kinetics of a non-linear reaction network around a non-equilibrium steady state. We find that the lifetimes of species change with burst input and confinement. Confinement increases the lifetimes of all species that are involved in any non-linear reaction as a reactant. Burst monotonically increases or decreases lifetimes. Competition between burst-induced and confinement-induced modulation may hence lead to a non-monotonic modulation. We quantify lifetime as the integral of the time autocorrelation function (ACF) of concentration fluctuations around a non-equilibrium steady state of the reaction network. Furthermore, we look at the first and second derivatives of the ACF, each of which is affected in opposite ways by burst and confinement. This allows discriminating between these two noise sources. We analytically derive the ACF from the linear Fokker–Planck approximation of the chemical master equation in order to establish a baseline for the burst-induced modulation at low confinement. Effects of higher confinement are then studied using a partial-propensity stochastic simulation algorithm. The results presented here may help understand the mechanisms that deviate stochastic kinetics from its deterministic counterpart. In addition, they may be instrumental when using fluorescence-lifetime imaging microscopy (FLIM) or fluorescence-correlation spectroscopy (FCS) to measure confinement and burst in systems with known reaction rates, or, alternatively, to correct for the effects of confinement and burst when experimentally measuring reaction rates., PLoS ONE, 6 (1), ISSN:1932-6203 more...

Mesoscopic oscillatory reaction systems, for example in cell biology, can exhibit stochastic oscillations in the form of cyclic random walks even if the corresponding macroscopic system does not oscillate. We study how the intrinsic noise from molecular discreteness influences the frequency spectrum of mesoscopic oscillators using as a model system a cascade of coupled Brusselators away from the Hopf bifurcation. The results show that the spectrum of an oscillator depends on the level of noise. In particular, the peak frequency of the oscillator is reduced by increasing noise, and the bandwidth increased. Along a cascade of coupled oscillators, the peak frequency is further reduced with every stage and also the bandwidth is reduced. These effects can help understand the role of noise in chemical oscillators and provide fingerprints for more reliable parameter identification and volume measurement from experimental spectra., Scientific Reports, 1, ISSN:2045-2322 more...

In this work we consider the regulation system present on the SPI1 pathogenicity island of Salmonella enterica serovar Typhimurium. It is well-known that HilA is the central regulator in the overall scheme of SPI1 regulation and directly binds to virulence operons and activates their expression. The regulation of the expression of HilA is via a complex feed-forward loop involving three transcriptional activators: HilC, HilD and RtsA, and the negative regulator HilE. Our aim is to model this regulation network and study its dynamical behavior. We show that this regulatory system can display a bistable behavior relevant to the biology of Salmonella, and that noise can be a driving force in this system. more...

The glow of a starry night sky, the smell of a freshly brewed cup of coffee or the sound of ocean waves breaking on the beach are representations of the physical world that have been created by the dynamic interactions of thousands of neurons in our brains. How the brain mediates perceptions, creates thoughts, stores memories and initiates actions remains one of the most profound puzzles in biology, if not all of science. A key to a mechanistic understanding of how the nervous system works is the ability to analyze the dynamics of neuronal networks in the living organism in the context of sensory stimulation and behaviour. Dynamic brain properties have been fairly well characterized on the microscopic level of individual neurons and on the macroscopic level of whole brain areas largely with the help of various electrophysiological techniques. However, our understanding of the mesoscopic level comprising local populations of hundreds to thousands of neurons (so called 'microcircuits') remains comparably poor. In large parts, this has been due to the technical difficulties involved in recording from large networks of neurons with single-cell spatial resolution and near- millisecond temporal resolution in the brain of living animals. In recent years, two-photon microscopy has emerged as a technique which meets many of these requirements and thus has become the method of choice for the interrogation of local neural circuits. Here, we review the state-of-research in the field of two-photon imaging of neuronal populations, covering the topics of microscope technology, suitable fluorescent indicator dyes, staining techniques, and in particular analysis techniques for extracting relevant information from the fluorescence data. We expect that functional analysis of neural networks using two-photon imaging will help to decipher fundamental operational principles of neural microcircuits., 36 pages, 4 figures, accepted for publication in Reports on Progress in Physics more...

Budding yeast (Saccharomyces cerevisiae) has been widely used as a model system to study fundamental biological processes. Genetic and biochemical approaches have allowed in the last decades to uncover the key components involved in many signaling pathways. Generally, most techniques measure the average behavior of a population of cells, and thus miss important cell-to-cell variations. With the recent progress in fluorescent proteins, new avenues have been opened to quantitatively study the dynamics of signaling in single living cells. In this chapter, we describe several techniques based on fluorescence measurements to quantify the activation of biological pathways. Flow cytometry allows for rapid quantification of the total fluorescence of a large number of single cells. In contrast, microscopy offers a lower throughput but allows to follow with a high temporal resolution the localization of proteins at sub-cellular resolution. Finally, advanced functional imaging techniques such as FRET and FCS offer the possibility to directly visualize the formation of protein complexes or to quantify the activity of proteins in vivo. Together these techniques present powerful new approaches to study cellular signaling and will greatly increase our understanding of the regulation of signaling networks in budding yeast and beyond. more...

Dynamic causal modelling (DCM) for steady-state responses (SSR) is a framework for inferring the mechanisms that underlie observed electrophysiological spectra, using biologically plausible generative models of neuronal dynamics. In this paper, we examine the dynamic repertoires of nonlinear conductance-based neural population models and propose a generative model of their power spectra. Our model comprises an ensemble of interconnected excitatory and inhibitory cells, where synaptic currents are mediated by fast, glutamatergic and GABAergic receptors and slower voltage-gated NMDA receptors. We explore two formulations of how hidden neuronal states (depolarisation and conductances) interact: through their mean and variance (mean-field model) or through their mean alone (neural-mass model). Both rest on a nonlinear Fokker–Planck description of population dynamics, which can exhibit bifurcations (phase transitions). We first characterise these phase transitions numerically: by varying critical model parameters, we elicit both fixed points and quasiperiodic dynamics that reproduce the spectral characteristics (~2–100Hz) of real electrophysiological data. We then introduce a predictor of spectral activity using centre manifold theory and linear stability analysis. This predictor is based on sampling the system's Jacobian over the orbits of hidden neuronal states. This predictor behaves consistently and smoothly in the region of phase transitions, which permits the use of gradient descent methods for model inversion. We demonstrate this by inverting generative models (DCMs) of SSRs, using simulated data that entails phase transitions. more...

Generative models of neuroimaging and electrophysiological data present new opportunities for accessing hidden or latent brain states. Dynamic causal modeling (DCM) uses Bayesian model inversion and selection to infer the synaptic mechanisms underlying empirically observed brain responses. DCM for electrophysiological data, in particular, aims to estimate the relative strength of synaptic transmission at different cell types and via specific neurotransmitters. Here, we report a DCM validation study concerning inference on excitatory and inhibitory synaptic transmission, using different doses of a volatile anaesthetic agent (isoflurane) to parametrically modify excitatory and inhibitory synaptic processing while recording local field potentials (LFPs) from primary auditory cortex (A1) and the posterior auditory field (PAF) in the auditory belt region in rodents. We test whether DCM can infer, from the LFP measurements, the expected drug-induced changes in synaptic transmission mediated via fast ionotropic receptors; i.e., excitatory (glutamatergic) AMPA and inhibitory GABAA receptors. Cross- and auto-spectra from the two regions were used to optimise three DCMs based on biologically plausible neural mass models and specific network architectures. Consistent with known extrinsic connectivity patterns in sensory hierarchies, we found that a model comprising forward connections from A1 to PAF and backward connections from PAF to A1 outperformed a model with forward connections from PAF to A1 and backward connections from A1 to PAF and a model with reciprocal lateral connections. The parameter estimates from the most plausible model indicated that the amplitude of fast glutamatergic excitatory postsynaptic potentials (EPSPs) and inhibitory postsynaptic potentials (IPSPs) behaved as predicted by previous neurophysiological studies. Specifically, with increasing levels of anaesthesia, glutamatergic EPSPs decreased linearly, whereas fast GABAergic IPSPs displayed a nonlinear (saturating) increase. The consistency of our model-based in vivo results with experimental in vitro results lends further validity to the capacity of DCM to infer on synaptic processes using macroscopic neurophysiological data. This work was supported by the Max Planck Society (MT, FJ, TK, HE, RG, RJM), the NEUROCHOICE project of SystemsX.ch (KES), and the Wellcome Trust (RJD, KJF, RJM). more...

This paper is about inferring or discovering the functional architecture of distributed systems using Dynamic Causal Modelling (DCM). We describe a scheme that recovers the (dynamic) Bayesian dependency graph (connections in a network) using observed network activity. This network discovery uses Bayesian model selection to identify the sparsity structure (absence of edges or connections) in a graph that best explains observed time-series. The implicit adjacency matrix specifies the form of the network (e.g., cyclic or acyclic) and its graph-theoretical attributes (e.g., degree distribution). The scheme is illustrated using functional magnetic resonance imaging (fMRI) time series to discover functional brain networks. Crucially, it can be applied to experimentally evoked responses (activation studies) or endogenous activity in task-free (resting state) fMRI studies. Unlike conventional approaches to network discovery, DCM permits the analysis of directed and cyclic graphs. Furthermore, it eschews (implausible) Markovian assumptions about the serial independence of random fluctuations. The scheme furnishes a network description of distributed activity in the brain that is optimal in the sense of having the greatest conditional probability, relative to other networks. The networks are characterised in terms of their connectivity or adjacency matrices and conditional distributions over the directed (and reciprocal) effective connectivity between connected nodes or regions. We envisage that this approach will provide a useful complement to current analyses of functional connectivity for both activation and resting-state studies., Research Highlights ►A new way of analysing effective connectivity. ►A way of searching over large sets of models (networks) using DCM. ►Identifies the best network or graph using Bayesian model evidence. ►Can be applied to resting state and activation studies. more...

Adaptive radiation is the rapid origination of multiple species from a single ancestor as the result of concurrent adaptation to disparate environments. This fundamental evolutionary process is considered to be responsible for the genesis of a great portion of the diversity of life. Bacteria have evolved enormous biological diversity by exploiting an exceptional range of environments, yet diversification of bacteria via adaptive radiation has been documented in a few cases only and the underlying molecular mechanisms are largely unknown. Here we show a compelling example of adaptive radiation in pathogenic bacteria and reveal their genetic basis. Our evolutionary genomic analyses of the α-proteobacterial genus Bartonella uncover two parallel adaptive radiations within these host-restricted mammalian pathogens. We identify a horizontally-acquired protein secretion system, which has evolved to target specific bacterial effector proteins into host cells as the evolutionary key innovation triggering these parallel adaptive radiations. We show that the functional versatility and adaptive potential of the VirB type IV secretion system (T4SS), and thereby translocated Bartonella effector proteins (Beps), evolved in parallel in the two lineages prior to their radiations. Independent chromosomal fixation of the virB operon and consecutive rounds of lineage-specific bep gene duplications followed by their functional diversification characterize these parallel evolutionary trajectories. Whereas most Beps maintained their ancestral domain constitution, strikingly, a novel type of effector protein emerged convergently in both lineages. This resulted in similar arrays of host cell-targeted effector proteins in the two lineages of Bartonella as the basis of their independent radiation. The parallel molecular evolution of the VirB/Bep system displays a striking example of a key innovation involved in independent adaptive processes and the emergence of bacterial pathogens. Furthermore, our study highlights the remarkable evolvability of T4SSs and their effector proteins, explaining their broad application in bacterial interactions with the environment., Author Summary Adaptive radiation is the rapid origination of an array of species by the divergent colonization of disparate ecological niches. In the case of pathogenic bacteria, radiations can lead to the emergence of novel human pathogens. Being divergently adapted to a range of different mammalian hosts, including humans as reservoir or incidental hosts, the genus Bartonella represents a suitable model to study genomic mechanisms underpinning divergent adaptation of pathogens. Here we show that two distinct lineages of Bartonella have radiated in parallel, resulting in two arrays of evolutionary distinct species adapted to overlapping sets of mammalian hosts. Such parallelisms display excellent models to reveal insights into the genetic mechanisms underlying these independent evolutionary processes. Our genome-wide analysis identifies a striking evolutionary parallelism in a horizontally-acquired protein secretion system in the two lineages. The parallel evolutionary trajectory of this system in the two lineages is characterized by the convergent origination of a wide array of adaptive functions dedicated to the cellular interaction within the mammalian hosts. The parallel evolution of the two radiating lineages on the ecological as well as on the molecular level suggests that the horizontal acquisition and the functional diversification of the secretion system display an evolutionary key innovation underlying adaptive evolution. more...

Fetal hemoglobin, HbF (α(2)γ(2)), is the main hemoglobin synthesized up to birth, but it subsequently declines and adult hemoglobin, HbA (α(2)β(2)), becomes predominant. Several studies have indicated that expression of the HbF subunit γ-globin might be regulated post-transcriptionally. This could be confered by ∼22-nucleotide long microRNAs that associate with argonaute proteins to specifically target γ-globin mRNAs and inhibit protein expression. Indeed, applying immunopurifications, we found that γ-globin mRNA was associated with argonaute 2 isolated from reticulocytes that contain low levels of HbF ( more...

Non-intermingling, adjacent populations of cells define compartment boundaries; such boundaries are often essential for the positioning and the maintenance of tissue-organizers during growth. In the developing wing primordium of Drosophila melanogaster, signaling by the secreted protein Hedgehog (Hh) is required for compartment boundary maintenance. However, the precise mechanism of Hh input remains poorly understood. Here, we combine experimental observations of perturbed Hh signaling with computer simulations of cellular behavior, and connect physical properties of cells to their Hh signaling status. We find that experimental disruption of Hh signaling has observable effects on cell sorting surprisingly far from the compartment boundary, which is in contrast to a previous model that confines Hh influence to the compartment boundary itself. We have recapitulated our experimental observations by simulations of Hh diffusion and transduction coupled to mechanical tension along cell-to-cell contact surfaces. Intriguingly, the best results were obtained under the assumption that Hh signaling cannot alter the overall tension force of the cell, but will merely re-distribute it locally inside the cell, relative to the signaling status of neighboring cells. Our results suggest a scenario in which homotypic interactions of a putative Hh target molecule at the cell surface are converted into a mechanical force. Such a scenario could explain why the mechanical output of Hh signaling appears to be confined to the compartment boundary, despite the longer range of the Hh molecule itself. Our study is the first to couple a cellular vertex model describing mechanical properties of cells in a growing tissue, to an explicit model of an entire signaling pathway, including a freely diffusible component. We discuss potential applications and challenges of such an approach., Author Summary In developing animal tissues, cells can often re-arrange locally and mix relatively freely. However, in some stereotypic and crucially important instances during body development, cells will strictly not intermingle, and instead form sharp boundaries along which they will sort out from each other. This mechanism helps organisms to establish signaling centers and to maintain distinct cellular identities. Often, cells at such boundaries will remain in close physical contact and are morphologically alike. Thus, the boundary itself can be difficult to observe unless the expression status of specific marker genes is monitored experimentally. How are these ‘compartment boundaries’ established? Here we devise a computational model that aims to describe one such boundary in a well-studied animal tissue: the developing wing primordium of Drosophila melanogaster. We model the production, diffusion and local sensing of an essential signaling molecule, the Hedgehog protein. We reveal one possible mechanism by which Hedgehog sensing can influence the mechanical properties of cells, and compare the simulated outcome to observations in experimentally perturbed, actual wing discs. Our relatively simple model suffices to establish a straight and stable compartment boundary. more...

Summary The contribution of dopamine to working memory has been studied extensively [1–3]. Here, we exploited its well characterized effects [1–3] to validate a novel human in vivo assay of ongoing synaptic [4, 5] processing. We obtained magnetoencephalographic (MEG) measurements from subjects performing a working memory (WM) task during a within-subject, placebo-controlled, pharmacological (dopaminergic) challenge. By applying dynamic causal modeling (DCM), a Bayesian technique for neuronal system identification [6], to MEG signals from prefrontal cortex, we demonstrate that it is possible to infer synaptic signaling by specific ion channels in behaving humans. Dopamine-induced enhancement of WM performance was accompanied by significant changes in MEG signal power, and a DCM assay disclosed related changes in synaptic signaling. By estimating the contribution of ionotropic receptors (AMPA, NMDA, and GABAA) to the observed spectral response, we demonstrate changes in their function commensurate with the synaptic effects of dopamine. The validity of our model is reinforced by a striking quantitative effect on NMDA and AMPA receptor signaling that predicted behavioral improvement over subjects. Our results provide a proof-of-principle demonstration of a novel framework for inferring, noninvasively, neuromodulatory influences on ion channel signaling via specific ionotropic receptors, providing a window on the hidden synaptic events mediating discrete psychological processes in humans., Highlights ► We present a DCM capable of assaying neurotransmitter function during human cognition ► We demonstrate this using dopaminergic modulation of working memory and MEG ► We find changes in ionotropic receptors commensurate with dopaminergic enhancement ► We uncover quantitative effects that can predict individual behavioral improvements more...

TOR (Target Of Rapamycin) is a highly conserved protein kinase that is important in both fundamental and clinical biology. In fundamental biology, TOR is a nutrient-sensitive, central controller of cell growth and aging. In clinical biology, TOR is implicated in many diseases and is the target of the drug rapamycin used in three different therapeutic areas. The yeast Saccharomyces cerevisiae has played a prominent role in both the discovery of TOR and the elucidation of its function. Here we review the TOR signaling network in S. cerevisiae. more...

Thymic output is a dynamic process, with high activity at birth punctuated by transient periods of involution during infection. Interferon-α (IFN-α) is a critical molecular mediator of pathogen-induced thymic involution, yet despite the importance of thymic involution, relatively little is known about the molecular integrators that establish sensitivity. Here we found that the microRNA network dependent on the endoribonuclease Dicer, and specifically microRNA miR-29a, was critical for diminishing the sensitivity of the thymic epithelium to simulated infection signals, protecting the thymus against inappropriate involution. In the absence of Dicer or the miR-29a cluster in the thymic epithelium, expression of the IFN-α receptor by the thymic epithelium was higher, which allowed suboptimal signals to trigger rapid loss of thymic cellularity. more...

Stochastic reaction-diffusion systems frequently exhibit behavior that is not predicted by deterministic simulation models. Stochastic simulation methods, however, are computationally expensive. We present a more efficient stochastic reaction-diffusion simulation algorithm that samples realizations from the exact solution of the reaction-diffusion master equation. The present algorithm, called partial-propensity stochastic reaction-diffusion (PSRD) method, uses an on-lattice discretization of the reaction-diffusion system and relies on partial-propensity methods for computational efficiency. We describe the algorithm in detail, provide a theoretical analysis of its computational cost, and demonstrate its computational performance in benchmarks. We then illustrate the application of PSRD to two- and three-dimensional pattern-forming Gray-Scott systems, highlighting the role of intrinsic noise in these systems. more...

First systematic analysis of the evolutionary conserved InR/TOR pathway interaction proteome in Drosophila. Quantitative mass spectrometry revealed that 22% of identified protein interactions are regulated by the growth hormone insulin affecting membrane proximal as well as intracellular signaling complexes. Systematic RNA interference linked a significant fraction of network components to the control of dTOR kinase activity. Combined biochemical and genetic data suggest dTTT, a dTOR-containing complex required for cell growth control by dTORC1 and dTORC2 in vivo., Cellular growth is a fundamental process that requires constant adaptations to changing environmental conditions, like growth factor and nutrient availability, energy levels and more. Over the years, the insulin receptor/target of rapamycin pathway (InR/TOR) emerged as a key signaling system for the control of metazoan cell growth. Genetic screens carried out in the fruit fly Drosophila melanogaster identified key InR/TOR pathway components and their relationships. Phenotypes such as altered cell growth are likely to emerge from perturbed dynamic networks containing InR/TOR pathway components, which stably or transiently interact with other cellular proteins to form complexes and networks thereof. Systematic studies on the topology and dynamics of protein interaction networks become therefore highly relevant to gain systems level understanding of deregulated cell growth. Despite much progress in genetic analysis only few systematic protein interaction studies have been reported for Drosophila, which in most cases lack quantitative information representing the dynamic nature of such networks. Here, we present the first quantitative affinity purification mass spectrometry (AP–MS/MS) analysis on the evolutionary conserved InR/TOR signaling network in Drosophila. Systematic RNAi-based functional analysis of identified network components revealed key components linked to the regulation of the central effector kinase dTOR. This includes also dTTT, a novel dTOR-containing complex required for the control of dTORC1 and dTORC2 in vivo. For systematic AP–MS analysis, we generated Drosophila Kc167 cell lines inducibly expressing affinity-tagged bait proteins previously linked to InR/TOR signaling. Bait expressing Kc167 cell lines were harvested before and after insulin stimulation for subsequent affinity purification. Following LC–MS/MS analysis and probabilistic data filtering using SAINT (Choi et al, 2010), we generated a quantitative network model from 97 high confidence protein–protein interactions and 58 network components (Figure 2). The presented network displayed a high degree of orthologous interactions conserved also in human cells and identified a number of novel molecular interactions with InR/TOR signaling components for future hypothesis driven analysis. To measure insulin-induced changes within the InR/TOR interaction proteome, we applied a recently introduced label-free quantitative MS approach (Rinner et al, 2007). The obtained quantitative data suggest that 22% of all interactions in the network are regulated by insulin. Major changes could be observed within the membrane proximal InR/chico/PI3K signaling complexes, and also in 14-3-3 protein containing signaling complexes and dTORC1, a complex that contains besides dTOR all major orthologous proteins found also in human mTORC1 including the two dTORC1 substrates d4E-BP (Thor) and S6 Kinase (S6K). Insulin triggered both, dissociation and association of dTORC1 proteins. Among the proteins that showed enhanced binding to dTORC1 upon insulin stimulation we found Unkempt, a RING-finger protein with a proposed role in ubiquitin-mediated protein degradation (Lores et al, 2010). Besides dTORC1 our systematic AP–MS analysis also revealed the presence of dTORC2, the second major TOR complex in Drosophila. dTORC2 contains the Drosophila orthologous of human mTORC2 proteins, but in contrast to dTORC1 was not affected upon insulin stimulation. Interestingly, we also found a specific set of proteins that were not linked to the canonical TOR complexes TORC1 and TORC2 in dTOR purifications. These include LqfR (liquid facets related), Pontin, Reptin, Spaghetti and the gene product of CG16908. We found the same set of proteins when we used CG16908 as a bait, suggesting complex formation among the identified proteins. None of the dTORC1/2 components besides dTOR was identified in CG16908 purifications, indicating that these proteins form dTOR complexes distinct from dTORC1 and dTORC2. Based on known interaction information from other species and data obtained from this study we refer to this complex as dTTT (Drosophila TOR, TELO2, TTI1) (Horejsi et al, 2010; [18]Hurov et al, 2010; [20]Kaizuka et al, 2010). A directed quantitative MS analysis of dTOR complex components suggests that dTORC1 is the most abundant dTOR complex we identified in Kc167 cells. We next studied the potential roles of the identified network components for controlling the activity of the dInR/TOR pathway using systematic RNAi depletion and quantitative western blotting to measure the changes in abundance of phosphorylated substrates of dTORC1 (Thor/d4E-BP, dS6K) and dTORC2 (dPKB) in RNAi-treated cells (Figure 5). Overall, we could identify 16 proteins (out of 58) whose depletion caused an at least 50% increase or decrease in the levels of phosphorylated d4E-BP, S6K and/or PKB compared with control GFP RNAi. Besides established pathway components, we found several novel regulators within the dInR/TOR interaction network. For example, RNAi against the novel insulin-regulated dTORC1 component Unkempt resulted in enhanced phosphorylation of the dTORC1 substrate d4E-BP, which suggests a negative role for Unkempt on dTORC1 activity. In contrast, depletion of CG16908 and LqfR caused hypo-phosphorylation of all dTOR substrates similar to dTOR itself, suggesting a positive role for the dTTT complex on dTOR activity. Subsequently, we tested whether dTTT components also plays a role in dTOR-mediated cell growth in vivo. Depletion of both dTTT components, CG16908 and LqfR, in the Drosophila eye resulted in a substantial decrease in eye size. Likewise, FLP-FRT-mediated mitotic recombination resulted in CG16908 and LqfR mutant clones with a similar reduced growth phenotype as observed in dTOR mutant clones. Hence, the combined biochemical and genetic analysis revealed dTTT as a dTOR-containing complex required for the activity of both dTORC1 and dTORC2 and thus plays a critical role in controlling cell growth. Taken together, these results illustrate how a systematic quantitative AP–MS approach when combined with systematic functional analysis in Drosophila can reveal novel insights into the dynamic organization of regulatory networks for cell growth control in metazoans., Using quantitative mass spectrometry, this study reports how insulin affects the modularity of the interaction proteome of the Drosophila InR/TOR pathway, an evolutionary conserved signaling system for the control of metazoan cell growth. Systematic functional analysis linked a significant number of identified network components to the control of dTOR activity and revealed dTTT, a dTOR complex required for in vivo cell growth control by dTORC1 and dTORC2., Genetic analysis in Drosophila melanogaster has been widely used to identify a system of genes that control cell growth in response to insulin and nutrients. Many of these genes encode components of the insulin receptor/target of rapamycin (InR/TOR) pathway. However, the biochemical context of this regulatory system is still poorly characterized in Drosophila. Here, we present the first quantitative study that systematically characterizes the modularity and hormone sensitivity of the interaction proteome underlying growth control by the dInR/TOR pathway. Applying quantitative affinity purification and mass spectrometry, we identified 97 high confidence protein interactions among 58 network components. In all, 22% of the detected interactions were regulated by insulin affecting membrane proximal as well as intracellular signaling complexes. Systematic functional analysis linked a subset of network components to the control of dTORC1 and dTORC2 activity. Furthermore, our data suggest the presence of three distinct dTOR kinase complexes, including the evolutionary conserved dTTT complex (Drosophila TOR, TELO2, TTI1). Subsequent genetic studies in flies suggest a role for dTTT in controlling cell growth via a dTORC1- and dTORC2-dependent mechanism. more...

The food-borne pathogen Salmonella enterica serovar Typhimurium invades mammalian epithelial cells. This multistep process comprises bacterial binding to the host cell, activation of the Salmonella type three secretion system 1 (T1), injection of effector proteins, triggering of host cell actin rearrangements, and S . Typhimurium entry. While the latter steps are well understood, much less is known about the initial binding step. Earlier work had implicated adhesins (but not T1) or T1 (but not other adhesins). We have studied here the Salmonella virulence factors mediating S . Typhimurium binding to HeLa cells. Using an automated microscopy assay and isogenic S . Typhimurium mutants, we analyzed the role of T1 and of several known adhesins (Fim, Pef, Lpf, Agf, and Shd) in host cell binding. In wild-type S . Typhimurium, host cell binding was mostly attributable to T1. However, in the absence of T1, Fim (but not Pef, Lpf, Agf, and Shd) also mediated HeLa cell binding. Furthermore, in the absence of T1 and type I fimbriae (Fim), we still observed residual binding, pointing toward at least one additional, unidentified binding mechanism. Dissociation experiments established that T1-mediated binding was irreversible (“docking”), while Fim-mediated binding was reversible (“reversible adhesion”). Finally, we show that noninvasive bacteria docking via T1 or adhering via Fim can efficiently invade HeLa cells, if actin rearrangements are triggered in trans by a wild-type S . Typhimurium helper strain. Our data show that binding to HeLa cells is mediated by at least two different mechanisms and that both can lead to invasion if actin rearrangements are triggered. more...