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Motivation Access to unprecedented amounts of quantitative biological data allows us to build and test biochemically accurate reaction–diffusion models of intracellular processes. However, any increase in model complexity increases the number of unknown parameters and, thus, the computational cost of model analysis. To efficiently characterize the behavior and robustness of models with many unknown parameters remains, therefore, a key challenge in systems biology. Results We propose a novel computational framework for efficient high-dimensional parameter space characterization of reaction–diffusion models in systems biology. The method leverages the Lp-Adaptation algorithm, an adaptive-proposal statistical method for approximate design centering and robustness estimation. Our approach is based on an oracle function, which predicts for any given point in parameter space whether the model fulfills given specifications. We propose specific oracles to efficiently predict four characteristics of Turing-type reaction–diffusion models: bistability, instability, capability of spontaneous pattern formation and capability of pattern maintenance. We benchmark the method and demonstrate that it enables global exploration of a model’s ability to undergo pattern-forming instabilities and to quantify robustness for model selection in polynomial time with dimensionality. We present an application of the framework to pattern formation on the endosomal membrane by the small GTPase Rab5 and its effectors, and we propose molecular mechanisms underlying this system. Availability and implementation Our code is implemented in MATLAB and is available as open source under https://git.mpi-cbg.de/mosaic/software/black-box-optimization/rd-parameter-space-screening. Supplementary information Supplementary data are available at Bioinformatics online.

International audience; Many cellular organelles, including endosomes, show compartmentalization into distinct functional domains, which, however, cannot be resolved by diffraction-limited light microscopy. Single molecule localization microscopy (SMLM) offers nanoscale resolution but data interpretation is often inconclusive when the ultrastructural context is missing. Correlative light electron microscopy (CLEM) combining SMLM with electron microscopy (EM) enables correlation of functional subdomains of organelles in relation to their underlying ultrastructure at nanometer resolution. However, the specific demands for EM sample preparation and the requirements for fluorescent single-molecule photo-switching are opposed. Here, we developed a novel superCLEM workflow that combines triple-color SMLM (dSTORM & PALM) and electron tomography using semi-thin Tokuyasu thawed cryosections. We applied the superCLEM approach to directly visualize nanoscale compartmentalization of endosomes in HeLa cells. Internalized, fluorescently labeled Transferrin and EGF were resolved into morphologically distinct domains within the same endosome. We found that the small GTPase Rab5 is organized in nanodomains on the globular part of early endosomes. The simultaneous visualization of several proteins in functionally distinct endosomal sub-compartments demonstrates the potential of superCLEM to link the ultrastructure of organelles with their molecular organization at nanoscale resolution.

[This corrects the article DOI: 10.1371/journal.pcbi.1008412.].

How epithelial cells coordinate their polarity to form functional tissues is an open question in cell biology. Here, we characterize a unique type of polarity found in liver tissue, nematic cell polarity, which is different from vectorial cell polarity in simple, sheet-like epithelia. We propose a conceptual and algorithmic framework to characterize complex patterns of polarity proteins on the surface of a cell in terms of a multipole expansion. To rigorously quantify previously observed tissue-level patterns of nematic cell polarity (Morales-Navarrete et al., eLife 2019), we introduce the concept of co-orientational order parameters, which generalize the known biaxial order parameters of the theory of liquid crystals. Applying these concepts to three-dimensional reconstructions of single cells from high-resolution imaging data of mouse liver tissue, we show that the axes of nematic cell polarity of hepatocytes exhibit local coordination and are aligned with the biaxially anisotropic sinusoidal network for blood transport. Our study characterizes liver tissue as a biological example of a biaxial liquid crystal. The general methodology developed here could be applied to other tissues and in-vitro organoids., Author summary Cell polarity enables cells to carry out specific functions. Cell polarity is characterized by the formation of different plasma membrane domains, each with specific composition of proteins, phospholipids and cytoskeletal components. In simple epithelial sheets, or tube-like tissues such as kidney, epithelial cells are known to display a single apical domain, facing a lumenal cavity, and a single basal domain on the opposite side of the cell, facing a basal layer of extracellular matrix. This apico-basal polarity defines a vector of cell polarity, which provides a direction of fluid transport, e.g., from the basal side of the sheet to the lumen-facing side. In more complex, three-dimensional epithelial tissues, such as liver tissue with its complex network of blood-transporting sinusoids, the membrane domains of hepatocyte cells display more intricate patterns, including rings and antipodal pairs of apical membrane. Here, we develop a mathematical framework to precisely characterize and quantify complex polarity patterns. Thereby, we reveal ordered patterns of cell polarity that span across a liver lobule. Our new method builds on physical concepts originally developed for ordered phases of liquid crystals. It provides a versatile tool to characterize the spatial organization of a complex three-dimensional tissue.

Can three-dimensional, microvasculature networks still ensure blood supply if individual links fail? We address this question in the sinusoidal network, a plexus-like microvasculature network, which transports nutrient-rich blood to every hepatocyte in liver tissue, by building on recent advances in high-resolution imaging and digital reconstruction of adult mice liver tissue. We find that the topology of the three-dimensional sinusoidal network reflects its two design requirements of a space-filling network that connects all hepatocytes, while using shortest transport routes: sinusoidal networks are sub-graphs of the Delaunay graph of their set of branching points, and also contain the corresponding minimum spanning tree, both to good approximation. To overcome the spatial limitations of experimental samples and generate arbitrarily-sized networks, we developed a network generation algorithm that reproduces the statistical features of 0.3-mm-sized samples of sinusoidal networks, using multi-objective optimization for node degree and edge length distribution. Nematic order in these simulated networks implies anisotropic transport properties, characterized by an empirical linear relation between a nematic order parameter and the anisotropy of the permeability tensor. Under the assumption that all sinusoid tubes have a constant and equal flow resistance, we predict that the distribution of currents in the network is very inhomogeneous, with a small number of edges carrying a substantial part of the flow—a feature known for hierarchical networks, but unexpected for plexus-like networks. We quantify network resilience in terms of a permeability-at-risk, i.e., permeability as function of the fraction of removed edges. We find that sinusoidal networks are resilient to random removal of edges, but vulnerable to the removal of high-current edges. Our findings suggest the existence of a mechanism counteracting flow inhomogeneity to balance metabolic load on the liver., Author summary The liver is the largest metabolic organ of the human body and pivotal for blood detoxification and the uptake of many medically relevant drugs. Inside liver tissue, a dense meshwork of blood micro-vessels, the sinusoidal network, contacts every hepatocyte cell. The architecture of these networks, and especially how their function responds to local damage is not well understood. Previous theoretical work addressed network resilience in simple two-dimensional networks such as vein networks of leaves but not in three-dimensional networks, partly due to the considerable difficulties of imaging three-dimensional tissues. Here, we build on unprecedented advances in imaging mouse liver tissue. By simulating arbitrarily-sized networks that faithfully reproduce the statistical features of spatially restricted experimental samples, we computationally characterize the relation between a weak alignment of the network along the flow direction and enhanced transport along this direction. A simple transport model predicts an inhomogeneous distribution of flow in the sinusoidal network. Concomitantly, these networks are resilient against the random removal of edges, but vulnerable against removal of ‘highway’ edges that carried a high flow in the unperturbed state. We speculate that yet unknown adaptive mechanisms balance the distribution of flows and thereby increase the resilience of this physiologically important network.

Objective Insulin release from pancreatic islet β cells should be tightly controlled to avoid hypoglycemia and insulin resistance. The cortical actin cytoskeleton is a gate for regulated exocytosis of insulin secretory granules (SGs) by restricting their mobility and access to the plasma membrane. Prior studies suggest that SGs interact with F-actin through their transmembrane cargo islet cell autoantigen 512 (Ica512) (also known as islet antigen 2/Ptprn). Here we investigated how Ica512 modulates SG trafficking and exocytosis. Methods Transcriptomic changes in Ica512−/− mouse islets were analyzed. Imaging as well as biophysical and biochemical methods were used to validate if and how the Ica512-regulated gene villin modulates insulin secretion in mouse islets and insulinoma cells. Results The F-actin modifier villin was consistently downregulated in Ica512−/− mouse islets and in Ica512-depleted insulinoma cells. Villin was enriched at the cell cortex of β cells and dispersed villin−/− islet cells were less round and less deformable. Basal mobility of SGs in villin-depleted cells was enhanced. Moreover, in cells depleted either of villin or Ica512 F-actin cages restraining cortical SGs were enlarged, basal secretion was increased while glucose-stimulated insulin release was blunted. The latter changes were reverted by overexpressing villin in Ica512-depleted cells, but not vice versa. Conclusion Our findings show that villin controls the size of the F-actin cages restricting SGs and, thus, regulates their dynamics and availability for exocytosis. Evidence that villin acts downstream of Ica512 also indicates that SGs directly influence the remodeling properties of the cortical actin cytoskeleton for tight control of insulin secretion., Highlights • Ica512-depletion reduces the genetic expression of the F-actin modifier villin. • Villin-depletion enhances basal insulin granule mobility and exocytosis. • Villin regulates the size of actin cages restraining insulin granules. • Villin acts downstream of insulin granule cargo Ica512. • The Ica512-villin genetic link enables granules to control cytoskeleton plasticity.

Most delivery systems for small interfering RNA therapeutics depend on endocytosis and release from endo-lysosomal compartments. One approach to improve delivery is to identify small molecules enhancing these steps. It is unclear to what extent such enhancers can be universally applied to different delivery systems and cell types. Here, we performed a compound library screen on two well-established siRNA delivery systems, lipid nanoparticles and cholesterol conjugated-siRNAs. We identified fifty-one enhancers improving gene silencing 2-5 fold. Strikingly, most enhancers displayed specificity for one delivery system only. By a combination of quantitative fluorescence and electron microscopy we found that the enhancers substantially differed in their mechanism of action, increasing either endocytic uptake or release of siRNAs from endosomes. Furthermore, they acted either on the delivery system itself or the cell, by modulating the endocytic system via distinct mechanisms. Interestingly, several compounds displayed activity on different cell types. As proof of principle, we showed that one compound enhanced siRNA delivery in primary endothelial cells in vitro and in the endocardium in the mouse heart. This study suggests that a pharmacological approach can improve the delivery of siRNAs in a system-specific fashion, by exploiting distinct mechanisms and acting upon multiple cell types.

Insulin secretion from pancreatic β-cells in response to sudden glucose stimulation is biphasic. Prolonged secretion in vivo requires synthesis, delivery to the plasma membrane (PM) and exocytosis of insulin secretory granules (SGs). Here, we provide the first agent-based space-resolved model for SG dynamics in pancreatic β-cells. Using recent experimental data, we consider a single β-cell with identical SGs moving on a phenomenologically represented cytoskeleton network. A single exocytotic machinery mediates SG exocytosis on the PM. This novel model reproduces the measured spatial organization of SGs and insulin secretion patterns under different stimulation protocols. It proposes that the insulin potentiation effect and the rising second-phase secretion are mainly due to the increasing number of docking sites on the PM. Furthermore, it shows that 6 min after glucose stimulation, the 'newcomer' SGs are recruited from a region within less than 600 nm from the PM.

Receptor tyrosine kinases (RTKs) are transmembrane receptors of great clinical interest due to their role in disease. Historically, therapeutics targeting RTKs have been identified using in vitro kinase assays. Due to frequent development of drug resistance, however, there is a need to identify more diverse compounds that inhibit mutated but not wild-type RTKs. Here, we describe MaMTH-DS (mammalian membrane two-hybrid drug screening), a live-cell platform for high-throughput identification of small molecules targeting functional protein-protein interactions of RTKs. We applied MaMTH-DS to an oncogenic epidermal growth factor receptor (EGFR) mutant resistant to the latest generation of clinically approved tyrosine kinase inhibitors (TKIs). We identified four mutant-specific compounds, including two that would not have been detected by conventional in vitro kinase assays. One of these targets mutant EGFR via a new mechanism of action, distinct from classical TKI inhibition. Our results demonstrate how MaMTH-DS is a powerful complement to traditional drug screening approaches.

Early endosomes are organized in a network of vesicles shaped by cycles of fusion, fission, and conversion to late endosomes. In yeast, endosome fusion and conversion are regulated, among others, by CORVET, a hexameric protein complex. In the mammalian endocytic system, distinct subpopulations of early endosomes labelled by the Rab5 effectors APPL1 and EEA1 are present. Here, the function of mammalian CORVET with respect to these endosomal subpopulations was investigated. Tgfbrap1 as CORVET-specific subunit and functional ortholog of Vps3p was identified, demonstrating that it is differentially distributed between APPL1 and EEA1 endosomes. Surprisingly, depletion of CORVET-specific subunits caused fragmentation of APPL1-positive endosomes but not EEA1 endosomes in vivo. These and in vitro data suggest that CORVET plays a role in endosome fusion independently of EEA1. Depletion of CORVET subunits caused accumulation of large EEA1 endosomes indicative of another role in the conversion of EEA1 endosomes into late endosomes. In addition, depletion of CORVET-specific subunits caused alterations in transport depending on both the type of cargo and the specific endosomal subpopulation. These results demonstrate that CORVET plays distinct roles at multiple stages in the mammalian endocytic pathway.

Platelet-derived growth factor (PDGF) isoforms regulate cell proliferation, migration and differentiation both in embryonic development and adult tissue remodeling. At the cellular level, growth-factor signaling is often modulated by endocytosis. Despite important functions of PDGF, its endocytosis remains poorly studied, mainly for lack of tools to track internalized ligand by microscopy. Here, we developed such a tool and quantitatively analyzed internalization and endosomal trafficking of PDGF-BB in human fibroblasts. We further show that PDGF can be internalized in the presence of dynamin inhibitors, arguing that both dynamin-dependent and dynamin-independent pathways can mediate PDGF uptake. Although these routes operate with somewhat different kinetics, they both ultimately lead to lysosomal degradation of PDGF. Although acute inhibition of dynamin activity only moderately affects PDGF endocytosis, it specifically decreases downstream signaling of PDGF via signal transducer and activator of transcription 3 (STAT3). This correlates with reduced expression of MYC and impaired cell entry into S-phase, indicating that dynamin activity is required for PDGF-induced mitogenesis. Our data support a general view that the components governing endocytic trafficking may selectively regulate certain signaling effectors activated by a growth factor.

Mutations that result in the defective trafficking of γ2 subunit containing GABAA receptors (γ2-GABAARs) are known to reduce synaptic inhibition. Whether perturbed clustering of non-mutated GABAARs similarly reduces synaptic inhibition in vivo is less clear. In this study we provide evidence that the loss of postsynaptic γ2-GABAARs upon postnatal ablation of gephyrin, the major scaffolding protein of inhibitory postsynapses, from mature principal neurons within the forebrain results in reduced induction of long-term potentiation (LTP) and impaired network excitability within the hippocampal dentate gyrus. The preferential reduction in not only synaptic γ2-GABAAR cluster number at dendritic sites but also the decrease in γ2-GABAAR density within individual clusters at dendritic inhibitory synapses suggests that distal synapses are more sensitive to the loss of gephyrin expression than proximal synapses. The fact that these mice display behavioural features of anxiety and epilepsy emphasises the importance of postsynaptic γ2-GABAAR clustering for synaptic inhibition.

The flash-induced voltage response of halorhodopsin at high NaCl concentration comprises two main kinetic components. The first component with tau approximately 1 micros does not exceed 4% of the overall response amplitude and is probably associated with the formation of the L (hR520) intermediate. The second main component with tau approximately 1-2.5 ms which is independent of Cl- concentration can be ascribed to the transmembrane Cl- translocation during the L intermediate decay. The photoelectric response in the absence of Cl- has the opposite polarity and does not exceed 6% of the overall response amplitude at high NaCl concentration. A pH decrease results in substitution of the Cl(-)-dependent components by the photoresponse which is similar to that in the absence of Cl-. Thus, the difference between photoresponses of chloride-binding and chloride-free halorhodopsin forms resembles that of bacteriorhodopsin purple neutral and blue acid forms, respectively. The photovoltage data obtained can hardly be explained within the framework of the photocycle scheme suggested by Varo et al. [Biochemistry 34 (1995), 14490-14499]. We suppose that the O-type intermediate belongs to some form of halorhodopsin incapable of Cl- transport.

Retromer, a peripheral membrane protein complex, plays an instrumental role in host of cellular processes by its ability to recycle receptors from endosomes to the trans-Golgi network. It consists of two distinct sub-complexes, a membrane recognizing, sorting nexins (SNX) complex and a cargo recognition, vacuolar protein sorting (Vps) complex. Small GTPase, Rab7 is known to recruit retromer on endosomal membrane via interactions with the Vps sub-complex. The molecular mechanism underlying the recruitment process including the role of individual Vps proteins is yet to be deciphered. In this study, we developed a FRET-based assay in HeLa cells that demonstrated the interaction of Rab7 with Vps35 and Vps26 in vivo. Furthermore, we showed that Rab7 recruits retromer to late endosomes via direct interactions with N-terminal conserved regions in Vps35. However, the single point mutation, which disrupts the interaction between Vps35 and Vps26, perturbed the Rab7-mediated recruitment of retromer in HeLa cells. Using biophysical measurements, we demonstrate that the association of Vps26 with Vps35 resulted in high affinity binding between the Vps sub-complex and the activated Rab7 suggesting for a possible allosteric role of Vps26. Thus, this study provides molecular insights into the essential role of Vps26 and Vps35 in Rab7-mediated recruitment of the core retromer complex.

APPL endosomes are a recently identified subpopulation of early endosomes characterized by the presence of two homologous Rab5 effector proteins APPL1 and APPL2. They exhibit only limited colocalization with EEA1, another Rab5 effector and a marker of the canonical early endosomes. Although APPL endosomes appear to play important roles in cargo trafficking and signal transduction, their protein composition and biochemical properties remain largely unknown. Here we employed membrane fractionation methods to characterize APPL endosomes biochemically. We demonstrate that they represent heterogeneous membrane structures which can be discriminated from the canonical EEA1-positive early endosomes by their partly different physical properties and a distinct migration pattern in the continuous density gradients. In search for other potential markers of APPL endosomes we identified Annexin A2 as an interacting partner of both APPL1 and APPL2. Annexin A2 is a Ca(2+) and phosphatidylinositol 4,5-bisphosphate binding protein, previously implicated in several endocytic steps. We show that Annexin A2 co-fractionates and colocalizes with APPL endosomes. Moreover, silencing of its expression causes solubilization of APPL2 from endosomes. Although Annexin A2 is not an exclusive marker of APPL endosomes, our data suggest that it has an important function in membrane recruitment of APPL proteins, acting in parallel to Rab5.

Udgivelsesdato: 2009-null Binding of epidermal growth factor (EGF) to its receptor leads to receptor dimerization, assembly of protein complexes, and activation of signaling networks that control key cellular responses. Despite their fundamental role in cell biology, little is known about protein complexes associated with the EGF receptor (EGFR) before growth factor stimulation. We used a modified membrane yeast two-hybrid system together with bioinformatics to identify 87 candidate proteins interacting with the ligand-unoccupied EGFR. Among them was histone deacetylase 6 (HDAC6), a cytoplasmic lysine deacetylase, which we found negatively regulated EGFR endocytosis and degradation by controlling the acetylation status of alpha-tubulin and, subsequently, receptor trafficking along microtubules. A negative feedback loop consisting of EGFR-mediated phosphorylation of HDAC6 Tyr(570) resulted in reduced deacetylase activity and increased acetylation of alpha-tubulin. This study illustrates the complexity of the EGFR-associated interactome and identifies protein acetylation as a previously unknown regulator of receptor endocytosis and degradation.

Nuclear movements play an essential role in metazoan development. Although the intracellular transport mechanisms underlying nuclear movements have been studied in detail, relatively little is known about signals from surrounding cells and tissues controlling these movements. Here, we show that, in gastrulating zebrafish embryos, convergence movements of nuclei within the yolk syncytial layer (YSL) are guided by mesoderm and endoderm progenitors migrating along the surface of the yolk towards the dorsal side of the developing gastrula. Progenitor cells direct the convergence movements of internal yolk syncytial nuclei (iYSN) by modulating cortical flow within the YSL in which the iYSN are entrained. The effect of mesoderm and endoderm progenitors on the convergence movement of iYSN depends on the expression of E-cadherin, indicating that adhesive contact between the cells and the YSL is required for the mesendoderm-modulated YSL cortical flow mediating nuclear convergence. In summary, our data reveal a crucial function for cortical flow in the coordination of syncytial nuclear movements with surrounding cells and tissues during zebrafish gastrulation.

Insulin maintains homeostasis of glucose by promoting its uptake into cells from the blood. Hyperglycemia triggers secretion of insulin from pancreatic β-cells. This process is mediated by secretory granule exocytosis. However, how β-cells keep granule stores relatively constant is still unknown. ICA512 is an intrinsic granule membrane protein, whose cytosolic domain binds β2-syntrophin, an F-actin-associated protein, and is cleaved upon granule exocytosis. The resulting cleaved cytosolic fragment, ICA512-CCF, reaches the nucleus and up-regulates the transcription of granule genes, including insulin and ICA512. Here, we show that ICA512-CCF also dimerizes with intact ICA512 on granules, thereby displacing it from β2-syntrophin. This leads to increased granule mobility and insulin release. Based on these findings, we propose a model whereby the generation of ICA512-CCF first amplifies insulin secretion. The ensuing reduction of granule stores would then increase the probability of newly generated ICA512-CCF to reach the nucleus and enhance granule biogenesis, thus allowing β-cells to constantly adjust production of granules to their storage size and consumption. Pharmacological modulation of these feedback loops may alleviate deficient insulin release in diabetes.

Phosphatidylinositol 4-phosphate (PI(4)P) is a key regulator of membrane transport required for the formation of transport carriers from the trans-Golgi network (TGN). The molecular mechanisms of PI(4)P signaling in this process are still poorly understood. In a search for PI(4)P effector molecules, we performed a screen for synthetic lethals in a background of reduced PI(4)P and found the gene GGA2. Our analysis uncovered a PI(4)P-dependent recruitment of the clathrin adaptor Gga2p to the TGN during Golgi-to-endosome trafficking. Gga2p recruitment to liposomes is stimulated both by PI(4)P and the small GTPase Arf1p in its active conformation, implicating these two molecules in the recruitment of Gga2p to the TGN, which ultimately controls the formation of clathrin-coated vesicles. PI(4)P binding occurs through a phosphoinositide-binding signature within the N-terminal VHS domain of Gga2p resembling a motif found in other clathrin interacting proteins. These data provide an explanation for the TGN-specific membrane recruitment of Gga2p.

The yeast phosphatidylinositol 4-kinase Pik1p is essential for proliferation, and it controls Golgi homeostasis and transport of newly synthesized proteins from this compartment. At the Golgi, phosphatidylinositol 4-phosphate recruits multiple cytosolic effectors involved in formation of post-Golgi transport vesicles. A second pool of catalytically active Pik1p localizes to the nucleus. The physiological significance and regulation of this dual localization of the lipid kinase remains unknown. Here, we show that Pik1p binds to the redundant 14-3-3 proteins Bmh1p and Bmh2p. We provide evidence that nucleocytoplasmic shuttling of Pik1p involves phosphorylation and that 14-3-3 proteins bind Pik1p in the cytoplasm. Nutrient deprivation results in relocation of Pik1p from the Golgi to the nucleus and increases the amount of Pik1p–14-3-3 complex, a process reversed upon restored nutrient supply. These data suggest a role of Pik1p nucleocytoplasmic shuttling in coordination of biosynthetic transport from the Golgi with nutrient signaling.

Functional genomics screens using multi-parametric assays are powerful approaches for identifying genes involved in particular cellular processes. However, they suffer from problems like noise, and often provide little insight into molecular mechanisms. A bottleneck for addressing these issues is the lack of computational methods for the systematic integration of multi-parametric phenotypic datasets with molecular interactions. Here, we present Integrative Multi Profile Analysis of Cellular Traits (IMPACT). The main goal of IMPACT is to identify the most consistent phenotypic profile among interacting genes. This approach utilizes two types of external information: sets of related genes (IMPACT-sets) and network information (IMPACT-modules). Based on the notion that interacting genes are more likely to be involved in similar functions than non-interacting genes, this data is used as a prior to inform the filtering of phenotypic profiles that are similar among interacting genes. IMPACT-sets selects the most frequent profile among a set of related genes. IMPACT-modules identifies sub-networks containing genes with similar phenotype profiles. The statistical significance of these selections is subsequently quantified via permutations of the data. IMPACT (1) handles multiple profiles per gene, (2) rescues genes with weak phenotypes and (3) accounts for multiple biases e.g. caused by the network topology. Application to a genome-wide RNAi screen on endocytosis showed that IMPACT improved the recovery of known endocytosis-related genes, decreased off-target effects, and detected consistent phenotypes. Those findings were confirmed by rescreening 468 genes. Additionally we validated an unexpected influence of the IGF-receptor on EGF-endocytosis. IMPACT facilitates the selection of high-quality phenotypic profiles using different types of independent information, thereby supporting the molecular interpretation of functional screens., Author Summary Genome-scale functional genomics screens are important tools for investigating the function of genes. Technological progress allows for the simultaneous measurement of multiple parameters quantifying the response of cells to gene perturbations such as RNA interference. Such multi-dimensional screens provide rich data, but there is a lack of computational methods for interpreting these complex measurements. We have developed two computational methods that combine the data from multi-dimensional functional genomics screens with protein interaction information. These methods search for phenotype patterns that are consistent among interacting genes. Thereby, we could reduce the noise in the data and facilitate the mechanistic interpretation of the findings. The performance of the methods was demonstrated through application to a genome-wide screen studying endocytosis. Subsequent experimental validation demonstrated the improved detection of phenotypic profiles through the use of protein interaction data. Our analysis revealed unexpected roles of specific network modules and protein complexes with respect to endocytosis. Detailed follow-up experiments investigating the dynamics of endocytosis uncovered crosstalk between the cancer-related EGF and IGF pathways with so far unknown effects on endocytosis and cargo trafficking.

In the bacteriorhodopsin-containing proteoliposomes, a laser flash is found to induce formation of a bathointermediate decaying in several seconds, the difference spectrum being similar to the purple–blue transition. Different pH buffers do not affect the intermediate, whereas an uncoupler, gramicidin A, and lipophilic ions accelerate decay of the intermediate or inhibit its formation. In the liposomes containing E204Q bacteriorhodopsin mutant, formation of the intermediate is suppressed. In the wild-type bacteriorhodopsin liposomes, the bathointermediate formation is pH-independent within the pH 5–7 range. The efficiency of the long-lived O intermediate formation increases at a low pH. In the wild-type as well as in the E204Q mutant purple membrane, the O intermediate decay is slowed down at slightly higher pH values than that of the purple–blue transition. It is suggested that the membrane potential affects the equilibrium between the bacteriorhodopsin ground state (Glu-204 is protonated and Asp-85 is deprotonated) and the O intermediate (Asp-85 is protonated and Glu-204 is deprotonated), stabilizing the latter by changing the relative affinity of Asp-85 and Glu-204 to H+. At a low pH, protonation of a proton-releasing group (possibly Glu-194) in the bacteriorhodopsin ground state seems to prevent deprotonation of the Glu-204 during the photocycle. Thus, all protonatable residues of the outward proton pathway should be protonated in the O intermediate. Under such conditions, membrane potential stabilization of the O intermediate in the liposomes can be attributed to the direct effect of the potential on the pK value of Asp-85.

The functional characterization of the molecular components of biological systems is an outstanding task in the post-genomic era and is often addressed by gene knockdown screening which quantifies phenotypes in the form of multiparametric profiles. The identification of sets of genes producing similar phenotypic effects is fulfilled by the clustering of profiles. Here we address the question of how to quantify the biological significance of clusters of phenotypic profiles with respect to protein-protein interaction (PPI) data. The dataset we used contains 20385 gene knockdown phenotypic profiles resulting from the genome-wide image-based multiparametric siRNA screen on endocytosis in HeLa cells, which has been carried out on in our lab. Each profile is produced from images of cells in a specific gene knockdown condition, and comprises a 40-dimensional vector of phenotypic parameters, which describe the distribution of endosomes labeled by fluorescent cargo. The profiles capture the morphological changes in the endocytic system resulting from different gene knockdowns. The dataset has been pre-filtered, discarding profiles showing weak effects. Protein-protein interaction data was taken from EMBL STRING database [1]. We demonstrated that the interacting proteins are 17% more likely to produce a correlated phenotype in the siRNA screen than non-interacting proteins. Based on this observation, we developed a method for the cross-validation of the clustering of phenotypic profiles using PPI data. The relevance of a cluster with respect to PPI is measured by the ratio of the number of interactions between genes in the cluster to the total number of interactions of these genes, and by the average size of a fully connected PPI module in the cluster. The significance of these values for a cluster of a size N is assessed by bootstrapping, using sets of N nearest neighbors of random phenotypic profiles, and the p-value combines both measures. We have applied this method to the results of clustering of the phenotypic profiles by means of a modified version of the "quick shift" [2] density-based clustering algorithm equipped with k-nearest neighbor (kNN) adaptive [3] von Mises-Fisher kernel for density estimate. The proposed measure shows significant p-value for the majority of the clusters. The p-value is sensitive to the artificial deterioration of cluster quality by addition of adjacent datapoints or removal of those on the border, and thus must allow optimization of clustering parameters. To demonstrate that, we have created a method for the tree-cutting in hierarchical clustering which maximizes the significance of resulting clusters with respect to the measure we developed.

Summary Pharmacological modulators of host-microbial interactions can in principle be identified using high-content screens. However, a severe limitation of this approach is the lack of insights into the mode of action of compounds selected during the primary screen. To overcome this problem, we developed a combined experimental and computational approach. We designed a quantitative multiparametric image-based assay to measure intracellular mycobacteria in primary human macrophages, screened a chemical library containing FDA-approved drugs, and validated three compounds for intracellular killing of M. tuberculosis . By integrating the multiparametric profiles of the chemicals with those of siRNAs from a genome-wide survey on endocytosis, we predicted and experimentally verified that two compounds modulate autophagy, whereas the third accelerates endosomal progression. Our findings demonstrate the value of integrating small molecules and genetic screens for identifying cellular mechanisms modulated by chemicals. Furthermore, selective pharmacological modulation of host trafficking pathways can be applied to intracellular pathogens beyond mycobacteria.

Background Given its recent rapid development and the central role that modeling plays in the discipline, systems biology clearly needs methods for automated modeling of dynamical systems. Process-based modeling focuses on explanatory models of dynamical systems; it constructs such models from measured time-course data and formalized modeling knowledge. In this paper, we apply process-based modeling to the practically relevant task of modeling the Rab5-Rab7 conversion switch in endocytosis. The task is difficult due to the limited observability of the system variables and the noisy measurements, which pose serious challenges to the process of model selection. To address these issues, we propose a domain-specific model selection criteria that take into account knowledge about the necessary properties of the simulated model behavior. Results In a series of modeling experiments, we compare the results of process-based modeling obtained with different model selection criteria. The first is the standard maximum likelihood criterion based solely on least-squares model error. The second one is a parsimony-based criterion that also takes into account model complexity. We also introduce three domain-specific criteria based on domain expert expectations about the simulated behavior of an endocytosis model. According to the first criterion, 90 of the candidate models are indistinguishable. Furthermore, taking into account the complexity of the model does not lead to better model selection. However, the use of domain-specific criteria results in a remarkable improvement over the other two model selection criteria. Conclusions We demonstrate the applicability of process-based modeling to the task of modeling the Rab5-Rab7 dynamics in endocytosis. Our experiments show that the domain-specific criteria outperform the standard domain-independent criteria for model selection. We also find that some of the model structures discarded as implausible in previous studies lead to the expected Rab5-Rab7 switch behavior. Electronic supplementary material The online version of this article (doi:10.1186/s12918-015-0175-x) contains supplementary material, which is available to authorized users.