Phenotypic feature quantification of patient derived 3D cancer spheroids in fluorescence microscopy image

NASA Astrophysics Data System (ADS)

Kang, Mi-Sun; Rhee, Seon-Min; Seo, Ji-Hyun; Kim, Myoung-Hee

2017-03-01

Patients' responses to a drug differ at the cellular level. Here, we present an image-based cell phenotypic feature quantification method for predicting the responses of patient-derived glioblastoma cells to a particular drug. We used high-content imaging to understand the features of patient-derived cancer cells. A 3D spheroid culture formation resembles the in vivo environment more closely than 2D adherent cultures do, and it allows for the observation of cellular aggregate characteristics. However, cell analysis at the individual level is more challenging. In this paper, we demonstrate image-based phenotypic screening of the nuclei of patient-derived cancer cells. We first stitched the images of each well of the 384-well plate with the same state. We then used intensity information to detect the colonies. The nuclear intensity and morphological characteristics were used for the segmentation of individual nuclei. Next, we calculated the position of each nucleus that is appeal of the spatial pattern of cells in the well environment. Finally, we compared the results obtained using 3D spheroid culture cells with those obtained using 2D adherent culture cells from the same patient being treated with the same drugs. This technique could be applied for image-based phenotypic screening of cells to determine the patient's response to the drug.

Polarity, cell division, and out-of-equilibrium dynamics control the growth of epithelial structures

PubMed Central

Cerruti, Benedetta; Puliafito, Alberto; Shewan, Annette M.; Yu, Wei; Combes, Alexander N.; Little, Melissa H.; Chianale, Federica; Primo, Luca; Serini, Guido; Mostov, Keith E.; Celani, Antonio

2013-01-01

The growth of a well-formed epithelial structure is governed by mechanical constraints, cellular apico-basal polarity, and spatially controlled cell division. Here we compared the predictions of a mathematical model of epithelial growth with the morphological analysis of 3D epithelial structures. In both in vitro cyst models and in developing epithelial structures in vivo, epithelial growth could take place close to or far from mechanical equilibrium, and was determined by the hierarchy of time-scales of cell division, cell–cell rearrangements, and lumen dynamics. Equilibrium properties could be inferred by the analysis of cell–cell contact topologies, and the nonequilibrium phenotype was altered by inhibiting ROCK activity. The occurrence of an aberrant multilumen phenotype was linked to fast nonequilibrium growth, even when geometric control of cell division was correctly enforced. We predicted and verified experimentally that slowing down cell division partially rescued a multilumen phenotype induced by altered polarity. These results improve our understanding of the development of epithelial organs and, ultimately, of carcinogenesis. PMID:24145168

Hybrid multiscale modeling and prediction of cancer cell behavior

PubMed Central

Habibi, Jafar

2017-01-01

Background Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. Methods In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Results Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Conclusion Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset. PMID:28846712

Hybrid multiscale modeling and prediction of cancer cell behavior.

PubMed

Zangooei, Mohammad Hossein; Habibi, Jafar

2017-01-01

Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.

Systems metabolic engineering: genome-scale models and beyond.

PubMed

Blazeck, John; Alper, Hal

2010-07-01

The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches--based on the data collected with high throughput technologies--to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems.

Discrete Logic Modelling Optimization to Contextualize Prior Knowledge Networks Using PRUNET

PubMed Central

Androsova, Ganna; del Sol, Antonio

2015-01-01

High-throughput technologies have led to the generation of an increasing amount of data in different areas of biology. Datasets capturing the cell’s response to its intra- and extra-cellular microenvironment allows such data to be incorporated as signed and directed graphs or influence networks. These prior knowledge networks (PKNs) represent our current knowledge of the causality of cellular signal transduction. New signalling data is often examined and interpreted in conjunction with PKNs. However, different biological contexts, such as cell type or disease states, may have distinct variants of signalling pathways, resulting in the misinterpretation of new data. The identification of inconsistencies between measured data and signalling topologies, as well as the training of PKNs using context specific datasets (PKN contextualization), are necessary conditions to construct reliable, predictive models, which are current challenges in the systems biology of cell signalling. Here we present PRUNET, a user-friendly software tool designed to address the contextualization of a PKNs to specific experimental conditions. As the input, the algorithm takes a PKN and the expression profile of two given stable steady states or cellular phenotypes. The PKN is iteratively pruned using an evolutionary algorithm to perform an optimization process. This optimization rests in a match between predicted attractors in a discrete logic model (Boolean) and a Booleanized representation of the phenotypes, within a population of alternative subnetworks that evolves iteratively. We validated the algorithm applying PRUNET to four biological examples and using the resulting contextualized networks to predict missing expression values and to simulate well-characterized perturbations. PRUNET constitutes a tool for the automatic curation of a PKN to make it suitable for describing biological processes under particular experimental conditions. The general applicability of the implemented algorithm makes PRUNET suitable for a variety of biological processes, for instance cellular reprogramming or transitions between healthy and disease states. PMID:26058016

Discovering cancer vulnerabilities using high-throughput micro-RNA screening.

PubMed

Nikolic, Iva; Elsworth, Benjamin; Dodson, Eoin; Wu, Sunny Z; Gould, Cathryn M; Mestdagh, Pieter; Marshall, Glenn M; Horvath, Lisa G; Simpson, Kaylene J; Swarbrick, Alexander

2017-12-15

Micro-RNAs (miRNAs) are potent regulators of gene expression and cellular phenotype. Each miRNA has the potential to target hundreds of transcripts within the cell thus controlling fundamental cellular processes such as survival and proliferation. Here, we exploit this important feature of miRNA networks to discover vulnerabilities in cancer phenotype, and map miRNA-target relationships across different cancer types. More specifically, we report the results of a functional genomics screen of 1280 miRNA mimics and inhibitors in eight cancer cell lines, and its presentation in a sophisticated interactive data portal. This resource represents the most comprehensive survey of miRNA function in oncology, incorporating breast cancer, prostate cancer and neuroblastoma. A user-friendly web portal couples this experimental data with multiple tools for miRNA target prediction, pathway enrichment analysis and visualization. In addition, the database integrates publicly available gene expression and perturbation data enabling tailored and context-specific analysis of miRNA function in a particular disease. As a proof-of-principle, we use the database and its innovative features to uncover novel determinants of the neuroblastoma malignant phenotype. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Molecular deconstruction, detection, and computational prediction of microenvironment-modulated cellular responses to cancer therapeutics

PubMed Central

LaBarge, Mark A; Parvin, Bahram; Lorens, James B

2014-01-01

The field of bioengineering has pioneered the application of new precision fabrication technologies to model the different geometric, physical or molecular components of tissue microenvironments on solid-state substrata. Tissue engineering approaches building on these advances are used to assemble multicellular mimetic-tissues where cells reside within defined spatial contexts. The functional responses of cells in fabricated microenvironments has revealed a rich interplay between the genome and extracellular effectors in determining cellular phenotypes, and in a number of cases has revealed the dominance of microenvironment over genotype. Precision bioengineered substrata are limited to a few aspects, whereas cell/tissue-derived microenvironments have many undefined components. Thus introducing a computational module may serve to integrate these types of platforms to create reasonable models of drug responses in human tissues. This review discusses how combinatorial microenvironment microarrays and other biomimetic microenvironments have revealed emergent properties of cells in particular microenvironmental contexts, the platforms that can measure phenotypic changes within those contexts, and the computational tools that can unify the microenvironment-imposed functional phenotypes with underlying constellations of proteins and genes. Ultimately we propose that a merger of these technologies will enable more accurate pre-clinical drug discovery. PMID:24582543

Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

PubMed

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

2015-02-01

Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have specific patterns and tissue-specificity, which are driven by aging and other cancer-inducing agents. This framework represents the logics of complex cancer biology as a myriad of phenotypic complexities governed by a limited set of underlying organizing principles. It therefore adds to our understanding of tumor evolution and tumorigenesis, and moreover, potential usefulness of predicting tumors' evolutionary paths and clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for cancer patients, as well as cancer risks for healthy individuals are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial impact on timely diagnosis, personalized treatment and personalized prevention of cancer. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Mitochondrial oxidative stress caused by Sod2 deficiency promotes cellular senescence and aging phenotypes in the skin

PubMed Central

Velarde, Michael C.; Flynn, James M.; Day, Nicholas U.; Melov, Simon; Campisi, Judith

2012-01-01

Cellular senescence arrests the proliferation of mammalian cells at risk for neoplastic transformation, and is also associated with aging. However, the factors that cause cellular senescence during aging are unclear. Excessive reactive oxygen species (ROS) have been shown to cause cellular senescence in culture, and accumulated molecular damage due to mitochondrial ROS has long been thought to drive aging phenotypes in vivo. Here, we test the hypothesis that mitochondrial oxidative stress can promote cellular senescence in vivo and contribute to aging phenotypes in vivo, specifically in the skin. We show that the number of senescent cells, as well as impaired mitochondrial (complex II) activity increase in naturally aged mouse skin. Using a mouse model of genetic Sod2 deficiency, we show that failure to express this important mitochondrial anti-oxidant enzyme also impairs mitochondrial complex II activity, causes nuclear DNA damage, and induces cellular senescence but not apoptosis in the epidermis. Sod2 deficiency also reduced the number of cells and thickness of the epidermis, while increasing terminal differentiation. Our results support the idea that mitochondrial oxidative stress and cellular senescence contribute to aging skin phenotypes in vivo. PMID:22278880

Characterizing heterogeneous cellular responses to perturbations.

PubMed

Slack, Michael D; Martinez, Elisabeth D; Wu, Lani F; Altschuler, Steven J

2008-12-09

Cellular populations have been widely observed to respond heterogeneously to perturbation. However, interpreting the observed heterogeneity is an extremely challenging problem because of the complexity of possible cellular phenotypes, the large dimension of potential perturbations, and the lack of methods for separating meaningful biological information from noise. Here, we develop an image-based approach to characterize cellular phenotypes based on patterns of signaling marker colocalization. Heterogeneous cellular populations are characterized as mixtures of phenotypically distinct subpopulations, and responses to perturbations are summarized succinctly as probabilistic redistributions of these mixtures. We apply our method to characterize the heterogeneous responses of cancer cells to a panel of drugs. We find that cells treated with drugs of (dis-)similar mechanism exhibit (dis-)similar patterns of heterogeneity. Despite the observed phenotypic diversity of cells observed within our data, low-complexity models of heterogeneity were sufficient to distinguish most classes of drug mechanism. Our approach offers a computational framework for assessing the complexity of cellular heterogeneity, investigating the degree to which perturbations induce redistributions of a limited, but nontrivial, repertoire of underlying states and revealing functional significance contained within distinct patterns of heterogeneous responses.

Label-free cell-cycle analysis by high-throughput quantitative phase time-stretch imaging flow cytometry

NASA Astrophysics Data System (ADS)

Mok, Aaron T. Y.; Lee, Kelvin C. M.; Wong, Kenneth K. Y.; Tsia, Kevin K.

2018-02-01

Biophysical properties of cells could complement and correlate biochemical markers to characterize a multitude of cellular states. Changes in cell size, dry mass and subcellular morphology, for instance, are relevant to cell-cycle progression which is prevalently evaluated by DNA-targeted fluorescence measurements. Quantitative-phase microscopy (QPM) is among the effective biophysical phenotyping tools that can quantify cell sizes and sub-cellular dry mass density distribution of single cells at high spatial resolution. However, limited camera frame rate and thus imaging throughput makes QPM incompatible with high-throughput flow cytometry - a gold standard in multiparametric cell-based assay. Here we present a high-throughput approach for label-free analysis of cell cycle based on quantitative-phase time-stretch imaging flow cytometry at a throughput of > 10,000 cells/s. Our time-stretch QPM system enables sub-cellular resolution even at high speed, allowing us to extract a multitude (at least 24) of single-cell biophysical phenotypes (from both amplitude and phase images). Those phenotypes can be combined to track cell-cycle progression based on a t-distributed stochastic neighbor embedding (t-SNE) algorithm. Using multivariate analysis of variance (MANOVA) discriminant analysis, cell-cycle phases can also be predicted label-free with high accuracy at >90% in G1 and G2 phase, and >80% in S phase. We anticipate that high throughput label-free cell cycle characterization could open new approaches for large-scale single-cell analysis, bringing new mechanistic insights into complex biological processes including diseases pathogenesis.

Digital signaling decouples activation probability and population heterogeneity.

PubMed

Kellogg, Ryan A; Tian, Chengzhe; Lipniacki, Tomasz; Quake, Stephen R; Tay, Savaş

2015-10-21

Digital signaling enhances robustness of cellular decisions in noisy environments, but it is unclear how digital systems transmit temporal information about a stimulus. To understand how temporal input information is encoded and decoded by the NF-κB system, we studied transcription factor dynamics and gene regulation under dose- and duration-modulated inflammatory inputs. Mathematical modeling predicted and microfluidic single-cell experiments confirmed that integral of the stimulus (or area, concentration × duration) controls the fraction of cells that activate NF-κB in the population. However, stimulus temporal profile determined NF-κB dynamics, cell-to-cell variability, and gene expression phenotype. A sustained, weak stimulation lead to heterogeneous activation and delayed timing that is transmitted to gene expression. In contrast, a transient, strong stimulus with the same area caused rapid and uniform dynamics. These results show that digital NF-κB signaling enables multidimensional control of cellular phenotype via input profile, allowing parallel and independent control of single-cell activation probability and population heterogeneity.

On the holistic approach in cellular and cancer biology: nonlinearity, complexity, and quasi-determinism of the dynamic cellular network.

PubMed

Waliszewski, P; Molski, M; Konarski, J

1998-06-01

A keystone of the molecular reductionist approach to cellular biology is a specific deductive strategy relating genotype to phenotype-two distinct categories. This relationship is based on the assumption that the intermediary cellular network of actively transcribed genes and their regulatory elements is deterministic (i.e., a link between expression of a gene and a phenotypic trait can always be identified, and evolution of the network in time is predetermined). However, experimental data suggest that the relationship between genotype and phenotype is nonbijective (i.e., a gene can contribute to the emergence of more than just one phenotypic trait or a phenotypic trait can be determined by expression of several genes). This implies nonlinearity (i.e., lack of the proportional relationship between input and the outcome), complexity (i.e. emergence of the hierarchical network of multiple cross-interacting elements that is sensitive to initial conditions, possesses multiple equilibria, organizes spontaneously into different morphological patterns, and is controlled in dispersed rather than centralized manner), and quasi-determinism (i.e., coexistence of deterministic and nondeterministic events) of the network. Nonlinearity within the space of the cellular molecular events underlies the existence of a fractal structure within a number of metabolic processes, and patterns of tissue growth, which is measured experimentally as a fractal dimension. Because of its complexity, the same phenotype can be associated with a number of alternative sequences of cellular events. Moreover, the primary cause initiating phenotypic evolution of cells such as malignant transformation can be favored probabilistically, but not identified unequivocally. Thermodynamic fluctuations of energy rather than gene mutations, the material traits of the fluctuations alter both the molecular and informational structure of the network. Then, the interplay between deterministic chaos, complexity, self-organization, and natural selection drives formation of malignant phenotype. This concept offers a novel perspective for investigation of tumorigenesis without invalidating current molecular findings. The essay integrates the ideas of the sciences of complexity in a biological context.

Characterizing Protein Interactions Employing a Genome-Wide siRNA Cellular Phenotyping Screen

PubMed Central

Suratanee, Apichat; Schaefer, Martin H.; Betts, Matthew J.; Soons, Zita; Mannsperger, Heiko; Harder, Nathalie; Oswald, Marcus; Gipp, Markus; Ramminger, Ellen; Marcus, Guillermo; Männer, Reinhard; Rohr, Karl; Wanker, Erich; Russell, Robert B.; Andrade-Navarro, Miguel A.; Eils, Roland; König, Rainer

2014-01-01

Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest. PMID:25255318

Determining Regulatory Networks Governing the Differentiation of Embryonic Stem Cells to Pancreatic Lineage

NASA Astrophysics Data System (ADS)

Banerjee, Ipsita

2009-03-01

Knowledge of pathways governing cellular differentiation to specific phenotype will enable generation of desired cell fates by careful alteration of the governing network by adequate manipulation of the cellular environment. With this aim, we have developed a novel method to reconstruct the underlying regulatory architecture of a differentiating cell population from discrete temporal gene expression data. We utilize an inherent feature of biological networks, that of sparsity, in formulating the network reconstruction problem as a bi-level mixed-integer programming problem. The formulation optimizes the network topology at the upper level and the network connectivity strength at the lower level. The method is first validated by in-silico data, before applying it to the complex system of embryonic stem (ES) cell differentiation. This formulation enables efficient identification of the underlying network topology which could accurately predict steps necessary for directing differentiation to subsequent stages. Concurrent experimental verification demonstrated excellent agreement with model prediction.

Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

PubMed Central

Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

2012-01-01

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

Sizing and phenotyping of cellular vesicles using Nanoparticle Tracking Analysis

PubMed Central

Dragovic, Rebecca A.; Gardiner, Christopher; Brooks, Alexandra S.; Tannetta, Dionne S.; Ferguson, David J.P.; Hole, Patrick; Carr, Bob; Redman, Christopher W.G.; Harris, Adrian L.; Dobson, Peter J.; Harrison, Paul; Sargent, Ian L.

2011-01-01

Cellular microvesicles and nanovesicles (exosomes) are involved in many disease processes and have major potential as biomarkers. However, developments in this area are constrained by limitations in the technology available for their measurement. Here we report on the use of fluorescence nanoparticle tracking analysis (NTA) to rapidly size and phenotype cellular vesicles. In this system vesicles are visualized by light scattering using a light microscope. A video is taken, and the NTA software tracks the brownian motion of individual vesicles and calculates their size and total concentration. Using human placental vesicles and plasma, we have demonstrated that NTA can measure cellular vesicles as small as ∼50 nm and is far more sensitive than conventional flow cytometry (lower limit ∼300 nm). By combining NTA with fluorescence measurement we have demonstrated that vesicles can be labeled with specific antibody-conjugated quantum dots, allowing their phenotype to be determined. From the Clinical Editor The authors of this study utilized fluorescence nanoparticle tracking analysis (NTA) to rapidly size and phenotype cellular vesicles, demonstrating that NTA is far more sensitive than conventional flow cytometry. PMID:21601655

Molecular deconstruction, detection, and computational prediction of microenvironment-modulated cellular responses to cancer therapeutics.

PubMed

Labarge, Mark A; Parvin, Bahram; Lorens, James B

2014-04-01

The field of bioengineering has pioneered the application of new precision fabrication technologies to model the different geometric, physical or molecular components of tissue microenvironments on solid-state substrata. Tissue engineering approaches building on these advances are used to assemble multicellular mimetic-tissues where cells reside within defined spatial contexts. The functional responses of cells in fabricated microenvironments have revealed a rich interplay between the genome and extracellular effectors in determining cellular phenotypes and in a number of cases have revealed the dominance of microenvironment over genotype. Precision bioengineered substrata are limited to a few aspects, whereas cell/tissue-derived microenvironments have many undefined components. Thus, introducing a computational module may serve to integrate these types of platforms to create reasonable models of drug responses in human tissues. This review discusses how combinatorial microenvironment microarrays and other biomimetic microenvironments have revealed emergent properties of cells in particular microenvironmental contexts, the platforms that can measure phenotypic changes within those contexts, and the computational tools that can unify the microenvironment-imposed functional phenotypes with underlying constellations of proteins and genes. Ultimately we propose that a merger of these technologies will enable more accurate pre-clinical drug discovery. Copyright © 2014 Elsevier B.V. All rights reserved.

Stochastic modeling and experimental analysis of phenotypic switching and survival of cancer cells under stress

NASA Astrophysics Data System (ADS)

Zamani Dahaj, Seyed Alireza; Kumar, Niraj; Sundaram, Bala; Celli, Jonathan; Kulkarni, Rahul

The phenotypic heterogeneity of cancer cells is critical to their survival under stress. A significant contribution to heterogeneity of cancer calls derives from the epithelial-mesenchymal transition (EMT), a conserved cellular program that is crucial for embryonic development. Several studies have investigated the role of EMT in growth of early stage tumors into invasive malignancies. Also, EMT has been closely associated with the acquisition of chemoresistance properties in cancer cells. Motivated by these studies, we analyze multi-phenotype stochastic models of the evolution of cancers cell populations under stress. We derive analytical results for time-dependent probability distributions that provide insights into the competing rates underlying phenotypic switching (e.g. during EMT) and the corresponding survival of cancer cells. Experimentally, we evaluate these model-based predictions by imaging human pancreatic cancer cell lines grown with and without cytotoxic agents and measure growth kinetics, survival, morphological changes and (terminal evaluation of) biomarkers with associated epithelial and mesenchymal phenotypes. The results derived suggest approaches for distinguishing between adaptation and selection scenarios for survival in the presence of external stresses.

Label-free imaging and temporal signature in phenotypic cellular assays: a new approach to high-content screening.

PubMed

Martin, Julio

2010-09-01

Some drug targets are not amenable to screening because of the lack of a practical or validated biological assay. Likewise, some screening assays may not be predictive of compound activity in a more disease-relevant scenario, or assay development may demand excessive allocation of resources (i.e., time, money or personnel) with limited knowledge of the actual tractability of the target. Label-free methodologies, implemented in microtiter plate format, may help address these issues and complement, simplify, or facilitate assays. Label-free biosensors, based on grating resonance or electrical impedance, are versatile platforms for detecting phenotypic changes in both engineered and native cells. Their non-invasive nature allows for the kinetic monitoring of multiple real-time cellular responses to external stimuli, as well as for the use of successive pharmacological challenges. The temporal signature recorded for a particular stimulus is characteristic of the cell type and the signaling pathway activated upon binding of a ligand to its receptor. Cellular label-free technology is an important technical advance in the study of functional pharmacological selectivity. Described in this overview are some of the hurdles encountered in modern drug discovery and the ways in which label-free technologies can be used to overcome these obstacles.

Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

PubMed

Lee, Jia-Ying Joey; Miller, James Alastair; Basu, Sreetama; Kee, Ting-Zhen Vanessa; Loo, Lit-Hsin

2018-06-01

Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide variety of chemicals is not currently available. Here, we report a study that uses high-throughput imaging and artificial intelligence to build an in vitro pulmonotoxicity assay by automatically comparing and selecting human lung-cell lines and their associated quantitative phenotypic features most predictive of in vivo pulmonotoxicity. This approach is called "High-throughput In vitro Phenotypic Profiling for Toxicity Prediction" (HIPPTox). We found that the resulting assay based on two phenotypic features of a human bronchial epithelial cell line, BEAS-2B, can accurately classify 33 reference chemicals with human pulmonotoxicity information (88.8% balance accuracy, 84.6% sensitivity, and 93.0% specificity). In comparison, the predictivity of a standard cell-viability assay on the same set of chemicals is much lower (77.1% balanced accuracy, 84.6% sensitivity, and 69.5% specificity). We also used the assay to evaluate 17 additional test chemicals with unknown/unclear human pulmonotoxicity, and experimentally confirmed that many of the pulmonotoxic reference and predicted-positive test chemicals induce DNA strand breaks and/or activation of the DNA-damage response (DDR) pathway. Therefore, HIPPTox helps us to uncover these common modes-of-action of pulmonotoxic chemicals. HIPPTox may also be applied to other cell types or models, and accelerate the development of predictive in vitro assays for other cell-type- or organ-specific toxicities.

Understanding Biological Regulation Through Synthetic Biology.

PubMed

Bashor, Caleb J; Collins, James J

2018-05-20

Engineering synthetic gene regulatory circuits proceeds through iterative cycles of design, building, and testing. Initial circuit designs must rely on often-incomplete models of regulation established by fields of reductive inquiry-biochemistry and molecular and systems biology. As differences in designed and experimentally observed circuit behavior are inevitably encountered, investigated, and resolved, each turn of the engineering cycle can force a resynthesis in understanding of natural network function. Here, we outline research that uses the process of gene circuit engineering to advance biological discovery. Synthetic gene circuit engineering research has not only refined our understanding of cellular regulation but furnished biologists with a toolkit that can be directed at natural systems to exact precision manipulation of network structure. As we discuss, using circuit engineering to predictively reorganize, rewire, and reconstruct cellular regulation serves as the ultimate means of testing and understanding how cellular phenotype emerges from systems-level network function.

Wild yeast harbor a variety of distinct amyloid structures with strong prion-inducing capabilities

PubMed Central

Westergard, Laura; True, Heather L.

2014-01-01

Summary Variation in amyloid structures profoundly influences a wide array of pathological phenotypes in mammalian protein conformation disorders and dominantly inherited phenotypes in yeast. Here, we describe, for the first time, naturally occurring, self-propagating, structural variants of a prion protein isolated from wild strains of the yeast Saccharomyces cerevisiae. Variants of the [RNQ+] prion propagating in a variety of wild yeast differ biochemically, in their intracellular distributions, and in their ability to promote formation of the [PSI+] prion. [PSI+] is an epigenetic regulator of cellular phenotype and adaptability. Strikingly, we find that most natural [RNQ+] variants induced [PSI+] at high frequencies and the majority of [PSI+] variants elicited strong cellular phenotypes. We hypothesize that the presence of an efficient [RNQ+] template primes the cell for [PSI+] formation in order to induce [PSI+] in conditions where it would be advantageous. These studies utilize naturally occurring structural variants to expand our understanding of the consequences of diverse prion conformations on cellular phenotypes. PMID:24673812

A Kinetic Model for Calcium Dynamics in RAW 264.7 Cells: 2. Knockdown Response and Long-Term Response

PubMed Central

Maurya, Mano Ram; Subramaniam, Shankar

2007-01-01

This article addresses how quantitative models such as the one proposed in the companion article can be used to study cellular network perturbations such as knockdowns and pharmacological perturbations in a predictive manner. Using the kinetic model for cytosolic calcium dynamics in RAW 264.7 cells developed in the companion article, the calcium response to complement 5a (C5a) for the knockdown of seven proteins (C5a receptor; G-β-2; G-α,i-2,3; regulator of G-protein signaling-10; G-protein coupled receptor kinase-2; phospholipase C β-3; arrestin) is predicted and validated against the data from the Alliance for Cellular Signaling. The knockdown responses provide insights into how altered expressions of important proteins in disease states result in intermediate measurable phenotypes. Long-term response and long-term dose response have also been predicted, providing insights into how the receptor desensitization, internalization, and recycle result in tolerance. Sensitivity analysis of long-term response shows that the mechanisms and parameters in the receptor recycle path are important for long-term calcium dynamics. PMID:17483189

Molecular and cellular alterations in Down syndrome: toward the identification of targets for therapeutics.

PubMed

Créau, Nicole

2012-01-01

Down syndrome is a complex disease that has challenged molecular and cellular research for more than 50 years. Understanding the molecular bases of morphological, cellular, and functional alterations resulting from the presence of an additional complete chromosome 21 would aid in targeting specific genes and pathways for rescuing some phenotypes. Recently, progress has been made by characterization of brain alterations in mouse models of Down syndrome. This review will highlight the main molecular and cellular findings recently described for these models, particularly with respect to their relationship to Down syndrome phenotypes.

The cellular and molecular etiology of the craniofacial defects in the avian ciliopathic mutant talpid2

USDA-ARS?s Scientific Manuscript database

talpid2 is an avian autosomal recessive mutant with a myriad of congenital malformations, including polydactyly and facial clefting. Although phenotypically similar to talpid3, talpid2 has a distinct facial phenotype and an unknown cellular, molecular and genetic basis. We set out to determine the e...

Life is determined by its environment

NASA Astrophysics Data System (ADS)

Torday, John S.; Miller, William B.

2016-10-01

A well-developed theory of evolutionary biology requires understanding of the origins of life on Earth. However, the initial conditions (ontology) and causal (epistemology) bases on which physiology proceeded have more recently been called into question, given the teleologic nature of Darwinian evolutionary thinking. When evolutionary development is focused on cellular communication, a distinctly different perspective unfolds. The cellular communicative-molecular approach affords a logical progression for the evolutionary narrative based on the basic physiologic properties of the cell. Critical to this appraisal is recognition of the cell as a fundamental reiterative unit of reciprocating communication that receives information from and reacts to epiphenomena to solve problems. Following the course of vertebrate physiology from its unicellular origins instead of its overt phenotypic appearances and functional associations provides a robust, predictive picture for the means by which complex physiology evolved from unicellular organisms. With this foreknowledge of physiologic principles, we can determine the fundamentals of Physiology based on cellular first principles using a logical, predictable method. Thus, evolutionary creativity on our planet can be viewed as a paradoxical product of boundary conditions that permit homeostatic moments of varying length and amplitude that can productively absorb a variety of epigenetic impacts to meet environmental challenges.

Life is determined by its environment

PubMed Central

Torday, John S.; Miller, William B.

2016-01-01

A well-developed theory of evolutionary biology requires understanding of the origins of life on Earth. However, the initial conditions (ontology) and causal (epistemology) bases on which physiology proceeded have more recently been called into question, given the teleologic nature of Darwinian evolutionary thinking. When evolutionary development is focused on cellular communication, a distinctly different perspective unfolds. The cellular communicative-molecular approach affords a logical progression for the evolutionary narrative based on the basic physiologic properties of the cell. Critical to this appraisal is recognition of the cell as a fundamental reiterative unit of reciprocating communication that receives information from and reacts to epiphenomena to solve problems. Following the course of vertebrate physiology from its unicellular origins instead of its overt phenotypic appearances and functional associations provides a robust, predictive picture for the means by which complex physiology evolved from unicellular organisms. With this foreknowledge of physiologic principles, we can determine the fundamentals of Physiology based on cellular first principles using a logical, predictable method. Thus, evolutionary creativity on our planet can be viewed as a paradoxical product of boundary conditions that permit homeostatic moments of varying length and amplitude that can productively absorb a variety of epigenetic impacts to meet environmental challenges. PMID:27708547

Role of cellular adhesions in tissue dynamics spectroscopy

NASA Astrophysics Data System (ADS)

Merrill, Daniel A.; An, Ran; Turek, John; Nolte, David

2014-02-01

Cellular adhesions play a critical role in cell behavior, and modified expression of cellular adhesion compounds has been linked to various cancers. We tested the role of cellular adhesions in drug response by studying three cellular culture models: three-dimensional tumor spheroids with well-developed cellular adhesions and extracellular matrix (ECM), dense three-dimensional cell pellets with moderate numbers of adhesions, and dilute three-dimensional cell suspensions in agarose having few adhesions. Our technique for measuring the drug response for the spheroids and cell pellets was biodynamic imaging (BDI), and for the suspensions was quasi-elastic light scattering (QELS). We tested several cytoskeletal chemotherapeutic drugs (nocodazole, cytochalasin-D, paclitaxel, and colchicine) on three cancer cell lines chosen from human colorectal adenocarcinoma (HT-29), human pancreatic carcinoma (MIA PaCa-2), and rat osteosarcoma (UMR-106) to exhibit differences in adhesion strength. Comparing tumor spheroid behavior to that of cell suspensions showed shifts in the spectral motion of the cancer tissues that match predictions based on different degrees of cell-cell contacts. The HT-29 cell line, which has the strongest adhesions in the spheroid model, exhibits anomalous behavior in some cases. These results highlight the importance of using three-dimensional tissue models in drug screening with cellular adhesions being a contributory factor in phenotypic differences between the drug responses of tissue and cells.

A novel approach to PTSD modeling in rats reveals alternating patterns of limbic activity in different types of stress reaction.

PubMed

Ritov, G; Boltyansky, B; Richter-Levin, G

2016-05-01

Human reactions to trauma exposure are extremely diverse, with some individuals exhibiting only time-limited distress and others qualifying for posttraumatic stress disorder diagnosis (PTSD). Furthermore, whereas most PTSD patients mainly display fear-based symptoms, a minority of patients display a co-morbid anhedonic phenotype. We employed an individual profiling approach to model these intriguing facets of the psychiatric condition in underwater-trauma exposed rats. Based on long-term assessments of anxiety-like and anhedonic behaviors, our analysis uncovered three separate phenotypes of stress response; an anxious, fear-based (38%), a co-morbid, fear-anhedonic (15%), and an exposed-unaffected group (47%). Immunohistochemical assessments for cellular activation (c-Fos) and activation of inhibition (c-Fos+GAD67) revealed a differential involvement of limbic regions and distinct co-activity patterns for each of these phenotypes, validating the behavioral categorization. In accordance with recent neurocognitive hypotheses for posttraumatic depression, we show that enhanced pretrauma anxiety predicts the progression of posttraumatic anhedonia only in the fear-anhedonic phenotype.

Cellular stress responses to chronic heat shock and shell damage in temperate Mya truncata.

PubMed

Sleight, Victoria A; Peck, Lloyd S; Dyrynda, Elisabeth A; Smith, Valerie J; Clark, Melody S

2018-05-12

Acclimation, via phenotypic flexibility, is a potential means for a fast response to climate change. Understanding the molecular mechanisms underpinning phenotypic flexibility can provide a fine-scale cellular understanding of how organisms acclimate. In the last 30 years, Mya truncata populations around the UK have faced an average increase in sea surface temperature of 0.7 °C and further warming of between 1.5 and 4 °C, in all marine regions adjacent to the UK, is predicted by the end of the century. Hence, data are required on the ability of M. truncata to acclimate to physiological stresses, and most notably, chronic increases in temperature. Animals in the present study were exposed to chronic heat-stress for 2 months prior to shell damage and subsequently, only 3, out of 20 damaged individuals, were able to repair their shells within 2 weeks. Differentially expressed genes (between control and damaged animals) were functionally enriched with processes relating to cellular stress, the immune response and biomineralisation. Comparative transcriptomics highlighted genes, and more broadly molecular mechanisms, that are likely to be pivotal in this lack of acclimation. This study demonstrates that discovery-led transcriptomic profiling of animals during stress-response experiments can shed light on the complexity of biological processes and changes within organisms that can be more difficult to detect at higher levels of biological organisation.

Optogenetic Approaches to Drug Discovery in Neuroscience and Beyond.

PubMed

Zhang, Hongkang; Cohen, Adam E

2017-07-01

Recent advances in optogenetics have opened new routes to drug discovery, particularly in neuroscience. Physiological cellular assays probe functional phenotypes that connect genomic data to patient health. Optogenetic tools, in particular tools for all-optical electrophysiology, now provide a means to probe cellular disease models with unprecedented throughput and information content. These techniques promise to identify functional phenotypes associated with disease states and to identify compounds that improve cellular function regardless of whether the compound acts directly on a target or through a bypass mechanism. This review discusses opportunities and unresolved challenges in applying optogenetic techniques throughout the discovery pipeline - from target identification and validation, to target-based and phenotypic screens, to clinical trials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Are There Roles for Brain Cell Senescence in Aging and Neurodegenerative Disorders?

PubMed Central

Tan, Florence C. C.; Hutchison, Emmette R.; Eitan, Erez; Mattson, Mark P.

2014-01-01

The term cellular senescence was introduced more than five decades ago to describe the state of growth arrest observed in aging cells. Since this initial discovery, the phenotypes associated with cellular senescence have expanded beyond growth arrest to include alterations in cellular metabolism, secreted cytokines, epigenetic regulation and protein expression. Recently, senescence has been shown to play an important role in vivo not only in relation to aging, but also during embryonic development. Thus, cellular senescence serves different purposes and comprises a wide range of distinct phenotypes across multiple cell types. Whether all cell types, including post-mitotic neurons, are capable of entering into a senescent state remains unclear. In this review we examine recent data that suggest that cellular senescence plays a role in brain aging and, notably, may not be limited to glia but also neurons. We suggest that there is a high level of similarity between some of the pathological changes that occur in the brain in Alzheimer’s and Parkinson’s diseases and those phenotypes observed in cellular senescence, leading us to propose that neurons and glia can exhibit hallmarks of senescence previously documented in peripheral tissues. PMID:25305051

Are there roles for brain cell senescence in aging and neurodegenerative disorders?

PubMed

Tan, Florence C C; Hutchison, Emmette R; Eitan, Erez; Mattson, Mark P

2014-12-01

The term cellular senescence was introduced more than five decades ago to describe the state of growth arrest observed in aging cells. Since this initial discovery, the phenotypes associated with cellular senescence have expanded beyond growth arrest to include alterations in cellular metabolism, secreted cytokines, epigenetic regulation and protein expression. Recently, senescence has been shown to play an important role in vivo not only in relation to aging, but also during embryonic development. Thus, cellular senescence serves different purposes and comprises a wide range of distinct phenotypes across multiple cell types. Whether all cell types, including post-mitotic neurons, are capable of entering into a senescent state remains unclear. In this review we examine recent data that suggest that cellular senescence plays a role in brain aging and, notably, may not be limited to glia but also neurons. We suggest that there is a high level of similarity between some of the pathological changes that occur in the brain in Alzheimer's and Parkinson's diseases and those phenotypes observed in cellular senescence, leading us to propose that neurons and glia can exhibit hallmarks of senescence previously documented in peripheral tissues.

miR-630 targets IGF1R to regulate response to HER-targeting drugs and overall cancer cell progression in HER2 over-expressing breast cancer

PubMed Central

2014-01-01

Background While the treatment of HER2 over-expressing breast cancer with recent HER-targeted drugs has been highly effective for some patients, primary (also known as innate) or acquired resistance limits the success of these drugs. microRNAs have potential as diagnostic, prognostic and predictive biomarkers, as well as replacement therapies. Here we investigated the role of microRNA-630 (miR-630) in breast cancer progression and as a predictive biomarker for response to HER-targeting drugs, ultimately yielding potential as a therapeutic approach to add value to these drugs. Methods We investigated the levels of intra- and extracellular miR-630 in cells and conditioned media from breast cancer cell lines with either innate- or acquired- resistance to HER-targeting lapatinib and neratinib, compared to their corresponding drug sensitive cell lines, using qPCR. To support the role of miR-630 in breast cancer, we examined the clinical relevance of this miRNA in breast cancer tumours versus matched peritumours. Transfection of miR-630 mimics and inhibitors was used to manipulate the expression of miR-630 to assess effects on response to HER-targeting drugs (lapatinib, neratinib and afatinib). Other phenotypic changes associated with cellular aggressiveness were evaluated by motility, invasion and anoikis assays. TargetScan prediction software, qPCR, immunoblotting and ELISAs, were used to assess miR-630’s regulation of mRNA, proteins and their phosphorylated forms. Results We established that introducing miR-630 into cells with innate- or acquired- resistance to HER-drugs significantly restored the efficacy of lapatinib, neratinib and afatinib; through a mechanism which we have determined to, at least partly, involve miR-630’s regulation of IGF1R. Conversely, we demonstrated that blocking miR-630 induced resistance/insensitivity to these drugs. Cellular motility, invasion, and anoikis were also observed as significantly altered by miR-630 manipulation, whereby introducing miR-630 into cells reduced cellular aggression while inhibition of miR-630 induced a more aggressive cellular phenotype. Conclusions Taken together, our findings suggest miR-630 as a key regulator of cancer cell progression in HER2 over-expressing breast cancer, through targeting of IGF1R. This study supports miR-630 as a diagnostic and a predictive biomarker for response to HER-targeted drugs and indicates that the therapeutic addition of miR-630 may enhance and improve patients’ response to HER-targeting drugs. PMID:24655723

miR-630 targets IGF1R to regulate response to HER-targeting drugs and overall cancer cell progression in HER2 over-expressing breast cancer.

PubMed

Corcoran, Claire; Rani, Sweta; Breslin, Susan; Gogarty, Martina; Ghobrial, Irene M; Crown, John; O'Driscoll, Lorraine

2014-03-24

While the treatment of HER2 over-expressing breast cancer with recent HER-targeted drugs has been highly effective for some patients, primary (also known as innate) or acquired resistance limits the success of these drugs. microRNAs have potential as diagnostic, prognostic and predictive biomarkers, as well as replacement therapies. Here we investigated the role of microRNA-630 (miR-630) in breast cancer progression and as a predictive biomarker for response to HER-targeting drugs, ultimately yielding potential as a therapeutic approach to add value to these drugs. We investigated the levels of intra- and extracellular miR-630 in cells and conditioned media from breast cancer cell lines with either innate- or acquired- resistance to HER-targeting lapatinib and neratinib, compared to their corresponding drug sensitive cell lines, using qPCR. To support the role of miR-630 in breast cancer, we examined the clinical relevance of this miRNA in breast cancer tumours versus matched peritumours. Transfection of miR-630 mimics and inhibitors was used to manipulate the expression of miR-630 to assess effects on response to HER-targeting drugs (lapatinib, neratinib and afatinib). Other phenotypic changes associated with cellular aggressiveness were evaluated by motility, invasion and anoikis assays. TargetScan prediction software, qPCR, immunoblotting and ELISAs, were used to assess miR-630's regulation of mRNA, proteins and their phosphorylated forms. We established that introducing miR-630 into cells with innate- or acquired- resistance to HER-drugs significantly restored the efficacy of lapatinib, neratinib and afatinib; through a mechanism which we have determined to, at least partly, involve miR-630's regulation of IGF1R. Conversely, we demonstrated that blocking miR-630 induced resistance/insensitivity to these drugs. Cellular motility, invasion, and anoikis were also observed as significantly altered by miR-630 manipulation, whereby introducing miR-630 into cells reduced cellular aggression while inhibition of miR-630 induced a more aggressive cellular phenotype. Taken together, our findings suggest miR-630 as a key regulator of cancer cell progression in HER2 over-expressing breast cancer, through targeting of IGF1R. This study supports miR-630 as a diagnostic and a predictive biomarker for response to HER-targeted drugs and indicates that the therapeutic addition of miR-630 may enhance and improve patients' response to HER-targeting drugs.

Vascular biology: cellular and molecular profiling.

PubMed

Baird, Alison E; Wright, Violet L

2006-02-01

Our understanding of the mechanisms underlying cerebrovascular atherosclerosis has improved in recent years, but significant gaps remain. New insights into the vascular biological processes that result in ischemic stroke may come from cellular and molecular profiling studies of the peripheral blood. In recent cellular profiling studies, increased levels of a proinflammatory T-cell subset (CD4 (+)CD28 (-)) have been associated with stroke recurrence and death. Expansion of this T-cell subset may occur after ischemic stroke and be a pathogenic mechanism leading to recurrent stroke and death. Increases in certain phenotypes of endothelial cell microparticles have been found in stroke patients relative to controls, possibly indicating a state of increased vascular risk. Molecular profiling approaches include gene expression profiling and proteomic methods that permit large-scale analyses of the transcriptome and the proteome, respectively. Ultimately panels of genes and proteins may be identified that are predictive of stroke risk. Cellular and molecular profiling studies of the peripheral blood and of atherosclerotic plaques may also pave the way for the development of therapeutic agents for primary and secondary stroke prevention.

Bistability, epigenetics, and bet-hedging in bacteria.

PubMed

Veening, Jan-Willem; Smits, Wiep Klaas; Kuipers, Oscar P

2008-01-01

Clonal populations of microbial cells often show a high degree of phenotypic variability under homogeneous conditions. Stochastic fluctuations in the cellular components that determine cellular states can cause two distinct subpopulations, a property called bistability. Phenotypic heterogeneity can be readily obtained by interlinking multiple gene regulatory pathways, effectively resulting in a genetic logic-AND gate. Although switching between states can occur within the cells' lifetime, cells can also pass their cellular state over to the next generation by a mechanism known as epigenetic inheritance and thus perpetuate the phenotypic state. Importantly, heterogeneous populations can demonstrate increased fitness compared with homogeneous populations. This suggests that microbial cells employ bet-hedging strategies to maximize survival. Here, we discuss the possible roles of interlinked bistable networks, epigenetic inheritance, and bet-hedging in bacteria.

The fate of chemoresistance in triple negative breast cancer (TNBC)

PubMed Central

O’Reilly, Elma A.; Gubbins, Luke; Sharma, Shiva; Tully, Riona; Guang, Matthew Ho Zhing; Weiner-Gorzel, Karolina; McCaffrey, John; Harrison, Michele; Furlong, Fiona; Kell, Malcolm; McCann, Amanda

2015-01-01

Background Treatment options for women presenting with triple negative breast cancer (TNBC) are limited due to the lack of a therapeutic target and as a result, are managed with standard chemotherapy such as paclitaxel (Taxol®). Following chemotherapy, the ideal tumour response is apoptotic cell death. Post-chemotherapy, cells can maintain viability by undergoing viable cellular responses such as cellular senescence, generating secretomes which can directly enhance the malignant phenotype. Scope of Review How tumour cells retain viability in response to chemotherapeutic engagement is discussed. In addition we discuss the implications of this retained tumour cell viability in the context of the development of recurrent and metastatic TNBC disease. Current adjuvant and neo-adjuvant treatments available and the novel potential therapies that are being researched are also reviewed. Major conclusions Cellular senescence and cytoprotective autophagy are potential mechanisms of chemoresistance in TNBC. These two non-apoptotic outcomes in response to chemotherapy are inextricably linked and are neglected outcomes of investigation in the chemotherapeutic arena. Cellular fate assessments may therefore have the potential to predict TNBC patient outcome. General Significance Focusing on the fact that cancer cells can bypass the desired cellular apoptotic response to chemotherapy through cellular senescence and cytoprotective autophagy will highlight the importance of targeting non-apoptotic survival pathways to enhance chemotherapeutic efficacy. PMID:26676166

High content screening in neurodegenerative diseases.

PubMed

Jain, Shushant; van Kesteren, Ronald E; Heutink, Peter

2012-01-06

The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be addressed as a matter of great urgency. Multiple complementary 'omics' approaches have provided clues as to the genetic risk factors and pathogenic mechanisms underlying numerous neurodegenerative diseases, but most findings still require functional validation. For example, a recent genome wide association study for Parkinson's Disease (PD), identified many new loci as risk factors for the disease, but the underlying causative variant(s) or pathogenic mechanism is not known. As each associated region can contain several genes, the functional evaluation of each of the genes on phenotypes associated with the disease, using traditional cell biology techniques would take too long. There is also a need to understand the molecular networks that link genetic mutations to the phenotypes they cause. It is expected that disease phenotypes are the result of multiple interactions that have been disrupted. Reconstruction of these networks using traditional molecular methods would be time consuming. Moreover, network predictions from independent studies of individual components, the reductionism approach, will probably underestimate the network complexity. This underestimation could, in part, explain the low success rate of drug approval due to undesirable or toxic side effects. Gaining a network perspective of disease related pathways using HT/HC cellular screening approaches, and identifying key nodes within these pathways, could lead to the identification of targets that are more suited for therapeutic intervention. High-throughput screening (HTS) is an ideal methodology to address these issues. but traditional methods were one dimensional whole-well cell assays, that used simplistic readouts for complex biological processes. They were unable to simultaneously quantify the many phenotypes observed in neurodegenerative diseases such as axonal transport deficits or alterations in morphology properties. This approach could not be used to investigate the dynamic nature of cellular processes or pathogenic events that occur in a subset of cells. To quantify such features one has to move to multi-dimensional phenotypes termed high-content screening (HCS). HCS is the cell-based quantification of several processes simultaneously, which provides a more detailed representation of the cellular response to various perturbations compared to HTS. HCS has many advantages over HTS, but conducting a high-throughput (HT)-high-content (HC) screen in neuronal models is problematic due to high cost, environmental variation and human error. In order to detect cellular responses on a 'phenomics' scale using HC imaging one has to reduce variation and error, while increasing sensitivity and reproducibility. Herein we describe a method to accurately and reliably conduct shRNA screens using automated cell culturing and HC imaging in neuronal cellular models. We describe how we have used this methodology to identify modulators for one particular protein, DJ1, which when mutated causes autosomal recessive parkinsonism. Combining the versatility of HC imaging with HT methods, it is possible to accurately quantify a plethora of phenotypes. This could subsequently be utilized to advance our understanding of the genome, the pathways involved in disease pathogenesis as well as identify potential therapeutic targets. Copyright © 2012 Creative Commons Attribution License

Elementary Mode Analysis: A Useful Metabolic Pathway Analysis Tool for Characterizing Cellular Metabolism

PubMed Central

Trinh, Cong T.; Wlaschin, Aaron; Srienc, Friedrich

2010-01-01

Elementary Mode Analysis is a useful Metabolic Pathway Analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering. PMID:19015845

Molecular phenotyping of severe asthma using pattern recognition of bronchoalveolar lavage-derived cytokines.

PubMed

Brasier, Allan R; Victor, Sundar; Boetticher, Gary; Ju, Hyunsu; Lee, Chang; Bleecker, Eugene R; Castro, Mario; Busse, William W; Calhoun, William J

2008-01-01

Asthma is a heterogeneous clinical disorder. Methods for objective identification of disease subtypes will focus on clinical interventions and help identify causative pathways. Few studies have explored phenotypes at a molecular level. We sought to discriminate asthma phenotypes on the basis of cytokine profiles in bronchoalveolar lavage (BAL) samples from patients with mild-moderate and severe asthma. Twenty-five cytokines were measured in BAL samples of 84 patients (41 severe, 43 mild-moderate) using bead-based multiplex immunoassays. The normalized data were subjected to statistical and informatics analysis. Four groups of asthmatic profiles could be identified on the basis of unsupervised analysis (hierarchical clustering) that were independent of treatment. One group, enriched in patients with severe asthma, showed differences in BAL cellular content, reductions in baseline pulmonary function, and enhanced response to methacholine provocation. Ten cytokines were identified that accurately predicted this group. Classification methods for predicting methacholine sensitivity were developed. The best model analysis predicted hyperresponders with 88% accuracy in 10 trials by using a 10-fold cross-validation. The cytokines that contributed to this model were IL-2, IL-4, and IL-5. On the basis of this classifier, 3 distinct hyperresponder classes were identified that varied in BAL eosinophil count and PC20 methacholine. Cytokine expression patterns in BAL can be used to identify distinct types of asthma and identify distinct subsets of methacholine hyperresponders. Further biomarker discovery in BAL may be informative.

Contribution of high-content imaging technologies to the development of anti-infective drugs.

PubMed

Ang, Michelle Lay Teng; Pethe, Kevin

2016-08-01

Originally developed to study fundamental aspects of cellular biology, high-content imaging (HCI) was rapidly adapted to study host-pathogen interactions at the cellular level and adopted as a technology of choice to unravel disease biology. HCI platforms allow for the visualization and quantification of discrete phenotypes that cannot be captured using classical screening approaches. A key advantage of high-content screening technologies lies in the possibility to develop and interrogate physiologically significant, predictive ex vivo disease models that reproduce complex conditions relevant for infection. Here we review and discuss recent advances in HCI technologies and chemical biology approaches that are contributing to an increased understanding of the intricate host-pathogen interrelationship on the cellular level, and which will foster the development of novel therapeutic approaches for the treatment of human bacterial and protozoan infections. © 2016 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC. © 2016 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC.

Metabolomics, Standards, and Metabolic Modeling for Synthetic Biology in Plants

PubMed Central

Hill, Camilla Beate; Czauderna, Tobias; Klapperstück, Matthias; Roessner, Ute; Schreiber, Falk

2015-01-01

Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions. PMID:26557642

Chemical Fluxes in Cellular Steady States Measured by Fluorescence Correlation Spectroscopy

NASA Astrophysics Data System (ADS)

Qian, Hong; Elson, Elliot L.

Genetically, identical cells adopt phenotypes that have different structures, functions, and metabolic properties. In multi-cellular organisms, for example, tissue-specific phenotypes distinguish muscle cells, liver cells, fibroblasts, and blood cells that differ in biochemical functions, geometric forms, and interactions with extracellular environments. Tissue-specific cells usually have different metabolic functions such as synthesis of distinct spectra of secreted proteins, e.g., by liver or pancreatic cells, or of structural proteins, e.g., muscle vs. epithelial cells. But more importantly, a phenotype should include a dynamic aspect: different phenotypes can have distinctly different dynamic functions such as contraction of muscle cells and locomotion of leukocytes. The phenotypes of differentiated tissue cells are typically stable, but they can respond to changes in external conditions, e.g., as in the hypertrophy of muscle cells in response to extra load [1] or the phenotypic shift of fibroblasts to myofibroblasts as part of the wound healing response [2]. Cells pass through sequences of phenotypes during development and also undergo malignant phenotypic transformations as occur in cancer and heart disease.

Virtual tissues in toxicology.

PubMed

Shah, Imran; Wambaugh, John

2010-02-01

New approaches are vital for efficiently evaluating human health risk of thousands of chemicals in commerce. In vitro models offer a high-throughput approach for assaying chemical-induced molecular and cellular changes; however, bridging these perturbations to in vivo effects across chemicals, dose, time, and species remains challenging. Technological advances in multiresolution imaging and multiscale simulation are making it feasible to reconstruct tissues in silico. In toxicology, these "virtual" tissues (VT) aim to predict histopathological outcomes from alterations of cellular phenotypes that are controlled by chemical-induced perturbations in molecular pathways. The behaviors of thousands of heterogeneous cells in tissues are simulated discretely using agent-based modeling (ABM), in which computational "agents" mimic cell interactions and cellular responses to the microenvironment. The behavior of agents is constrained by physical laws and biological rules derived from experimental evidence. VT extend compartmental physiologic models to simulate both acute insults as well as the chronic effects of low-dose exposure. Furthermore, agent behavior can encode the logic of signaling and genetic regulatory networks to evaluate the role of different pathways in chemical-induced injury. To extrapolate toxicity across species, chemicals, and doses, VT require four main components: (a) organization of prior knowledge on physiologic events to define the mechanistic rules for agent behavior, (b) knowledge on key chemical-induced molecular effects, including activation of stress sensors and changes in molecular pathways that alter the cellular phenotype, (c) multiresolution quantitative and qualitative analysis of histologic data to characterize and measure chemical-, dose-, and time-dependent physiologic events, and (d) multiscale, spatiotemporal simulation frameworks to effectively calibrate and evaluate VT using experimental data. This investigation presents the motivation, implementation, and application of VT with examples from hepatotoxicity and carcinogenesis.

Role of environmental and antibiotic stress on Staphylococcus epidermidis biofilm microstructure.

PubMed

Stewart, Elizabeth J; Satorius, Ashley E; Younger, John G; Solomon, Michael J

2013-06-11

Cellular clustering and separation of Staphylococcus epidermidis surface adherent biofilms were found to depend significantly on both antibiotic and environmental stress present during growth under steady flow. Image analysis techniques common to colloidal science were applied to image volumes acquired with high-resolution confocal laser scanning microscopy to extract spatial positions of individual bacteria in volumes of size ~30 × 30 × 15 μm(3). The local number density, cluster distribution, and radial distribution function were determined at each condition by analyzing the statistics of the bacterial spatial positions. Environmental stressors of high osmotic pressure (776 mM NaCl) and sublethal antibiotic dose (1.9 μg/mL vancomycin) decreased the average bacterial local number density 10-fold. Device-associated bacterial biofilms are frequently exposed to these environmental and antibiotic stressors while undergoing flow in the bloodstream. Characteristic density phenotypes associated with low, medium, and high local number densities were identified in unstressed S. epidermidis biofilms, while stressed biofilms contained medium- and low-density phenotypes. All biofilms exhibited clustering at length scales commensurate with cell division (~1.0 μm). However, density phenotypes differed in cellular connectivity at the scale of ~6 μm. On this scale, nearly all cells in the high- and medium-density phenotypes were connected into a single cluster with a structure characteristic of a densely packed disordered fluid. However, in the low-density phenotype, the number of clusters was greater, equal to 4% of the total number of cells, and structures were fractal in nature with d(f) =1.7 ± 0.1. The work advances the understanding of biofilm growth, informs the development of predictive models of transport and mechanical properties of biofilms, and provides a method for quantifying the kinetics of bacterial surface colonization as well as biofilm fracture and fragmentation.

Poly-Omic Prediction of Complex Traits: OmicKriging

PubMed Central

Wheeler, Heather E.; Aquino-Michaels, Keston; Gamazon, Eric R.; Trubetskoy, Vassily V.; Dolan, M. Eileen; Huang, R. Stephanie; Cox, Nancy J.; Im, Hae Kyung

2014-01-01

High-confidence prediction of complex traits such as disease risk or drug response is an ultimate goal of personalized medicine. Although genome-wide association studies have discovered thousands of well-replicated polymorphisms associated with a broad spectrum of complex traits, the combined predictive power of these associations for any given trait is generally too low to be of clinical relevance. We propose a novel systems approach to complex trait prediction, which leverages and integrates similarity in genetic, transcriptomic, or other omics-level data. We translate the omic similarity into phenotypic similarity using a method called Kriging, commonly used in geostatistics and machine learning. Our method called OmicKriging emphasizes the use of a wide variety of systems-level data, such as those increasingly made available by comprehensive surveys of the genome, transcriptome, and epigenome, for complex trait prediction. Furthermore, our OmicKriging framework allows easy integration of prior information on the function of subsets of omics-level data from heterogeneous sources without the sometimes heavy computational burden of Bayesian approaches. Using seven disease datasets from the Wellcome Trust Case Control Consortium (WTCCC), we show that OmicKriging allows simple integration of sparse and highly polygenic components yielding comparable performance at a fraction of the computing time of a recently published Bayesian sparse linear mixed model method. Using a cellular growth phenotype, we show that integrating mRNA and microRNA expression data substantially increases performance over either dataset alone. Using clinical statin response, we show improved prediction over existing methods. PMID:24799323

Inferring fitness landscapes and selection on phenotypic states from single-cell genealogical data

PubMed Central

Kussell, Edo

2017-01-01

Recent advances in single-cell time-lapse microscopy have revealed non-genetic heterogeneity and temporal fluctuations of cellular phenotypes. While different phenotypic traits such as abundance of growth-related proteins in single cells may have differential effects on the reproductive success of cells, rigorous experimental quantification of this process has remained elusive due to the complexity of single cell physiology within the context of a proliferating population. We introduce and apply a practical empirical method to quantify the fitness landscapes of arbitrary phenotypic traits, using genealogical data in the form of population lineage trees which can include phenotypic data of various kinds. Our inference methodology for fitness landscapes determines how reproductivity is correlated to cellular phenotypes, and provides a natural generalization of bulk growth rate measures for single-cell histories. Using this technique, we quantify the strength of selection acting on different cellular phenotypic traits within populations, which allows us to determine whether a change in population growth is caused by individual cells’ response, selection within a population, or by a mixture of these two processes. By applying these methods to single-cell time-lapse data of growing bacterial populations that express a resistance-conferring protein under antibiotic stress, we show how the distributions, fitness landscapes, and selection strength of single-cell phenotypes are affected by the drug. Our work provides a unified and practical framework for quantitative measurements of fitness landscapes and selection strength for any statistical quantities definable on lineages, and thus elucidates the adaptive significance of phenotypic states in time series data. The method is applicable in diverse fields, from single cell biology to stem cell differentiation and viral evolution. PMID:28267748

Internal Disequilibria and Phenotypic Diversification during Replication of Hepatitis C Virus in a Noncoevolving Cellular Environment

PubMed Central

Moreno, Elena; Gallego, Isabel; Gregori, Josep; Lucía-Sanz, Adriana; Soria, María Eugenia; Castro, Victoria; Beach, Nathan M.; Manrubia, Susanna; Quer, Josep; Esteban, Juan Ignacio; Rice, Charles M.; Gómez, Jordi; Gastaminza, Pablo

2017-01-01

ABSTRACT Viral quasispecies evolution upon long-term virus replication in a noncoevolving cellular environment raises relevant general issues, such as the attainment of population equilibrium, compliance with the molecular-clock hypothesis, or stability of the phenotypic profile. Here, we evaluate the adaptation, mutant spectrum dynamics, and phenotypic diversification of hepatitis C virus (HCV) in the course of 200 passages in human hepatoma cells in an experimental design that precluded coevolution of the cells with the virus. Adaptation to the cells was evidenced by increase in progeny production. The rate of accumulation of mutations in the genomic consensus sequence deviated slightly from linearity, and mutant spectrum analyses revealed a complex dynamic of mutational waves, which was sustained beyond passage 100. The virus underwent several phenotypic changes, some of which impacted the virus-host relationship, such as enhanced cell killing, a shift toward higher virion density, and increased shutoff of host cell protein synthesis. Fluctuations in progeny production and failure to reach population equilibrium at the genomic level suggest internal instabilities that anticipate an unpredictable HCV evolution in the complex liver environment. IMPORTANCE Long-term virus evolution in an unperturbed cellular environment can reveal features of virus evolution that cannot be explained by comparing natural viral isolates. In the present study, we investigate genetic and phenotypic changes that occur upon prolonged passage of hepatitis C virus (HCV) in human hepatoma cells in an experimental design in which host cell evolutionary change is prevented. Despite replication in a noncoevolving cellular environment, the virus exhibited internal population disequilibria that did not decline with increased adaptation to the host cells. The diversification of phenotypic traits suggests that disequilibria inherent to viral populations may provide a selective advantage to viruses that can be fully exploited in changing environments. PMID:28275194

Reactivity of commercially available monoclonal antibodies to human CD antigens with peripheral blood leucocytes of dromedary camels (Camelus dromedarius)

PubMed Central

Hussen, Jamal; Shawaf, Turke; Al-herz, Abdulkareem Imran; Alturaifi, Hussain R.; Alluwaimi, Ahmed M.

2017-01-01

Monoclonal antibodies (mAbs) to cell surface molecules have been proven as a key tool for phenotypic and functional characterization of the cellular immune response. One of the major difficulties in studying camel cellular immunity consists in the lack of mAbs that dtect their leukocyte differentiation antigens. In the present study two-parameter flow cytometry was used to screen existing commercially available mAbs to human leukocyte antigens and major histocompatibility molecules (MHC) for their reactivity with camel leukocytes. The comparison of patterns of reactivity obtained after labelling human and camel leukocytes have shown that mAbs specific to human cluster of differentiation (CD) 18, CD11a, CD11b and CD14 are predicted to be cross-reactive with homologous camel antigens. PMID:28652982

Platform for combined analysis of functional and biomolecular phenotypes of the same cell.

PubMed

Kelbauskas, L; Ashili, S; Zeng, J; Rezaie, A; Lee, K; Derkach, D; Ueberroth, B; Gao, W; Paulson, T; Wang, H; Tian, Y; Smith, D; Reid, B; Meldrum, Deirdre R

2017-03-16

Functional and molecular cell-to-cell variability is pivotal at the cellular, tissue and whole-organism levels. Yet, the ultimate goal of directly correlating the function of the individual cell with its biomolecular profile remains elusive. We present a platform for integrated analysis of functional and transcriptional phenotypes in the same single cells. We investigated changes in the cellular respiration and gene expression diversity resulting from adaptation to repeated episodes of acute hypoxia in a premalignant progression model. We find differential, progression stage-specific alterations in phenotypic heterogeneity and identify cells with aberrant phenotypes. To our knowledge, this study is the first demonstration of an integrated approach to elucidate how heterogeneity at the transcriptional level manifests in the physiologic profile of individual cells in the context of disease progression.

The extraction of simple relationships in growth factor-specific multiple-input and multiple-output systems in cell-fate decisions by backward elimination PLS regression.

PubMed

Akimoto, Yuki; Yugi, Katsuyuki; Uda, Shinsuke; Kudo, Takamasa; Komori, Yasunori; Kubota, Hiroyuki; Kuroda, Shinya

2013-01-01

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

TnSeq of Mycobacterium tuberculosis clinical isolates reveals strain-specific antibiotic liabilities

PubMed Central

Carey, Allison F.; Rock, Jeremy M.; Krieger, Inna V.; Gagneux, Sebastien; Sacchettini, James C.; Fortune, Sarah M.

2018-01-01

Once considered a phenotypically monomorphic bacterium, there is a growing body of work demonstrating heterogeneity among Mycobacterium tuberculosis (Mtb) strains in clinically relevant characteristics, including virulence and response to antibiotics. However, the genetic and molecular basis for most phenotypic differences among Mtb strains remains unknown. To investigate the basis of strain variation in Mtb, we performed genome-wide transposon mutagenesis coupled with next-generation sequencing (TnSeq) for a panel of Mtb clinical isolates and the reference strain H37Rv to compare genetic requirements for in vitro growth across these strains. We developed an analytic approach to identify quantitative differences in genetic requirements between these genetically diverse strains, which vary in genomic structure and gene content. Using this methodology, we found differences between strains in their requirements for genes involved in fundamental cellular processes, including redox homeostasis and central carbon metabolism. Among the genes with differential requirements were katG, which encodes the activator of the first-line antitubercular agent isoniazid, and glcB, which encodes malate synthase, the target of a novel small-molecule inhibitor. Differences among strains in their requirement for katG and glcB predicted differences in their response to these antimicrobial agents. Importantly, these strain-specific differences in antibiotic response could not be predicted by genetic variants identified through whole genome sequencing or by gene expression analysis. Our results provide novel insight into the basis of variation among Mtb strains and demonstrate that TnSeq is a scalable method to predict clinically important phenotypic differences among Mtb strains. PMID:29505613

Evolution of early embryogenesis in rhabditid nematodes

PubMed Central

Brauchle, Michael; Kiontke, Karin; MacMenamin, Philip; Fitch, David H. A.; Piano, Fabio

2009-01-01

The cell biological events that guide early embryonic development occur with great precision within species but can be quite diverse across species. How these cellular processes evolve and which molecular components underlie evolutionary changes is poorly understood. To begin to address these questions, we systematically investigated early embryogenesis, from the one- to the four-cell embryo, in 34 nematode species related to C. elegans. We found 40 cell-biological characters that captured the phenotypic differences between these species. By tracing the evolutionary changes on a molecular phylogeny, we found that these characters evolved multiple times and independently of one another. Strikingly, all these phenotypes are mimicked by single-gene RNAi experiments in C. elegans. We use these comparisons to hypothesize the molecular mechanisms underlying the evolutionary changes. For example, we predict that a cell polarity module was altered during the evolution of the Protorhabditis group and show that PAR-1, a kinase localized asymmetrically in C. elegans early embryos, is symmetrically localized in the one-cell stage of Protorhabditis group species. Our genome-wide approach identifies candidate molecules—and thereby modules—associated with evolutionary changes in cell-biological phenotypes. PMID:19643102

HSP90 Inhibition and Cellular Stress Elicits Phenotypic Plasticity in Hematopoietic Differentiation

PubMed Central

Lawag, Abdalla A.; Napper, Jennifer M.; Hunter, Caroline A.; Bacon, Nickolas A.; Deskins, Seth; El-hamdani, Manaf; Govender, Sarah-Leigh; Koc, Emine C.

2017-01-01

Abstract Cancer cells exist in a state of Darwinian selection using mechanisms that produce changes in gene expression through genetic and epigenetic alteration to facilitate their survival. Cellular plasticity, or the ability to alter cellular phenotype, can assist in survival of premalignant cells as they progress to full malignancy by providing another mechanism of adaptation. The connection between cellular stress and the progression of cancer has been established, although the details of the mechanisms have yet to be fully elucidated. The molecular chaperone HSP90 is often upregulated in cancers as they progress, presumably to allow cancer cells to deal with misfolded proteins and cellular stress associated with transformation. The objective of this work is to test the hypothesis that inhibition of HSP90 results in increased cell plasticity in mammalian systems that can confer a greater adaptability to selective pressures. The approach used is a murine in vitro model system of hematopoietic differentiation that utilizes a murine hematopoietic stem cell line, erythroid myeloid lymphoid (EML) clone 1, during their maturation from stem cells to granulocytic progenitors. During the differentiation protocol, 80%–90% of the cells die when placed in medium where the major growth factor is granulocyte–macrophage-colony stimulating factor. Using this selection point model, EML cells exhibit increases in cellular plasticity when they are better able to adapt to this medium and survive. Increases in cellular plasticity were found to occur upon exposure to geldanamycin to inhibit HSP90, when subjected to various forms of cellular stress, or inhibition of histone acetylation. Furthermore, we provide evidence that the cellular plasticity associated with inhibition of HSP90 in this model involves epigenetic mechanisms and is dependent upon high levels of stem cell factor signaling. This work provides evidence for a role of HSP90 and cellular stress in inducing phenotypic plasticity in mammalian systems that has new implications for cellular stress in progression and evolution of cancer. PMID:28910138

HSP90 Inhibition and Cellular Stress Elicits Phenotypic Plasticity in Hematopoietic Differentiation.

PubMed

Lawag, Abdalla A; Napper, Jennifer M; Hunter, Caroline A; Bacon, Nickolas A; Deskins, Seth; El-Hamdani, Manaf; Govender, Sarah-Leigh; Koc, Emine C; Sollars, Vincent E

2017-10-01

Cancer cells exist in a state of Darwinian selection using mechanisms that produce changes in gene expression through genetic and epigenetic alteration to facilitate their survival. Cellular plasticity, or the ability to alter cellular phenotype, can assist in survival of premalignant cells as they progress to full malignancy by providing another mechanism of adaptation. The connection between cellular stress and the progression of cancer has been established, although the details of the mechanisms have yet to be fully elucidated. The molecular chaperone HSP90 is often upregulated in cancers as they progress, presumably to allow cancer cells to deal with misfolded proteins and cellular stress associated with transformation. The objective of this work is to test the hypothesis that inhibition of HSP90 results in increased cell plasticity in mammalian systems that can confer a greater adaptability to selective pressures. The approach used is a murine in vitro model system of hematopoietic differentiation that utilizes a murine hematopoietic stem cell line, erythroid myeloid lymphoid (EML) clone 1, during their maturation from stem cells to granulocytic progenitors. During the differentiation protocol, 80%-90% of the cells die when placed in medium where the major growth factor is granulocyte-macrophage-colony stimulating factor. Using this selection point model, EML cells exhibit increases in cellular plasticity when they are better able to adapt to this medium and survive. Increases in cellular plasticity were found to occur upon exposure to geldanamycin to inhibit HSP90, when subjected to various forms of cellular stress, or inhibition of histone acetylation. Furthermore, we provide evidence that the cellular plasticity associated with inhibition of HSP90 in this model involves epigenetic mechanisms and is dependent upon high levels of stem cell factor signaling. This work provides evidence for a role of HSP90 and cellular stress in inducing phenotypic plasticity in mammalian systems that has new implications for cellular stress in progression and evolution of cancer.

Cellular FLIP can substitute for the herpes simplex virus type 1 latency-associated transcript gene to support a wild-type virus reactivation phenotype in mice

PubMed Central

Jin, Ling; Carpenter, Dale; Moerdyk-Schauwecker, Megan; Vanarsdall, Adam L; Osorio, Nelson; Hsiang, Chinhui; Jones, Clinton; Wechsler, Steven L

2010-01-01

Latency-associated transcript (LAT) deletion mutants of herpes simplex virus type 1 (HSV-1) have reduced reactivation phenotypes. Thus, LAT plays an essential role in the latency-reactivation cycle of HSV-1. We have shown that LAT has antiapoptosis activity and demonstrated that the chimeric virus, dLAT-cpIAP, resulting from replacing LAT with the baculovirus antiapoptosis gene cpIAP, has a wild-type HSV-1 reactivation phenotype in mice and rabbits. Thus, LAT can be replaced by an alternative antiapoptosis gene, confirming that LAT’s antiapoptosis activity plays an important role in the mechanism by which LAT enhances the virus’ reactivation phenotype. However, because cpIAP interferes with both of the major apoptosis pathways, these studies did not address whether LAT’s proreactivation phenotype function was due to blocking the extrinsic (Fas-ligand–, caspase-8–, or caspase-10–dependent pathway) or the intrinsic (mitochondria-, caspase-9–dependent pathway) pathway, or whether both pathways must be blocked. Here we constructed an HSV-1 LAT(−) mutant that expresses cellular FLIP (cellular FLICE-like inhibitory protein) under control of the LAT promoter and in place of LAT nucleotides 76 to 1667. Mice were ocularly infected with this mutant, designated dLAT-FLIP, and the reactivation phenotype was determined using the trigeminal ganglia explant model. dLAT-FLIP had a reactivation phenotype similar to wild-type virus and significantly higher than the LAT(−) mutant dLAT2903. Thus, the LAT function responsible for enhancing the reactivation phenotype could be replaced with an antiapoptosis gene that primarily blocks the extrinsic signaling apoptosis pathway. PMID:18989818

A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability.

PubMed

Barik, Debashis; Ball, David A; Peccoud, Jean; Tyson, John J

2016-12-01

The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.

A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability

PubMed Central

Ball, David A.

2016-01-01

The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally. PMID:27935947

Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment.

PubMed

Anderson, Alexander R A; Weaver, Alissa M; Cummings, Peter T; Quaranta, Vito

2006-12-01

Emergence of invasive behavior in cancer is life-threatening, yet ill-defined due to its multifactorial nature. We present a multiscale mathematical model of cancer invasion, which considers cellular and microenvironmental factors simultaneously and interactively. Unexpectedly, the model simulations predict that harsh tumor microenvironment conditions (e.g., hypoxia, heterogenous extracellular matrix) exert a dramatic selective force on the tumor, which grows as an invasive mass with fingering margins, dominated by a few clones with aggressive traits. In contrast, mild microenvironment conditions (e.g., normoxia, homogeneous matrix) allow clones with similar aggressive traits to coexist with less aggressive phenotypes in a heterogeneous tumor mass with smooth, noninvasive margins. Thus, the genetic make-up of a cancer cell may realize its invasive potential through a clonal evolution process driven by definable microenvironmental selective forces. Our mathematical model provides a theoretical/experimental framework to quantitatively characterize this selective pressure for invasion and test ways to eliminate it.

Disease networks. Uncovering disease-disease relationships through the incomplete interactome.

PubMed

Menche, Jörg; Sharma, Amitabh; Kitsak, Maksim; Ghiassian, Susan Dina; Vidal, Marc; Loscalzo, Joseph; Barabási, Albert-László

2015-02-20

According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes. Copyright © 2015, American Association for the Advancement of Science.

A systems approach to integrative biology: an overview of statistical methods to elucidate association and architecture.

PubMed

Ciaccio, Mark F; Finkle, Justin D; Xue, Albert Y; Bagheri, Neda

2014-07-01

An organism's ability to maintain a desired physiological response relies extensively on how cellular and molecular signaling networks interpret and react to environmental cues. The capacity to quantitatively predict how networks respond to a changing environment by modifying signaling regulation and phenotypic responses will help inform and predict the impact of a changing global enivronment on organisms and ecosystems. Many computational strategies have been developed to resolve cue-signal-response networks. However, selecting a strategy that answers a specific biological question requires knowledge both of the type of data being collected, and of the strengths and weaknesses of different computational regimes. We broadly explore several computational approaches, and we evaluate their accuracy in predicting a given response. Specifically, we describe how statistical algorithms can be used in the context of integrative and comparative biology to elucidate the genomic, proteomic, and/or cellular networks responsible for robust physiological response. As a case study, we apply this strategy to a dataset of quantitative levels of protein abundance from the mussel, Mytilus galloprovincialis, to uncover the temperature-dependent signaling network. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Application of biodynamic imaging for personalized chemotherapy in canine lymphoma

NASA Astrophysics Data System (ADS)

Custead, Michelle R.

Biodynamic imaging (BDI) is a novel phenotypic cancer profiling technology which characterizes changes in cellular and subcellular motion in living tumor tissue samples following in vitro or ex vivo treatment with chemotherapeutics. The ability of BDI to predict clinical response to single-agent doxorubicin chemotherapy was tested in ten dogs with naturally-occurring non-Hodgkin's lymphomas (NHL). Pre-treatment tumor biopsy samples were obtained from all dogs and treated with doxorubicin (10 muM) ex vivo. BDI captured cellular and subcellular motility measures on all biopsy samples at baseline and at regular intervals for 9 hours following drug application. All dogs subsequently received treatment with a standard single-agent doxorubicin protocol. Objective response (OR) to doxorubicin and progression-free survival time (PFST) following chemotherapy were recorded for all dogs. The dynamic biomarkers measured by BDI were entered into a multivariate logistic model to determine the extent to which BDI predicted OR and PFST following doxorubicin therapy. The model showed that the sensitivity, specificity, and accuracy of BDI for predicting treatment outcome were 95%, 91%, and 93%, respectively. To account for possible over-fitting of data to the predictive model, cross-validation with a one-left-out analysis was performed, and the adjusted sensitivity, specificity, and accuracy following this analysis were 93%, 87%, and 91%, respectively. These findings suggest that BDI can predict, with high accuracy, treatment outcome following single-agent doxorubicin chemotherapy in a relevant spontaneous canine cancer model, and is a promising novel technology for advancing personalized cancer medicine.

Platform for combined analysis of functional and biomolecular phenotypes of the same cell

PubMed Central

Kelbauskas, L.; Ashili, S.; Zeng, J.; Rezaie, A.; Lee, K.; Derkach, D.; Ueberroth, B.; Gao, W.; Paulson, T.; Wang, H.; Tian, Y.; Smith, D.; Reid, B.; Meldrum, Deirdre R.

2017-01-01

Functional and molecular cell-to-cell variability is pivotal at the cellular, tissue and whole-organism levels. Yet, the ultimate goal of directly correlating the function of the individual cell with its biomolecular profile remains elusive. We present a platform for integrated analysis of functional and transcriptional phenotypes in the same single cells. We investigated changes in the cellular respiration and gene expression diversity resulting from adaptation to repeated episodes of acute hypoxia in a premalignant progression model. We find differential, progression stage-specific alterations in phenotypic heterogeneity and identify cells with aberrant phenotypes. To our knowledge, this study is the first demonstration of an integrated approach to elucidate how heterogeneity at the transcriptional level manifests in the physiologic profile of individual cells in the context of disease progression. PMID:28300162

Melanoma cells revive an embryonic transcriptional network to dictate phenotypic heterogeneity.

PubMed

Vandamme, Niels; Berx, Geert

2014-01-01

Compared to the overwhelming amount of literature describing how epithelial-to-mesenchymal transition (EMT)-inducing transcription factors orchestrate cellular plasticity in embryogenesis and epithelial cells, the functions of these factors in non-epithelial contexts, such as melanoma, are less clear. Melanoma is an aggressive tumor arising from melanocytes, endowed with unique features of cellular plasticity. The reversible phenotype-switching between differentiated and invasive phenotypes is increasingly appreciated as a mechanism accounting for heterogeneity in melanoma and is driven by oncogenic signaling and environmental cues. This phenotypic switch is coupled with an intriguing and somewhat counterintuitive signaling switch of EMT-inducing transcription factors. In contrast to carcinomas, different EMT-inducing transcription factors have antagonizing effects in melanoma. Balancing between these different EMT transcription factors is likely the key to successful metastatic spread of melanoma.

A Hybrid Cellular Automaton Model of Clonal Evolution in Cancer: The Emergence of the Glycolytic Phenotype

PubMed Central

Gerlee, P.; Anderson, A.R.A.

2009-01-01

We present a cellular automaton model of clonal evolution in cancer aimed at investigating the emergence of the glycolytic phenotype. In the model each cell is equipped with a micro-environment response network that determines the behaviour or phenotype of the cell based on the local environment. The response network is modelled using a feed-forward neural network, which is subject to mutations when the cells divide. This implies that cells might react differently to the environment and when space and nutrients are limited only the fittest cells will survive. With this model we have investigated the impact of the environment on the growth dynamics of the tumour. In particular we have analysed the influence of the tissue oxygen concentration and extra-cellular matrix density on the dynamics of the model. We found that the environment influences both the growth and evolutionary dynamics of the tumour. For low oxygen concentration we observe tumours with a fingered morphology, while increasing the matrix density gives rise to more compact tumours with wider fingers. The distribution of phenotypes in the tumour is also affected, and we observe that the glycolytic phenotype is most likely to emerge in a poorly oxygenated tissue with a high matrix density. Our results suggest that it is the combined effect of the oxygen concentration and matrix density that creates an environment where the glycolytic phenotype has a growth advantage and consequently is most likely to appear. PMID:18068192

Measurement of Oxidative Stress: Mitochondrial Function Using the Seahorse System.

PubMed

Leung, Dilys T H; Chu, Simon

2018-01-01

The Seahorse XFp Analyzer is a powerful tool for the assessment of various parameters of cellular respiration. Here we describe the process of the Seahorse Cell Phenotype Test using the Seahorse XFp Analyzer to characterize the metabolic phenotype of live cells. The Seahorse XFp Analyzer can also be coupled with other assays to measure cellular energetics. Given that mitochondrial dysfunction is implicated in preeclampsia, the Seahorse XFp Analyzer will serve as a useful tool for the understanding of pathological metabolism in this disorder.

Organelles – understanding noise and heterogeneity in cell biology at an intermediate scale

PubMed Central

Chang, Amy Y.

2017-01-01

ABSTRACT Many studies over the years have shown that non-genetic mechanisms for producing cell-to-cell variation can lead to highly variable behaviors across genetically identical populations of cells. Most work to date has focused on gene expression noise as the primary source of phenotypic heterogeneity, yet other sources may also contribute. In this Commentary, we explore organelle-level heterogeneity as a potential secondary source of cellular ‘noise’ that contributes to phenotypic heterogeneity. We explore mechanisms for generating organelle heterogeneity and present evidence of functional links between organelle morphology and cellular behavior. Given the many instances in which molecular-level heterogeneity has been linked to phenotypic heterogeneity, we posit that organelle heterogeneity may similarly contribute to overall phenotypic heterogeneity and underline the importance of studying organelle heterogeneity to develop a more comprehensive understanding of phenotypic heterogeneity. Finally, we conclude with a discussion of the medical challenges associated with phenotypic heterogeneity and outline how improved methods for characterizing and controlling this heterogeneity may lead to improved therapeutic strategies and outcomes for patients. PMID:28183729

Common genetic variation drives molecular heterogeneity in human iPSCs.

PubMed

Kilpinen, Helena; Goncalves, Angela; Leha, Andreas; Afzal, Vackar; Alasoo, Kaur; Ashford, Sofie; Bala, Sendu; Bensaddek, Dalila; Casale, Francesco Paolo; Culley, Oliver J; Danecek, Petr; Faulconbridge, Adam; Harrison, Peter W; Kathuria, Annie; McCarthy, Davis; McCarthy, Shane A; Meleckyte, Ruta; Memari, Yasin; Moens, Nathalie; Soares, Filipa; Mann, Alice; Streeter, Ian; Agu, Chukwuma A; Alderton, Alex; Nelson, Rachel; Harper, Sarah; Patel, Minal; White, Alistair; Patel, Sharad R; Clarke, Laura; Halai, Reena; Kirton, Christopher M; Kolb-Kokocinski, Anja; Beales, Philip; Birney, Ewan; Danovi, Davide; Lamond, Angus I; Ouwehand, Willem H; Vallier, Ludovic; Watt, Fiona M; Durbin, Richard; Stegle, Oliver; Gaffney, Daniel J

2017-06-15

Technology utilizing human induced pluripotent stem cells (iPS cells) has enormous potential to provide improved cellular models of human disease. However, variable genetic and phenotypic characterization of many existing iPS cell lines limits their potential use for research and therapy. Here we describe the systematic generation, genotyping and phenotyping of 711 iPS cell lines derived from 301 healthy individuals by the Human Induced Pluripotent Stem Cells Initiative. Our study outlines the major sources of genetic and phenotypic variation in iPS cells and establishes their suitability as models of complex human traits and cancer. Through genome-wide profiling we find that 5-46% of the variation in different iPS cell phenotypes, including differentiation capacity and cellular morphology, arises from differences between individuals. Additionally, we assess the phenotypic consequences of genomic copy-number alterations that are repeatedly observed in iPS cells. In addition, we present a comprehensive map of common regulatory variants affecting the transcriptome of human pluripotent cells.

Common genetic variation drives molecular heterogeneity in human iPSCs

PubMed Central

Leha, Andreas; Afzal, Vackar; Alasoo, Kaur; Ashford, Sofie; Bala, Sendu; Bensaddek, Dalila; Casale, Francesco Paolo; Culley, Oliver J; Danecek, Petr; Faulconbridge, Adam; Harrison, Peter W; Kathuria, Annie; McCarthy, Davis; McCarthy, Shane A; Meleckyte, Ruta; Memari, Yasin; Moens, Nathalie; Soares, Filipa; Mann, Alice; Streeter, Ian; Agu, Chukwuma A; Alderton, Alex; Nelson, Rachel; Harper, Sarah; Patel, Minal; White, Alistair; Patel, Sharad R; Clarke, Laura; Halai, Reena; Kirton, Christopher M; Kolb-Kokocinski, Anja; Beales, Philip; Birney, Ewan; Danovi, Davide; Lamond, Angus I; Ouwehand, Willem H; Vallier, Ludovic; Watt, Fiona M; Durbin, Richard

2017-01-01

Induced pluripotent stem cell (iPSC) technology has enormous potential to provide improved cellular models of human disease. However, variable genetic and phenotypic characterisation of many existing iPSC lines limits their potential use for research and therapy. Here, we describe the systematic generation, genotyping and phenotyping of 711 iPSC lines derived from 301 healthy individuals by the Human Induced Pluripotent Stem Cells Initiative (HipSci: http://www.hipsci.org). Our study outlines the major sources of genetic and phenotypic variation in iPSCs and establishes their suitability as models of complex human traits and cancer. Through genome-wide profiling we find that 5-46% of the variation in different iPSC phenotypes, including differentiation capacity and cellular morphology, arises from differences between individuals. Additionally, we assess the phenotypic consequences of rare, genomic copy number mutations that are repeatedly observed in iPSC reprogramming and present a comprehensive map of common regulatory variants affecting the transcriptome of human pluripotent cells. PMID:28489815

The finite state projection approach to analyze dynamics of heterogeneous populations

NASA Astrophysics Data System (ADS)

Johnson, Rob; Munsky, Brian

2017-06-01

Population modeling aims to capture and predict the dynamics of cell populations in constant or fluctuating environments. At the elementary level, population growth proceeds through sequential divisions of individual cells. Due to stochastic effects, populations of cells are inherently heterogeneous in phenotype, and some phenotypic variables have an effect on division or survival rates, as can be seen in partial drug resistance. Therefore, when modeling population dynamics where the control of growth and division is phenotype dependent, the corresponding model must take account of the underlying cellular heterogeneity. The finite state projection (FSP) approach has often been used to analyze the statistics of independent cells. Here, we extend the FSP analysis to explore the coupling of cell dynamics and biomolecule dynamics within a population. This extension allows a general framework with which to model the state occupations of a heterogeneous, isogenic population of dividing and expiring cells. The method is demonstrated with a simple model of cell-cycle progression, which we use to explore possible dynamics of drug resistance phenotypes in dividing cells. We use this method to show how stochastic single-cell behaviors affect population level efficacy of drug treatments, and we illustrate how slight modifications to treatment regimens may have dramatic effects on drug efficacy.

Internal Disequilibria and Phenotypic Diversification during Replication of Hepatitis C Virus in a Noncoevolving Cellular Environment.

PubMed

Moreno, Elena; Gallego, Isabel; Gregori, Josep; Lucía-Sanz, Adriana; Soria, María Eugenia; Castro, Victoria; Beach, Nathan M; Manrubia, Susanna; Quer, Josep; Esteban, Juan Ignacio; Rice, Charles M; Gómez, Jordi; Gastaminza, Pablo; Domingo, Esteban; Perales, Celia

2017-05-15

Viral quasispecies evolution upon long-term virus replication in a noncoevolving cellular environment raises relevant general issues, such as the attainment of population equilibrium, compliance with the molecular-clock hypothesis, or stability of the phenotypic profile. Here, we evaluate the adaptation, mutant spectrum dynamics, and phenotypic diversification of hepatitis C virus (HCV) in the course of 200 passages in human hepatoma cells in an experimental design that precluded coevolution of the cells with the virus. Adaptation to the cells was evidenced by increase in progeny production. The rate of accumulation of mutations in the genomic consensus sequence deviated slightly from linearity, and mutant spectrum analyses revealed a complex dynamic of mutational waves, which was sustained beyond passage 100. The virus underwent several phenotypic changes, some of which impacted the virus-host relationship, such as enhanced cell killing, a shift toward higher virion density, and increased shutoff of host cell protein synthesis. Fluctuations in progeny production and failure to reach population equilibrium at the genomic level suggest internal instabilities that anticipate an unpredictable HCV evolution in the complex liver environment. IMPORTANCE Long-term virus evolution in an unperturbed cellular environment can reveal features of virus evolution that cannot be explained by comparing natural viral isolates. In the present study, we investigate genetic and phenotypic changes that occur upon prolonged passage of hepatitis C virus (HCV) in human hepatoma cells in an experimental design in which host cell evolutionary change is prevented. Despite replication in a noncoevolving cellular environment, the virus exhibited internal population disequilibria that did not decline with increased adaptation to the host cells. The diversification of phenotypic traits suggests that disequilibria inherent to viral populations may provide a selective advantage to viruses that can be fully exploited in changing environments. Copyright © 2017 American Society for Microbiology.

Interplay between the Localization and Kinetics of Phosphorylation in Flagellar Pole Development of the Bacterium Caulobacter crescentus

PubMed Central

Tropini, Carolina; Huang, Kerwyn Casey

2012-01-01

Bacterial cells maintain sophisticated levels of intracellular organization that allow for signal amplification, response to stimuli, cell division, and many other critical processes. The mechanisms underlying localization and their contribution to fitness have been difficult to uncover, due to the often challenging task of creating mutants with systematically perturbed localization but normal enzymatic activity, and the lack of quantitative models through which to interpret subtle phenotypic changes. Focusing on the model bacterium Caulobacter crescentus, which generates two different types of daughter cells from an underlying asymmetric distribution of protein phosphorylation, we use mathematical modeling to investigate the contribution of the localization of histidine kinases to the establishment of cellular asymmetry and subsequent developmental outcomes. We use existing mutant phenotypes and fluorescence data to parameterize a reaction-diffusion model of the kinases PleC and DivJ and their cognate response regulator DivK. We then present a systematic computational analysis of the effects of changes in protein localization and abundance to determine whether PleC localization is required for correct developmental timing in Caulobacter. Our model predicts the developmental phenotypes of several localization mutants, and suggests that a novel strain with co-localization of PleC and DivJ could provide quantitative insight into the signaling threshold required for flagellar pole development. Our analysis indicates that normal development can be maintained through a wide range of localization phenotypes, and that developmental defects due to changes in PleC localization can be rescued by increased PleC expression. We also show that the system is remarkably robust to perturbation of the kinetic parameters, and while the localization of either PleC or DivJ is required for asymmetric development, the delocalization of one of these two components does not prevent flagellar pole development. We further find that allosteric regulation of PleC observed in vitro does not affect the predicted in vivo developmental phenotypes. Taken together, our model suggests that cells can tolerate perturbations to localization phenotypes, whose evolutionary origins may be connected with reducing protein expression or with decoupling pre- and post-division phenotypes. PMID:22876167

Intelligent Interfaces for Mining Large-Scale RNAi-HCS Image Databases

PubMed Central

Lin, Chen; Mak, Wayne; Hong, Pengyu; Sepp, Katharine; Perrimon, Norbert

2010-01-01

Recently, High-content screening (HCS) has been combined with RNA interference (RNAi) to become an essential image-based high-throughput method for studying genes and biological networks through RNAi-induced cellular phenotype analyses. However, a genome-wide RNAi-HCS screen typically generates tens of thousands of images, most of which remain uncategorized due to the inadequacies of existing HCS image analysis tools. Until now, it still requires highly trained scientists to browse a prohibitively large RNAi-HCS image database and produce only a handful of qualitative results regarding cellular morphological phenotypes. For this reason we have developed intelligent interfaces to facilitate the application of the HCS technology in biomedical research. Our new interfaces empower biologists with computational power not only to effectively and efficiently explore large-scale RNAi-HCS image databases, but also to apply their knowledge and experience to interactive mining of cellular phenotypes using Content-Based Image Retrieval (CBIR) with Relevance Feedback (RF) techniques. PMID:21278820

Comparative systems biology across an evolutionary gradient within the Shewanella genus.

PubMed

Konstantinidis, Konstantinos T; Serres, Margrethe H; Romine, Margaret F; Rodrigues, Jorge L M; Auchtung, Jennifer; McCue, Lee-Ann; Lipton, Mary S; Obraztsova, Anna; Giometti, Carol S; Nealson, Kenneth H; Fredrickson, James K; Tiedje, James M

2009-09-15

To what extent genotypic differences translate to phenotypic variation remains a poorly understood issue of paramount importance for several cornerstone concepts of microbiology including the species definition. Here, we take advantage of the completed genomic sequences, expressed proteomic profiles, and physiological studies of 10 closely related Shewanella strains and species to provide quantitative insights into this issue. Our analyses revealed that, despite extensive horizontal gene transfer within these genomes, the genotypic and phenotypic similarities among the organisms were generally predictable from their evolutionary relatedness. The power of the predictions depended on the degree of ecological specialization of the organisms evaluated. Using the gradient of evolutionary relatedness formed by these genomes, we were able to partly isolate the effect of ecology from that of evolutionary divergence and to rank the different cellular functions in terms of their rates of evolution. Our ranking also revealed that whole-cell protein expression differences among these organisms, when the organisms were grown under identical conditions, were relatively larger than differences at the genome level, suggesting that similarity in gene regulation and expression should constitute another important parameter for (new) species description. Collectively, our results provide important new information toward beginning a systems-level understanding of bacterial species and genera.

Mutations in the Gardos channel (KCNN4) are associated with hereditary xerocytosis.

PubMed

Glogowska, Edyta; Lezon-Geyda, Kimberly; Maksimova, Yelena; Schulz, Vincent P; Gallagher, Patrick G

2015-09-10

Hereditary xerocytosis (HX; MIM 194380) is an autosomal-dominant hemolytic anemia characterized by primary erythrocyte dehydration. In many patients, heterozygous mutations associated with delayed channel inactivation have been identified in PIEZO1. This report describes patients from 2 well-phenotyped HX kindreds, including from one of the first HX kindreds described, who lack predicted heterozygous PIEZO1-linked variants. Whole-exome sequencing identified novel, heterozygous mutations affecting the Gardos channel, encoded by the KCNN4 gene, in both kindreds. Segregation analyses confirmed transmission of the Gardos channel mutations with disease phenotype in affected individuals. The KCNN4 variants were different mutations in the same residue, which is highly conserved across species and within members of the small-intermediate family of calcium-activated potassium channel proteins. Both mutations were predicted to be deleterious by mutation effect algorithms. In sickle erythrocytes, the Gardos channel is activated under deoxy conditions, leading to cellular dehydration due to salt and water loss. The identification of KCNN4 mutations in HX patients supports recent studies that indicate it plays a critical role in normal erythrocyte deformation in the microcirculation and participates in maintenance of erythrocyte volume homeostasis. © 2015 by The American Society of Hematology.

Mutations in the Gardos channel (KCNN4) are associated with hereditary xerocytosis

PubMed Central

Glogowska, Edyta; Lezon-Geyda, Kimberly; Maksimova, Yelena; Schulz, Vincent P.

2015-01-01

Hereditary xerocytosis (HX; MIM 194380) is an autosomal-dominant hemolytic anemia characterized by primary erythrocyte dehydration. In many patients, heterozygous mutations associated with delayed channel inactivation have been identified in PIEZO1. This report describes patients from 2 well-phenotyped HX kindreds, including from one of the first HX kindreds described, who lack predicted heterozygous PIEZO1-linked variants. Whole-exome sequencing identified novel, heterozygous mutations affecting the Gardos channel, encoded by the KCNN4 gene, in both kindreds. Segregation analyses confirmed transmission of the Gardos channel mutations with disease phenotype in affected individuals. The KCNN4 variants were different mutations in the same residue, which is highly conserved across species and within members of the small-intermediate family of calcium-activated potassium channel proteins. Both mutations were predicted to be deleterious by mutation effect algorithms. In sickle erythrocytes, the Gardos channel is activated under deoxy conditions, leading to cellular dehydration due to salt and water loss. The identification of KCNN4 mutations in HX patients supports recent studies that indicate it plays a critical role in normal erythrocyte deformation in the microcirculation and participates in maintenance of erythrocyte volume homeostasis. PMID:26198474

Inducible and reversible phenotypes in a novel mouse model of Friedreich’s Ataxia

PubMed Central

Gao, Kun; Swarup, Vivek; Versano, Revital; Dong, Hongmei; Jordan, Maria C

2017-01-01

Friedreich's ataxia (FRDA), the most common inherited ataxia, is caused by recessive mutations that reduce the levels of frataxin (FXN), a mitochondrial iron binding protein. We developed an inducible mouse model of Fxn deficiency that enabled us to control the onset and progression of disease phenotypes by the modulation of Fxn levels. Systemic knockdown of Fxn in adult mice led to multiple phenotypes paralleling those observed in human patients across multiple organ systems. By reversing knockdown after clinical features appear, we were able to determine to what extent observed phenotypes represent reversible cellular dysfunction. Remarkably, upon restoration of near wild-type FXN levels, we observed significant recovery of function, associated pathology and transcriptomic dysregulation even after substantial motor dysfunction and pathology were observed. This model will be of broad utility in therapeutic development and in refining our understanding of the relative contribution of reversible cellular dysfunction at different stages in disease. PMID:29257745

Rubella viruses shift cellular bioenergetics to a more oxidative and glycolytic phenotype with a strain-specific requirement for glutamine.

PubMed

Bilz, Nicole C; Jahn, Kristin; Lorenz, Mechthild; Lüdtke, Anja; Hübschen, Judith M; Geyer, Henriette; Mankertz, Annette; Hübner, Denise; Liebert, Uwe G; Claus, Claudia

2018-06-27

The flexible regulation of cellular metabolic pathways enables cellular adaptation to changes in energy demand under conditions of stress such as posed by a virus infection. To analyze such an impact on cellular metabolism, rubella virus (RV) was used in this study. RV replication under selected substrate supplementation with glucose, pyruvate, and glutamine as essential nutrients for mammalian cells revealed its requirement for glutamine. The assessment of the mitochondrial respiratory (based on oxygen consumption rate, OCR) and glycolytic (based on extracellular acidification rate, ECAR) rate and capacity by respective stress tests through Seahorse technology enabled determination of the bioenergetic phenotype of RV-infected cells. Irrespective of the cellular metabolic background, RV infection induced a shift of the bioenergetic state of epithelial (Vero and A549) and endothelial (HUVEC) cells to a higher oxidative and glycolytic level. Interestingly there was a RV strain-specific, but genotype-independent demand for glutamine to induce a significant increase in metabolic activity. While glutaminolysis appeared to be rather negligible for RV replication, glutamine could serve as donor of its amide nitrogen in biosynthesis pathways for important metabolites. This study suggests that the capacity of rubella viruses to induce metabolic alterations could evolve differently during natural infection. Thus, changes in cellular bioenergetics represent an important component of virus-host interactions and could complement our understanding of the viral preference for a distinct host cell population. Importance RV pathologies, especially during embryonal development, could be connected with its impact on mitochondrial metabolism. With bioenergetic phenotyping we pursued a rather novel approach in virology. For the first time it was shown that a virus infection could shift the bioenergetics of its infected host cell to a higher energetic state. Notably, the capacity to induce such alterations varied among different RV isolates. Thus, our data adds viral adaptation of cellular metabolic activity to its specific needs as a novel aspect to virus-host evolution. Additionally, this study emphasizes the implementation of different viral strains in the study of virus-host interactions and the use of bioenergetic phenotyping of infected cells as a biomarker for virus-induced pathological alterations. Copyright © 2018 American Society for Microbiology.

Tumor Heterogenity Research Interactive Visualization Environment (THRIVE) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

A platform for quantitative evaluation of intratumoral spatial heterogeneity in multiplexed immunofluorescence images, via characterization of the spatial interactions between different cellular phenotypes and non-cellular constituents in the tumor microenvironment.

Epigenetic regulation of cell fate reprogramming in aging and disease: A predictive computational model.

PubMed

Folguera-Blasco, Núria; Cuyàs, Elisabet; Menéndez, Javier A; Alarcón, Tomás

2018-03-01

Understanding the control of epigenetic regulation is key to explain and modify the aging process. Because histone-modifying enzymes are sensitive to shifts in availability of cofactors (e.g. metabolites), cellular epigenetic states may be tied to changing conditions associated with cofactor variability. The aim of this study is to analyse the relationships between cofactor fluctuations, epigenetic landscapes, and cell state transitions. Using Approximate Bayesian Computation, we generate an ensemble of epigenetic regulation (ER) systems whose heterogeneity reflects variability in cofactor pools used by histone modifiers. The heterogeneity of epigenetic metabolites, which operates as regulator of the kinetic parameters promoting/preventing histone modifications, stochastically drives phenotypic variability. The ensemble of ER configurations reveals the occurrence of distinct epi-states within the ensemble. Whereas resilient states maintain large epigenetic barriers refractory to reprogramming cellular identity, plastic states lower these barriers, and increase the sensitivity to reprogramming. Moreover, fine-tuning of cofactor levels redirects plastic epigenetic states to re-enter epigenetic resilience, and vice versa. Our ensemble model agrees with a model of metabolism-responsive loss of epigenetic resilience as a cellular aging mechanism. Our findings support the notion that cellular aging, and its reversal, might result from stochastic translation of metabolic inputs into resilient/plastic cell states via ER systems.

NIBBS-search for fast and accurate prediction of phenotype-biased metabolic systems.

PubMed

Schmidt, Matthew C; Rocha, Andrea M; Padmanabhan, Kanchana; Shpanskaya, Yekaterina; Banfield, Jill; Scott, Kathleen; Mihelcic, James R; Samatova, Nagiza F

2012-01-01

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS.

NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

PubMed Central

Padmanabhan, Kanchana; Shpanskaya, Yekaterina; Banfield, Jill; Scott, Kathleen; Mihelcic, James R.; Samatova, Nagiza F.

2012-01-01

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS. PMID:22589706

Possible roles of mechanical cell elimination intrinsic to growing tissues from the perspective of tissue growth efficiency and homeostasis.

PubMed

Lee, Sang-Woo; Morishita, Yoshihiro

2017-07-01

Cell competition is a phenomenon originally described as the competition between cell populations with different genetic backgrounds; losing cells with lower fitness are eliminated. With the progress in identification of related molecules, some reports described the relevance of cell mechanics during elimination. Furthermore, recent live imaging studies have shown that even in tissues composed of genetically identical cells, a non-negligible number of cells are eliminated during growth. Thus, mechanical cell elimination (MCE) as a consequence of mechanical cellular interactions is an unavoidable event in growing tissues and a commonly observed phenomenon. Here, we studied MCE in a genetically-homogeneous tissue from the perspective of tissue growth efficiency and homeostasis. First, we propose two quantitative measures, cell and tissue fitness, to evaluate cellular competitiveness and tissue growth efficiency, respectively. By mechanical tissue simulation in a pure population where all cells have the same mechanical traits, we clarified the dependence of cell elimination rate or cell fitness on different mechanical/growth parameters. In particular, we found that geometrical (specifically, cell size) and mechanical (stress magnitude) heterogeneities are common determinants of the elimination rate. Based on these results, we propose possible mechanical feedback mechanisms that could improve tissue growth efficiency and density/stress homeostasis. Moreover, when cells with different mechanical traits are mixed (e.g., in the presence of phenotypic variation), we show that MCE could drive a drastic shift in cell trait distribution, thereby improving tissue growth efficiency through the selection of cellular traits, i.e. intra-tissue "evolution". Along with the improvement of growth efficiency, cell density, stress state, and phenotype (mechanical traits) were also shown to be homogenized through growth. More theoretically, we propose a mathematical model that approximates cell competition dynamics, by which the time evolution of tissue fitness and cellular trait distribution can be predicted without directly simulating a cell-based mechanical model.

Possible roles of mechanical cell elimination intrinsic to growing tissues from the perspective of tissue growth efficiency and homeostasis

PubMed Central

2017-01-01

Cell competition is a phenomenon originally described as the competition between cell populations with different genetic backgrounds; losing cells with lower fitness are eliminated. With the progress in identification of related molecules, some reports described the relevance of cell mechanics during elimination. Furthermore, recent live imaging studies have shown that even in tissues composed of genetically identical cells, a non-negligible number of cells are eliminated during growth. Thus, mechanical cell elimination (MCE) as a consequence of mechanical cellular interactions is an unavoidable event in growing tissues and a commonly observed phenomenon. Here, we studied MCE in a genetically-homogeneous tissue from the perspective of tissue growth efficiency and homeostasis. First, we propose two quantitative measures, cell and tissue fitness, to evaluate cellular competitiveness and tissue growth efficiency, respectively. By mechanical tissue simulation in a pure population where all cells have the same mechanical traits, we clarified the dependence of cell elimination rate or cell fitness on different mechanical/growth parameters. In particular, we found that geometrical (specifically, cell size) and mechanical (stress magnitude) heterogeneities are common determinants of the elimination rate. Based on these results, we propose possible mechanical feedback mechanisms that could improve tissue growth efficiency and density/stress homeostasis. Moreover, when cells with different mechanical traits are mixed (e.g., in the presence of phenotypic variation), we show that MCE could drive a drastic shift in cell trait distribution, thereby improving tissue growth efficiency through the selection of cellular traits, i.e. intra-tissue “evolution”. Along with the improvement of growth efficiency, cell density, stress state, and phenotype (mechanical traits) were also shown to be homogenized through growth. More theoretically, we propose a mathematical model that approximates cell competition dynamics, by which the time evolution of tissue fitness and cellular trait distribution can be predicted without directly simulating a cell-based mechanical model. PMID:28704373

Alterative Expression and Localization of Profilin 1/VASPpS157 and Cofilin 1/VASPpS239 Regulates Metastatic Growth and Is Modified by DHA Supplementation.

PubMed

Ali, Mehboob; Heyob, Kathryn; Jacob, Naduparambil K; Rogers, Lynette K

2016-09-01

Profilin 1, cofilin 1, and vasodialator-stimulated phosphoprotein (VASP) are actin-binding proteins (ABP) that regulate actin remodeling and facilitate cancer cell metastases. miR-17-92 is highly expressed in metastatic tumors and profilin1 and cofilin1 are predicted targets. Docosahexaenoic acid (DHA) inhibits cancer cell proliferation and adhesion. These studies tested the hypothesis that the metastatic phenotype is driven by changes in ABPs including alternative phosphorylation and/or changes in subcellular localization. In addition, we tested the efficacy of DHA supplementation to attenuate or inhibit these changes. Human lung cancer tissue sections were analyzed for F-actin content and expression and cellular localization of profilin1, cofilin1, and VASP (S157 or S239 phosphorylation). The metastatic phenotype was investigated in A549 and MLE12 cells lines using 8 Br-cAMP as a metastasis inducer and DHA as a therapeutic agent. Migration was assessed by wound assay and expression measured by Western blot and confocal analysis. miR-17-92 expression was measured by qRT-PCR. Results indicated increased expression and altered cellular distribution of profilin1/VASP(pS157), but no changes in cofilin1/VASP(pS239) in the human malignant tissues compared with normal tissues. In A549 and MLE12 cells, the expression patterns of profilin1/VASP(pS157) or cofilin1/VASP(pS239) suggested an interaction in regulation of actin dynamics. Furthermore, DHA inhibited cancer cell migration and viability, ABP expression and cellular localization, and modulated expression of miR-17-92 in A549 cells with minimal effects in MLE12 cells. Further investigations are warranted to understand ABP interactions, changes in cellular localization, regulation by miR-17-92, and DHA as a novel therapeutic. Mol Cancer Ther; 15(9); 2220-31. ©2016 AACR. ©2016 American Association for Cancer Research.

Alterative Expression and Localization of Profilin 1/VASPpS157 and Cofilin 1/VASPpS239 Regulates Metastatic Growth and is Modified by DHA Supplementation

PubMed Central

Ali, Mehboob; Heyob, Kathryn; Jacob, Naduparambil K.; Rogers, Lynette K.

2016-01-01

Profilin 1, cofilin 1, and vasodialator stimulated phosphoprotein (VASP) are actin binding proteins (ABP) which regulate actin remodelling and facilitate cancer cell metastases. MiR~17–92 is highly expressed in metastatic tumors and profilin1 and cofilin1 are predicted targets. Docosahexaenoic acid (DHA) inhibits cancer cell proliferation and adhesion. These studies tested the hypothesis that the metastatic phenotype is driven by changes in ABPs including alternative phosphorylation and/or changes in subcellular localization. Additionally, we tested the efficacy of DHA supplementation to attenuate or inhibit these changes. Human lung cancer tissue sections were analyzed for F-actin content and expression and cellular localization of profilin1, cofilin1 and VASP (S157 or S239 phosphorylation). The metastatic phenotype was investigated in A549 and MLE12 cells lines using 8 Br-cAMP as a metastasis inducer and DHA as a therapeutic agent. Migration was assessed by wound assay and expression measured by western blot and confocal analysis. MiR~17–92 expression was measured by qRT-PCR. Results indicated increased expression and altered cellular distribution of profilin1/VASPpS157 but no changes in cofilin1/VASPpS239 in the human malignant tissues compared to normal tissues. In A549 and MLE12 cells, the expression patterns of profilin1/VASPpS157 or cofilin1/VASPpS239 suggested an interaction in regulation of actin dynamics. Furthermore, DHA inhibited cancer cell migration and viability, ABP expression and cellular localization, and modulated expression of miR~17–92 in A549 cells with minimal effects in MLE12 cells. Further investigations are warranted to understand ABP interactions, changes in cellular localization, regulation by miR~17–92, and DHA as a novel therapeutic. PMID:27496138

Photo-induced toxic epidermal necrolysis caused by clobazam.

PubMed

Redondo, P; Vicente, J; España, A; Subira, M L; De Felipe, I; Quintanilla, E

1996-12-01

Toxic epidermal necrolysis (TEN) is a life-threatening disease, the pathogenesis of which remains largely unknown. We describe a 23-year-old woman under treatment with clobazam who developed lesions of TEN in light-exposed areas. Patch and photopatch tests with clobazam were negative. The cellular phenotype and cytokines were studied in blister fluid. The cellular infiltrate was composed mainly of T lymphocytes with a predominant cytotoxic phenotype. There was an increase in the level of tumour necrosis factor (TNF)-alpha in blister fluid compared with the control (a patient with bullous pemphigoid).

Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis

PubMed Central

Huang, Bin; Jolly, Mohit Kumar; Lu, Mingyang; Tsarfaty, Ilan; Ben-Jacob, Eshel; Onuchic, Jose’ N

2015-01-01

Cellular plasticity during cancer metastasis is a major clinical challenge. Two key cellular plasticity mechanisms —Epithelial-to-Mesenchymal Transition (EMT) and Mesenchymal-to-Amoeboid Transition (MAT) – have been carefully investigated individually, yet a comprehensive understanding of their interconnections remains elusive. Previously, we have modeled the dynamics of the core regulatory circuits for both EMT (miR-200/ZEB/miR-34/SNAIL) and MAT (Rac1/RhoA). We now extend our previous work to study the coupling between these two core circuits by considering the two microRNAs (miR-200 and miR-34) as external signals to the core MAT circuit. We show that this coupled circuit enables four different stable steady states (phenotypes) that correspond to hybrid epithelial/mesenchymal (E/M), mesenchymal (M), amoeboid (A) and hybrid amoeboid/mesenchymal (A/M) phenotypes. Our model recapitulates the metastasis-suppressing role of the microRNAs even in the presence of EMT-inducing signals like Hepatocyte Growth Factor (HGF). It also enables mapping the microRNA levels to the transitions among various cell migration phenotypes. Finally, it offers a mechanistic understanding for the observed phenotypic transitions among different cell migration phenotypes, specifically the Collective-to-Amoeboid Transition (CAT). PMID:26627083

Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE).

PubMed

Shekhar, Karthik; Brodin, Petter; Davis, Mark M; Chakraborty, Arup K

2014-01-07

Mass cytometry enables an unprecedented number of parameters to be measured in individual cells at a high throughput, but the large dimensionality of the resulting data severely limits approaches relying on manual "gating." Clustering cells based on phenotypic similarity comes at a loss of single-cell resolution and often the number of subpopulations is unknown a priori. Here we describe ACCENSE, a tool that combines nonlinear dimensionality reduction with density-based partitioning, and displays multivariate cellular phenotypes on a 2D plot. We apply ACCENSE to 35-parameter mass cytometry data from CD8(+) T cells derived from specific pathogen-free and germ-free mice, and stratify cells into phenotypic subpopulations. Our results show significant heterogeneity within the known CD8(+) T-cell subpopulations, and of particular note is that we find a large novel subpopulation in both specific pathogen-free and germ-free mice that has not been described previously. This subpopulation possesses a phenotypic signature that is distinct from conventional naive and memory subpopulations when analyzed by ACCENSE, but is not distinguishable on a biaxial plot of standard markers. We are able to automatically identify cellular subpopulations based on all proteins analyzed, thus aiding the full utilization of powerful new single-cell technologies such as mass cytometry.

ω-3 polyunsaturated fatty acids direct differentiation of the membrane phenotype in mesenchymal stem cells to potentiate osteogenesis

PubMed Central

Levental, Kandice R.; Surma, Michal A.; Skinkle, Allison D.; Lorent, Joseph H.; Zhou, Yong; Klose, Christian; Chang, Jeffrey T.; Hancock, John F.; Levental, Ilya

2017-01-01

Mammalian cells produce hundreds of dynamically regulated lipid species that are actively turned over and trafficked to produce functional membranes. These lipid repertoires are susceptible to perturbations from dietary sources, with potentially profound physiological consequences. However, neither the lipid repertoires of various cellular membranes, their modulation by dietary fats, nor their effects on cellular phenotypes have been widely explored. We report that differentiation of human mesenchymal stem cells (MSCs) into osteoblasts or adipocytes results in extensive remodeling of the plasma membrane (PM), producing cell-specific membrane compositions and biophysical properties. The distinct features of osteoblast PMs enabled rational engineering of membrane phenotypes to modulate differentiation in MSCs. Specifically, supplementation with docosahexaenoic acid (DHA), a lipid component characteristic of osteoblast membranes, induced broad lipidomic remodeling in MSCs that reproduced compositional and structural aspects of the osteoblastic PM phenotype. The PM changes induced by DHA supplementation potentiated osteogenic differentiation of MSCs concurrent with enhanced Akt activation at the PM. These observations prompt a model wherein the DHA-induced lipidome leads to more stable membrane microdomains, which serve to increase Akt activity and thereby enhance osteogenic differentiation. More broadly, our investigations suggest a general mechanism by which dietary fats affect cellular physiology through remodeling of membrane lipidomes, biophysical properties, and signaling. PMID:29134198

Genome-scale reconstruction of the metabolic network in Yersinia pestis CO92

NASA Astrophysics Data System (ADS)

Navid, Ali; Almaas, Eivind

2007-03-01

The gram-negative bacterium Yersinia pestis is the causative agent of bubonic plague. Using publicly available genomic, biochemical and physiological data, we have developed a constraint-based flux balance model of metabolism in the CO92 strain (biovar Orientalis) of this organism. The metabolic reactions were appropriately compartmentalized, and the model accounts for the exchange of metabolites, as well as the import of nutrients and export of waste products. We have characterized the metabolic capabilities and phenotypes of this organism, after comparing the model predictions with available experimental observations to evaluate accuracy and completeness. We have also begun preliminary studies into how cellular metabolism affects virulence.

Urokinase Receptor Counteracts Vascular Smooth Muscle Cell Functional Changes Induced by Surface Topography

PubMed Central

Kiyan, Yulia; Kurselis, Kestutis; Kiyan, Roman; Haller, Hermann; Chichkov, Boris N.; Dumler, Inna

2013-01-01

Current treatments for human coronary artery disease necessitate the development of the next generations of vascular bioimplants. Recent reports provide evidence that controlling cell orientation and morphology through topographical patterning might be beneficial for bioimplants and tissue engineering scaffolds. However, a concise understanding of cellular events underlying cell-biomaterial interaction remains missing. In this study, applying methods of laser material processing, we aimed to obtain useful markers to guide in the choice of better vascular biomaterials. Our data show that topographically treated human primary vascular smooth muscle cells (VSMC) have a distinct differentiation profile. In particular, cultivation of VSMC on the microgrooved biocompatible polymer E-shell induces VSMC modulation from synthetic to contractile phenotype and directs formation and maintaining of cell-cell communication and adhesion structures. We show that the urokinase receptor (uPAR) interferes with VSMC behavior on microstructured surfaces and serves as a critical regulator of VSMC functional fate. Our findings suggest that microtopography of the E-shell polymer could be important in determining VSMC phenotype and cytoskeleton organization. They further suggest uPAR as a useful target in the development of predictive models for clinical VSMC phenotyping on functional advanced biomaterials. PMID:23843899

Semi-supervised learning for genomic prediction of novel traits with small reference populations: an application to residual feed intake in dairy cattle.

PubMed

Yao, Chen; Zhu, Xiaojin; Weigel, Kent A

2016-11-07

Genomic prediction for novel traits, which can be costly and labor-intensive to measure, is often hampered by low accuracy due to the limited size of the reference population. As an option to improve prediction accuracy, we introduced a semi-supervised learning strategy known as the self-training model, and applied this method to genomic prediction of residual feed intake (RFI) in dairy cattle. We describe a self-training model that is wrapped around a support vector machine (SVM) algorithm, which enables it to use data from animals with and without measured phenotypes. Initially, a SVM model was trained using data from 792 animals with measured RFI phenotypes. Then, the resulting SVM was used to generate self-trained phenotypes for 3000 animals for which RFI measurements were not available. Finally, the SVM model was re-trained using data from up to 3792 animals, including those with measured and self-trained RFI phenotypes. Incorporation of additional animals with self-trained phenotypes enhanced the accuracy of genomic predictions compared to that of predictions that were derived from the subset of animals with measured phenotypes. The optimal ratio of animals with self-trained phenotypes to animals with measured phenotypes (2.5, 2.0, and 1.8) and the maximum increase achieved in prediction accuracy measured as the correlation between predicted and actual RFI phenotypes (5.9, 4.1, and 2.4%) decreased as the size of the initial training set (300, 400, and 500 animals with measured phenotypes) increased. The optimal number of animals with self-trained phenotypes may be smaller when prediction accuracy is measured as the mean squared error rather than the correlation between predicted and actual RFI phenotypes. Our results demonstrate that semi-supervised learning models that incorporate self-trained phenotypes can achieve genomic prediction accuracies that are comparable to those obtained with models using larger training sets that include only animals with measured phenotypes. Semi-supervised learning can be helpful for genomic prediction of novel traits, such as RFI, for which the size of reference population is limited, in particular, when the animals to be predicted and the animals in the reference population originate from the same herd-environment.

Monocyte Activation in Immunopathology: Cellular Test for Development of Diagnostics and Therapy.

PubMed

Ivanova, Ekaterina A; Orekhov, Alexander N

2016-01-01

Several highly prevalent human diseases are associated with immunopathology. Alterations in the immune system are found in such life-threatening disorders as cancer and atherosclerosis. Monocyte activation followed by macrophage polarization is an important step in normal immune response to pathogens and other relevant stimuli. Depending on the nature of the activation signal, macrophages can acquire pro- or anti-inflammatory phenotypes that are characterized by the expression of distinct patterns of secreted cytokines and surface antigens. This process is disturbed in immunopathologies resulting in abnormal monocyte activation and/or bias of macrophage polarization towards one or the other phenotype. Such alterations could be used as important diagnostic markers and also as possible targets for the development of immunomodulating therapy. Recently developed cellular tests are designed to analyze the phenotype and activity of living cells circulating in patient's bloodstream. Monocyte/macrophage activation test is a successful example of cellular test relevant for atherosclerosis and oncopathology. This test demonstrated changes in macrophage activation in subclinical atherosclerosis and breast cancer and could also be used for screening a panel of natural agents with immunomodulatory activity. Further development of cellular tests will allow broadening the scope of their clinical implication. Such tests may become useful tools for drug research and therapy optimization.

Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages

PubMed Central

Pradervand, Sylvain; Maurya, Mano R; Subramaniam, Shankar

2006-01-01

Background Release of immuno-regulatory cytokines and chemokines during inflammatory response is mediated by a complex signaling network. Multiple stimuli produce different signals that generate different cytokine responses. Current knowledge does not provide a complete picture of these signaling pathways. However, using specific markers of signaling pathways, such as signaling proteins, it is possible to develop a 'coarse-grained network' map that can help understand common regulatory modules for various cytokine responses and help differentiate between the causes of their release. Results Using a systematic profiling of signaling responses and cytokine release in RAW 264.7 macrophages made available by the Alliance for Cellular Signaling, an analysis strategy is presented that integrates principal component regression and exhaustive search-based model reduction to identify required signaling factors necessary and sufficient to predict the release of seven cytokines (G-CSF, IL-1α, IL-6, IL-10, MIP-1α, RANTES, and TNFα) in response to selected ligands. This study provides a model-based quantitative estimate of cytokine release and identifies ten signaling components involved in cytokine production. The models identified capture many of the known signaling pathways involved in cytokine release and predict potentially important novel signaling components, like p38 MAPK for G-CSF release, IFNγ- and IL-4-specific pathways for IL-1a release, and an M-CSF-specific pathway for TNFα release. Conclusion Using an integrative approach, we have identified the pathways responsible for the differential regulation of cytokine release in RAW 264.7 macrophages. Our results demonstrate the power of using heterogeneous cellular data to qualitatively and quantitatively map intermediate cellular phenotypes. PMID:16507166

A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes.

PubMed

Aghaeepour, Nima; Chattopadhyay, Pratip; Chikina, Maria; Dhaene, Tom; Van Gassen, Sofie; Kursa, Miron; Lambrecht, Bart N; Malek, Mehrnoush; McLachlan, G J; Qian, Yu; Qiu, Peng; Saeys, Yvan; Stanton, Rick; Tong, Dong; Vens, Celine; Walkowiak, Sławomir; Wang, Kui; Finak, Greg; Gottardo, Raphael; Mosmann, Tim; Nolan, Garry P; Scheuermann, Richard H; Brinkman, Ryan R

2016-01-01

The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of computational methods for identifying cell populations in multidimensional flow cytometry data. Here we report the results of FlowCAP-IV where algorithms from seven different research groups predicted the time to progression to AIDS among a cohort of 384 HIV+ subjects, using antigen-stimulated peripheral blood mononuclear cell (PBMC) samples analyzed with a 14-color staining panel. Two approaches (FlowReMi.1 and flowDensity-flowType-RchyOptimyx) provided statistically significant predictive value in the blinded test set. Manual validation of submitted results indicated that unbiased analysis of single cell phenotypes could reveal unexpected cell types that correlated with outcomes of interest in high dimensional flow cytometry datasets. © 2015 International Society for Advancement of Cytometry.

Multi-Scale Molecular Deconstruction of the Serotonin Neuron System.

PubMed

Okaty, Benjamin W; Freret, Morgan E; Rood, Benjamin D; Brust, Rachael D; Hennessy, Morgan L; deBairos, Danielle; Kim, Jun Chul; Cook, Melloni N; Dymecki, Susan M

2015-11-18

Serotonergic (5HT) neurons modulate diverse behaviors and physiology and are implicated in distinct clinical disorders. Corresponding diversity in 5HT neuronal phenotypes is becoming apparent and is likely rooted in molecular differences, yet a comprehensive approach characterizing molecular variation across the 5HT system is lacking, as is concomitant linkage to cellular phenotypes. Here we combine intersectional fate mapping, neuron sorting, and genome-wide RNA-seq to deconstruct the mouse 5HT system at multiple levels of granularity-from anatomy, to genetic sublineages, to single neurons. Our unbiased analyses reveal principles underlying system organization, 5HT neuron subtypes, constellations of differentially expressed genes distinguishing subtypes, and predictions of subtype-specific functions. Using electrophysiology, subtype-specific neuron silencing, and conditional gene knockout, we show that these molecularly defined 5HT neuron subtypes are functionally distinct. Collectively, this resource classifies molecular diversity across the 5HT system and discovers sertonergic subtypes, markers, organizing principles, and subtype-specific functions with potential disease relevance. Copyright © 2015 Elsevier Inc. All rights reserved.

Differential epigenetic reprogramming in response to specific endocrine therapies promotes cholesterol biosynthesis and cellular invasion

PubMed Central

Nguyen, Van T. M.; Barozzi, Iros; Faronato, Monica; Lombardo, Ylenia; Steel, Jennifer H.; Patel, Naina; Darbre, Philippa; Castellano, Leandro; Győrffy, Balázs; Woodley, Laura; Meira, Alba; Patten, Darren K.; Vircillo, Valentina; Periyasamy, Manikandan; Ali, Simak; Frige, Gianmaria; Minucci, Saverio; Coombes, R. Charles; Magnani, Luca

2015-01-01

Endocrine therapies target the activation of the oestrogen receptor alpha (ERα) via distinct mechanisms, but it is not clear whether breast cancer cells can adapt to treatment using drug-specific mechanisms. Here we demonstrate that resistance emerges via drug-specific epigenetic reprogramming. Resistant cells display a spectrum of phenotypical changes with invasive phenotypes evolving in lines resistant to the aromatase inhibitor (AI). Orthogonal genomics analysis of reprogrammed regulatory regions identifies individual drug-induced epigenetic states involving large topologically associating domains (TADs) and the activation of super-enhancers. AI-resistant cells activate endogenous cholesterol biosynthesis (CB) through stable epigenetic activation in vitro and in vivo. Mechanistically, CB sparks the constitutive activation of oestrogen receptors alpha (ERα) in AI-resistant cells, partly via the biosynthesis of 27-hydroxycholesterol. By targeting CB using statins, ERα binding is reduced and cell invasion is prevented. Epigenomic-led stratification can predict resistance to AI in a subset of ERα-positive patients. PMID:26610607

Multi-Scale Molecular Deconstruction of the Serotonin Neuron System

PubMed Central

Okaty, Benjamin W.; Freret, Morgan E.; Rood, Benjamin D.; Brust, Rachael D.; Hennessy, Morgan L.; deBairos, Danielle; Kim, Jun Chul; Cook, Melloni N.; Dymecki, Susan M.

2016-01-01

Summary Serotonergic (5HT) neurons modulate diverse behaviors and physiology and are implicated in distinct clinical disorders. Corresponding diversity in 5HT neuronal phenotypes is becoming apparent and is likely rooted in molecular differences, yet a comprehensive approach characterizing molecular variation across the 5HT system is lacking, as is concomitant linkage to cellular phenotypes. Here we combine intersectional fate mapping, neuron sorting, and genome-wide RNA-Seq to deconstruct the mouse 5HT system at multiple levels of granularity—from anatomy, to genetic sublineages, to single neurons. Our unbiased analyses reveal: principles underlying system organization, novel 5HT neuron subtypes, constellations of differentially expressed genes distinguishing subtypes, and predictions of subtype-specific functions. Using electrophysiology, subtype-specific neuron silencing, and conditional gene knockout, we show that these molecularly defined 5HT neuron subtypes are functionally distinct. Collectively, this resource classifies molecular diversity across the 5HT system and discovers new subtypes, markers, organizing principles, and subtype-specific functions with potential disease relevance. PMID:26549332

De novo missense mutations in the NAA10 gene cause severe non-syndromic developmental delay in males and females

PubMed Central

Popp, Bernt; Støve, Svein I; Endele, Sabine; Myklebust, Line M; Hoyer, Juliane; Sticht, Heinrich; Azzarello-Burri, Silvia; Rauch, Anita; Arnesen, Thomas; Reis, André

2015-01-01

Recent studies revealed the power of whole-exome sequencing to identify mutations in sporadic cases with non-syndromic intellectual disability. We now identified de novo missense variants in NAA10 in two unrelated individuals, a boy and a girl, with severe global developmental delay but without any major dysmorphism by trio whole-exome sequencing. Both de novo variants were predicted to be deleterious, and we excluded other variants in this gene. This X-linked gene encodes N-alpha-acetyltransferase 10, the catalytic subunit of the NatA complex involved in multiple cellular processes. A single hypomorphic missense variant p.(Ser37Pro) was previously associated with Ogden syndrome in eight affected males from two different families. This rare disorder is characterized by a highly recognizable phenotype, global developmental delay and results in death during infancy. In an attempt to explain the discrepant phenotype, we used in vitro N-terminal acetylation assays which suggested that the severity of the phenotype correlates with the remaining catalytic activity. The variant in the Ogden syndrome patients exhibited a lower activity than the one seen in the boy with intellectual disability, while the variant in the girl was the most severe exhibiting only residual activity in the acetylation assays used. We propose that N-terminal acetyltransferase deficiency is clinically heterogeneous with the overall catalytic activity determining the phenotypic severity. PMID:25099252

Regulation of Plant Cellular and Organismal Development by SUMO.

PubMed

Elrouby, Nabil

2017-01-01

This chapter clearly demonstrates the breadth and spectrum of the processes that SUMO regulates during plant development. The gross phenotypes observed in mutants of the SUMO conjugation and deconjugation enzymes reflect these essential roles, and detailed analyses of these mutants under different growth conditions revealed roles in biotic and abiotic stress responses, phosphate starvation, nitrate and sulphur metabolism, freezing and drought tolerance and response to excess copper. SUMO functions also intersect with those regulated by several hormones such as salicylic acid , abscisic acid , gibberellins and auxin, and detailed studies provide mechanistic clues of how sumoylation may regulate these processes. The regulation of COP1 and PhyB functions by sumoylation provides very strong evidence that SUMO is heavily involved in the regulation of light signaling in plants. At the cellular and subcellular levels, SUMO regulates meristem architecture, the switch from the mitotic cycle into the endocycle, meiosis, centromere decondensation and exit from mitosis, transcriptional control, and release from transcriptional silencing. Most of these advances in our understanding of SUMO functions during plant development emerged over the past 6-7 years, and they may only predict a prominent rise of SUMO as a major regulator of eukaryotic cellular and organismal growth and development.

Whole genome prediction and heritability of childhood asthma phenotypes.

PubMed

McGeachie, Michael J; Clemmer, George L; Croteau-Chonka, Damien C; Castaldi, Peter J; Cho, Michael H; Sordillo, Joanne E; Lasky-Su, Jessica A; Raby, Benjamin A; Tantisira, Kelan G; Weiss, Scott T

2016-12-01

While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma-related phenotypes. We applied several WGP methods to a well-phenotyped cohort of 832 children with mild-to-moderate asthma from CAMP. We assessed narrow-sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre- and post-bronchodilator forced expiratory volume in 1 sec (FEV 1 ), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort. We found that longitudinal lung function phenotypes demonstrated significant narrow-sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4-8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts. Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP-prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma-related heritable traits.

Estimating genetic and phenotypic parameters of cellular immune-associated traits in dairy cows.

PubMed

Denholm, Scott J; McNeilly, Tom N; Banos, Georgios; Coffey, Mike P; Russell, George C; Bagnall, Ainsley; Mitchell, Mairi C; Wall, Eileen

2017-04-01

Data collected from an experimental Holstein-Friesian research herd were used to determine genetic and phenotypic parameters of innate and adaptive cellular immune-associated traits. Relationships between immune-associated traits and production, health, and fertility traits were also investigated. Repeated blood leukocyte records were analyzed in 546 cows for 9 cellular immune-associated traits, including percent T cell subsets, B cells, NK cells, and granulocytes. Variance components were estimated by univariate analysis. Heritability estimates were obtained for all 9 traits, the highest of which were observed in the T cell subsets percent CD4 + , percent CD8 + , CD4 + :CD8 + ratio, and percent NKp46 + cells (0.46, 0.41, 0.43 and 0.42, respectively), with between-individual variation accounting for 59 to 81% of total phenotypic variance. Associations between immune-associated traits and production, health, and fertility traits were investigated with bivariate analyses. Strong genetic correlations were observed between percent NKp46 + and stillbirth rate (0.61), and lameness episodes and percent CD8 + (-0.51). Regarding production traits, the strongest relationships were between CD4 + :CD8 + ratio and weight phenotypes (-0.52 for live weight; -0.51 for empty body weight). Associations between feed conversion traits and immune-associated traits were also observed. Our results provide evidence that cellular immune-associated traits are heritable and repeatable, and the noticeable variation between animals would permit selection for altered trait values, particularly in the case of the T cell subsets. The associations we observed between immune-associated, health, fertility, and production traits suggest that genetic selection for cellular immune-associated traits could provide a useful tool in improving animal health, fitness, and fertility. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY 2.0 license (http://creativecommons.org/licenses/by/2.0/).

PDT-based combinations in overcoming chemoresistance from stromal and heterotypic cellular communication (Conference Presentation)

NASA Astrophysics Data System (ADS)

Rizvi, Imran; Bulin, Anne-Laure; Anbil, Sriram R.; Briars, Emma A.; Vecchio, Daniela; Celli, Jonathan P.; Broekgaarden, Mans; Hasan, Tayyaba

2017-02-01

Targeting the molecular and cellular cues that influence treatment resistance in tumors is critical to effectively treating unresponsive populations of stubborn disease. The informed design of mechanism-based combinations is emerging as increasingly important to targeting resistance and improving the efficacy of conventional treatments, while minimizing toxicity. Photodynamic therapy (PDT) has been shown to synergize with conventional agents and to overcome the evasion pathways that cause resistance. Increasing evidence shows that PDT-based combinations cooperate mechanistically with, and improve the therapeutic index of, traditional chemotherapies. These and other findings emphasize the importance of including PDT as part of comprehensive treatment plans for cancer, particularly in complex disease sites. Identifying effective combinations requires a multi-faceted approach that includes the development of bioengineered cancer models and corresponding image analysis tools. The molecular and phenotypic basis of verteporfin-mediated PDT-based enhancement of chemotherapeutic efficacy and predictability in complex 3D models for ovarian cancer will be presented.

Cryopreservation has no effect on function of natural killer cells differentiated in vitro from umbilical cord blood CD34(+) cells.

PubMed

Domogala, Anna; Madrigal, J Alejandro; Saudemont, Aurore

2016-06-01

Natural killer (NK) cells offer the potential for a powerful cellular immunotherapy because they can target malignant cells without being direct effectors of graft-versus-host disease. We have previously shown that high numbers of functional NK cells can be differentiated in vitro from umbilical cord blood (CB) CD34(+) cells. To develop a readily available, off-the-shelf cellular product, it is essential that NK cells differentiated in vitro can be frozen and thawed while maintaining the same phenotype and functions. We evaluated the phenotype and function of fresh and frozen NK cells differentiated in vitro. We also assessed whether the concentration of NK cells at the time of freezing had an impact on cell viability. We found that cell concentration of NK cells at the time of freezing did not have an impact on their viability and on cell recovery post-thaw. Moreover, freezing of differentiated NK cells in vitro did not affect their phenotype, cytotoxicity and degranulation capacity toward K562 cells, cytokine production and proliferation. We are therefore able to generate large numbers of functional NK cells from CB CD34(+) cells that maintain the same phenotype and function post-cryopreservation, which will allow for multiple infusions of a highly cytotoxic NK cell product. Copyright © 2016 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Unique and shared functions of nuclear lamina LEM domain proteins in Drosophila.

PubMed

Barton, Lacy J; Wilmington, Shameika R; Martin, Melinda J; Skopec, Hannah M; Lovander, Kaylee E; Pinto, Belinda S; Geyer, Pamela K

2014-06-01

The nuclear lamina is an extensive protein network that contributes to nuclear structure and function. LEM domain (LAP2, emerin, MAN1 domain, LEM-D) proteins are components of the nuclear lamina, identified by a shared ∼45-amino-acid motif that binds Barrier-to-autointegration factor (BAF), a chromatin-interacting protein. Drosophila melanogaster has three nuclear lamina LEM-D proteins, named Otefin (Ote), Bocksbeutel (Bocks), and dMAN1. Although these LEM-D proteins are globally expressed, loss of either Ote or dMAN1 causes tissue-specific defects in adult flies that differ from each other. The reason for such distinct tissue-restricted defects is unknown. Here, we generated null alleles of bocks, finding that loss of Bocks causes no overt adult phenotypes. Next, we defined phenotypes associated with lem-d double mutants. Although the absence of individual LEM-D proteins does not affect viability, loss of any two proteins causes lethality. Mutant phenotypes displayed by lem-d double mutants differ from baf mutants, suggesting that BAF function is retained in animals with a single nuclear lamina LEM-D protein. Interestingly, lem-d double mutants displayed distinct developmental and cellular mutant phenotypes, suggesting that Drosophila LEM-D proteins have developmental functions that are differentially shared with other LEM-D family members. This conclusion is supported by studies showing that ectopically produced LEM-D proteins have distinct capacities to rescue the tissue-specific phenotypes found in single lem-d mutants. Our findings predict that cell-specific mutant phenotypes caused by loss of LEM-D proteins reflect both the constellation of LEM-D proteins within the nuclear lamina and the capacity of functional compensation of the remaining LEM-D proteins. Copyright © 2014 by the Genetics Society of America.

Unique and Shared Functions of Nuclear Lamina LEM Domain Proteins in Drosophila

PubMed Central

Barton, Lacy J.; Wilmington, Shameika R.; Martin, Melinda J.; Skopec, Hannah M.; Lovander, Kaylee E.; Pinto, Belinda S.; Geyer, Pamela K.

2014-01-01

The nuclear lamina is an extensive protein network that contributes to nuclear structure and function. LEM domain (LAP2, emerin, MAN1 domain, LEM-D) proteins are components of the nuclear lamina, identified by a shared ∼45-amino-acid motif that binds Barrier-to-autointegration factor (BAF), a chromatin-interacting protein. Drosophila melanogaster has three nuclear lamina LEM-D proteins, named Otefin (Ote), Bocksbeutel (Bocks), and dMAN1. Although these LEM-D proteins are globally expressed, loss of either Ote or dMAN1 causes tissue-specific defects in adult flies that differ from each other. The reason for such distinct tissue-restricted defects is unknown. Here, we generated null alleles of bocks, finding that loss of Bocks causes no overt adult phenotypes. Next, we defined phenotypes associated with lem-d double mutants. Although the absence of individual LEM-D proteins does not affect viability, loss of any two proteins causes lethality. Mutant phenotypes displayed by lem-d double mutants differ from baf mutants, suggesting that BAF function is retained in animals with a single nuclear lamina LEM-D protein. Interestingly, lem-d double mutants displayed distinct developmental and cellular mutant phenotypes, suggesting that Drosophila LEM-D proteins have developmental functions that are differentially shared with other LEM-D family members. This conclusion is supported by studies showing that ectopically produced LEM-D proteins have distinct capacities to rescue the tissue-specific phenotypes found in single lem-d mutants. Our findings predict that cell-specific mutant phenotypes caused by loss of LEM-D proteins reflect both the constellation of LEM-D proteins within the nuclear lamina and the capacity of functional compensation of the remaining LEM-D proteins. PMID:24700158

Recurrent postural vasovagal syncope: sympathetic nervous system phenotypes.

PubMed

Vaddadi, Gautam; Guo, Ling; Esler, Murray; Socratous, Florentia; Schlaich, Markus; Chopra, Reena; Eikelis, Nina; Lambert, Gavin; Trauer, Thomas; Lambert, Elisabeth

2011-10-01

The pathophysiology of vasovagal syncope is poorly understood, and the treatment usually ineffective. Our clinical experience is that patients with vasovagal syncope fall into 2 groups, based on their supine systolic blood pressure, which is either normal (>100 mm Hg) or low (70-100 mm Hg). We investigated neural circulatory control in these 2 phenotypes. Sympathetic nervous testing was at 3 levels: electric, measuring sympathetic nerve firing (microneurography); neurochemical, quantifying norepinephrine spillover to plasma; and cellular, with Western blot analysis of sympathetic nerve proteins. Testing was done during head-up tilt (HUT), simulating the gravitational stress of standing, in 18 healthy control subjects and 36 patients with vasovagal syncope, 15 with the low blood pressure phenotype and 21 with normal blood pressure. Microneurography and norepinephrine spillover increased significantly during HUT in healthy subjects. The microneurography response during HUT was normal in normal blood pressure and accentuated in low blood pressure phenotype (P=0.05). Norepinephrine spillover response was paradoxically subnormal during HUT in both patient groups (P=0.001), who thus exhibited disjunction between nerve firing and neurotransmitter release; this lowered norepinephrine availability, impairing the neural circulatory response. Subnormal norepinephrine spillover in low blood pressure phenotype was linked to low tyrosine hydroxylase (43.7% normal, P=0.001), rate-limiting in norepinephrine synthesis, and in normal blood pressure to increased levels of the norepinephrine transporter (135% normal, P=0.019), augmenting transmitter reuptake. Patients with recurrent vasovagal syncope, when phenotyped into 2 clinical groups based on their supine blood pressure, show unique sympathetic nervous system abnormalities. It is predicted that future therapy targeting the specific mechanisms identified in the present report should translate into more effective treatment.

Physiologically Shrinking the Solution Space of a Saccharomyces cerevisiae Genome-Scale Model Suggests the Role of the Metabolic Network in Shaping Gene Expression Noise.

PubMed

Chi, Baofang; Tao, Shiheng; Liu, Yanlin

2015-01-01

Sampling the solution space of genome-scale models is generally conducted to determine the feasible region for metabolic flux distribution. Because the region for actual metabolic states resides only in a small fraction of the entire space, it is necessary to shrink the solution space to improve the predictive power of a model. A common strategy is to constrain models by integrating extra datasets such as high-throughput datasets and C13-labeled flux datasets. However, studies refining these approaches by performing a meta-analysis of massive experimental metabolic flux measurements, which are closely linked to cellular phenotypes, are limited. In the present study, experimentally identified metabolic flux data from 96 published reports were systematically reviewed. Several strong associations among metabolic flux phenotypes were observed. These phenotype-phenotype associations at the flux level were quantified and integrated into a Saccharomyces cerevisiae genome-scale model as extra physiological constraints. By sampling the shrunken solution space of the model, the metabolic flux fluctuation level, which is an intrinsic trait of metabolic reactions determined by the network, was estimated and utilized to explore its relationship to gene expression noise. Although no correlation was observed in all enzyme-coding genes, a relationship between metabolic flux fluctuation and expression noise of genes associated with enzyme-dosage sensitive reactions was detected, suggesting that the metabolic network plays a role in shaping gene expression noise. Such correlation was mainly attributed to the genes corresponding to non-essential reactions, rather than essential ones. This was at least partially, due to regulations underlying the flux phenotype-phenotype associations. Altogether, this study proposes a new approach in shrinking the solution space of a genome-scale model, of which sampling provides new insights into gene expression noise.

Genetically Predicted Body Mass Index and Alzheimer’s Disease Related Phenotypes in Three Large Samples: Mendelian Randomization Analyses

PubMed Central

Mukherjee, Shubhabrata; Walter, Stefan; Kauwe, John S.K.; Saykin, Andrew J.; Bennett, David A.; Larson, Eric B.; Crane, Paul K.; Glymour, M. Maria

2015-01-01

Observational research shows that higher body mass index (BMI) increases Alzheimer’s disease (AD) risk, but it is unclear whether this association is causal. We applied genetic variants that predict BMI in Mendelian Randomization analyses, an approach that is not biased by reverse causation or confounding, to evaluate whether higher BMI increases AD risk. We evaluated individual level data from the AD Genetics Consortium (ADGC: 10,079 AD cases and 9,613 controls), the Health and Retirement Study (HRS: 8,403 participants with algorithm-predicted dementia status) and published associations from the Genetic and Environmental Risk for AD consortium (GERAD1: 3,177 AD cases and 7,277 controls). No evidence from individual SNPs or polygenic scores indicated BMI increased AD risk. Mendelian Randomization effect estimates per BMI point (95% confidence intervals) were: ADGC OR=0.95 (0.90, 1.01); HRS OR=1.00 (0.75, 1.32); GERAD1 OR=0.96 (0.87, 1.07). One subscore (cellular processes not otherwise specified) unexpectedly predicted lower AD risk. PMID:26079416

Connecting synthetic chemistry decisions to cell and genome biology using small-molecule phenotypic profiling

PubMed Central

Wagner, Bridget K.; Clemons, Paul A.

2009-01-01

Discovering small-molecule modulators for thousands of gene products requires multiple stages of biological testing, specificity evaluation, and chemical optimization. Many cellular profiling methods, including cellular sensitivity, gene-expression, and cellular imaging, have emerged as methods to assess the functional consequences of biological perturbations. Cellular profiling methods applied to small-molecule science provide opportunities to use complex phenotypic information to prioritize and optimize small-molecule structures simultaneously against multiple biological endpoints. As throughput increases and cost decreases for such technologies, we see an emerging paradigm of using more information earlier in probe- and drug-discovery efforts. Moreover, increasing access to public datasets makes possible the construction of “virtual” profiles of small-molecule performance, even when multiplexed measurements were not performed or when multidimensional profiling was not the original intent. We review some key conceptual advances in small-molecule phenotypic profiling, emphasizing connections to other information, such as protein-binding measurements, genetic perturbations, and cell states. We argue that to maximally leverage these measurements in probe and drug discovery requires a fundamental connection to synthetic chemistry, allowing the consequences of synthetic decisions to be described in terms of changes in small-molecule profiles. Mining such data in the context of chemical structure and synthesis strategies can inform decisions about chemistry procurement and library development, leading to optimal small-molecule screening collections. PMID:19825513

Perturbation Biology: Inferring Signaling Networks in Cellular Systems

PubMed Central

Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

2013-01-01

We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

Proteomics to assess the role of phenotypic plasticity in aquatic organisms exposed to pollution and global warming.

PubMed

Silvestre, Frédéric; Gillardin, Virginie; Dorts, Jennifer

2012-11-01

Nowadays, the unprecedented rates of anthropogenic changes in ecosystems suggest that organisms have to migrate to new distributional ranges or to adapt commensurately quickly to new conditions to avoid becoming extinct. Pollution and global warming are two of the most important threats aquatic organisms will have to face in the near future. If genetic changes in a population in response to natural selection are extensively studied, the role of acclimation through phenotypic plasticity (the property of a given genotype to produce different phenotypes in response to particular environmental conditions) in a species to deal with new environmental conditions remains largely unknown. Proteomics is the extensive study of the protein complement of a genome. It is dynamic and depends on the specific tissue, developmental stage, and environmental conditions. As the final product of gene expression, it is subjected to several regulatory steps from gene transcription to the functional protein. Consequently, there is a discrepancy between the abundance of mRNA and the abundance of the corresponding protein. Moreover, proteomics is closer to physiology and gives a more functional knowledge of the regulation of gene expression than does transcriptomics. The study of protein-expression profiles, however, gives a better portrayal of the cellular phenotype and is considered as a key link between the genotype and the organismal phenotype. Under new environmental conditions, we can observe a shift of the protein-expression pattern defining a new cellular phenotype that can possibly improve the fitness of the organism. It is now necessary to define a proteomic norm of reaction for organisms acclimating to environmental stressors. Its link to fitness will give new insights into how organisms can evolve in a changing environment. The proteomic literature bearing on chronic exposure to pollutants and on acclimation to heat stress in aquatic organisms, as well as potential application of proteomics in evolutionary issues, are outlined. While the transcriptome responses are commonly investigated, proteomics approaches now need to be intensified, with the new perspective of integrating the cellular phenotype with the organismal phenotype and with the mechanisms of the regulation of gene expression, such as epigenetics.

Genetic Variation in the Nuclear and Organellar Genomes Modulates Stochastic Variation in the Metabolome, Growth, and Defense

PubMed Central

Joseph, Bindu; Corwin, Jason A.; Kliebenstein, Daniel J.

2015-01-01

Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype. PMID:25569687

Genetic variation in the nuclear and organellar genomes modulates stochastic variation in the metabolome, growth, and defense.

PubMed

Joseph, Bindu; Corwin, Jason A; Kliebenstein, Daniel J

2015-01-01

Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype.

Antibacterial Drug Discovery: Some Assembly Required.

PubMed

Tommasi, Rubén; Iyer, Ramkumar; Miller, Alita A

2018-05-11

Our limited understanding of the molecular basis for compound entry into and efflux out of Gram-negative bacteria is now recognized as a key bottleneck for the rational discovery of novel antibacterial compounds. Traditional, large-scale biochemical or target-agnostic phenotypic antibacterial screening efforts have, as a result, not been very fruitful. A main driver of this knowledge gap has been the historical lack of predictive cellular assays, tools, and models that provide structure-activity relationships to inform optimization of compound accumulation. A variety of recent approaches has recently been described to address this conundrum. This Perspective explores these approaches and considers ways in which their integration could successfully redirect antibacterial drug discovery efforts.

Cellular Plasticity and Heterogeneity of EGFR Mutant Lung Cancer

DTIC Science & Technology

2015-09-01

AWARD NUMBER: W81XWH-14-1-0177 TITLE: Cellular Plasticity and Heterogeneity of EGFR Mutant Lung Cancer PRINCIPAL INVESTIGATOR: Katerina Politi...CONTRACT NUMBER Cellular Plasticity and Heterogeneity of EGFR Mutant Lung Cancer 5b. GRANT NUMBER W81XWH-14-1-0177 5c. PROGRAM ELEMENT NUMBER 6...Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Phenotypic changes have been observed in EGFR mutant lung cancers that become resistant to targeted

Prediction of gene-phenotype associations in humans, mice, and plants using phenologs.

PubMed

Woods, John O; Singh-Blom, Ulf Martin; Laurent, Jon M; McGary, Kriston L; Marcotte, Edward M

2013-06-21

Phenotypes and diseases may be related to seemingly dissimilar phenotypes in other species by means of the orthology of underlying genes. Such "orthologous phenotypes," or "phenologs," are examples of deep homology, and may be used to predict additional candidate disease genes. In this work, we develop an unsupervised algorithm for ranking phenolog-based candidate disease genes through the integration of predictions from the k nearest neighbor phenologs, comparing classifiers and weighting functions by cross-validation. We also improve upon the original method by extending the theory to paralogous phenotypes. Our algorithm makes use of additional phenotype data--from chicken, zebrafish, and E. coli, as well as new datasets for C. elegans--establishing that several types of annotations may be treated as phenotypes. We demonstrate the use of our algorithm to predict novel candidate genes for human atrial fibrillation (such as HRH2, ATP4A, ATP4B, and HOPX) and epilepsy (e.g., PAX6 and NKX2-1). We suggest gene candidates for pharmacologically-induced seizures in mouse, solely based on orthologous phenotypes from E. coli. We also explore the prediction of plant gene-phenotype associations, as for the Arabidopsis response to vernalization phenotype. We are able to rank gene predictions for a significant portion of the diseases in the Online Mendelian Inheritance in Man database. Additionally, our method suggests candidate genes for mammalian seizures based only on bacterial phenotypes and gene orthology. We demonstrate that phenotype information may come from diverse sources, including drug sensitivities, gene ontology biological processes, and in situ hybridization annotations. Finally, we offer testable candidates for a variety of human diseases, plant traits, and other classes of phenotypes across a wide array of species.

Novel in vitro and mathematical models for the prediction of chemical toxicity.

PubMed

Williams, Dominic P; Shipley, Rebecca; Ellis, Marianne J; Webb, Steve; Ward, John; Gardner, Iain; Creton, Stuart

2013-01-01

The focus of much scientific and medical research is directed towards understanding the disease process and defining therapeutic intervention strategies. The scientific basis of drug safety is very complex and currently remains poorly understood, despite the fact that adverse drug reactions (ADRs) are a major health concern and a serious impediment to development of new medicines. Toxicity issues account for ∼21% drug attrition during drug development and safety testing strategies require considerable animal use. Mechanistic relationships between drug plasma levels and molecular/cellular events that culminate in whole organ toxicity underpins development of novel safety assessment strategies. Current in vitro test systems are poorly predictive of toxicity of chemicals entering the systemic circulation, particularly to the liver. Such systems fall short because of (1) the physiological gap between cells currently used and human hepatocytes existing in their native state, (2) the lack of physiological integration with other cells/systems within organs, required to amplify the initial toxicological lesion into overt toxicity, (3) the inability to assess how low level cell damage induced by chemicals may develop into overt organ toxicity in a minority of patients, (4) lack of consideration of systemic effects. Reproduction of centrilobular and periportal hepatocyte phenotypes in in vitro culture is crucial for sensitive detection of cellular stress. Hepatocyte metabolism/phenotype is dependent on cell position along the liver lobule, with corresponding differences in exposure to substrate, oxygen and hormone gradients. Application of bioartificial liver (BAL) technology can encompass in vitro predictive toxicity testing with enhanced sensitivity and improved mechanistic understanding. Combining this technology with mechanistic mathematical models describing intracellular metabolism, fluid-flow, substrate, hormone and nutrient distribution provides the opportunity to design the BAL specifically to mimic the in vivo scenario. Such mathematical models enable theoretical hypothesis testing, will inform the design of in vitro experiments, and will enable both refinement and reduction of in vivo animal trials. In this way, development of novel mathematical modelling tools will help to focus and direct in vitro and in vivo research, and can be used as a framework for other areas of drug safety science.

Novel in vitro and mathematical models for the prediction of chemical toxicity

PubMed Central

Shipley, Rebecca; Ellis, Marianne J.; Webb, Steve; Ward, John; Gardner, Iain; Creton, Stuart

2013-01-01

The focus of much scientific and medical research is directed towards understanding the disease process and defining therapeutic intervention strategies. The scientific basis of drug safety is very complex and currently remains poorly understood, despite the fact that adverse drug reactions (ADRs) are a major health concern and a serious impediment to development of new medicines. Toxicity issues account for ∼21% drug attrition during drug development and safety testing strategies require considerable animal use. Mechanistic relationships between drug plasma levels and molecular/cellular events that culminate in whole organ toxicity underpins development of novel safety assessment strategies. Current in vitro test systems are poorly predictive of toxicity of chemicals entering the systemic circulation, particularly to the liver. Such systems fall short because of (1) the physiological gap between cells currently used and human hepatocytes existing in their native state, (2) the lack of physiological integration with other cells/systems within organs, required to amplify the initial toxicological lesion into overt toxicity, (3) the inability to assess how low level cell damage induced by chemicals may develop into overt organ toxicity in a minority of patients, (4) lack of consideration of systemic effects. Reproduction of centrilobular and periportal hepatocyte phenotypes in in vitro culture is crucial for sensitive detection of cellular stress. Hepatocyte metabolism/phenotype is dependent on cell position along the liver lobule, with corresponding differences in exposure to substrate, oxygen and hormone gradients. Application of bioartificial liver (BAL) technology can encompass in vitro predictive toxicity testing with enhanced sensitivity and improved mechanistic understanding. Combining this technology with mechanistic mathematical models describing intracellular metabolism, fluid-flow, substrate, hormone and nutrient distribution provides the opportunity to design the BAL specifically to mimic the in vivo scenario. Such mathematical models enable theoretical hypothesis testing, will inform the design of in vitro experiments, and will enable both refinement and reduction of in vivo animal trials. In this way, development of novel mathematical modelling tools will help to focus and direct in vitro and in vivo research, and can be used as a framework for other areas of drug safety science. PMID:26966512

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

PubMed

Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark

2016-01-01

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

Phycobilisome truncation causes widespread proteome changes in Synechocystis sp. PCC 6803

DOE PAGES

Liberton, Michelle; Chrisler, William B.; Nicora, Carrie D.; ...

2017-03-02

Here, cyanobacteria, such as Synechocystis sp. PCC 6803, utilize large antenna systems to optimize light harvesting and energy transfer to reaction centers. Understanding the structure and function of these complexes, particularly when altered, will help direct bio-design efforts to optimize biofuel production. Three specific phycobilisome (PBS) complex truncation mutants were studied, ranging from progressive truncation of phycocyanin rods in the CB and CK strains, to full removal of all phycocyanin and allophycocyanin cores in the PAL mutant. We applied comprehensive proteomic analyses to investigate both direct and downstream molecular systems implications of each truncation. Results showed that PBS truncation inmore » Synechocystis sp. PCC 6803 dramatically alters core cellular mechanisms beyond energy capture and electron transport, placing constraints upon cellular processes that dramatically altered phenotypes. This included primarily membrane associated functions and altered regulation of cellular resources (i.e., iron, nitrite/nitrate, bicarbonate). Additionally, each PBS truncation, though progressive in nature, exhibited unique phenotypes compare to WT, and hence we assert that in the current realm of extensive bioengineering and bio-design, there remains a continuing need to assess systems-wide protein based abundances to capture potential indirect phenotypic effects.« less

Phycobilisome truncation causes widespread proteome changes in Synechocystis sp. PCC 6803

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liberton, Michelle; Chrisler, William B.; Nicora, Carrie D.

Here, cyanobacteria, such as Synechocystis sp. PCC 6803, utilize large antenna systems to optimize light harvesting and energy transfer to reaction centers. Understanding the structure and function of these complexes, particularly when altered, will help direct bio-design efforts to optimize biofuel production. Three specific phycobilisome (PBS) complex truncation mutants were studied, ranging from progressive truncation of phycocyanin rods in the CB and CK strains, to full removal of all phycocyanin and allophycocyanin cores in the PAL mutant. We applied comprehensive proteomic analyses to investigate both direct and downstream molecular systems implications of each truncation. Results showed that PBS truncation inmore » Synechocystis sp. PCC 6803 dramatically alters core cellular mechanisms beyond energy capture and electron transport, placing constraints upon cellular processes that dramatically altered phenotypes. This included primarily membrane associated functions and altered regulation of cellular resources (i.e., iron, nitrite/nitrate, bicarbonate). Additionally, each PBS truncation, though progressive in nature, exhibited unique phenotypes compare to WT, and hence we assert that in the current realm of extensive bioengineering and bio-design, there remains a continuing need to assess systems-wide protein based abundances to capture potential indirect phenotypic effects.« less

Dynamics of phenotypic switching of bacterial cells with temporal fluctuations in pressure

NASA Astrophysics Data System (ADS)

Nepal, Sudip; Kumar, Pradeep

2018-05-01

Phenotypic switching is one of the mechanisms by which bacteria thrive in ever changing environmental conditions around them. Earlier studies have shown that the application of steady high hydrostatic pressure leads to stochastic switching of mesophilic bacteria from a cellular phenotype having a normal cell cycle to another phenotype lacking cell division. Here, we have studied the dynamics of this phenotypic switching with fluctuating periodic pressure using a set of experiments and a theoretical model. Our results suggest that the phenotypic switching rate from high-pressure phenotype to low-pressure phenotype in the reversible regime is larger as compared to the switching rate from low-pressure phenotype to high-pressure phenotype. Furthermore, we find that even though the cell division and elongation are presumably regulated by a large number of genes the underlying physics of the dynamics of stochastic switching at high pressure is captured reasonably well by a simple two-state model.

Humanity in a Dish: Population Genetics with iPSCs.

PubMed

Warren, Curtis R; Cowan, Chad A

2018-01-01

Induced pluripotent stem cells (iPSCs) are powerful tools for investigating the relationship between genotype and phenotype. Recent publications have described iPSC cohort studies of common genetic variants and their effects on gene expression and cellular phenotypes. These in vitro quantitative trait locus (QTL) studies are the first experiments in a new paradigm with great potential: iPSC-based functional population genetic studies. iPSC collections from large cohorts are currently under development to facilitate the next wave of these studies, which have the potential to discover the effects of common genetic variants on cellular phenotypes and to uncover the molecular basis of common genetic diseases. Here, we describe the recent advances in this developing field, and provide a road map for future in vitro functional population genetic studies and trial-in-a-dish experiments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Correlated mRNAs and miRNAs from co-expression and regulatory networks affect porcine muscle and finally meat properties.

PubMed

Ponsuksili, Siriluck; Du, Yang; Hadlich, Frieder; Siengdee, Puntita; Murani, Eduard; Schwerin, Manfred; Wimmers, Klaus

2013-08-05

Physiological processes aiding the conversion of muscle to meat involve many genes associated with muscle structure and metabolic processes. MicroRNAs regulate networks of genes to orchestrate cellular functions, in turn regulating phenotypes. We applied weighted gene co-expression network analysis to identify co-expression modules that correlated to meat quality phenotypes and were highly enriched for genes involved in glucose metabolism, response to wounding, mitochondrial ribosome, mitochondrion, and extracellular matrix. Negative correlation of miRNA with mRNA and target prediction were used to select transcripts out of the modules of trait-associated mRNAs to further identify those genes that are correlated with post mortem traits. Porcine muscle co-expression transcript networks that correlated to post mortem traits were identified. The integration of miRNA and mRNA expression analyses, as well as network analysis, enabled us to interpret the differentially-regulated genes from a systems perspective. Linking co-expression networks of transcripts and hierarchically organized pairs of miRNAs and mRNAs to meat properties yields new insight into several biological pathways underlying phenotype differences. These pathways may also be diagnostic for many myopathies, which are accompanied by deficient nutrient and oxygen supply of muscle fibers.

Polarity-defective mutants of Aspergillus nidulans.

PubMed

Osherov, N; Mathew, J; May, G S

2000-12-01

We have identified two polarity-defective (pod) mutants in Aspergillus nidulans from a collection of heat-sensitive lethal mutants. At restrictive temperature, these mutants are capable of nuclear division but are unable to establish polar hyphal growth. We cloned the two pod genes by complementation of their heat-sensitive lethal phenotypes. The libraries used to clone the pod genes are under the control of the bidirectional niaD and niiA promoters. Complementation of the pod mutants is dependent on growth on inducing medium. We show that rescue of the heat-sensitive phenotype on inducing media is independent of the orientation of the gene relative to the niaD or niiA promoters, demonstrating that the intergenic region between the niaD and the niiA genes functions as an orientation-independent enhancer and repressor that is capable of functioning over long distances. The products of the podG and the podH genes were identified as homologues of the alpha subunit of yeast mitochondrial phenylalanyl--tRNA synthetase and transcription factor IIF interacting component of the CTD phosphatase. Neither of these gene products would have been predicted to produce a pod mutant phenotype based on studies of cellular polarity mutants in other organisms. The implications of these results are discussed. Copyright 2000 Academic Press.

Loss of the interferon-γ-inducible regulatory immunity-related GTPase (IRG), Irgm1, causes activation of effector IRG proteins on lysosomes, damaging lysosomal function and predicting the dramatic susceptibility of Irgm1-deficient mice to infection.

PubMed

Maric-Biresev, Jelena; Hunn, Julia P; Krut, Oleg; Helms, J Bernd; Martens, Sascha; Howard, Jonathan C

2016-04-20

The interferon-γ (IFN-γ)-inducible immunity-related GTPase (IRG), Irgm1, plays an essential role in restraining activation of the IRG pathogen resistance system. However, the loss of Irgm1 in mice also causes a dramatic but unexplained susceptibility phenotype upon infection with a variety of pathogens, including many not normally controlled by the IRG system. This phenotype is associated with lymphopenia, hemopoietic collapse, and death of the mouse. We show that the three regulatory IRG proteins (GMS sub-family), including Irgm1, each of which localizes to distinct sets of endocellular membranes, play an important role during the cellular response to IFN-γ, each protecting specific membranes from off-target activation of effector IRG proteins (GKS sub-family). In the absence of Irgm1, which is localized mainly at lysosomal and Golgi membranes, activated GKS proteins load onto lysosomes, and are associated with reduced lysosomal acidity and failure to process autophagosomes. Another GMS protein, Irgm3, is localized to endoplasmic reticulum (ER) membranes; in the Irgm3-deficient mouse, activated GKS proteins are found at the ER. The Irgm3-deficient mouse does not show the drastic phenotype of the Irgm1 mouse. In the Irgm1/Irgm3 double knock-out mouse, activated GKS proteins associate with lipid droplets, but not with lysosomes, and the Irgm1/Irgm3(-/-) does not have the generalized immunodeficiency phenotype expected from its Irgm1 deficiency. The membrane targeting properties of the three GMS proteins to specific endocellular membranes prevent accumulation of activated GKS protein effectors on the corresponding membranes and thus enable GKS proteins to distinguish organellar cellular membranes from the membranes of pathogen vacuoles. Our data suggest that the generalized lymphomyeloid collapse that occurs in Irgm1(-/-) mice upon infection with a variety of pathogens may be due to lysosomal damage caused by off-target activation of GKS proteins on lysosomal membranes and consequent failure of autophagosomal processing.

Design of synthetic bacterial communities for predictable plant phenotypes

PubMed Central

Herrera Paredes, Sur; Gao, Tianxiang; Law, Theresa F.; Finkel, Omri M.; Mucyn, Tatiana; Teixeira, Paulo José Pereira Lima; Salas González, Isaí; Feltcher, Meghan E.; Powers, Matthew J.; Shank, Elizabeth A.; Jones, Corbin D.; Jojic, Vladimir; Dangl, Jeffery L.; Castrillo, Gabriel

2018-01-01

Specific members of complex microbiota can influence host phenotypes, depending on both the abiotic environment and the presence of other microorganisms. Therefore, it is challenging to define bacterial combinations that have predictable host phenotypic outputs. We demonstrate that plant–bacterium binary-association assays inform the design of small synthetic communities with predictable phenotypes in the host. Specifically, we constructed synthetic communities that modified phosphate accumulation in the shoot and induced phosphate starvation–responsive genes in a predictable fashion. We found that bacterial colonization of the plant is not a predictor of the plant phenotypes we analyzed. Finally, we demonstrated that characterizing a subset of all possible bacterial synthetic communities is sufficient to predict the outcome of untested bacterial consortia. Our results demonstrate that it is possible to infer causal relationships between microbiota membership and host phenotypes and to use these inferences to rationally design novel communities. PMID:29462153

The biological role of actinin-4 (ACTN4) in malignant phenotypes of cancer.

PubMed

Honda, Kazufumi

2015-01-01

Invasion and metastasis are malignant phenotypes in cancer that lead to patient death. Cell motility is involved in these processes. In 1998, we identified overexpression of the actin-bundling protein actinin-4 in several types of cancer. Protein expression of actinin-4 is closely associated with the invasive phenotypes of cancers. Actinin-4 is predominantly expressed in the cellular protrusions that stimulate the invasive phenotype in cancer cells and is essential for formation of cellular protrusions such as filopodia and lamellipodia. ACTN4 (gene name encoding actinin-4 protein) is located on human chromosome 19q. ACTN4 amplification is frequently observed in patients with carcinomas of the pancreas, ovary, lung, and salivary gland, and patients with ACTN4 amplifications have worse outcomes than patients without amplification. In addition, nuclear distribution of actinin-4 is frequently observed in small cell lung, breast, and ovarian cancer. Actinin-4, when expressed in cancer cell nuclei, functions as a transcriptional co-activator. In this review, we summarize recent developments regarding the biological roles of actinin-4 in cancer invasion.

Oxidative Stress, Bone Marrow Failure, and Genome Instability in Hematopoietic Stem Cells

PubMed Central

Richardson, Christine; Yan, Shan; Vestal, C. Greer

2015-01-01

Reactive oxygen species (ROS) can be generated by defective endogenous reduction of oxygen by cellular enzymes or in the mitochondrial respiratory pathway, as well as by exogenous exposure to UV or environmental damaging agents. Regulation of intracellular ROS levels is critical since increases above normal concentrations lead to oxidative stress and DNA damage. A growing body of evidence indicates that the inability to regulate high levels of ROS leading to alteration of cellular homeostasis or defective repair of ROS-induced damage lies at the root of diseases characterized by both neurodegeneration and bone marrow failure as well as cancer. That these diseases may be reflective of the dynamic ability of cells to respond to ROS through developmental stages and aging lies in the similarities between phenotypes at the cellular level. This review summarizes work linking the ability to regulate intracellular ROS to the hematopoietic stem cell phenotype, aging, and disease. PMID:25622253

Enhanced conversion of induced neuronal cells (iN cells) from human fibroblasts: utility in uncovering cellular deficits in mental illness-associated chromosomal abnormalities

PubMed Central

Passeri, Eleonora; Wilson, Ashley M.; Primerano, Amedeo; Kondo, Mari A.; Sengupta, Srona; Srivastava, Rupali; Koga, Minori; Obie, Cassandra; Zandi, Peter P.; Goes, Fernando S.; Valle, David; Rapoport, Judith L.; Sawa, Akira; Kano, Shin-ichi; Ishizuka, Koko

2016-01-01

The novel technology of induced neuronal cells (iN cells) is promising for translational neuroscience, as it allows the conversion of human fibroblasts into cells with postmitotic neuronal traits. However, a major technical barrier is the low conversion rate. To overcome this problem, we optimized the conversion media. Using our improved formulation, we studied how major mental illness-associated chromosomal abnormalities may impact the characteristics of iN cells. We demonstrated that our new iN cell culture protocol enabled us to obtain more precise measurement of neuronal cellular phenotypes than previous iN cell methods. Thus, this iN cell culture provides a platform to efficiently obtain possible cellular phenotypes caused by genetic differences, which can be more thoroughly studied in research using other human cell models such as induced pluripotent stem cells. PMID:26260244

GC[Formula: see text]NMF: A Novel Matrix Factorization Framework for Gene-Phenotype Association Prediction.

PubMed

Zhang, Yaogong; Liu, Jiahui; Liu, Xiaohu; Hong, Yuxiang; Fan, Xin; Huang, Yalou; Wang, Yuan; Xie, Maoqiang

2018-04-24

Gene-phenotype association prediction can be applied to reveal the inherited basis of human diseases and facilitate drug development. Gene-phenotype associations are related to complex biological processes and influenced by various factors, such as relationship between phenotypes and that among genes. While due to sparseness of curated gene-phenotype associations and lack of integrated analysis of the joint effect of multiple factors, existing applications are limited to prediction accuracy and potential gene-phenotype association detection. In this paper, we propose a novel method by exploiting weighted graph constraint learned from hierarchical structures of phenotype data and group prior information among genes by inheriting advantages of Non-negative Matrix Factorization (NMF), called Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization (GC[Formula: see text]NMF). Specifically, first we introduce the depth of parent-child relationships between two adjacent phenotypes in hierarchical phenotypic data as weighted graph constraint for a better phenotype understanding. Second, we utilize intra-group correlation among genes in a gene group as group constraint for gene understanding. Such information provides us with the intuition that genes in a group probably result in similar phenotypes. The model not only allows us to achieve a high-grade prediction performance, but also helps us to learn interpretable representation of genes and phenotypes simultaneously to facilitate future biological analysis. Experimental results on biological gene-phenotype association datasets of mouse and human demonstrate that GC[Formula: see text]NMF can obtain superior prediction accuracy and good understandability for biological explanation over other state-of-the-arts methods.

Comparative multi-omics systems analysis of Escherichia coli strains B and K-12.

PubMed

Yoon, Sung Ho; Han, Mee-Jung; Jeong, Haeyoung; Lee, Choong Hoon; Xia, Xiao-Xia; Lee, Dae-Hee; Shim, Ji Hoon; Lee, Sang Yup; Oh, Tae Kwang; Kim, Jihyun F

2012-05-25

Elucidation of a genotype-phenotype relationship is critical to understand an organism at the whole-system level. Here, we demonstrate that comparative analyses of multi-omics data combined with a computational modeling approach provide a framework for elucidating the phenotypic characteristics of organisms whose genomes are sequenced. We present a comprehensive analysis of genome-wide measurements incorporating multifaceted holistic data - genome, transcriptome, proteome, and phenome - to determine the differences between Escherichia coli B and K-12 strains. A genome-scale metabolic network of E. coli B was reconstructed and used to identify genetic bases of the phenotypes unique to B compared with K-12 through in silico complementation testing. This systems analysis revealed that E. coli B is well-suited for production of recombinant proteins due to a greater capacity for amino acid biosynthesis, fewer proteases, and lack of flagella. Furthermore, E. coli B has an additional type II secretion system and a different cell wall and outer membrane composition predicted to be more favorable for protein secretion. In contrast, E. coli K-12 showed a higher expression of heat shock genes and was less susceptible to certain stress conditions. This integrative systems approach provides a high-resolution system-wide view and insights into why two closely related strains of E. coli, B and K-12, manifest distinct phenotypes. Therefore, systematic understanding of cellular physiology and metabolism of the strains is essential not only to determine culture conditions but also to design recombinant hosts.

Comparative multi-omics systems analysis of Escherichia coli strains B and K-12

PubMed Central

2012-01-01

Background Elucidation of a genotype-phenotype relationship is critical to understand an organism at the whole-system level. Here, we demonstrate that comparative analyses of multi-omics data combined with a computational modeling approach provide a framework for elucidating the phenotypic characteristics of organisms whose genomes are sequenced. Results We present a comprehensive analysis of genome-wide measurements incorporating multifaceted holistic data - genome, transcriptome, proteome, and phenome - to determine the differences between Escherichia coli B and K-12 strains. A genome-scale metabolic network of E. coli B was reconstructed and used to identify genetic bases of the phenotypes unique to B compared with K-12 through in silico complementation testing. This systems analysis revealed that E. coli B is well-suited for production of recombinant proteins due to a greater capacity for amino acid biosynthesis, fewer proteases, and lack of flagella. Furthermore, E. coli B has an additional type II secretion system and a different cell wall and outer membrane composition predicted to be more favorable for protein secretion. In contrast, E. coli K-12 showed a higher expression of heat shock genes and was less susceptible to certain stress conditions. Conclusions This integrative systems approach provides a high-resolution system-wide view and insights into why two closely related strains of E. coli, B and K-12, manifest distinct phenotypes. Therefore, systematic understanding of cellular physiology and metabolism of the strains is essential not only to determine culture conditions but also to design recombinant hosts. PMID:22632713

Nonlinear ghost waves accelerate the progression of high-grade brain tumors

NASA Astrophysics Data System (ADS)

Pardo, Rosa; Martínez-González, Alicia; Pérez-García, Víctor M.

2016-10-01

We study a reduced continuous model describing the evolution of high grade gliomas in response to hypoxic events through the interplay of different cellular phenotypes. We show that hypoxic events, even when sporadic and/or limited in space, may have a crucial role on the acceleration of high grade gliomas growth. Our modeling approach is based on two cellular phenotypes. One of them is more migratory and a second one is more proliferative. Transitions between both phenotypes are driven by the local oxygen values, assumed in this simple model to be uniform. Surprisingly, even very localized in time hypoxia events leading to transient migratory populations have the potential to accelerate the tumor's invasion speed up to speeds close to those of the migratory phenotype. The high invasion speed persists for times much longer than the lifetime of the hypoxic event. Moreover, the phenomenon is observed both when the migratory cells form a persistent wave of cells located on the invasion front and when they form a evanescent "ghost" wave disappearing after a short time by decay to the more proliferative phenotype. Our findings are obtained through numerical simulations of the model equations both in 1D and higher dimensional scenarios. We also provide a deeper mathematical analysis of some aspects of the problem such as the conditions for the existence of persistent waves of cells with a more migratory phenotype.

PPARα siRNA–Treated Expression Profiles Uncover the Causal Sufficiency Network for Compound-Induced Liver Hypertrophy

PubMed Central

Dai, Xudong; Souza, Angus T. De; Dai, Hongyue; Lewis, David L; Lee, Chang-kyu; Spencer, Andy G; Herweijer, Hans; Hagstrom, Jim E; Linsley, Peter S; Bassett, Douglas E; Ulrich, Roger G; He, Yudong D

2007-01-01

Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor α (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARα-induced liver hypertrophy is supported by their ability to predict non-PPARα–induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events. PMID:17335344

Pathway-Enriched Gene Signature Associated with 53BP1 Response to PARP Inhibition in Triple-Negative Breast Cancer.

PubMed

Hassan, Saima; Esch, Amanda; Liby, Tiera; Gray, Joe W; Heiser, Laura M

2017-12-01

Effective treatment of patients with triple-negative (ER-negative, PR-negative, HER2-negative) breast cancer remains a challenge. Although PARP inhibitors are being evaluated in clinical trials, biomarkers are needed to identify patients who will most benefit from anti-PARP therapy. We determined the responses of three PARP inhibitors (veliparib, olaparib, and talazoparib) in a panel of eight triple-negative breast cancer cell lines. Therapeutic responses and cellular phenotypes were elucidated using high-content imaging and quantitative immunofluorescence to assess markers of DNA damage (53BP1) and apoptosis (cleaved PARP). We determined the pharmacodynamic changes as percentage of cells positive for 53BP1, mean number of 53BP1 foci per cell, and percentage of cells positive for cleaved PARP. Inspired by traditional dose-response measures of cell viability, an EC 50 value was calculated for each cellular phenotype and each PARP inhibitor. The EC 50 values for both 53BP1 metrics strongly correlated with IC 50 values for each PARP inhibitor. Pathway enrichment analysis identified a set of DNA repair and cell cycle-associated genes that were associated with 53BP1 response following PARP inhibition. The overall accuracy of our 63 gene set in predicting response to olaparib in seven breast cancer patient-derived xenograft tumors was 86%. In triple-negative breast cancer patients who had not received anti-PARP therapy, the predicted response rate of our gene signature was 45%. These results indicate that 53BP1 is a biomarker of response to anti-PARP therapy in the laboratory, and our DNA damage response gene signature may be used to identify patients who are most likely to respond to PARP inhibition. Mol Cancer Ther; 16(12); 2892-901. ©2017 AACR . ©2017 American Association for Cancer Research.

Induction of vascular endothelial phenotype and cellular proliferation from human cord blood stem cells cultured in simulated microgravity

NASA Astrophysics Data System (ADS)

Chiu, Brian; Z-M Wan, Jim; Abley, Doris; Akabutu, John

2005-05-01

Recent studies have demonstrated that stem cells derived from adult hematopoietic tissues are capable of trans-differentiation into non-hematopoietic cells, and that the culture in microgravity ( μg) may modulate the proliferation and differentiation. We investigated the application of μg to human umbilical cord blood stem cells (CBSC) in the induction of vascular endothelial phenotype expression and cellular proliferation. CD34+ mononuclear cells were isolated from waste human umbilical cord blood samples and cultured in simulated μg for 14 days. The cells were seeded in rotary wall vessels (RWV) with or without microcarrier beads (MCB) and vascular endothelial growth factor was added during culture. Controls consisted of culture in 1 G. The cell cultures in RWV were examined by inverted microscopy. Cell counts, endothelial cell and leukocyte markers performed by flow-cytometry and FACS scan were assayed at days 1, 4, 7 and at the termination of the experiments. Culture in RWV revealed significantly increased cellular proliferation with three-dimensional (3D) tissue-like aggregates. At day 4, CD34+ cells cultured in RWV bioreactor without MCB developed vascular tubular assemblies and exhibited endothelial phenotypic markers. These data suggest that CD34+ human umbilical cord blood progenitors are capable of trans-differentiation into vascular endothelial cell phenotype and assemble into 3D tissue structures. Culture of CBSC in simulated μg may be potentially beneficial in the fields of stem cell biology and somatic cell therapy.

Reduction of protein translation and activation of autophagy protect against PINK1 pathogenesis in Drosophila melanogaster.

PubMed

Liu, Song; Lu, Bingwei

2010-12-09

Mutations in PINK1 and Parkin cause familial, early onset Parkinson's disease. In Drosophila melanogaster, PINK1 and Parkin mutants show similar phenotypes, such as swollen and dysfunctional mitochondria, muscle degeneration, energy depletion, and dopaminergic (DA) neuron loss. We previously showed that PINK1 and Parkin genetically interact with the mitochondrial fusion/fission pathway, and PINK1 and Parkin were recently proposed to form a mitochondrial quality control system that involves mitophagy. However, the in vivo relationships among PINK1/Parkin function, mitochondrial fission/fusion, and autophagy remain unclear; and other cellular events critical for PINK1 pathogenesis remain to be identified. Here we show that PINK1 genetically interacted with the protein translation pathway. Enhanced translation through S6K activation significantly exacerbated PINK1 mutant phenotypes, whereas reduction of translation showed suppression. Induction of autophagy by Atg1 overexpression also rescued PINK1 mutant phenotypes, even in the presence of activated S6K. Downregulation of translation and activation of autophagy were already manifested in PINK1 mutant, suggesting that they represent compensatory cellular responses to mitochondrial dysfunction caused by PINK1 inactivation, presumably serving to conserve energy. Interestingly, the enhanced PINK1 mutant phenotype in the presence of activated S6K could be fully rescued by Parkin, apparently in an autophagy-independent manner. Our results reveal complex cellular responses to PINK1 inactivation and suggest novel therapeutic strategies through manipulation of the compensatory responses.

Reduction of Protein Translation and Activation of Autophagy Protect against PINK1 Pathogenesis in Drosophila melanogaster

PubMed Central

Liu, Song; Lu, Bingwei

2010-01-01

Mutations in PINK1 and Parkin cause familial, early onset Parkinson's disease. In Drosophila melanogaster, PINK1 and Parkin mutants show similar phenotypes, such as swollen and dysfunctional mitochondria, muscle degeneration, energy depletion, and dopaminergic (DA) neuron loss. We previously showed that PINK1 and Parkin genetically interact with the mitochondrial fusion/fission pathway, and PINK1 and Parkin were recently proposed to form a mitochondrial quality control system that involves mitophagy. However, the in vivo relationships among PINK1/Parkin function, mitochondrial fission/fusion, and autophagy remain unclear; and other cellular events critical for PINK1 pathogenesis remain to be identified. Here we show that PINK1 genetically interacted with the protein translation pathway. Enhanced translation through S6K activation significantly exacerbated PINK1 mutant phenotypes, whereas reduction of translation showed suppression. Induction of autophagy by Atg1 overexpression also rescued PINK1 mutant phenotypes, even in the presence of activated S6K. Downregulation of translation and activation of autophagy were already manifested in PINK1 mutant, suggesting that they represent compensatory cellular responses to mitochondrial dysfunction caused by PINK1 inactivation, presumably serving to conserve energy. Interestingly, the enhanced PINK1 mutant phenotype in the presence of activated S6K could be fully rescued by Parkin, apparently in an autophagy-independent manner. Our results reveal complex cellular responses to PINK1 inactivation and suggest novel therapeutic strategies through manipulation of the compensatory responses. PMID:21151574

Predicting Phenotypes from Genetic Crosses: A Mathematical Concept to Help Struggling Biology Students

ERIC Educational Resources Information Center

Baurhoo, Neerusha; Darwish, Shireef

2012-01-01

Predicting phenotypic outcomes from genetic crosses is often very difficult for biology students, especially those with learning disabilities. With our mathematical concept, struggling students in inclusive biology classrooms are now better equipped to solve genetic problems and predict phenotypes, because of improved understanding of dominance…

Potential Role of Lateral Gene Transfer in the Evolution of Biofilm Communities at the Lost City Hydrothermal Field and in the Earliest Stages of Cellular Evolution

NASA Astrophysics Data System (ADS)

Brazelton, W. J.; Mehta, M. P.; Baross, J. A.

2010-04-01

DNA sequencing and metabolic activity measurements show that lateral gene transfer promotes phenotypic diversity in single-species archaeal biofilms attached to hydrothermal chimneys. This system may be a useful model for early cellular evolution.

In-vitro analysis of Quantum Molecular Resonance effects on human mesenchymal stromal cells

PubMed Central

Sella, Sabrina; Adami, Valentina; Amati, Eliana; Bernardi, Martina; Chieregato, Katia; Gatto, Pamela; Menarin, Martina; Pozzato, Alessandro; Pozzato, Gianantonio; Astori, Giuseppe

2018-01-01

Electromagnetic fields play an essential role in cellular functions interfering with cellular pathways and tissue physiology. In this context, Quantum Molecular Resonance (QMR) produces waves with a specific form at high-frequencies (4–64 MHz) and low intensity through electric fields. We evaluated the effects of QMR stimulation on bone marrow derived mesenchymal stromal cells (MSC). MSC were treated with QMR for 10 minutes for 4 consecutive days for 2 weeks at different nominal powers. Cell morphology, phenotype, multilineage differentiation, viability and proliferation were investigated. QMR effects were further investigated by cDNA microarray validated by real-time PCR. After 1 and 2 weeks of QMR treatment morphology, phenotype and multilineage differentiation were maintained and no alteration of cellular viability and proliferation were observed between treated MSC samples and controls. cDNA microarray analysis evidenced more transcriptional changes on cells treated at 40 nominal power than 80 ones. The main enrichment lists belonged to development processes, regulation of phosphorylation, regulation of cellular pathways including metabolism, kinase activity and cellular organization. Real-time PCR confirmed significant increased expression of MMP1, PLAT and ARHGAP22 genes while A2M gene showed decreased expression in treated cells compared to controls. Interestingly, differentially regulated MMP1, PLAT and A2M genes are involved in the extracellular matrix (ECM) remodelling through the fibrinolytic system that is also implicated in embryogenesis, wound healing and angiogenesis. In our model QMR-treated MSC maintained unaltered cell phenotype, viability, proliferation and the ability to differentiate into bone, cartilage and adipose tissue. Microarray analysis may suggest an involvement of QMR treatment in angiogenesis and in tissue regeneration probably through ECM remodelling. PMID:29293552

Hypothesis: solid tumours behave as systemic metabolic dictators.

PubMed

Lee, Yang-Ming; Chang, Wei-Chun; Ma, Wen-Lung

2016-06-01

Current knowledge regarding mechanisms of carcinogenesis in human beings centres around the accumulation of genetic instability, amplified cellular signalling, disturbed cellular energy metabolism and microenvironmental regulation governed by complicated cell-cell interactions. In this article, we provide an alternative view of cancer biology. We propose that cancer behaves as a systemic dictator that interacts with tissues throughout the body to control their metabolism and eventually homeostasis. The mechanism of development of this endocrine organ-like tumour (EOLT) tissue might be the driving force for cancer progression. Here, we review the literature that led to the development of this hypothesis. The EOLT phenotype can be defined as a tumour that alters systemic homeostasis. The literature indicates that the EOLT phenotype is present throughout cancer progression. The feedback mechanism that governs the interaction between tumours and various organs is unknown. We believe that investigating the mechanism of EOLT development may advance the current knowledge of regulation within the tumour macroenvironment and consequently lead to new diagnostic methods and therapy. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Compound annotation with real time cellular activity profiles to improve drug discovery.

PubMed

Fang, Ye

2016-01-01

In the past decade, a range of innovative strategies have been developed to improve the productivity of pharmaceutical research and development. In particular, compound annotation, combined with informatics, has provided unprecedented opportunities for drug discovery. In this review, a literature search from 2000 to 2015 was conducted to provide an overview of the compound annotation approaches currently used in drug discovery. Based on this, a framework related to a compound annotation approach using real-time cellular activity profiles for probe, drug, and biology discovery is proposed. Compound annotation with chemical structure, drug-like properties, bioactivities, genome-wide effects, clinical phenotypes, and textural abstracts has received significant attention in early drug discovery. However, these annotations are mostly associated with endpoint results. Advances in assay techniques have made it possible to obtain real-time cellular activity profiles of drug molecules under different phenotypes, so it is possible to generate compound annotation with real-time cellular activity profiles. Combining compound annotation with informatics, such as similarity analysis, presents a good opportunity to improve the rate of discovery of novel drugs and probes, and enhance our understanding of the underlying biology.

SNP-associations and phenotype predictions from hundreds of microbial genomes without genome alignments.

PubMed

Hall, Barry G

2014-01-01

SNP-association studies are a starting point for identifying genes that may be responsible for specific phenotypes, such as disease traits. The vast bulk of tools for SNP-association studies are directed toward SNPs in the human genome, and I am unaware of any tools designed specifically for such studies in bacterial or viral genomes. The PPFS (Predict Phenotypes From SNPs) package described here is an add-on to kSNP , a program that can identify SNPs in a data set of hundreds of microbial genomes. PPFS identifies those SNPs that are non-randomly associated with a phenotype based on the χ² probability, then uses those diagnostic SNPs for two distinct, but related, purposes: (1) to predict the phenotypes of strains whose phenotypes are unknown, and (2) to identify those diagnostic SNPs that are most likely to be causally related to the phenotype. In the example illustrated here, from a set of 68 E. coli genomes, for 67 of which the pathogenicity phenotype was known, there were 418,500 SNPs. Using the phenotypes of 36 of those strains, PPFS identified 207 diagnostic SNPs. The diagnostic SNPs predicted the phenotypes of all of the genomes with 97% accuracy. It then identified 97 SNPs whose probability of being causally related to the pathogenic phenotype was >0.999. In a second example, from a set of 116 E. coli genome sequences, using the phenotypes of 65 strains PPFS identified 101 SNPs that predicted the source host (human or non-human) with 90% accuracy.

Evaluation of Cellular Phenotypes Implicated in Immunopathogenesis and Monitoring Immune Reconstitution Inflammatory Syndrome in HIV/Leprosy Cases

PubMed Central

Giacoia-Gripp, Carmem Beatriz Wagner; Sales, Anna Maria; Nery, José Augusto da Costa; Santos-Oliveira, Joanna Reis; de Oliveira, Ariane Leite; Sarno, Euzenir Nunes; Morgado, Mariza Gonçalves

2011-01-01

Background It is now evident that HAART-associated immunological improvement often leads to a variety of new clinical manifestations, collectively termed immune reconstitution inflammatory syndrome, or IRIS. This phenomenon has already been described in cases of HIV coinfection with Mycobacterium leprae, most of them belonging to the tuberculoid spectrum of leprosy disease, as observed in leprosy reversal reaction (RR). However, the events related to the pathogenesis of this association need to be clarified. This study investigated the immunological profile of HIV/leprosy patients, with special attention to the cellular activation status, to better understand the mechanisms related to IRIS/RR immunopathogenesis, identifying any potential biomarkers for IRIS/RR intercurrence. Methods/Principal Findings Eighty-five individuals were assessed in this study: HIV/leprosy and HIV-monoinfected patients, grouped according to HIV-viral load levels, leprosy patients without HIV coinfection, and healthy controls. Phenotypes were evaluated by flow cytometry for T cell subsets and immune differentiation/activation markers. As expected, absolute counts of the CD4+ and CD8+ T cells from the HIV-infected individuals changed in relation to those of the leprosy patients and controls. However, there were no significant differences among the groups, whether in the expression of cellular differentiation phenotypes or cellular activation, as reflected by the expression of CD38 and HLA-DR. Six HIV/leprosy patients identified as IRIS/RR were analyzed during IRIS/RR episodes and after prednisone treatment. These patients presented high cellular activation levels regarding the expression of CD38 in CD8+ cells T during IRIS/RR (median: 77,15%), dropping significantly (p<0,05) during post-IRIS/RR moments (median: 29,7%). Furthermore, an increase of cellular activation seems to occur prior to IRIS/RR. Conclusion/Significance These data suggest CD38 expression in CD8+ T cells interesting tool identifying HIV/leprosy individuals at risk for IRIS/RR. So, a comparative investigation to leprosy patients at RR should be conducted. PMID:22205964

Evaluation of cellular phenotypes implicated in immunopathogenesis and monitoring immune reconstitution inflammatory syndrome in HIV/leprosy cases.

PubMed

Giacoia-Gripp, Carmem Beatriz Wagner; Sales, Anna Maria; Nery, José Augusto da Costa; Santos-Oliveira, Joanna Reis; de Oliveira, Ariane Leite; Sarno, Euzenir Nunes; Morgado, Mariza Gonçalves

2011-01-01

It is now evident that HAART-associated immunological improvement often leads to a variety of new clinical manifestations, collectively termed immune reconstitution inflammatory syndrome, or IRIS. This phenomenon has already been described in cases of HIV coinfection with Mycobacterium leprae, most of them belonging to the tuberculoid spectrum of leprosy disease, as observed in leprosy reversal reaction (RR). However, the events related to the pathogenesis of this association need to be clarified. This study investigated the immunological profile of HIV/leprosy patients, with special attention to the cellular activation status, to better understand the mechanisms related to IRIS/RR immunopathogenesis, identifying any potential biomarkers for IRIS/RR intercurrence. Eighty-five individuals were assessed in this study: HIV/leprosy and HIV-monoinfected patients, grouped according to HIV-viral load levels, leprosy patients without HIV coinfection, and healthy controls. Phenotypes were evaluated by flow cytometry for T cell subsets and immune differentiation/activation markers. As expected, absolute counts of the CD4+ and CD8+ T cells from the HIV-infected individuals changed in relation to those of the leprosy patients and controls. However, there were no significant differences among the groups, whether in the expression of cellular differentiation phenotypes or cellular activation, as reflected by the expression of CD38 and HLA-DR. Six HIV/leprosy patients identified as IRIS/RR were analyzed during IRIS/RR episodes and after prednisone treatment. These patients presented high cellular activation levels regarding the expression of CD38 in CD8+ cells T during IRIS/RR (median: 77,15%), dropping significantly (p<0,05) during post-IRIS/RR moments (median: 29,7%). Furthermore, an increase of cellular activation seems to occur prior to IRIS/RR. These data suggest CD38 expression in CD8+ T cells interesting tool identifying HIV/leprosy individuals at risk for IRIS/RR. So, a comparative investigation to leprosy patients at RR should be conducted.

Fluorescence-based detection and quantification of features of cellular senescence.

PubMed

Cho, Sohee; Hwang, Eun Seong

2011-01-01

Cellular senescence is a spontaneous organismal defense mechanism against tumor progression which is raised upon the activation of oncoproteins or other cellular environmental stresses that must be circumvented for tumorigenesis to occur. It involves growth-arrest state of normal cells after a number of active divisions. There are multiple experimental routes that can drive cells into a state of senescence. Normal somatic cells and cancer cells enter a state of senescence upon overexpression of oncogenic Ras or Raf protein or by imposing certain kinds of stress such as cellular tumor suppressor function. Both flow cytometry and confocal imaging analysis techniques are very useful in quantitative analysis of cellular senescence phenomenon. They allow quantitative estimates of multiple different phenotypes expressed in multiple cell populations simultaneously. Here we review the various types of fluorescence methodologies including confocal imaging and flow cytometry that are frequently utilized to study a variety of senescence. First, we discuss key cell biological changes occurring during senescence and review the current understanding on the mechanisms of these changes with the goal of improving existing protocols and further developing new ones. Next, we list specific senescence phenotypes associated with each cellular trait along with the principles of their assay methods and the significance of the assay outcomes. We conclude by selecting appropriate references that demonstrate a typical example of each method. Copyright © 2011 Elsevier Inc. All rights reserved.

Life stress, glucocorticoid signaling, and the aging epigenome: Implications for aging-related diseases.

PubMed

Gassen, Nils C; Chrousos, George P; Binder, Elisabeth B; Zannas, Anthony S

2017-03-01

Life stress has been associated with accelerated cellular aging and increased risk for developing aging-related diseases; however, the underlying molecular mechanisms remain elusive. A highly relevant process that may underlie this association is epigenetic regulation. In this review, we build upon existing evidence to propose a model whereby exposure to life stress, in part via its effects on the hypothalamic-pituitary axis and the glucocorticoid signaling system, may alter the epigenetic landscape across the lifespan and, consequently, influence genomic regulation and function in ways that are conducive to the development of aging-related diseases. This model is supported by recent studies showing that life stressors and stress-related phenotypes can accelerate epigenetic aging, a measure that is based on DNA methylation prediction of chronological age and has been associated with several aging-related disease phenotypes. We discuss the implications of this model for the prevention and treatment of aging-related diseases, as well as the challenges and limitations of this line of research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Selecting the Best: Evolutionary Engineering of Chemical Production in Microbes.

PubMed

Shepelin, Denis; Hansen, Anne Sofie Lærke; Lennen, Rebecca; Luo, Hao; Herrgård, Markus J

2018-05-11

Microbial cell factories have proven to be an economical means of production for many bulk, specialty, and fine chemical products. However, we still lack both a holistic understanding of organism physiology and the ability to predictively tune enzyme activities in vivo, thus slowing down rational engineering of industrially relevant strains. An alternative concept to rational engineering is to use evolution as the driving force to select for desired changes, an approach often described as evolutionary engineering. In evolutionary engineering, in vivo selections for a desired phenotype are combined with either generation of spontaneous mutations or some form of targeted or random mutagenesis. Evolutionary engineering has been used to successfully engineer easily selectable phenotypes, such as utilization of a suboptimal nutrient source or tolerance to inhibitory substrates or products. In this review, we focus primarily on a more challenging problem-the use of evolutionary engineering for improving the production of chemicals in microbes directly. We describe recent developments in evolutionary engineering strategies, in general, and discuss, in detail, case studies where production of a chemical has been successfully achieved through evolutionary engineering by coupling production to cellular growth.

Laminins and cancer stem cells: Partners in crime?

PubMed

Qin, Yan; Rodin, Sergey; Simonson, Oscar E; Hollande, Frédéric

2017-08-01

As one of the predominant protein families within the extracellular matrix both structurally and functionally, laminins have been shown to be heavily involved in tumor progression and drug resistance. Laminins participate in key cellular events for tumor angiogenesis, cell invasion and metastasis development, including the regulation of epithelial-mesenchymal transition and basement membrane remodeling, which are tightly associated with the phenotypic characteristics of stem-like cells, particularly in the context of cancer. In addition, a great deal of studies and reports has highlighted the critical roles of laminins in modulating stem cell phenotype and differentiation, as part of the stem cell niche. Stemming from these discoveries a growing body of literature suggests that laminins may act as regulators of cancer stem cells, a tumor cell subpopulation that plays an instrumental role in long-term cancer maintenance, metastasis development and therapeutic resistance. The accumulating evidence in this emerging research area suggests that laminins represent potential therapeutic targets for anti-cancer treatments against cancer stem cells, and that they may be used as predictive and prognostic markers to inform clinical management and improve patient survival. Copyright © 2016 Elsevier Ltd. All rights reserved.

Convergence of Hippocampal Pathophysiology in Syngap+/- and Fmr1-/y Mice.

PubMed

Barnes, Stephanie A; Wijetunge, Lasani S; Jackson, Adam D; Katsanevaki, Danai; Osterweil, Emily K; Komiyama, Noboru H; Grant, Seth G N; Bear, Mark F; Nägerl, U Valentin; Kind, Peter C; Wyllie, David J A

2015-11-11

Previous studies have hypothesized that diverse genetic causes of intellectual disability (ID) and autism spectrum disorders (ASDs) converge on common cellular pathways. Testing this hypothesis requires detailed phenotypic analyses of animal models with genetic mutations that accurately reflect those seen in the human condition (i.e., have structural validity) and which produce phenotypes that mirror ID/ASDs (i.e., have face validity). We show that SynGAP haploinsufficiency, which causes ID with co-occurring ASD in humans, mimics and occludes the synaptic pathophysiology associated with deletion of the Fmr1 gene. Syngap(+/-) and Fmr1(-/y) mice show increases in basal protein synthesis and metabotropic glutamate receptor (mGluR)-dependent long-term depression that, unlike in their wild-type controls, is independent of new protein synthesis. Basal levels of phosphorylated ERK1/2 are also elevated in Syngap(+/-) hippocampal slices. Super-resolution microscopy reveals that Syngap(+/-) and Fmr1(-/y) mice show nanoscale alterations in dendritic spine morphology that predict an increase in biochemical compartmentalization. Finally, increased basal protein synthesis is rescued by negative regulators of the mGlu subtype 5 receptor and the Ras-ERK1/2 pathway, indicating that therapeutic interventions for fragile X syndrome may benefit patients with SYNGAP1 haploinsufficiency. As the genetics of intellectual disability (ID) and autism spectrum disorders (ASDs) are unraveled, a key issue is whether genetically divergent forms of these disorders converge on common biochemical/cellular pathways and hence may be amenable to common therapeutic interventions. This study compares the pathophysiology associated with the loss of fragile X mental retardation protein (FMRP) and haploinsufficiency of synaptic GTPase-activating protein (SynGAP), two prevalent monogenic forms of ID. We show that Syngap(+/-) mice phenocopy Fmr1(-/y) mice in the alterations in mGluR-dependent long-term depression, basal protein synthesis, and dendritic spine morphology. Deficits in basal protein synthesis can be rescued by pharmacological interventions that reduce the mGlu5 receptor-ERK1/2 signaling pathway, which also rescues the same deficit in Fmr1(-/y) mice. Our findings support the hypothesis that phenotypes associated with genetically diverse forms of ID/ASDs result from alterations in common cellular/biochemical pathways. Copyright © 2015 Barnes et al.

Macrophage phenotype is associated with disease severity in preterm infants with chronic lung disease.

PubMed

Prince, Lynne R; Maxwell, Nicola C; Gill, Sharonjit K; Dockrell, David H; Sabroe, Ian; McGreal, Eamon P; Kotecha, Sailesh; Whyte, Moira K

2014-01-01

The etiology of persistent lung inflammation in preterm infants with chronic lung disease of prematurity (CLD) is poorly characterized, hampering efforts to stratify prognosis and treatment. Airway macrophages are important innate immune cells with roles in both the induction and resolution of tissue inflammation. To investigate airway innate immune cellular phenotypes in preterm infants with respiratory distress syndrome (RDS) or CLD. Bronchoalveolar lavage (BAL) fluid was obtained from term and preterm infants requiring mechanical ventilation. BAL cells were phenotyped by flow cytometry. Preterm birth was associated with an increase in the proportion of non-classical CD14(+)/CD16(+) monocytes on the day of delivery (58.9 ± 5.8% of total mononuclear cells in preterm vs 33.0 ± 6.1% in term infants, p = 0.02). Infants with RDS were born with significantly more CD36(+) macrophages compared with the CLD group (70.3 ± 5.3% in RDS vs 37.6 ± 8.9% in control, p = 0.02). At day 3, infants born at a low gestational age are more likely to have greater numbers of CD14(+) mononuclear phagocytes in the airway (p = 0.03), but fewer of these cells are functionally polarized as assessed by HLA-DR (p = 0.05) or CD36 (p = 0.05) positivity, suggesting increased recruitment of monocytes or a failure to mature these cells in the lung. These findings suggest that macrophage polarization may be affected by gestational maturity, that more immature macrophage phenotypes may be associated with the progression of RDS to CLD and that phenotyping mononuclear cells in BAL could predict disease outcome.

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.

PubMed

Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees

2018-06-07

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

Open PHACTS computational protocols for in silico target validation of cellular phenotypic screens: knowing the knowns† †The authors declare no competing interests. ‡ ‡Electronic supplementary information (ESI) available: Pipeline Pilot protocols, xls file with the output of the Pipeline Pilot protocols, KNIME workflows, and supplementary figures showing the Pipeline Pilot protocols. See DOI: 10.1039/c6md00065g Click here for additional data file.

PubMed Central

Zdrazil, B.; Neefs, J.-M.; Van Vlijmen, H.; Herhaus, C.; Caracoti, A.; Brea, J.; Roibás, B.; Loza, M. I.; Queralt-Rosinach, N.; Furlong, L. I.; Gaulton, A.; Bartek, L.; Senger, S.; Chichester, C.; Engkvist, O.; Evelo, C. T.; Franklin, N. I.; Marren, D.; Ecker, G. F.

2016-01-01

Phenotypic screening is in a renaissance phase and is expected by many academic and industry leaders to accelerate the discovery of new drugs for new biology. Given that phenotypic screening is per definition target agnostic, the emphasis of in silico and in vitro follow-up work is on the exploration of possible molecular mechanisms and efficacy targets underlying the biological processes interrogated by the phenotypic screening experiments. Herein, we present six exemplar computational protocols for the interpretation of cellular phenotypic screens based on the integration of compound, target, pathway, and disease data established by the IMI Open PHACTS project. The protocols annotate phenotypic hit lists and allow follow-up experiments and mechanistic conclusions. The annotations included are from ChEMBL, ChEBI, GO, WikiPathways and DisGeNET. Also provided are protocols which select from the IUPHAR/BPS Guide to PHARMACOLOGY interaction file selective compounds to probe potential targets and a correlation robot which systematically aims to identify an overlap of active compounds in both the phenotypic as well as any kinase assay. The protocols are applied to a phenotypic pre-lamin A/C splicing assay selected from the ChEMBL database to illustrate the process. The computational protocols make use of the Open PHACTS API and data and are built within the Pipeline Pilot and KNIME workflow tools. PMID:27774140

Sod1 Loss Induces Intrinsic Superoxide Accumulation Leading to p53-Mediated Growth Arrest and Apoptosis

PubMed Central

Watanabe, Kenji; Shibuya, Shuichi; Koyama, Hirofumi; Ozawa, Yusuke; Toda, Toshihiko; Yokote, Koutaro; Shimizu, Takahiko

2013-01-01

Oxidative damages induced by a redox imbalance cause age-related changes in cells and tissues. Superoxide dismutase (SOD) enzymes play a major role in the antioxidant system and they also catalyze superoxide radicals (O2•−). Since the loss of cytoplasmic SOD (SOD1) resulted in aging-like phenotypes in several types of mouse tissue, SOD1 is essential for the maintenance of tissue homeostasis. To clarify the cellular function of SOD1, we investigated the cellular phenotypes of Sod1-deficient fibroblasts. We demonstrated that Sod1 deficiency impaired proliferation and induced apoptosis associated with O2•− accumulation in the cytoplasm and mitochondria in fibroblasts. Sod1 loss also decreased the mitochondrial membrane potential and led to DNA damage-mediated p53 activation. Antioxidant treatments effectively improved the cellular phenotypes through suppression of both intracellular O2•− accumulation and p53 activation in Sod1-deficient fibroblasts. In vivo experiments revealed that transdermal treatment with a vitamin C derivative significantly reversed the skin thinning commonly associated with the upregulated p53 action in the skin. Our findings revealed that intrinsic O2•− accumulation promoted p53-mediated growth arrest and apoptosis as well as mitochondrial disfunction in the fibroblasts. PMID:23708100

Loss of the Mechanotransducer Zyxin Promotes a Synthetic Phenotype of Vascular Smooth Muscle Cells

PubMed Central

Ghosh, Subhajit; Kollar, Branislav; Nahar, Taslima; Suresh Babu, Sahana; Wojtowicz, Agnieszka; Sticht, Carsten; Gretz, Norbert; Wagner, Andreas H; Korff, Thomas; Hecker, Markus

2015-01-01

Background Exposure of vascular smooth muscle cells (VSMCs) to excessive cyclic stretch such as in hypertension causes a shift in their phenotype. The focal adhesion protein zyxin can transduce such biomechanical stimuli to the nucleus of both endothelial cells and VSMCs, albeit with different thresholds and kinetics. However, there is no distinct vascular phenotype in young zyxin-deficient mice, possibly due to functional redundancy among other gene products belonging to the zyxin family. Analyzing zyxin function in VSMCs at the cellular level might thus offer a better mechanistic insight. We aimed to characterize zyxin-dependent changes in gene expression in VSMCs exposed to biomechanical stretch and define the functional role of zyxin in controlling the resultant VSMC phenotype. Methods and Results DNA microarray analysis was used to identify genes and pathways that were zyxin regulated in static and stretched human umbilical artery–derived and mouse aortic VSMCs. Zyxin-null VSMCs showed a remarkable shift to a growth-promoting, less apoptotic, promigratory and poorly contractile phenotype with ≈90% of the stretch-responsive genes being zyxin dependent. Interestingly, zyxin-null cells already seemed primed for such a synthetic phenotype, with mechanical stretch further accentuating it. This could be accounted for by higher RhoA activity and myocardin-related transcription factor-A mainly localized to the nucleus of zyxin-null VSMCs, and a condensed and localized accumulation of F-actin upon stretch. Conclusions At the cellular level, zyxin is a key regulator of stretch-induced gene expression. Loss of zyxin drives VSMCs toward a synthetic phenotype, a process further consolidated by exaggerated stretch. PMID:26071033

Accuracy of different bioinformatics methods in detecting antibiotic resistance and virulence factors from Staphylococcus aureus whole genome sequences.

PubMed

Mason, Amy; Foster, Dona; Bradley, Phelim; Golubchik, Tanya; Doumith, Michel; Gordon, N Claire; Pichon, Bruno; Iqbal, Zamin; Staves, Peter; Crook, Derrick; Walker, A Sarah; Kearns, Angela; Peto, Tim

2018-06-20

Background : In principle, whole genome sequencing (WGS) can predict phenotypic resistance directly from genotype, replacing laboratory-based tests. However, the contribution of different bioinformatics methods to genotype-phenotype discrepancies has not been systematically explored to date. Methods : We compared three WGS-based bioinformatics methods (Genefinder (read-based), Mykrobe (de Bruijn graph-based) and Typewriter (BLAST-based)) for predicting presence/absence of 83 different resistance determinants and virulence genes, and overall antimicrobial susceptibility, in 1379 Staphylococcus aureus isolates previously characterised by standard laboratory methods (disc diffusion, broth and/or agar dilution and PCR). Results : 99.5% (113830/114457) of individual resistance-determinant/virulence gene predictions were identical between all three methods, with only 627 (0.5%) discordant predictions, demonstrating high overall agreement (Fliess-Kappa=0.98, p<0.0001). Discrepancies when identified were in only one of the three methods for all genes except the cassette recombinase, ccrC(b ). Genotypic antimicrobial susceptibility prediction matched laboratory phenotype in 98.3% (14224/14464) cases (2720 (18.8%) resistant, 11504 (79.5%) susceptible). There was greater disagreement between the laboratory phenotypes and the combined genotypic predictions (97 (0.7%) phenotypically-susceptible but all bioinformatic methods reported resistance; 89 (0.6%) phenotypically-resistant, but all bioinformatics methods reported susceptible) than within the three bioinformatics methods (54 (0.4%) cases, 16 phenotypically-resistant, 38 phenotypically-susceptible). However, in 36/54 (67%), the consensus genotype matched the laboratory phenotype. Conclusions : In this study, the choice between these three specific bioinformatic methods to identify resistance-determinants or other genes in S. aureus did not prove critical, with all demonstrating high concordance with each other and phenotypic/molecular methods. However, each has some limitations and therefore consensus methods provide some assurance. Copyright © 2018 American Society for Microbiology.

Gamma Interferon Release Assays for Detection of Mycobacterium tuberculosis Infection

PubMed Central

Denkinger, Claudia M.; Kik, Sandra V.; Rangaka, Molebogeng X.; Zwerling, Alice; Oxlade, Olivia; Metcalfe, John Z.; Cattamanchi, Adithya; Dowdy, David W.; Dheda, Keertan; Banaei, Niaz

2014-01-01

SUMMARY Identification and treatment of latent tuberculosis infection (LTBI) can substantially reduce the risk of developing active disease. However, there is no diagnostic gold standard for LTBI. Two tests are available for identification of LTBI: the tuberculin skin test (TST) and the gamma interferon (IFN-γ) release assay (IGRA). Evidence suggests that both TST and IGRA are acceptable but imperfect tests. They represent indirect markers of Mycobacterium tuberculosis exposure and indicate a cellular immune response to M. tuberculosis. Neither test can accurately differentiate between LTBI and active TB, distinguish reactivation from reinfection, or resolve the various stages within the spectrum of M. tuberculosis infection. Both TST and IGRA have reduced sensitivity in immunocompromised patients and have low predictive value for progression to active TB. To maximize the positive predictive value of existing tests, LTBI screening should be reserved for those who are at sufficiently high risk of progressing to disease. Such high-risk individuals may be identifiable by using multivariable risk prediction models that incorporate test results with risk factors and using serial testing to resolve underlying phenotypes. In the longer term, basic research is necessary to identify highly predictive biomarkers. PMID:24396134

Phenotypic Characterization of Retinoic Acid Differentiated SH-SY5Y Cells by Transcriptional Profiling

PubMed Central

Korecka, Joanna A.; van Kesteren, Ronald E.; Blaas, Eva; Spitzer, Sonia O.; Kamstra, Jorke H.; Smit, August B.; Swaab, Dick F.; Verhaagen, Joost; Bossers, Koen

2013-01-01

Multiple genetic and environmental factors play a role in the development and progression of Parkinson’s disease (PD). The main neuropathological hallmark of PD is the degeneration of dopaminergic (DAergic) neurons in the substantia nigra pars compacta. To study genetic and molecular contributors to the disease process, there is a great need for readily accessible cells with prominent DAergic features that can be used for reproducible in vitro cellular screening. Here, we investigated the molecular phenotype of retinoic acid (RA) differentiated SH-SY5Y cells using genome wide transcriptional profiling combined with gene ontology, transcription factor and molecular pathway analysis. We demonstrated that RA induces a general neuronal differentiation program in SH-SY5Y cells and that these cells develop a predominantly mature DAergic-like neurotransmitter phenotype. This phenotype is characterized by increased dopamine levels together with a substantial suppression of other neurotransmitter phenotypes, such as those for noradrenaline, acetylcholine, glutamate, serotonin and histamine. In addition, we show that RA differentiated SH-SY5Y cells express the dopamine and noradrenalin neurotransmitter transporters that are responsible for uptake of MPP(+), a well known DAergic cell toxicant. MPP(+) treatment alters mitochondrial activity according to its proposed cytotoxic effect in DAergic neurons. Taken together, RA differentiated SH-SY5Y cells have a DAergic-like phenotype, and provide a good cellular screening tool to find novel genes or compounds that affect cytotoxic processes that are associated with PD. PMID:23724009

MOLECULAR CLASSIFICATION OF OUTCOMES FROM DENGUE VIRUS -3 INFECTIONS

PubMed Central

Brasier, Allan R.; Zhao, Yingxin; Wiktorowicz, John E.; Spratt, Heidi M.; Nascimento, Eduardo J. M.; Cordeiro, Marli T.; Soman, Kizhake V.; Ju, Hyunsu; Recinos, Adrian; Stafford, Susan; Wu, Zheng; Marques, Ernesto T.A.; Vasilakis, Nikos

2015-01-01

Objectives Dengue virus (DENV) infection is a significant risk to over a third of the human population that causes a wide spectrum of illness, ranging from sub-clinical disease to intermediate syndrome of vascular complications called Dengue Fever Complicated (DFC) and severe, dengue hemorrhagic fever (DHF). Methods for discriminating outcomes will impact clinical trials and understanding disease pathophysiology. Study Design We integrated a proteomics discovery pipeline with a heuristics to develop a molecular classifier to identify an intermediate phenotype of DENV-3 infectious outcome. Results 121 differentially expressed proteins were identified in plasma from DHF vs dengue fever (DF), and informative candidates were selected using nonparametric statistics. These were combined with markers that measure complement activation, acute phase response, cellular leak, granulocyte differentiation and viral load. From this, we applied quantitative proteomics to select a 15 member panel of proteins that accurately predicted DF, DHF, and DFC using a Random Forest Classifier. The classifier primarily relied on acute phase (A2M), complement (CFD), platelet counts and cellular leak (TPM4) to produce an 86% accuracy of prediction with an area under the receiver operating curve of >0.9 for DHF and DFC vs DF. Conclusions Integrating discovery and heuristic approaches to sample distinct pathophysiological processes is a powerful approach in infectious disease. Early detection of intermediate outcomes of DENV-3 will speed clinical trials evaluating vaccines or drug interventions. PMID:25728087

Molecular classification of outcomes from dengue virus -3 infections.

PubMed

Brasier, Allan R; Zhao, Yingxin; Wiktorowicz, John E; Spratt, Heidi M; Nascimento, Eduardo J M; Cordeiro, Marli T; Soman, Kizhake V; Ju, Hyunsu; Recinos, Adrian; Stafford, Susan; Wu, Zheng; Marques, Ernesto T A; Vasilakis, Nikos

2015-03-01

Dengue virus (DENV) infection is a significant risk to over a third of the human population that causes a wide spectrum of illness, ranging from sub-clinical disease to intermediate syndrome of vascular complications called dengue fever complicated (DFC) and severe, dengue hemorrhagic fever (DHF). Methods for discriminating outcomes will impact clinical trials and understanding disease pathophysiology. We integrated a proteomics discovery pipeline with a heuristics approach to develop a molecular classifier to identify an intermediate phenotype of DENV-3 infectious outcome. 121 differentially expressed proteins were identified in plasma from DHF vs dengue fever (DF), and informative candidates were selected using nonparametric statistics. These were combined with markers that measure complement activation, acute phase response, cellular leak, granulocyte differentiation and viral load. From this, we applied quantitative proteomics to select a 15 member panel of proteins that accurately predicted DF, DHF, and DFC using a random forest classifier. The classifier primarily relied on acute phase (A2M), complement (CFD), platelet counts and cellular leak (TPM4) to produce an 86% accuracy of prediction with an area under the receiver operating curve of >0.9 for DHF and DFC vs DF. Integrating discovery and heuristic approaches to sample distinct pathophysiological processes is a powerful approach in infectious disease. Early detection of intermediate outcomes of DENV-3 will speed clinical trials evaluating vaccines or drug interventions. Copyright © 2015 Elsevier B.V. All rights reserved.

A Kinetic Model for Calcium Dynamics in RAW 264.7 Cells: 1. Mechanisms, Parameters, and Subpopulational Variability

PubMed Central

Maurya, Mano Ram; Subramaniam, Shankar

2007-01-01

Calcium (Ca2+) is an important second messenger and has been the subject of numerous experimental measurements and mechanistic studies in intracellular signaling. Calcium profile can also serve as a useful cellular phenotype. Kinetic models of calcium dynamics provide quantitative insights into the calcium signaling networks. We report here the development of a complex kinetic model for calcium dynamics in RAW 264.7 cells stimulated by the C5a ligand. The model is developed using the vast number of measurements of in vivo calcium dynamics carried out in the Alliance for Cellular Signaling (AfCS) Laboratories. Ligand binding, phospholipase C-β (PLC-β) activation, inositol 1,4,5-trisphosphate (IP3) receptor (IP3R) dynamics, and calcium exchange with mitochondria and extracellular matrix have all been incorporated into the model. The experimental data include data from both native and knockdown cell lines. Subpopulational variability in measurements is addressed by allowing nonkinetic parameters to vary across datasets. The model predicts temporal response of Ca2+ concentration for various doses of C5a under different initial conditions. The optimized parameters for IP3R dynamics are in agreement with the legacy data. Further, the half-maximal effect concentration of C5a and the predicted dose response are comparable to those seen in AfCS measurements. Sensitivity analysis shows that the model is robust to parametric perturbations. PMID:17483174

Cellular microparticle and thrombogram phenotypes in the Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) Study: correlation with coagulopathy

PubMed Central

Matijevic, Nena; Wang, Yao-Wei W.; Wade, Charles E.; Holcomb, John B.; Cotton, Bryan A.; Schreiber, Martin A.; Muskat, Peter; Fox, Erin E.; del Junco, Deborah J.; Cardenas, Jessica C.; Rahbar, Mohammad H.; Cohen, Mitchell Jay

2014-01-01

Background Trauma-induced coagulopathy following severe injury is associated with increased bleeding and mortality. Injury may result in alteration of cellular phenotypes and release of cell-derived microparticles (MP). Circulating MPs are procoagulant and support thrombin generation (TG) and clotting. We evaluated MP and TG phenotypes in severely injured patients at admission, in relation to coagulopathy and bleeding. Methods As part of the Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study, research blood samples were obtained from 180 trauma patients requiring transfusions at 5 participating centers. Twenty five healthy controls and 40 minimally injured patients were analyzed for comparisons. Laboratory criteria for coagulopathy was activated partial thromboplastin time (APTT) ≥35 sec. Samples were analyzed by Calibrated Automated Thrombogram to assess TG, and by flow cytometry for MP phenotypes [platelet (PMP), erythrocyte (RMP), leukocyte (LMP), endothelial (EMP), tissue factor (TFMP), and Annexin V positive (AVMP)]. Results 21.7% of patients were coagulopathic with the median (IQR) APTT of 44 sec (37, 53), and an Injury Severity Score of 26 (17, 35). Compared to controls, patients had elevated EMP, RMP, LMP, and TFMP (all p<0.001), and enhanced TG (p<0.0001). However, coagulopathic PROMMTT patients had significantly lower PMP, TFMP, and TG, higher substantial bleeding, and higher mortality compared to non-coagulopathic patients (all p<0.001). Conclusions Cellular activation and enhanced TG are predominant after trauma and independent of injury severity. Coagulopathy was associated with lower thrombin peak and rate compared to non-coagulopathic patients, while lower levels of TF-bearing PMPs were associated with substantial bleeding. PMID:25086657

Neurophysiology of Drosophila Models of Parkinson's Disease

PubMed Central

West, Ryan J. H.; Furmston, Rebecca; Williams, Charles A. C.; Elliott, Christopher J. H.

2015-01-01

We provide an insight into the role Drosophila has played in elucidating neurophysiological perturbations associated with Parkinson's disease- (PD-) related genes. Synaptic signalling deficits are observed in motor, central, and sensory systems. Given the neurological impact of disease causing mutations within these same genes in humans the phenotypes observed in fly are of significant interest. As such we observe four unique opportunities provided by fly nervous system models of Parkinson's disease. Firstly, Drosophila models are instrumental in exploring the mechanisms of neurodegeneration, with several PD-related mutations eliciting related phenotypes including sensitivity to energy supply and vesicular deformities. These are leading to the identification of plausible cellular mechanisms, which may be specific to (dopaminergic) neurons and synapses rather than general cellular phenotypes. Secondly, models show noncell autonomous signalling within the nervous system, offering the opportunity to develop our understanding of the way pathogenic signalling propagates, resembling Braak's scheme of spreading pathology in PD. Thirdly, the models link physiological deficits to changes in synaptic structure. While the structure-function relationship is complex, the genetic tractability of Drosophila offers the chance to separate fundamental changes from downstream consequences. Finally, the strong neuronal phenotypes permit relevant first in vivo drug testing. PMID:25960916

Semiautomated confocal imaging of fungal pathogenesis on plants: Microscopic analysis of macroscopic specimens.

PubMed

Minker, Katharine R; Biedrzycki, Meredith L; Kolagunda, Abhishek; Rhein, Stephen; Perina, Fabiano J; Jacobs, Samuel S; Moore, Michael; Jamann, Tiffany M; Yang, Qin; Nelson, Rebecca; Balint-Kurti, Peter; Kambhamettu, Chandra; Wisser, Randall J; Caplan, Jeffrey L

2018-02-01

The study of phenotypic variation in plant pathogenesis provides fundamental information about the nature of disease resistance. Cellular mechanisms that alter pathogenesis can be elucidated with confocal microscopy; however, systematic phenotyping platforms-from sample processing to image analysis-to investigate this do not exist. We have developed a platform for 3D phenotyping of cellular features underlying variation in disease development by fluorescence-specific resolution of host and pathogen interactions across time (4D). A confocal microscopy phenotyping platform compatible with different maize-fungal pathosystems (fungi: Setosphaeria turcica, Cochliobolus heterostrophus, and Cercospora zeae-maydis) was developed. Protocols and techniques were standardized for sample fixation, optical clearing, species-specific combinatorial fluorescence staining, multisample imaging, and image processing for investigation at the macroscale. The sample preparation methods presented here overcome challenges to fluorescence imaging such as specimen thickness and topography as well as physiological characteristics of the samples such as tissue autofluorescence and presence of cuticle. The resulting imaging techniques provide interesting qualitative and quantitative information not possible with conventional light or electron 2D imaging. Microsc. Res. Tech., 81:141-152, 2018. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The antiproliferative aspects of mortalin (review).

PubMed

Wadhwa, R; Mitsui, Y; Ide, T; Kaul, S

1995-07-01

Cellular mortal and immortal phenotypes as defined by the limited and the infinite capacity of cells to divide are the characteristics of normal and cancerous cells in culture. Numerous strategies that have been employed to understand the mechanism(s) of normal as well as tumor cell growth have revealed that these are genetically controlled, however, the genes and the synchronized regulations remain largely undefined so far. The present report reviews the identification of mortalin, a novel member of murine hsp70 family of proteins, as a gene involved in pathways that determine divisional phenotype of cells in vitro. In the present study, the anti-proliferative activity of mortalin is demonstrated also in human skin fibroblasts (TIG-73PD) by microinjection of anti-mortalin antibody. Furthermore, studies on the mortalin immunofluorescence patterns in SV40-immortalized pre-crisis and post-crisis human cells have revealed that the change in the intracellular distribution of mortalin is linked to the change in the divisional phenotype of cells. Thus, the studies to resolve the molecular basis of association of the cytosolically distributed form of mortalin with cellular mortal phenotype would be important in understanding of the mechanism(s) that determine replicative potential of cells in culture.

Editor's Highlight: Development of an In vitro Assay Measuring Uterine-Specific Estrogenic Responses for Use in Chemical Safety Assessment.

PubMed

Miller, Michelle M; Alyea, Rebecca A; LeSommer, Caroline; Doheny, Daniel L; Rowley, Sean M; Childs, Kristin M; Balbuena, Pergentino; Ross, Susan M; Dong, Jian; Sun, Bin; Andersen, Melvin A; Clewell, Rebecca A

2016-11-01

A toxicity pathway approach was taken to develop an in vitro assay using human uterine epithelial adenocarcinoma (Ishikawa) cells as a replacement for measuring an in vivo uterotrophic response to estrogens. The Ishikawa cell was determined to be fit for the purpose of recapitulating in vivo uterine response by verifying fidelity of the biological pathway components and the dose-response predictions to women of child-bearing age. Expression of the suite of estrogen receptors that control uterine proliferation (ERα66, ERα46, ERα36, ERβ, G-protein coupled estrogen receptor (GPER)) were confirmed across passages and treatment conditions. Phenotypic responses to ethinyl estradiol (EE) from transcriptional activation of ER-mediated genes, to ALP enzyme induction and cellular proliferation occurred at concentrations consistent with estrogenic activity in adult women (low picomolar). To confirm utility of this model to predict concentration-response for uterine proliferation with xenobiotics, we tested the concentration-response for compounds with known uterine estrogenic activity in humans and compared the results to assays from the ToxCast and Tox21 suite of estrogen assays. The Ishikawa proliferation assay was consistent with in vivo responses and was a more sensitive measure of uterine response. Because this assay was constructed by first mapping the key molecular events for cellular response, and then ensuring that the assay incorporated these events, the resulting cellular assay should be a reliable tool for identifying estrogenic compounds and may provide improved quantitation of chemical concentration response for in vitro-based safety assessments. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology.

A platform for high-throughput bioenergy production phenotype characterization in single cells

PubMed Central

Kelbauskas, Laimonas; Glenn, Honor; Anderson, Clifford; Messner, Jacob; Lee, Kristen B.; Song, Ganquan; Houkal, Jeff; Su, Fengyu; Zhang, Liqiang; Tian, Yanqing; Wang, Hong; Bussey, Kimberly; Johnson, Roger H.; Meldrum, Deirdre R.

2017-01-01

Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell survival and recurrence, however, remains poorly understood due to ensemble averaging of the current approaches. We present a technology platform for performing oxygen consumption and extracellular acidification measurements of several hundreds to 1,000 individual cells per assay, while offering simultaneous analysis of cellular communication effects on the energy production phenotype. The platform comprises two major components: a tandem optical sensor for combined oxygen and pH detection, and a microwell device for isolation and analysis of single and few cells in hermetically sealed sub-nanoliter chambers. Our approach revealed subpopulations of cells with aberrant energy production profiles and enables determination of cellular response variability to electron transfer chain inhibitors and ion uncouplers. PMID:28349963

Microenvironmental independence associated with tumor progression.

PubMed

Anderson, Alexander R A; Hassanein, Mohamed; Branch, Kevin M; Lu, Jenny; Lobdell, Nichole A; Maier, Julie; Basanta, David; Weidow, Brandy; Narasanna, Archana; Arteaga, Carlos L; Reynolds, Albert B; Quaranta, Vito; Estrada, Lourdes; Weaver, Alissa M

2009-11-15

Tumor-microenvironment interactions are increasingly recognized to influence tumor progression. To understand the competitive dynamics of tumor cells in diverse microenvironments, we experimentally parameterized a hybrid discrete-continuum mathematical model with phenotypic trait data from a set of related mammary cell lines with normal, transformed, or tumorigenic properties. Surprisingly, in a resource-rich microenvironment, with few limitations on proliferation or migration, transformed (but not tumorigenic) cells were most successful and outcompeted other cell types in heterogeneous tumor simulations. Conversely, constrained microenvironments with limitations on space and/or growth factors gave a selective advantage to phenotypes derived from tumorigenic cell lines. Analysis of the relative performance of each phenotype in constrained versus unconstrained microenvironments revealed that, although all cell types grew more slowly in resource-constrained microenvironments, the most aggressive cells were least affected by microenvironmental constraints. A game theory model testing the relationship between microenvironment resource availability and competitive cellular dynamics supports the concept that microenvironmental independence is an advantageous cellular trait in resource-limited microenvironments.

Mechanism of hard-nanomaterial clearance by the liver.

PubMed

Tsoi, Kim M; MacParland, Sonya A; Ma, Xue-Zhong; Spetzler, Vinzent N; Echeverri, Juan; Ouyang, Ben; Fadel, Saleh M; Sykes, Edward A; Goldaracena, Nicolas; Kaths, Johann M; Conneely, John B; Alman, Benjamin A; Selzner, Markus; Ostrowski, Mario A; Adeyi, Oyedele A; Zilman, Anton; McGilvray, Ian D; Chan, Warren C W

2016-11-01

The liver and spleen are major biological barriers to translating nanomedicines because they sequester the majority of administered nanomaterials and prevent delivery to diseased tissue. Here we examined the blood clearance mechanism of administered hard nanomaterials in relation to blood flow dynamics, organ microarchitecture and cellular phenotype. We found that nanomaterial velocity reduces 1,000-fold as they enter and traverse the liver, leading to 7.5 times more nanomaterial interaction with hepatic cells relative to peripheral cells. In the liver, Kupffer cells (84.8 ± 6.4%), hepatic B cells (81.5 ± 9.3%) and liver sinusoidal endothelial cells (64.6 ± 13.7%) interacted with administered PEGylated quantum dots, but splenic macrophages took up less material (25.4 ± 10.1%) due to differences in phenotype. The uptake patterns were similar for two other nanomaterial types and five different surface chemistries. Potential new strategies to overcome off-target nanomaterial accumulation may involve manipulating intra-organ flow dynamics and modulating the cellular phenotype to alter hepatic cell interactions.

Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping.

PubMed

Treweek, Jennifer B; Chan, Ken Y; Flytzanis, Nicholas C; Yang, Bin; Deverman, Benjamin E; Greenbaum, Alon; Lignell, Antti; Xiao, Cheng; Cai, Long; Ladinsky, Mark S; Bjorkman, Pamela J; Fowlkes, Charless C; Gradinaru, Viviana

2015-11-01

To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue fixation-embedding, detergent-clearing and staining protocols that can be used to transform excised organs and whole organisms into optically transparent samples within 1-2 weeks without compromising their cellular architecture or endogenous fluorescence. PACT (passive CLARITY technique) and PARS (perfusion-assisted agent release in situ) use tissue-hydrogel hybrids to stabilize tissue biomolecules during selective lipid extraction, resulting in enhanced clearing efficiency and sample integrity. Furthermore, the macromolecule permeability of PACT- and PARS-processed tissue hybrids supports the diffusion of immunolabels throughout intact tissue, whereas RIMS (refractive index matching solution) grants high-resolution imaging at depth by further reducing light scattering in cleared and uncleared samples alike. These methods are adaptable to difficult-to-image tissues, such as bone (PACT-deCAL), and to magnified single-cell visualization (ePACT). Together, these protocols and solutions enable phenotyping of subcellular components and tracing cellular connectivity in intact biological networks.

The successes and future prospects of the linear antisense RNA amplification methodology.

PubMed

Li, Jifen; Eberwine, James

2018-05-01

It has been over a quarter of a century since the introduction of the linear RNA amplification methodology known as antisense RNA (aRNA) amplification. Whereas most molecular biology techniques are rapidly replaced owing to the fast-moving nature of development in the field, the aRNA procedure has become a base that can be built upon through varied uses of the technology. The technique was originally developed to assess RNA populations from small amounts of starting material, including single cells, but over time its use has evolved to include the detection of various cellular entities such as proteins, RNA-binding-protein-associated cargoes, and genomic DNA. In this Perspective we detail the linear aRNA amplification procedure and its use in assessing various components of a cell's chemical phenotype. This procedure is particularly useful in efforts to multiplex the simultaneous detection of various cellular processes. These efforts are necessary to identify the quantitative chemical phenotype of cells that underlies cellular function.

Patient-derived iPSCs show premature neural differentiation and neuron-type specific phenotypes relevant to neurodevelopment

PubMed Central

Yeh, Erika; Dao, Dang Q.; Wu, Zhi Y.; Kandalam, Santoshi M.; Camacho, Federico M.; Tom, Curtis; Zhang, Wandong; Krencik, Robert; Rauen, Katherine A.; Ullian, Erik M.; Weiss, Lauren A.

2017-01-01

Ras/MAPK pathway signaling is a major participant in neurodevelopment, and evidence suggests that BRAF, a key Ras signal mediator, influences human behavior. We studied the role of the mutation BRAFQ257R, the most common cause of cardiofaciocutaneous syndrome (CFC), in an induced pluripotent stem cell (iPSC)-derived model of human neurodevelopment. In iPSC-derived neuronal cultures from CFC subjects, we observed decreased p-AKT and p-ERK1/2 compared to controls, as well as a depleted neural progenitor pool and rapid neuronal maturation. Pharmacological PI3K/AKT pathway manipulation recapitulated cellular phenotypes in control cells and attenuated them in CFC cells. CFC cultures displayed altered cellular subtype ratios and increased intrinsic excitability. Moreover, in CFC cells, Ras/MAPK pathway activation and morphological abnormalities exhibited cell subtype-specific differences. Our results highlight the importance of exploring specific cellular subtypes and of using iPSC models to reveal relevant human-specific neurodevelopmental events. PMID:29158583

Lytic and latent antigens of the human gammaherpesviruses Kaposi's sarcoma-associated herpesvirus and Epstein-Barr virus induce T-cell responses with similar functional properties and memory phenotypes.

PubMed

Bihl, Florian; Narayan, Murli; Chisholm, John V; Henry, Leah M; Suscovich, Todd J; Brown, Elizabeth E; Welzel, Tania M; Kaufmann, Daniel E; Zaman, Tauheed M; Dollard, Sheila; Martin, Jeff N; Wang, Fred; Scadden, David T; Kaye, Kenneth M; Brander, Christian

2007-05-01

The cellular immunity against Kaposi's sarcoma-associated herpesvirus (KSHV) is poorly characterized and has not been compared to T-cell responses against other human herpesviruses. Here, novel and dominant targets of KSHV-specific cellular immunity are identified and compared to T cells specific for lytic and latent antigens in a second human gammaherpesvirus, Epstein-Barr virus. The data identify a novel HLA-B57- and HLA-B58-restricted epitope in the Orf57 protein and show consistently close parallels in immune phenotypes and functional response patterns between cells targeting lytic or latent KSHV- and EBV-encoded antigens, suggesting common mechanisms in the induction of these responses.

A method to measure cellular adhesion utilizing a polymer micro-cantilever

NASA Astrophysics Data System (ADS)

Gaitas, Angelo; Malhotra, Ricky; Pienta, Kenneth

2013-09-01

In the present study we engineered a micro-machined polyimide cantilever with an embedded sensing element to investigate cellular adhesion, in terms of its relative ability to stick to a cross-linker, 3,3'-dithiobis[sulfosuccinimidylpropionate], coated on the cantilever surface. To achieve this objective, we investigated adhesive properties of three human prostate cancer cell lines, namely, a bone metastasis derived human prostate cancer cell line (PC3), a brain metastasis derived human prostate cancer cell line (DU145), and a subclone of PC3 (PC3-EMT14). We found that PC3-EMT14, which displays a mesenchymal phenotype, has the least adhesion compared to PC3 and DU145, which exhibit an epithelial phenotype.

Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems

PubMed Central

Zhao, Jiangsan; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A.; Nakhforoosh, Alireza

2017-01-01

Abstract Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. PMID:28168270

The impact of cellular senescence in skin ageing: A notion of mosaic and therapeutic strategies.

PubMed

Toutfaire, Marie; Bauwens, Emilie; Debacq-Chainiaux, Florence

2017-10-15

Cellular senescence is now recognized as one of the nine hallmarks of ageing. Recent data show the involvement of senescent cells in tissue ageing and some age-related diseases. Skin represents an ideal model for the study of ageing. Indeed, skin ageing varies between individuals depending on their chronological age but also on their exposure to various exogenous factors (mainly ultraviolet rays). If senescence traits can be detected with ageing in the skin, the senescent phenotype varies among the various skin cell types. Moreover, the origin of cellular senescence in the skin is still unknown, and multiple origins are possible. This reflects the mosaic of skin ageing. Senescent cells can interfere with their microenvironment, either via the direct secretion of factors (the senescence-associated secretory phenotype) or via other methods of communication, such as extracellular vesicles. Knowledge regarding the impact of cellular senescence on skin ageing could be integrated into dermatology research, especially to limit the appearance of senescent cells after photo(chemo)therapy or in age-related skin diseases. Therapeutic approaches include the clearance of senescent cells via the use of senolytics or via the cooperation with the immune system. Copyright © 2017 Elsevier Inc. All rights reserved.

Engineering microbial phenotypes through rewiring of genetic networks

PubMed Central

Rodrigues, Rui T.L.; Lee, Sangjin; Haines, Matthew

2017-01-01

Abstract The ability to program cellular behaviour is a major goal of synthetic biology, with applications in health, agriculture and chemicals production. Despite efforts to build ‘orthogonal’ systems, interactions between engineered genetic circuits and the endogenous regulatory network of a host cell can have a significant impact on desired functionality. We have developed a strategy to rewire the endogenous cellular regulatory network of yeast to enhance compatibility with synthetic protein and metabolite production. We found that introducing novel connections in the cellular regulatory network enabled us to increase the production of heterologous proteins and metabolites. This strategy is demonstrated in yeast strains that show significantly enhanced heterologous protein expression and higher titers of terpenoid production. Specifically, we found that the addition of transcriptional regulation between free radical induced signalling and nitrogen regulation provided robust improvement of protein production. Assessment of rewired networks revealed the importance of key topological features such as high betweenness centrality. The generation of rewired transcriptional networks, selection for specific phenotypes, and analysis of resulting library members is a powerful tool for engineering cellular behavior and may enable improved integration of heterologous protein and metabolite pathways. PMID:28369627

Genomic agonism and phenotypic antagonism between estrogen and progesterone receptors in breast cancer

PubMed Central

Singhal, Hari; Greene, Marianne E.; Tarulli, Gerard; Zarnke, Allison L.; Bourgo, Ryan J.; Laine, Muriel; Chang, Ya-Fang; Ma, Shihong; Dembo, Anna G.; Raj, Ganesh V.; Hickey, Theresa E.; Tilley, Wayne D.; Greene, Geoffrey L.

2016-01-01

The functional role of progesterone receptor (PR) and its impact on estrogen signaling in breast cancer remain controversial. In primary ER+ (estrogen receptor–positive)/PR+ human tumors, we report that PR reprograms estrogen signaling as a genomic agonist and a phenotypic antagonist. In isolation, estrogen and progestin act as genomic agonists by regulating the expression of common target genes in similar directions, but at different levels. Similarly, in isolation, progestin is also a weak phenotypic agonist of estrogen action. However, in the presence of both hormones, progestin behaves as a phenotypic estrogen antagonist. PR remodels nucleosomes to noncompetitively redirect ER genomic binding to distal enhancers enriched for BRCA1 binding motifs and sites that link PR and ER/PR complexes. When both hormones are present, progestin modulates estrogen action, such that responsive transcriptomes, cellular processes, and ER/PR recruitment to genomic sites correlate with those observed with PR alone, but not ER alone. Despite this overall correlation, the transcriptome patterns modulated by dual treatment are sufficiently different from individual treatments, such that antagonism of oncogenic processes is both predicted and observed. Combination therapies using the selective PR modulator/antagonist (SPRM) CDB4124 in combination with tamoxifen elicited 70% cytotoxic tumor regression of T47D tumor xenografts, whereas individual therapies inhibited tumor growth without net regression. Our findings demonstrate that PR redirects ER chromatin binding to antagonize estrogen signaling and that SPRMs can potentiate responses to antiestrogens, suggesting that cotargeting of ER and PR in ER+/PR+ breast cancers should be explored. PMID:27386569

Antibiotic efficacy is linked to bacterial cellular respiration

PubMed Central

Lobritz, Michael A.; Belenky, Peter; Porter, Caroline B. M.; Gutierrez, Arnaud; Yang, Jason H.; Schwarz, Eric G.; Dwyer, Daniel J.; Khalil, Ahmad S.; Collins, James J.

2015-01-01

Bacteriostatic and bactericidal antibiotic treatments result in two fundamentally different phenotypic outcomes—the inhibition of bacterial growth or, alternatively, cell death. Most antibiotics inhibit processes that are major consumers of cellular energy output, suggesting that antibiotic treatment may have important downstream consequences on bacterial metabolism. We hypothesized that the specific metabolic effects of bacteriostatic and bactericidal antibiotics contribute to their overall efficacy. We leveraged the opposing phenotypes of bacteriostatic and bactericidal drugs in combination to investigate their activity. Growth inhibition from bacteriostatic antibiotics was associated with suppressed cellular respiration whereas cell death from most bactericidal antibiotics was associated with accelerated respiration. In combination, suppression of cellular respiration by the bacteriostatic antibiotic was the dominant effect, blocking bactericidal killing. Global metabolic profiling of bacteriostatic antibiotic treatment revealed that accumulation of metabolites involved in specific drug target activity was linked to the buildup of energy metabolites that feed the electron transport chain. Inhibition of cellular respiration by knockout of the cytochrome oxidases was sufficient to attenuate bactericidal lethality whereas acceleration of basal respiration by genetically uncoupling ATP synthesis from electron transport resulted in potentiation of the killing effect of bactericidal antibiotics. This work identifies a link between antibiotic-induced cellular respiration and bactericidal lethality and demonstrates that bactericidal activity can be arrested by attenuated respiration and potentiated by accelerated respiration. Our data collectively show that antibiotics perturb the metabolic state of bacteria and that the metabolic state of bacteria impacts antibiotic efficacy. PMID:26100898

Thermodynamic Constraints Improve Metabolic Networks.

PubMed

Krumholz, Elias W; Libourel, Igor G L

2017-08-08

In pursuit of establishing a realistic metabolic phenotypic space, the reversibility of reactions is thermodynamically constrained in modern metabolic networks. The reversibility constraints follow from heuristic thermodynamic poise approximations that take anticipated cellular metabolite concentration ranges into account. Because constraints reduce the feasible space, draft metabolic network reconstructions may need more extensive reconciliation, and a larger number of genes may become essential. Notwithstanding ubiquitous application, the effect of reversibility constraints on the predictive capabilities of metabolic networks has not been investigated in detail. Instead, work has focused on the implementation and validation of the thermodynamic poise calculation itself. With the advance of fast linear programming-based network reconciliation, the effects of reversibility constraints on network reconciliation and gene essentiality predictions have become feasible and are the subject of this study. Networks with thermodynamically informed reversibility constraints outperformed gene essentiality predictions compared to networks that were constrained with randomly shuffled constraints. Unconstrained networks predicted gene essentiality as accurately as thermodynamically constrained networks, but predicted substantially fewer essential genes. Networks that were reconciled with sequence similarity data and strongly enforced reversibility constraints outperformed all other networks. We conclude that metabolic network analysis confirmed the validity of the thermodynamic constraints, and that thermodynamic poise information is actionable during network reconciliation. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

The cancer glycocalyx mechanically primes integrin-mediated growth and survival

PubMed Central

Paszek, Matthew J.; DuFort, Christopher C.; Rossier, Olivier; Bainer, Russell; Mouw, Janna K.; Godula, Kamil; Hudak, Jason E.; Lakins, Jonathon N.; Wijekoon, Amanda C.; Cassereau, Luke; Rubashkin, Matthew G.; Magbanua, Mark J.; Thorn, Kurt S.; Davidson, Michael W.; Rugo, Hope S.; Park, John W.; Hammer, Daniel A.; Giannone, Grégory; Bertozzi, Carolyn R.; Weaver, Valerie M.

2015-01-01

Malignancy is associated with altered expression of glycans and glycoproteins that contribute to the cellular glycocalyx. We constructed a glycoprotein expression signature, which revealed that metastatic tumours upregulate expression of bulky glycoproteins. A computational model predicted that these glycoproteins would influence transmembrane receptor spatial organization and function. We tested this prediction by investigating whether bulky glycoproteins in the glycocalyx promote a tumour phenotype in human cells by increasing integrin adhesion and signalling. Our data revealed that a bulky glycocalyx facilitates integrin clustering by funnelling active integrins into adhesions and altering integrin state by applying tension to matrix-bound integrins, independent of actomyosin contractility. Expression of large tumour-associated glycoproteins in non-transformed mammary cells promoted focal adhesion assembly and facilitated integrin-dependent growth factor signalling to support cell growth and survival. Clinical studies revealed that large glycoproteins are abundantly expressed on circulating tumour cells from patients with advanced disease. Thus, a bulky glycocalyx is a feature of tumour cells that could foster metastasis by mechanically enhancing cell-surface receptor function. PMID:25030168

Phenome-driven disease genetics prediction toward drug discovery.

PubMed

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-06-15

Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e(-4)) and 81.3% (P < e(-12)) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn's disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn's disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn's disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. nlp. edu/public/data/DMN © The Author 2015. Published by Oxford University Press.

Childhood asthma-predictive phenotype.

PubMed

Guilbert, Theresa W; Mauger, David T; Lemanske, Robert F

2014-01-01

Wheezing is a fairly common symptom in early childhood, but only some of these toddlers will experience continued wheezing symptoms in later childhood. The definition of the asthma-predictive phenotype is in children with frequent, recurrent wheezing in early life who have risk factors associated with the continuation of asthma symptoms in later life. Several asthma-predictive phenotypes were developed retrospectively based on large, longitudinal cohort studies; however, it can be difficult to differentiate these phenotypes clinically as the expression of symptoms, and risk factors can change with time. Genetic, environmental, developmental, and host factors and their interactions may contribute to the development, severity, and persistence of the asthma phenotype over time. Key characteristics that distinguish the childhood asthma-predictive phenotype include the following: male sex; a history of wheezing, with lower respiratory tract infections; history of parental asthma; history of atopic dermatitis; eosinophilia; early sensitization to food or aeroallergens; or lower lung function in early life. Copyright © 2014 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Discovering Pediatric Asthma Phenotypes on the Basis of Response to Controller Medication Using Machine Learning.

PubMed

Ross, Mindy K; Yoon, Jinsung; van der Schaar, Auke; van der Schaar, Mihaela

2018-01-01

Pediatric asthma has variable underlying inflammation and symptom control. Approaches to addressing this heterogeneity, such as clustering methods to find phenotypes and predict outcomes, have been investigated. However, clustering based on the relationship between treatment and clinical outcome has not been performed, and machine learning approaches for long-term outcome prediction in pediatric asthma have not been studied in depth. Our objectives were to use our novel machine learning algorithm, predictor pursuit (PP), to discover pediatric asthma phenotypes on the basis of asthma control in response to controller medications, to predict longitudinal asthma control among children with asthma, and to identify features associated with asthma control within each discovered pediatric phenotype. We applied PP to the Childhood Asthma Management Program study data (n = 1,019) to discover phenotypes on the basis of asthma control between assigned controller therapy groups (budesonide vs. nedocromil). We confirmed PP's ability to discover phenotypes using the Asthma Clinical Research Network/Childhood Asthma Research and Education network data. We next predicted children's asthma control over time and compared PP's performance with that of traditional prediction methods. Last, we identified clinical features most correlated with asthma control in the discovered phenotypes. Four phenotypes were discovered in both datasets: allergic not obese (A + /O - ), obese not allergic (A - /O + ), allergic and obese (A + /O + ), and not allergic not obese (A - /O - ). Of the children with well-controlled asthma in the Childhood Asthma Management Program dataset, we found more nonobese children treated with budesonide than with nedocromil (P = 0.015) and more obese children treated with nedocromil than with budesonide (P = 0.008). Within the obese group, more A + /O + children's asthma was well controlled with nedocromil than with budesonide (P = 0.022) or with placebo (P = 0.011). The PP algorithm performed significantly better (P < 0.001) than traditional machine learning algorithms for both short- and long-term asthma control prediction. Asthma control and bronchodilator response were the features most predictive of short-term asthma control, regardless of type of controller medication or phenotype. Bronchodilator response and serum eosinophils were the most predictive features of asthma control, regardless of type of controller medication or phenotype. Advanced statistical machine learning approaches can be powerful tools for discovery of phenotypes based on treatment response and can aid in asthma control prediction in complex medical conditions such as asthma.

Predicting biomaterial property-dendritic cell phenotype relationships from the multivariate analysis of responses to polymethacrylates

PubMed Central

Kou, Peng Meng; Pallassana, Narayanan; Bowden, Rebeca; Cunningham, Barry; Joy, Abraham; Kohn, Joachim; Babensee, Julia E.

2011-01-01

Dendritic cells (DCs) play a critical role in orchestrating the host responses to a wide variety of foreign antigens and are essential in maintaining immune tolerance. Distinct biomaterials have been shown to differentially affect the phenotype of DCs, which suggested that biomaterials may be used to modulate immune response towards the biologic component in combination products. The elucidation of biomaterial property-DC phenotype relationships is expected to inform rational design of immuno-modulatory biomaterials. In this study, DC response to a set of 12 polymethacrylates (pMAs) was assessed in terms of surface marker expression and cytokine profile. Principal component analysis (PCA) determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an immature DC phenotype. Partial square linear regression, a multivariate modeling approach, was implemented and successfully predicted biomaterial-induced DC phenotype in terms of surface marker expression from biomaterial properties with R2prediction = 0.76. Furthermore, prediction of DC phenotype was effective based on only theoretical chemical composition of the bulk polymers with R2prediction = 0.80. These results demonstrated that immune cell response can be predicted from biomaterial properties, and computational models will expedite future biomaterial design and selection. PMID:22136715

Correspondence between the CYP2C19 and CYP3A4 genotypes with the inferred metabolizer phenotype by omeprazole administration in Mexican healthy children.

PubMed

Favela-Mendoza, A F; Martínez-Cortes, G; Romero-Prado, M M; Romero-Tejeda, E M; Islas-Carbajal, M C; Sosa-Macias, M; Lares-Asseff, I; Rangel-Villalobos, H

2018-05-07

CYP2C19 genotypes presumably allow the prediction of the metabolizer phenotypes: poor (PMs), extensive (EMs) and ultra-rapid (UMs). However, evidence from previous studies regarding this predictive power is unclear, which is important because the benefits expected by healthcare institutions and patients are based on this premise. Therefore, we aimed to complete a formal evaluation of the diagnostic value of CYP2C19 and CYP3A4 genes for predicting metabolizer phenotypes established by omeprazole (OME) administration in 118 healthy children from Jalisco (western Mexico). The genotypes for CYP3A4*1B and CYP2C19*2, *3, *4, *5 and *17 alleles were determined. CYP2C19 and CYP3A4 phenotypes were obtained after 20 mg OME administration and HPLC quantification in plasma to estimate the Hydroxylation Index (HI = OME/HOME) and Sulfonation Index (SI = OME/SOME), respectively. The distribution of genotypes and phenotypes for CYP2C19 and CYP3A4 was similar to previous studies in Mexico and Latin America. We estimated the CYP2C19 UM, EM and PM phenotype frequency in 0.84%, 96.61% and 2.54%, respectively. Although differences in the HI distribution were observed between CYP2C19 genotypes, they showed a poor diagnostic ability to predict the CYP2C19 metabolizer phenotype. Similarly, the number of CYP2C19 and CYP3A4 functional alleles was correlated with the HI distribution, but also their diagnostic ability to predict the CYP2C19 phenotype was poor. The CYP2C19 phenotype is not predicted by the number of functional alleles of CYP2C19 and CYP3A4 genes. Phenotyping is still the most valuable alternative to dose individualization for CYP2C19 substrate drugs. © 2018 John Wiley & Sons Ltd.

A probabilistic model to predict clinical phenotypic traits from genome sequencing.

PubMed

Chen, Yun-Ching; Douville, Christopher; Wang, Cheng; Niknafs, Noushin; Yeo, Grace; Beleva-Guthrie, Violeta; Carter, Hannah; Stenson, Peter D; Cooper, David N; Li, Biao; Mooney, Sean; Karchin, Rachel

2014-09-01

Genetic screening is becoming possible on an unprecedented scale. However, its utility remains controversial. Although most variant genotypes cannot be easily interpreted, many individuals nevertheless attempt to interpret their genetic information. Initiatives such as the Personal Genome Project (PGP) and Illumina's Understand Your Genome are sequencing thousands of adults, collecting phenotypic information and developing computational pipelines to identify the most important variant genotypes harbored by each individual. These pipelines consider database and allele frequency annotations and bioinformatics classifications. We propose that the next step will be to integrate these different sources of information to estimate the probability that a given individual has specific phenotypes of clinical interest. To this end, we have designed a Bayesian probabilistic model to predict the probability of dichotomous phenotypes. When applied to a cohort from PGP, predictions of Gilbert syndrome, Graves' disease, non-Hodgkin lymphoma, and various blood groups were accurate, as individuals manifesting the phenotype in question exhibited the highest, or among the highest, predicted probabilities. Thirty-eight PGP phenotypes (26%) were predicted with area-under-the-ROC curve (AUC)>0.7, and 23 (15.8%) of these were statistically significant, based on permutation tests. Moreover, in a Critical Assessment of Genome Interpretation (CAGI) blinded prediction experiment, the models were used to match 77 PGP genomes to phenotypic profiles, generating the most accurate prediction of 16 submissions, according to an independent assessor. Although the models are currently insufficiently accurate for diagnostic utility, we expect their performance to improve with growth of publicly available genomics data and model refinement by domain experts.

The fetal programming of telomere biology hypothesis: an update

PubMed Central

Entringer, Sonja; Buss, Claudia; Wadhwa, Pathik D.

2018-01-01

Research on mechanisms underlying fetal programming of health and disease risk has focused primarily on processes that are specific to cell types, organs or phenotypes of interest. However, the observation that developmental conditions concomitantly influence a diverse set of phenotypes, the majority of which are implicated in age-related disorders, raises the possibility that such developmental conditions may additionally exert effects via a common underlying mechanism that involves cellular/molecular ageing–related processes. In this context, we submit that telomere biology represents a process of particular interest in humans because, firstly, this system represents among the most salient antecedent cellular phenotypes for common age-related disorders; secondly, its initial (newborn) setting appears to be particularly important for its long-term effects; and thirdly, its initial setting appears to be plastic and under developmental regulation. We propose that the effects of suboptimal intrauterine conditions on the initial setting of telomere length and telomerase expression/activity capacity may be mediated by the programming actions of stress-related maternal–placental–fetal oxidative, immune, endocrine and metabolic pathways in a manner that may ultimately accelerate cellular dysfunction, ageing and disease susceptibility over the lifespan. This perspectives paper provides an overview of each of the elements underlying this hypothesis, with an emphasis on recent developments, findings and future directions. This article is part of the theme issue ‘Understanding diversity in telomere dynamics’. PMID:29335381

The fetal programming of telomere biology hypothesis: an update.

PubMed

Entringer, Sonja; de Punder, Karin; Buss, Claudia; Wadhwa, Pathik D

2018-03-05

Research on mechanisms underlying fetal programming of health and disease risk has focused primarily on processes that are specific to cell types, organs or phenotypes of interest. However, the observation that developmental conditions concomitantly influence a diverse set of phenotypes, the majority of which are implicated in age-related disorders, raises the possibility that such developmental conditions may additionally exert effects via a common underlying mechanism that involves cellular/molecular ageing-related processes. In this context, we submit that telomere biology represents a process of particular interest in humans because, firstly, this system represents among the most salient antecedent cellular phenotypes for common age-related disorders; secondly, its initial (newborn) setting appears to be particularly important for its long-term effects; and thirdly, its initial setting appears to be plastic and under developmental regulation. We propose that the effects of suboptimal intrauterine conditions on the initial setting of telomere length and telomerase expression/activity capacity may be mediated by the programming actions of stress-related maternal-placental-fetal oxidative, immune, endocrine and metabolic pathways in a manner that may ultimately accelerate cellular dysfunction, ageing and disease susceptibility over the lifespan. This perspectives paper provides an overview of each of the elements underlying this hypothesis, with an emphasis on recent developments, findings and future directions.This article is part of the theme issue 'Understanding diversity in telomere dynamics'. © 2018 The Author(s).

A genome-wide CRISPR library for high-throughput genetic screening in Drosophila cells.

PubMed

Bassett, Andrew R; Kong, Lesheng; Liu, Ji-Long

2015-06-20

The simplicity of the CRISPR/Cas9 system of genome engineering has opened up the possibility of performing genome-wide targeted mutagenesis in cell lines, enabling screening for cellular phenotypes resulting from genetic aberrations. Drosophila cells have proven to be highly effective in identifying genes involved in cellular processes through similar screens using partial knockdown by RNAi. This is in part due to the lower degree of redundancy between genes in this organism, whilst still maintaining highly conserved gene networks and orthologs of many human disease-causing genes. The ability of CRISPR to generate genetic loss of function mutations not only increases the magnitude of any effect over currently employed RNAi techniques, but allows analysis over longer periods of time which can be critical for certain phenotypes. In this study, we have designed and built a genome-wide CRISPR library covering 13,501 genes, among which 8989 genes are targeted by three or more independent single guide RNAs (sgRNAs). Moreover, we describe strategies to monitor the population of guide RNAs by high throughput sequencing (HTS). We hope that this library will provide an invaluable resource for the community to screen loss of function mutations for cellular phenotypes, and as a source of guide RNA designs for future studies. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Photo- and electropatterning of hydrogel-encapsulated living cell arrays.

PubMed

Albrecht, Dirk R; Tsang, Valerie Liu; Sah, Robert L; Bhatia, Sangeeta N

2005-01-01

Living cells have the potential to serve as sensors, naturally integrating the response to stimuli to generate predictions about cell fate (e.g., differentiation, migration, proliferation, apoptosis). Miniaturized arrays of living cells further offer the capability to interrogate many cells in parallel and thereby enable high-throughput and/or combinatorial assays. However, the interface between living cells and synthetic chip platforms is a critical one wherein the cellular phenotype must be preserved to generate useful signals. While some cell types retain tissue-specific features on a flat (2-D) surface, it has become increasingly apparent that a 3-D physical environment will be required for others. In this paper, we present two independent methods for creating living cell arrays that are encapsulated within a poly(ethylene glycol)-based hydrogel to create a local 3-D microenvironment. First, 'photopatterning' selectively crosslinks hydrogel microstructures containing living cells with approximately 100 microm feature size. Second, 'electropatterning' utilizes dielectrophoretic forces to position cells within a prepolymer solution prior to crosslinking, forming cell patterns with micron resolution. We further combine these methods to obtain hierarchical control of cell positioning over length scales ranging from microns to centimeters. This level of microenvironmental control should enable the fabrication of next-generation cellular microarrays in which robust 3-D cultures of cells are presented with appropriate physical and chemical cues and, consequently, report on cellular responses that resemble in vivo behavior.

Pericentrin in cellular function and disease

PubMed Central

Delaval, Benedicte

2010-01-01

Pericentrin is an integral component of the centrosome that serves as a multifunctional scaffold for anchoring numerous proteins and protein complexes. Through these interactions, pericentrin contributes to a diversity of fundamental cellular processes. Recent studies link pericentrin to a growing list of human disorders. Studies on pericentrin at the cellular, molecular, and, more recently, organismal level, provide a platform for generating models to elucidate the etiology of these disorders. Although the complexity of phenotypes associated with pericentrin-mediated disorders is somewhat daunting, insights into the cellular basis of disease are beginning to come into focus. In this review, we focus on human conditions associated with loss or elevation of pericentrin and propose cellular and molecular models that might explain them. PMID:19951897

Mapping the cellular and molecular heterogeneity of normal and malignant breast tissues and cultured cell lines

PubMed Central

2010-01-01

Introduction Normal and neoplastic breast tissues are comprised of heterogeneous populations of epithelial cells exhibiting various degrees of maturation and differentiation. While cultured cell lines have been derived from both normal and malignant tissues, it remains unclear to what extent they retain similar levels of differentiation and heterogeneity as that found within breast tissues. Methods We used 12 reduction mammoplasty tissues, 15 primary breast cancer tissues, and 20 human breast epithelial cell lines (16 cancer lines, 4 normal lines) to perform flow cytometry for CD44, CD24, epithelial cell adhesion molecule (EpCAM), and CD49f expression, as well as immunohistochemistry, and in vivo tumor xenograft formation studies to extensively analyze the molecular and cellular characteristics of breast epithelial cell lineages. Results Human breast tissues contain four distinguishable epithelial differentiation states (two luminal phenotypes and two basal phenotypes) that differ on the basis of CD24, EpCAM and CD49f expression. Primary human breast cancer tissues also contain these four cellular states, but in altered proportions compared to normal tissues. In contrast, cultured cancer cell lines are enriched for rare basal and mesenchymal epithelial phenotypes, which are normally present in small numbers within human tissues. Similarly, cultured normal human mammary epithelial cell lines are enriched for rare basal and mesenchymal phenotypes that represent a minor fraction of cells within reduction mammoplasty tissues. Furthermore, although normal human mammary epithelial cell lines exhibit features of bi-potent progenitor cells they are unable to differentiate into mature luminal breast epithelial cells under standard culture conditions. Conclusions As a group breast cancer cell lines represent the heterogeneity of human breast tumors, but individually they exhibit increased lineage-restricted profiles that fall short of truly representing the intratumoral heterogeneity of individual breast tumors. Additionally, normal human mammary epithelial cell lines fail to retain much of the cellular diversity found in human breast tissues and are enriched for differentiation states that are a minority in breast tissues, although they do exhibit features of bi-potent basal progenitor cells. These findings suggest that collections of cell lines representing multiple cell types can be used to model the cellular heterogeneity of tissues. PMID:20964822

Many Saccharomyces cerevisiae Cell Wall Protein Encoding Genes Are Coregulated by Mss11, but Cellular Adhesion Phenotypes Appear Only Flo Protein Dependent.

PubMed

Bester, Michael C; Jacobson, Dan; Bauer, Florian F

2012-01-01

The outer cell wall of the yeast Saccharomyces cerevisiae serves as the interface with the surrounding environment and directly affects cell-cell and cell-surface interactions. Many of these interactions are facilitated by specific adhesins that belong to the Flo protein family. Flo mannoproteins have been implicated in phenotypes such as flocculation, substrate adhesion, biofilm formation, and pseudohyphal growth. Genetic data strongly suggest that individual Flo proteins are responsible for many specific cellular adhesion phenotypes. However, it remains unclear whether such phenotypes are determined solely by the nature of the expressed FLO genes or rather as the result of a combination of FLO gene expression and other cell wall properties and cell wall proteins. Mss11 has been shown to be a central element of FLO1 and FLO11 gene regulation and acts together with the cAMP-PKA-dependent transcription factor Flo8. Here we use genome-wide transcription analysis to identify genes that are directly or indirectly regulated by Mss11. Interestingly, many of these genes encode cell wall mannoproteins, in particular, members of the TIR and DAN families. To examine whether these genes play a role in the adhesion properties associated with Mss11 expression, we assessed deletion mutants of these genes in wild-type and flo11Δ genetic backgrounds. This analysis shows that only FLO genes, in particular FLO1/10/11, appear to significantly impact on such phenotypes. Thus adhesion-related phenotypes are primarily dependent on the balance of FLO gene expression.

Phenotypic plasticity and epithelial-to-mesenchymal transition in the behaviour and therapeutic response of oral squamous cell carcinoma.

PubMed

Vig, Navin; Mackenzie, Ian C; Biddle, Adrian

2015-10-01

It is increasingly recognised that phenotypic plasticity, apparently driven by epigenetic mechanisms, plays a key role in tumour behaviour and markedly influences the important processes of therapeutic survival and metastasis. An important source of plasticity in malignancy is epithelial-to-mesenchymal transition (EMT), a common epigenetically controlled event that results in transition of malignant cells between different phenotypic states that confer motility and enhance survival. In this review, we discuss the importance of phenotypic plasticity and its contribution to cellular heterogeneity in oral squamous cell carcinoma with emphasis on aspects of drug resistance and EMT. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds.

PubMed

Feng, Yan; Mitchison, Timothy J; Bender, Andreas; Young, Daniel W; Tallarico, John A

2009-07-01

Multi-parameter phenotypic profiling of small molecules provides important insights into their mechanisms of action, as well as a systems level understanding of biological pathways and their responses to small molecule treatments. It therefore deserves more attention at an early step in the drug discovery pipeline. Here, we summarize the technologies that are currently in use for phenotypic profiling--including mRNA-, protein- and imaging-based multi-parameter profiling--in the drug discovery context. We think that an earlier integration of phenotypic profiling technologies, combined with effective experimental and in silico target identification approaches, can improve success rates of lead selection and optimization in the drug discovery process.

Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems.

PubMed

Zhao, Jiangsan; Bodner, Gernot; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A; Nakhforoosh, Alireza

2017-02-01

Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Hyper telomere recombination accelerates replicative senescence and may promote premature aging

PubMed Central

Hagelstrom, R. Tanner; Blagoev, Krastan B.; Niedernhofer, Laura J.; Goodwin, Edwin H.; Bailey, Susan M.

2010-01-01

Werner syndrome and Bloom syndrome result from defects in the RecQ helicases Werner (WRN) and Bloom (BLM), respectively, and display premature aging phenotypes. Similarly, XFE progeroid syndrome results from defects in the ERCC1-XPF DNA repair endonuclease. To gain insight into the origin of cellular senescence and human aging, we analyzed the dependence of sister chromatid exchange (SCE) frequencies on location [i.e., genomic (G-SCE) vs. telomeric (T-SCE) DNA] in primary human fibroblasts deficient in WRN, BLM, or ERCC1-XPF. Consistent with our other studies, we found evidence of elevated T-SCE in telomerase-negative but not telomerase-positive backgrounds. In telomerase-negative WRN-deficient cells, T-SCE—but not G-SCE—frequencies were significantly increased compared with controls. In contrast, SCE frequencies were significantly elevated in BLM-deficient cells irrespective of genome location. In ERCC1-XPF-deficient cells, neither T- nor G-SCE frequencies differed from controls. A theoretical model was developed that allowed an in silico investigation into the cellular consequences of increased T-SCE frequency. The model predicts that in cells with increased T-SCE, the onset of replicative senescence is dramatically accelerated even though the average rate of telomere loss has not changed. Premature cellular senescence may act as a powerful tumor-suppressor mechanism in telomerase-deficient cells with mutations that cause T-SCE levels to rise. Furthermore, T-SCE-driven premature cellular senescence may be a factor contributing to accelerated aging in Werner and Bloom syndromes, but not XFE progeroid syndrome. PMID:20798040

Transcription Factors MYOCD, SRF, Mesp1 and SMARCD3 Enhance the Cardio-Inducing Effect of GATA4, TBX5, and MEF2C during Direct Cellular Reprogramming

PubMed Central

Christoforou, Nicolas; Chellappan, Malathi; Adler, Andrew F.; Kirkton, Robert D.; Wu, Tianyi; Addis, Russell C.; Bursac, Nenad; Leong, Kam W.

2013-01-01

Transient overexpression of defined combinations of master regulator genes can effectively induce cellular reprogramming: the acquisition of an alternative predicted phenotype from a differentiated cell lineage. This can be of particular importance in cardiac regenerative medicine wherein the heart lacks the capacity to heal itself, but simultaneously contains a large pool of fibroblasts. In this study we determined the cardio-inducing capacity of ten transcription factors to actuate cellular reprogramming of mouse embryonic fibroblasts into cardiomyocyte-like cells. Overexpression of transcription factors MYOCD and SRF alone or in conjunction with Mesp1 and SMARCD3 enhanced the basal but necessary cardio-inducing effect of the previously reported GATA4, TBX5, and MEF2C. In particular, combinations of five or seven transcription factors enhanced the activation of cardiac reporter vectors, and induced an upregulation of cardiac-specific genes. Global gene expression analysis also demonstrated a significantly greater cardio-inducing effect when the transcription factors MYOCD and SRF were used. Detection of cross-striated cells was highly dependent on the cell culture conditions and was enhanced by the addition of valproic acid and JAK inhibitor. Although we detected Ca2+ transient oscillations in the reprogrammed cells, we did not detect significant changes in resting membrane potential or spontaneously contracting cells. This study further elucidates the cardio-inducing effect of the transcriptional networks involved in cardiac cellular reprogramming, contributing to the ongoing rational design of a robust protocol required for cardiac regenerative therapies. PMID:23704920

Age-related epigenetic drift and phenotypic plasticity loss: implications in prevention of age-related human diseases

PubMed Central

Li, Yuanyuan; Tollefsbol, Trygve O

2016-01-01

Aging is considered as one of the most important developmental processes in organisms and is closely associated with global deteriorations of epigenetic markers such as aberrant methylomic patterns. This altered epigenomic state, referred to ‘epigenetic drift’, reflects deficient maintenance of epigenetic marks and contributes to impaired cellular and molecular functions in aged cells. Epigenetic drift-induced abnormal changes during aging are scantily repaired by epigenetic modulators. This inflexibility in the aged epigenome may lead to an age-related decline in phenotypic plasticity at the cellular and molecular levels due to epigenetic drift. This perspective aims to provide novel concepts for understanding epigenetic effects on the aging process and to provide insights into epigenetic prevention and therapeutic strategies for age-related human disease. PMID:27882781

Abrogation of E-cadherin-mediated cell-cell contact in mouse embryonic stem cells results in reversible LIF-independent self-renewal.

PubMed

Soncin, Francesca; Mohamet, Lisa; Eckardt, Dominik; Ritson, Sarah; Eastham, Angela M; Bobola, Nicoletta; Russell, Angela; Davies, Steve; Kemler, Rolf; Merry, Catherine L R; Ward, Christopher M

2009-09-01

We have previously demonstrated that differentiation of embryonic stem (ES) cells is associated with downregulation of cell surface E-cadherin. In this study, we assessed the function of E-cadherin in mouse ES cell pluripotency and differentiation. We show that inhibition of E-cadherin-mediated cell-cell contact in ES cells using gene knockout (Ecad(-/-)), RNA interference (EcadRNAi), or a transhomodimerization-inhibiting peptide (CHAVC) results in cellular proliferation and maintenance of an undifferentiated phenotype in fetal bovine serum-supplemented medium in the absence of leukemia inhibitory factor (LIF). Re-expression of E-cadherin in Ecad(-/-), EcadRNAi, and CHAVC-treated ES cells restores cellular dependence to LIF supplementation. Although reversal of the LIF-independent phenotype in Ecad(-/-) ES cells is dependent on the beta-catenin binding domain of E-cadherin, we show that beta-catenin null (betacat(-/-)) ES cells also remain undifferentiated in the absence of LIF. This suggests that LIF-independent self-renewal of Ecad(-/-) ES cells is unlikely to be via beta-catenin signaling. Exposure of Ecad(-/-), EcadRNAi, and CHAVC-treated ES cells to the activin receptor-like kinase inhibitor SB431542 led to differentiation of the cells, which could be prevented by re-expression of E-cadherin. To confirm the role of transforming growth factor beta family signaling in the self-renewal of Ecad(-/-) ES cells, we show that these cells maintain an undifferentiated phenotype when cultured in serum-free medium supplemented with Activin A and Nodal, with fibroblast growth factor 2 required for cellular proliferation. We conclude that transhomodimerization of E-cadherin protein is required for LIF-dependent ES cell self-renewal and that multiple self-renewal signaling networks subsist in ES cells, with activity dependent upon the cellular context.

Raf-1 levels determine the migration rate of primary endometrial stromal cells of patients with endometriosis

PubMed Central

Yotova, Iveta; Quan, Ping; Gaba, Aulona; Leditznig, Nadja; Pateisky, Petra; Kurz, Christine; Tschugguel, Walter

2012-01-01

Endometriosis is a disease characterized by the localization of endometrial tissue outside the uterine cavity. The differences observed in migration of human endometrial stromal cells (hESC) obtained from patients with endometriosis versus healthy controls were proposed to correlate with the abnormal activation of Raf-1/ROCKII signalling pathway. To evaluate the mechanism by which Raf-1 regulates cytoskeleton reorganization and motility, we used primary eutopic (Eu-, n = 16) and ectopic (Ec-, n = 8; isolated from ovarian cysts) hESC of patients with endometriosis and endometriosis-free controls (Co-hESC, n = 14). Raf-1 siRNA knockdown in Co- and Eu-hESC resulted in contraction and decreased migration versus siRNA controls. This phenotype was reversed following the re-expression of Raf-1 in these cells. Lowest Raf-1 levels in Ec-hESC were associated with hyperactivated ROCKII and ezrin/radixin/moesin (E/R/M), impaired migration and a contracted phenotype similar to Raf-1 knockdown in Co- and Eu-hESC. We further show that the mechanism by which Raf-1 mediates migration in hESC includes direct myosin light chain phosphatase (MYPT1) phosphorylation and regulation of the levels of E/R/M, paxillin, MYPT1 and myosin light chain (MLC) phosphorylation indirectly via the hyperactivation of ROCKII kinase. Furthermore, we suggest that in contrast to Co-and Eu-hESC, where the cellular Raf-1 levels regulate the rate of migration, the low cellular Raf-1 content in Ec-hESC, might ensure their restricted migration by preserving the contracted cellular phenotype. In conclusion, our findings suggest that cellular levels of Raf-1 adjust the threshold of hESC migration in endometriosis. PMID:22225925

Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

PubMed Central

Karaçalı, Bilge; Vamvakidou, Alexandra P; Tözeren, Aydın

2007-01-01

Background Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Methods Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system. Results Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images. Conclusion Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development. PMID:17822559

Helicase-inactivating mutations as a basis for dominant negative phenotypes

PubMed Central

Wu, Yuliang

2010-01-01

There is ample evidence from studies of both unicellular and multicellular organisms that helicase-inactivating mutations lead to cellular dysfunction and disease phenotypes. In this review, we will discuss the mechanisms underlying the basis for abnormal phenotypes linked to mutations in genes encoding DNA helicases. Recent evidence demonstrates that a clinically relevant patient missense mutation in Fanconi Anemia Complementation Group J exerts detrimental effects on the biochemical activities of the FANC J helicase, and these molecular defects are responsible for aberrant genomic stability and a poor DNA damage response. The ability of FANC J to use the energy from AT P hydrolysis to produce the force required to unwind duplex or G-quadruplex DNA structures or destabilize protein bound to DNA is required for its DNA repair functions in vivo. Strikingly, helicase-inactivating mutations can exert a spectrum of dominant negative phenotypes, indicating that expression of the mutant helicase protein potentially interferes with normal DNA metabolism and has an effect on basic cellular processes such as DNA replication, the DNA damage response and protein trafficking. This review emphasizes that future studies of clinically relevant mutations in helicase genes will be important to understand the molecular pathologies of the associated diseases and their impact on heterozygote carriers. PMID:20980836

Phenotypic, Functional, and Safety Control at Preimplantation Phase of MSC-Based Therapy.

PubMed

Lech, Wioletta; Figiel-Dabrowska, Anna; Sarnowska, Anna; Drela, Katarzyna; Obtulowicz, Patrycja; Noszczyk, Bartlomiej Henryk; Buzanska, Leonora; Domanska-Janik, Krystyna

2016-01-01

Mesenchymal stem cells (MSC) exhibit enormous heterogeneity which can modify their regenerative properties and therefore influence therapeutic effectiveness as well as safety of these cells transplantation. In addition the high phenotypic plasticity of MSC population makes it enormously sensitive to any changes in environmental properties including fluctuation in oxygen concentration. We have shown here that lowering oxygen level far below air atmosphere has a beneficial impact on various parameters characteristic for umbilical cord Wharton Jelly- (WJ-) MSC and adipose tissue- (AD-) derived MSC cultures. This includes their cellular composition, rate of proliferation, and maintenance of stemness properties together with commitment to cell differentiation toward mesodermal and neural lineages. In addition, the culture genomic stability increased significantly during long-term cell passaging and eventually protected cells against spontaneous transformation. Also by comparing of two routinely used methods of MSCs isolation (mechanical versus enzymatic) we have found substantial divergence arising between cell culture properties increasing along the time of cultivation in vitro. Thus, in this paper we highlight the urgent necessity to develop the more sensitive and selective methods for prediction and control cells fate and functioning during the time of growth in vitro.

Liver peroxisomal alanine:glyoxylate aminotransferase and the effects of mutations associated with Primary Hyperoxaluria Type I: An overview.

PubMed

Oppici, Elisa; Montioli, Riccardo; Cellini, Barbara

2015-09-01

Liver peroxisomal alanine:glyoxylate aminotransferase (AGT) (EC 2.6.1.44) catalyses the conversion of l-alanine and glyoxylate to pyruvate and glycine, a reaction that allows glyoxylate detoxification. Inherited mutations on the AGXT gene encoding AGT lead to Primary Hyperoxaluria Type I (PH1), a rare disorder characterized by the deposition of calcium oxalate crystals primarily in the urinary tract. Here we describe the results obtained on the biochemical features of AGT as well as on the molecular and cellular effects of polymorphic and pathogenic mutations. A complex scenario on the molecular pathogenesis of PH1 emerges in which the co-inheritance of polymorphic changes and the condition of homozygosis or compound heterozygosis are two important factors that determine the enzymatic phenotype of PH1 patients. All the reported data represent relevant steps toward the understanding of genotype/phenotype correlations, the prediction of the response of the patients to the available therapies, and the development of new therapeutic approaches. This article is part of a Special Issue entitled: Cofactor-dependent proteins: evolution, chemical diversity and bio-applications. Copyright © 2015 Elsevier B.V. All rights reserved.

Genomic assisted selection for enhancing line breeding: merging genomic and phenotypic selection in winter wheat breeding programs with preliminary yield trials.

PubMed

Michel, Sebastian; Ametz, Christian; Gungor, Huseyin; Akgöl, Batuhan; Epure, Doru; Grausgruber, Heinrich; Löschenberger, Franziska; Buerstmayr, Hermann

2017-02-01

Early generation genomic selection is superior to conventional phenotypic selection in line breeding and can be strongly improved by including additional information from preliminary yield trials. The selection of lines that enter resource-demanding multi-environment trials is a crucial decision in every line breeding program as a large amount of resources are allocated for thoroughly testing these potential varietal candidates. We compared conventional phenotypic selection with various genomic selection approaches across multiple years as well as the merit of integrating phenotypic information from preliminary yield trials into the genomic selection framework. The prediction accuracy using only phenotypic data was rather low (r = 0.21) for grain yield but could be improved by modeling genetic relationships in unreplicated preliminary yield trials (r = 0.33). Genomic selection models were nevertheless found to be superior to conventional phenotypic selection for predicting grain yield performance of lines across years (r = 0.39). We subsequently simplified the problem of predicting untested lines in untested years to predicting tested lines in untested years by combining breeding values from preliminary yield trials and predictions from genomic selection models by a heritability index. This genomic assisted selection led to a 20% increase in prediction accuracy, which could be further enhanced by an appropriate marker selection for both grain yield (r = 0.48) and protein content (r = 0.63). The easy to implement and robust genomic assisted selection gave thus a higher prediction accuracy than either conventional phenotypic or genomic selection alone. The proposed method took the complex inheritance of both low and high heritable traits into account and appears capable to support breeders in their selection decisions to develop enhanced varieties more efficiently.

Effect of Phospholipidosis on the Cellular Pharmacokinetics of ChloroquineS⃞

PubMed Central

Zheng, Nan; Zhang, Xinyuan

2011-01-01

In vivo, the weakly basic, lipophilic drug chloroquine (CQ) accumulates in the kidney to concentrations more than a thousand-fold greater than those in plasma. To study the cellular pharmacokinetics of chloroquine in cells derived from the distal tubule, Madin-Darby canine kidney cells were incubated with CQ under various conditions. CQ progressively accumulated without exhibiting steady-state behavior. Experiments failed to yield evidence that known active transport mechanisms mediated CQ uptake at the plasma membrane. CQ induced a phospholipidosis-like phenotype, characterized by the appearance of numerous multivesicular and multilamellar bodies (MLBs/MVBs) within the lumen of expanded cytoplasmic vesicles. Other induced phenotypic changes including changes in the volume and pH of acidic organelles were measured, and the integrated effects of all these changes were computationally modeled to establish their impact on intracellular CQ mass accumulation. Based on the passive transport behavior of CQ, the measured phenotypic changes fully accounted for the continuous, nonsteady-state CQ accumulation kinetics. Consistent with the simulation results, Raman confocal microscopy of live cells confirmed that CQ became highly concentrated within induced, expanded cytoplasmic vesicles that contained multiple MLBs/MVBs. Progressive CQ accumulation was increased by sucrose, a compound that stimulated the phospholipidosis-like phenotype, and was decreased by bafilomycin A1, a compound that inhibited this phenotype. Thus, phospholipidosis-associated changes in organelle structure and intracellular membrane content can exert a major influence on the local bioaccumulation and biodistribution of drugs. PMID:21156819

Interpreting phenotypic antibiotic tolerance and persister cells as evolution via epigenetic inheritance.

PubMed

Day, Troy

2016-04-01

Epigenetic inheritance is the transmission of nongenetic material such as gene expression levels, RNA and other biomolecules from parents to offspring. There is a growing realization that such forms of inheritance can play an important role in evolution. Bacteria represent a prime example of epigenetic inheritance because a large array of cellular components is transmitted to offspring, in addition to genetic material. Interestingly, there is an extensive and growing empirical literature showing that many bacteria can form 'persister' cells that are phenotypically resistant or tolerant to antibiotics, but most of these results are not interpreted within the context of epigenetic inheritance. Instead, persister cells are usually viewed as a genetically encoded bet-hedging strategy that has evolved in response to a fluctuating environment. Here I show, using a relatively simple model, that many of these empirical findings can be more simply understood as arising from a combination of epigenetic inheritance and cellular noise. I therefore suggest that phenotypic drug tolerance in bacteria might represent one of the best-studied examples of evolution under epigenetic inheritance. © 2016 John Wiley & Sons Ltd.

Cancer cell metabolism and the modulating effects of nitric oxide.

PubMed

Chang, Ching-Fang; Diers, Anne R; Hogg, Neil

2015-02-01

Altered metabolic phenotype has been recognized as a hallmark of tumor cells for many years, but this aspect of the cancer phenotype has come into greater focus in recent years. NOS2 (inducible nitric oxide synthase of iNOS) has been implicated as a component in many aggressive tumor phenotypes, including melanoma, glioblastoma, and breast cancer. Nitric oxide has been well established as a modulator of cellular bioenergetics pathways, in many ways similar to the alteration of cellular metabolism observed in aggressive tumors. In this review we attempt to bring these concepts together with the general hypothesis that one function of NOS2 and NO in cancer is to modulate metabolic processes to facilitate increased tumor aggression. There are many mechanisms by which NO can modulate tumor metabolism, including direct inhibition of respiration, alterations in mitochondrial mass, oxidative inhibition of bioenergetic enzymes, and the stimulation of secondary signaling pathways. Here we review metabolic alterations in the context of cancer cells and discuss the role of NO as a potential mediator of these changes. Copyright © 2015. Published by Elsevier Inc.

Roles of GSK3 in metabolic shift toward abnormal anabolism in cell senescence.

PubMed

Kim, You-Mie; Seo, Yong-Hak; Park, Chan-Bae; Yoon, Soo-Han; Yoon, Gyesoon

2010-07-01

Diverse metabolic alterations, including mitochondrial dysfunction, have often been reported as characteristic phenotypes of senescent cells. However, the overall consequence of senescent metabolic features, how they develop, and how they are linked to other senescent phenotypes, such as enlarged cell volume, increased granularity, and oxidative stress, is not clear. We investigated the potential roles of glycogen synthase kinase 3 (GSK3), a multifunctional kinase, in the development of the metabolic phenotypes in cell senescence. The inactivation of GSK3 via phosphorylation is commonly observed in diverse cell senescences. Furthermore, subcytotoxic concentration of GSK3 inhibitor was sufficient to induce cellular senescence, accompanied by augmented anabolism, such as enhanced protein synthesis, and increased glycogenesis and lipogenesis, in addition to mitochondrial dysfunction. Anabolism was accomplished through glycogen synthase, eIF2B, and SREBP1. These metabolic features seem to contribute to an increase in cellular mass by increasing glycogen granules, protein mass, and organelles. Taken together, our results suggest that GSK3 is one of the key modulators of metabolic alteration, leading the cells to senescence.

Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping

PubMed Central

Treweek, Jennifer B; Deverman, Benjamin E; Greenbaum, Alon; Lignell, Antti; Xiao, Cheng; Cai, Long; Ladinsky, Mark S; Bjorkman, Pamela J; Fowlkes, Charless C; Gradinaru, Viviana

2016-01-01

To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue fixation-embedding, detergent-clearing and staining protocols that can be used to transform excised organs and whole organisms into optically transparent samples within 1–2 weeks without compromising their cellular architecture or endogenous fluorescence. PACT (passive CLARITY technique) and PARS (perfusion-assisted agent release in situ) use tissue-hydrogel hybrids to stabilize tissue biomolecules during selective lipid extraction, resulting in enhanced clearing efficiency and sample integrity. Furthermore, the macromolecule permeability of PACT- and PARS-processed tissue hybrids supports the diffusion of immunolabels throughout intact tissue, whereas RIMS (refractive index matching solution) grants high-resolution imaging at depth by further reducing light scattering in cleared and uncleared samples alike. These methods are adaptable to difficult-to-image tissues, such as bone (PACT-deCAL), and to magnified single-cell visualization (ePACT). Together, these protocols and solutions enable phenotyping of subcellular components and tracing cellular connectivity in intact biological networks. PMID:26492141

Dynamic Microenvironment Induces Phenotypic Plasticity of Esophageal Cancer Cells Under Flow

NASA Astrophysics Data System (ADS)

Calibasi Kocal, Gizem; Güven, Sinan; Foygel, Kira; Goldman, Aaron; Chen, Pu; Sengupta, Shiladitya; Paulmurugan, Ramasamy; Baskin, Yasemin; Demirci, Utkan

2016-12-01

Cancer microenvironment is a remarkably heterogeneous composition of cellular and non-cellular components, regulated by both external and intrinsic physical and chemical stimuli. Physical alterations driven by increased proliferation of neoplastic cells and angiogenesis in the cancer microenvironment result in the exposure of the cancer cells to elevated levels of flow-based shear stress. We developed a dynamic microfluidic cell culture platform utilizing eshopagael cancer cells as model cells to investigate the phenotypic changes of cancer cells upon exposure to fluid shear stress. We report the epithelial to hybrid epithelial/mesenchymal transition as a result of decreasing E-Cadherin and increasing N-Cadherin and vimentin expressions, higher clonogenicity and ALDH positive expression of cancer cells cultured in a dynamic microfluidic chip under laminar flow compared to the static culture condition. We also sought regulation of chemotherapeutics in cancer microenvironment towards phenotypic control of cancer cells. Such in vitro microfluidic system could potentially be used to monitor how the interstitial fluid dynamics affect cancer microenvironment and plasticity on a simple, highly controllable and inexpensive bioengineered platform.

Cancer Cell Metabolism and the Modulating Effects of Nitric Oxide

PubMed Central

Chang, Ching-Fang; Diers, Anne R.; Hogg, Neil

2016-01-01

Altered metabolic phenotype has been recognized as a hallmark of tumor cells for many years, but this aspect of the cancer phenotype has come into greater focus in recent years. NOS2 (inducible nitric oxide synthase of iNOS) has been implicated as a component in many aggressive tumor phenotypes, including melanoma, glioblastoma and breast cancer. Nitric oxide has been well established as a modulator of cellular bioenergetics pathways, in many ways similar to the alteration of cellular metabolism observed in aggressive tumors. In this review we attempt to bring these concepts together with the general hypothesis that one function of NOS2 and NO in cancer is to modulate metabolic processes to facilitate increased tumor aggression. There are many mechanisms by which NO can modulate tumor metabolism, including direct inhibition of respiration, alterations in mitochondrial mass, oxidative inhibition of bioenergetic enzymes, and the stimulation of secondary signaling pathways. Here we review metabolic alterations in the context of cancer cells and discuss the role of NO as a potential mediator of these changes. PMID:25464273

GLUT3 gene expression is critical for embryonic growth, brain development and survival.

PubMed

Carayannopoulos, Mary O; Xiong, Fuxia; Jensen, Penny; Rios-Galdamez, Yesenia; Huang, Haigen; Lin, Shuo; Devaskar, Sherin U

2014-04-01

Glucose is the primary energy source for eukaryotic cells and the predominant substrate for the brain. GLUT3 is essential for trans-placental glucose transport and highly expressed in the mammalian brain. To further elucidate the role of GLUT3 in embryonic development, we utilized the vertebrate whole animal model system of Danio rerio as a tractable system for defining the cellular and molecular mechanisms altered by impaired glucose transport and metabolism related to perturbed expression of GLUT3. The comparable orthologue of human GLUT3 was identified and the expression of this gene abrogated during early embryonic development. In a dose-dependent manner embryonic brain development was disrupted resulting in a phenotype of aberrant brain organogenesis, associated with embryonic growth restriction and increased cellular apoptosis. Rescue of the morphant phenotype was achieved by providing exogenous GLUT3 mRNA. We conclude that GLUT3 is critically important for brain organogenesis and embryonic growth. Disruption of GLUT3 is responsible for the phenotypic spectrum of embryonic growth restriction to demise and neural apoptosis with microcephaly. Copyright © 2014 Elsevier Inc. All rights reserved.

Histone methylation and aging: Lessons learned from model systems

PubMed Central

McCauley, Brenna S.; Dang, Weiwei

2014-01-01

Aging induces myriad cellular and, ultimately, physiological changes that cause a decline in an organism's functional capabilities. Although the aging process and pathways that regulate it have been extensively studied, only in the last decade have we begun to appreciate that dynamic histone methylation may contribute to this process. In this review, we discuss recent work implicating histone methylation in aging. Loss of certain histone methyltransferases and demethylases changes lifespan in invertebrates, and alterations in histone methylation in aged organisms regulate lifespan and aging phenotypes, including oxidative stress-induced hormesis in yeast, insulin signaling in Caenorhabiditis elegans and mammals, and the senescence-associated secretory phenotype in mammals. In all cases where histone methylation has been shown to impact aging and aging phenotypes, it does so by regulating transcription, suggesting that this is a major mechanism of its action in this context. Histone methylation additionally regulates or is regulated by other cellular pathways that contribute to or combat aging. Given the numerous processes that regulate aging and histone methylation, and are in turn regulated by them, the role of histone methylation in aging is almost certainly underappreciated. PMID:24859460

Disruption of Src Is Associated with Phenotypes Related to Williams-Beuren Syndrome and Altered Cellular Localization of TFII-I1,2

PubMed Central

Ivakine, Evgueni A.; Lam, Emily; Deurloo, Marielle; Dida, Joana; Zirngibl, Ralph A.

2015-01-01

Abstract Src is a nonreceptor protein tyrosine kinase that is expressed widely throughout the central nervous system and is involved in diverse biological functions. Mice homozygous for a spontaneous mutation in Src (Src thl/thl) exhibited hypersociability and hyperactivity along with impairments in visuospatial, amygdala-dependent, and motor learning as well as an increased startle response to loud tones. The phenotype of Src thl/thl mice showed significant overlap with Williams-Beuren syndrome (WBS), a disorder caused by the deletion of several genes, including General Transcription Factor 2-I (GTF2I). Src phosphorylation regulates the movement of GTF2I protein (TFII-I) between the nucleus, where it is a transcriptional activator, and the cytoplasm, where it regulates trafficking of transient receptor potential cation channel, subfamily C, member 3 (TRPC3) subunits to the plasma membrane. Here, we demonstrate altered cellular localization of both TFII-I and TRPC3 in the Src mutants, suggesting that disruption of Src can phenocopy behavioral phenotypes observed in WBS through its regulation of TFII-I. PMID:26464974

GLUT3 Gene Expression is Critical for Embryonic Growth, Brain Development and Survival

PubMed Central

Carayannopoulos, Mary O.; Xiong, Fuxia; Jensen, Penny; Rios-Galdamez, Yesenia; Huang, Haigen; Lin, Shuo; Devaskar, Sherin U.

2015-01-01

Glucose is the primary energy source for eukaryotic cells and the predominant substrate for the brain. GLUT3 is essential for trans-placental glucose transport and highly expressed in the mammalian brain. To further elucidate the role of GLUT3 in embryonic development, we utilized the vertebrate whole animal model system of Danio rerio as a tractable system for defining the cellular and molecular mechanisms altered by impaired glucose transport and metabolism related to perturbed expression of GLUT3. The comparable orthologue of human GLUT3 was identified and the expression of this gene abrogated during early embryonic development. In a dose-dependent manner embryonic brain development was disrupted resulting in a phenotype of aberrant brain organogenesis, associated with embryonic growth restriction and increased cellular apoptosis. Rescue of the morphant phenotype was achieved by providing exogenous GLUT3 mRNA. We conclude that GLUT3 is critically important for brain organogenesis and embryonic growth. Disruption of GLUT3 is responsible for the phenotypic spectrum of embryonic growth restriction to demise and neural apoptosis with microcephaly. PMID:24529979

Linking stem cell function and growth pattern of intestinal organoids.

PubMed

Thalheim, Torsten; Quaas, Marianne; Herberg, Maria; Braumann, Ulf-Dietrich; Kerner, Christiane; Loeffler, Markus; Aust, Gabriela; Galle, Joerg

2018-01-15

Intestinal stem cells (ISCs) require well-defined signals from their environment in order to carry out their specific functions. Most of these signals are provided by neighboring cells that form a stem cell niche, whose shape and cellular composition self-organize. Major features of this self-organization can be studied in ISC-derived organoid culture. In this system, manipulation of essential pathways of stem cell maintenance and differentiation results in well-described growth phenotypes. We here provide an individual cell-based model of intestinal organoids that enables a mechanistic explanation of the observed growth phenotypes. In simulation studies of the 3D structure of expanding organoids, we investigate interdependences between Wnt- and Notch-signaling which control the shape of the stem cell niche and, thus, the growth pattern of the organoids. Similar to in vitro experiments, changes of pathway activities alter the cellular composition of the organoids and, thereby, affect their shape. Exogenous Wnt enforces transitions from branched into a cyst-like growth pattern; known to occur spontaneously during long term organoid expansion. Based on our simulation results, we predict that the cyst-like pattern is associated with biomechanical changes of the cells which assign them a growth advantage. The results suggest ongoing stem cell adaptation to in vitro conditions during long term expansion by stabilizing Wnt-activity. Our study exemplifies the potential of individual cell-based modeling in unraveling links between molecular stem cell regulation and 3D growth of tissues. This kind of modeling combines experimental results in the fields of stem cell biology and cell biomechanics constituting a prerequisite for a better understanding of tissue regeneration as well as developmental processes. Copyright © 2017 Elsevier Inc. All rights reserved.

The topology and dynamics of complex networks

NASA Astrophysics Data System (ADS)

Dezso, Zoltan

We start with a brief introduction about the topological properties of real networks. Most real networks are scale-free, being characterized by a power-law degree distribution. The scale-free nature of real networks leads to unexpected properties such as the vanishing epidemic threshold. Traditional methods aiming to reduce the spreading rate of viruses cannot succeed on eradicating the epidemic on a scale-free network. We demonstrate that policies that discriminate between the nodes, curing mostly the highly connected nodes, can restore a finite epidemic threshold and potentially eradicate the virus. We find that the more biased a policy is towards the hubs, the more chance it has to bring the epidemic threshold above the virus' spreading rate. We continue by studying a large Web portal as a model system for a rapidly evolving network. We find that the visitation pattern of a news document decays as a power law, in contrast with the exponential prediction provided by simple models of site visitation. This is rooted in the inhomogeneous nature of the browsing pattern characterizing individual users: the time interval between consecutive visits by the same user to the site follows a power law distribution, in contrast with the exponential expected for Poisson processes. We show that the exponent characterizing the individual user's browsing patterns determines the power-law decay in a document's visitation. Finally, we turn our attention to biological networks and demonstrate quantitatively that protein complexes in the yeast, Saccharomyces cerevisiae, are comprised of a core in which subunits are highly coexpressed, display the same deletion phenotype (essential or non-essential) and share identical functional classification and cellular localization. The results allow us to define the deletion phenotype and cellular task of most known complexes, and to identify with high confidence the biochemical role of hundreds of proteins with yet unassigned functionality.

Phenome-driven disease genetics prediction toward drug discovery

PubMed Central

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-01-01

Motivation: Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. Results: To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e−4) and 81.3% (P < e−12) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn’s disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn’s disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn’s disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. Availability and implementation: nlp.case.edu/public/data/DMN Contact: rxx@case.edu PMID:26072493

Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.

PubMed

Liu, Mei; Wu, Yonghui; Chen, Yukun; Sun, Jingchun; Zhao, Zhongming; Chen, Xue-wen; Matheny, Michael Edwin; Xu, Hua

2012-06-01

Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance. Many studies have utilized either chemical structures or molecular pathways of the drugs to predict ADRs. Here, the authors propose a machine-learning-based approach for ADR prediction by integrating the phenotypic characteristics of a drug, including indications and other known ADRs, with the drug's chemical structures and biological properties, including protein targets and pathway information. A large-scale study was conducted to predict 1385 known ADRs of 832 approved drugs, and five machine-learning algorithms for this task were compared. This evaluation, based on a fivefold cross-validation, showed that the support vector machine algorithm outperformed the others. Of the three types of information, phenotypic data were the most informative for ADR prediction. When biological and phenotypic features were added to the baseline chemical information, the ADR prediction model achieved significant improvements in area under the curve (from 0.9054 to 0.9524), precision (from 43.37% to 66.17%), and recall (from 49.25% to 63.06%). Most importantly, the proposed model successfully predicted the ADRs associated with withdrawal of rofecoxib and cerivastatin. The results suggest that phenotypic information on drugs is valuable for ADR prediction. Moreover, they demonstrate that different models that combine chemical, biological, or phenotypic information can be built from approved drugs, and they have the potential to detect clinically important ADRs in both preclinical and post-marketing phases.

The UL24 protein of herpes simplex virus 1 affects the sub-cellular distribution of viral glycoproteins involved in fusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ben Abdeljelil, Nawel; Rochette, Pierre-Alexandre; Pearson, Angela, E-mail: angela.pearson@iaf.inrs.ca

2013-09-15

Mutations in UL24 of herpes simplex virus type 1 can lead to a syncytial phenotype. We hypothesized that UL24 affects the sub-cellular distribution of viral glycoproteins involved in fusion. In non-immortalized human foreskin fibroblasts (HFFs) we detected viral glycoproteins B (gB), gD, gH and gL present in extended blotches throughout the cytoplasm with limited nuclear membrane staining; however, in HFFs infected with a UL24-deficient virus (UL24X), staining for the viral glycoproteins appeared as long, thin streaks running across the cell. Interestingly, there was a decrease in co-localized staining of gB and gD with F-actin at late times in UL24X-infected HFFs.more » Treatment with chemical agents that perturbed the actin cytoskeleton hindered the formation of UL24X-induced syncytia in these cells. These data support a model whereby the UL24 syncytial phenotype results from a mislocalization of viral glycoproteins late in infection. - Highlights: • UL24 affects the sub-cellular distribution of viral glycoproteins required for fusion. • Sub-cellular distribution of viral glycoproteins varies in cell-type dependent manner. • Drugs targeting actin microfilaments affect formation of UL24-related syncytia in HFFs.« less

Senescent intervertebral disc cells exhibit perturbed matrix homeostasis phenotype.

PubMed

Ngo, Kevin; Patil, Prashanti; McGowan, Sara J; Niedernhofer, Laura J; Robbins, Paul D; Kang, James; Sowa, Gwendolyn; Vo, Nam

2017-09-01

Aging greatly increases the risk for intervertebral disc degeneration (IDD) as a result of proteoglycan loss due to reduced synthesis and enhanced degradation of the disc matrix proteoglycan (PG). How disc matrix PG homeostasis becomes perturbed with age is not known. The goal of this study is to determine whether cellular senescence is a source of this perturbation. We demonstrated that disc cellular senescence is dramatically increased in the DNA repair-deficient Ercc1 -/Δ mouse model of human progeria. In these accelerated aging mice, increased disc cellular senescence is closely associated with the rapid loss of disc PG. We also directly examine PG homeostasis in oxidative damage-induced senescent human cells using an in vitro cell culture model system. Senescence of human disc cells treated with hydrogen peroxide was confirmed by growth arrest, senescence-associated β-galactosidase activity, γH2AX foci, and acquisition of senescence-associated secretory phenotype. Senescent human disc cells also exhibited perturbed matrix PG homeostasis as evidenced by their decreased capacity to synthesize new matrix PG and enhanced degradation of aggrecan, a major matrix PG. of the disc. Our in vivo and in vitro findings altogether suggest that disc cellular senescence is an important driver of PG matrix homeostatic perturbation and PG loss. Published by Elsevier B.V.

Tumor Heterogeneity in Breast Cancer

PubMed Central

Turashvili, Gulisa; Brogi, Edi

2017-01-01

Breast cancer is a heterogeneous disease and differs greatly among different patients (intertumor heterogeneity) and even within each individual tumor (intratumor heterogeneity). Clinical and morphologic intertumor heterogeneity is reflected by staging systems and histopathologic classification of breast cancer. Heterogeneity in the expression of established prognostic and predictive biomarkers, hormone receptors, and human epidermal growth factor receptor 2 oncoprotein is the basis for targeted treatment. Molecular classifications are indicators of genetic tumor heterogeneity, which is probed with multigene assays and can lead to improved stratification into low- and high-risk groups for personalized therapy. Intratumor heterogeneity occurs at the morphologic, genomic, transcriptomic, and proteomic levels, creating diagnostic and therapeutic challenges. Understanding the molecular and cellular mechanisms of tumor heterogeneity that are relevant to the development of treatment resistance is a major area of research. Despite the improved knowledge of the complex genetic and phenotypic features underpinning tumor heterogeneity, there has been only limited advancement in diagnostic, prognostic, or predictive strategies for breast cancer. The current guidelines for reporting of biomarkers aim to maximize patient eligibility for targeted therapy, but do not take into account intratumor heterogeneity. The molecular classification of breast cancer is not implemented in routine clinical practice. Additional studies and in-depth analysis are required to understand the clinical significance of rapidly accumulating data. This review highlights inter- and intratumor heterogeneity of breast carcinoma with special emphasis on pathologic findings, and provides insights into the clinical significance of molecular and cellular mechanisms of heterogeneity. PMID:29276709

PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources.

PubMed

Kahanda, Indika; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa

2015-01-01

The human phenotype ontology (HPO) was recently developed as a standardized vocabulary for describing the phenotype abnormalities associated with human diseases. At present, only a small fraction of human protein coding genes have HPO annotations. But, researchers believe that a large portion of currently unannotated genes are related to disease phenotypes. Therefore, it is important to predict gene-HPO term associations using accurate computational methods. In this work we demonstrate the performance advantage of the structured SVM approach which was shown to be highly effective for Gene Ontology term prediction in comparison to several baseline methods. Furthermore, we highlight a collection of informative data sources suitable for the problem of predicting gene-HPO associations, including large scale literature mining data.

Molecular Genetics of Ubiquinone Biosynthesis in Animals

PubMed Central

Wang, Ying; Hekimi, Siegfried

2014-01-01

Ubiquinone (UQ), also known as coenzyme Q (CoQ), is a redox-active lipid present in all cellular membranes where it functions in a variety of cellular processes. The best known functions of UQ are to act as a mobile electron carrier in the mitochondrial respiratory chain and to serve as a lipid soluble antioxidant in cellular membranes. All eukaryotic cells synthesize their own UQ. Most of the current knowledge on the UQ biosynthetic pathway was obtained by studying Escherichia coli and S. cerevisiae UQ-deficient mutants. The orthologues of all the genes known from yeast studies to be involved in UQ biosynthesis have subsequently been found in higher organisms. Animal mutants with different genetic defects in UQ biosynthesis display very different phenotypes, despite the fact that in all these mutants the same biosynthetic pathway is affected. This review summarizes the present knowledge of the eukaryotic biosynthesis of UQ, with focus on the biosynthetic genes identified in animals, including C. elegans, rodents and humans. Moreover, we review the phenotypes of mutants in these genes and discuss the functional consequences of UQ deficiency in general. PMID:23190198

The effect of hydrodynamic conditions on the phenotype of Pseudomonas fluorescens biofilms.

PubMed

Simões, Manuel; Pereira, Maria O; Sillankorva, Sanna; Azeredo, Joana; Vieira, Maria J

2007-01-01

This study investigated the phenotypic characteristics of monoculture P. fluorescens biofilms grown under turbulent and laminar flow, using flow cells reactors with stainless steel substrata. The cellular physiology and the overall biofilm activity, structure and composition were characterized, and compared, within hydrodynamically distinct conditions. The results indicate that turbulent flow-generated biofilm cells were significantly less extensive, with decreased metabolic activity and a lower protein and polysaccharides composition per cell than those from laminar flow-generated biofilms. The effect of flow regime did not cause significantly different outer membrane protein expression. From the analysis of biofilm activity, structure and composition, turbulent flow-generated biofilms were metabolically more active, had twice more mass per cm(2), and higher cellular density and protein content (mainly cellular) than laminar flow-generated biofilms. Conversely, laminar flow-generated biofilms presented higher total and matrix polysaccharide contents. Direct visualisation and scanning electron microscopy analysis showed that these different flows generate structurally different biofilms, corroborating the quantitative results. The combination of applied methods provided useful information regarding a broad spectrum of biofilm parameters, which can contribute to control and model biofilm processes.

New concept: cellular senescence in pathophysiology of cholangiocarcinoma.

PubMed

Sasaki, Motoko; Nakanuma, Yasuni

2016-01-01

Cholangiocarcinoma, a malignant tumor arising in the hepatobiliary system, presents with poor prognosis because of difficulty in its early detection/diagnosis. Recent progress revealed that cellular senescence may be involved in the pathophysiology of cholangiocarcinoma. Cellular senescence is defined as permanent growth arrest caused by several cellular injuries, such as oncogenic mutations and oxidative stress. "Oncogene-induced" and/or stress-induced senescence may occur in the process of multi-step cholangiocarcinogenesis, and overexpression of a polycomb group protein EZH2 may play a role in the escape from, and/or bypassing of, senescence. Furthermore, senescent cells may play important roles in tumor development and progression via the production of senescence-associated secretory phenotypes. Cellular senescence may be a new target for the prevention, early diagnosis, and therapy of cholangiocarcinoma in the near future.

Quantitative Assessment of Thermodynamic Constraints on the Solution Space of Genome-Scale Metabolic Models

PubMed Central

Hamilton, Joshua J.; Dwivedi, Vivek; Reed, Jennifer L.

2013-01-01

Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. PMID:23870272

Functional analysis of rare variants in mismatch repair proteins augments results from computation-based predictive methods

PubMed Central

Arora, Sanjeevani; Huwe, Peter J.; Sikder, Rahmat; Shah, Manali; Browne, Amanda J.; Lesh, Randy; Nicolas, Emmanuelle; Deshpande, Sanat; Hall, Michael J.; Dunbrack, Roland L.; Golemis, Erica A.

2017-01-01

ABSTRACT The cancer-predisposing Lynch Syndrome (LS) arises from germline mutations in DNA mismatch repair (MMR) genes, predominantly MLH1, MSH2, MSH6, and PMS2. A major challenge for clinical diagnosis of LS is the frequent identification of variants of uncertain significance (VUS) in these genes, as it is often difficult to determine variant pathogenicity, particularly for missense variants. Generic programs such as SIFT and PolyPhen-2, and MMR gene-specific programs such as PON-MMR and MAPP-MMR, are often used to predict deleterious or neutral effects of VUS in MMR genes. We evaluated the performance of multiple predictive programs in the context of functional biologic data for 15 VUS in MLH1, MSH2, and PMS2. Using cell line models, we characterized VUS predicted to range from neutral to pathogenic on mRNA and protein expression, basal cellular viability, viability following treatment with a panel of DNA-damaging agents, and functionality in DNA damage response (DDR) signaling, benchmarking to wild-type MMR proteins. Our results suggest that the MMR gene-specific classifiers do not always align with the experimental phenotypes related to DDR. Our study highlights the importance of complementary experimental and computational assessment to develop future predictors for the assessment of VUS. PMID:28494185

Virtual Institute of Microbial Stress and Survival: Deduction of Stress Response Pathways in Metal and Radionuclide Reducing Microorganisms

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2004-04-17

The projects application goals are to: (1) To understand bacterial stress-response to the unique stressors in metal/radionuclide contamination sites; (2) To turn this understanding into a quantitative, data-driven model for exploring policies for natural and biostimulatory bioremediation; (3) To implement proposed policies in the field and compare results to model predictions; and (4) Close the experimental/computation cycle by using discrepancies between models and predictions to drive new measurements and construction of new models. The projects science goals are to: (1) Compare physiological and molecular response of three target microorganisms to environmental perturbation; (2) Deduce the underlying regulatory pathways that controlmore » these responses through analysis of phenotype, functional genomic, and molecular interaction data; (3) Use differences in the cellular responses among the target organisms to understand niche specific adaptations of the stress and metal reduction pathways; (4) From this analysis derive an understanding of the mechanisms of pathway evolution in the environment; and (5) Ultimately, derive dynamical models for the control of these pathways to predict how natural stimulation can optimize growth and metal reduction efficiency at field sites.« less

Computer Simulation of Embryonic Systems: What can a ...

EPA Pesticide Factsheets

(1) Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative pr

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative predic

Molecular Pathways: Extracting Medical Knowledge from High Throughput Genomic Data

PubMed Central

Goldstein, Theodore; Paull, Evan O.; Ellis, Matthew J.; Stuart, Joshua M.

2013-01-01

High-throughput genomic data that measures RNA expression, DNA copy number, mutation status and protein levels provide us with insights into the molecular pathway structure of cancer. Genomic lesions (amplifications, deletions, mutations) and epigenetic modifications disrupt biochemical cellular pathways. While the number of possible lesions is vast, different genomic alterations may result in concordant expression and pathway activities, producing common tumor subtypes that share similar phenotypic outcomes. How can these data be translated into medical knowledge that provides prognostic and predictive information? First generation mRNA expression signatures such as Genomic Health's Oncotype DX already provide prognostic information, but do not provide therapeutic guidance beyond the current standard of care – which is often inadequate in high-risk patients. Rather than building molecular signatures based on gene expression levels, evidence is growing that signatures based on higher-level quantities such as from genetic pathways may provide important prognostic and diagnostic cues. We provide examples of how activities for molecular entities can be predicted from pathway analysis and how the composite of all such activities, referred to here as the “activitome,” help connect genomic events to clinical factors in order to predict the drivers of poor outcome. PMID:23430023

Environmental and genetic modulation of the phenotypic expression of antibiotic resistance

PubMed Central

Andersson, Dan I

2017-01-01

Abstract Antibiotic resistance can be acquired by mutation or horizontal transfer of a resistance gene, and generally an acquired mechanism results in a predictable increase in phenotypic resistance. However, recent findings suggest that the environment and/or the genetic context can modify the phenotypic expression of specific resistance genes/mutations. An important implication from these findings is that a given genotype does not always result in the expected phenotype. This dissociation of genotype and phenotype has important consequences for clinical bacteriology and for our ability to predict resistance phenotypes from genetics and DNA sequences. A related problem concerns the degree to which the genes/mutations currently identified in vitro can fully explain the in vivo resistance phenotype, or whether there is a significant additional amount of presently unknown mutations/genes (genetic ‘dark matter’) that could contribute to resistance in clinical isolates. Finally, a very important question is whether/how we can identify the genetic features that contribute to making a successful pathogen, and predict why some resistant clones are very successful and spread globally? In this review, we describe different environmental and genetic factors that influence phenotypic expression of antibiotic resistance genes/mutations and how this information is needed to understand why particular resistant clones spread worldwide and to what extent we can use DNA sequences to predict evolutionary success. PMID:28333270

Multicenter Evaluation of the Accelerate PhenoTest BC Kit for Rapid Identification and Phenotypic Antimicrobial Susceptibility Testing Using Morphokinetic Cellular Analysis

PubMed Central

2018-01-01

ABSTRACT We describe results from a multicenter study evaluating the Accelerate Pheno system, a first of its kind diagnostic system that rapidly identifies common bloodstream pathogens from positive blood cultures within 90 min and determines bacterial phenotypic antimicrobial susceptibility testing (AST) results within ∼7 h. A combination of fresh clinical and seeded blood cultures were tested, and results from the Accelerate Pheno system were compared to Vitek 2 results for identification (ID) and broth microdilution or disk diffusion for AST. The Accelerate Pheno system accurately identified 14 common bacterial pathogens and two Candida spp. with sensitivities ranging from 94.6 to 100%. Of fresh positive blood cultures, 89% received a monomicrobial call with a positive predictive value of 97.3%. Six common Gram-positive cocci were evaluated for ID. Five were tested against eight antibiotics, two resistance phenotypes (methicillin-resistant Staphylococcus aureus and Staphylococcus spp. [MRSA/MRS]), and inducible clindamycin resistance (MLSb). From the 4,142 AST results, the overall essential agreement (EA) and categorical agreement (CA) were 97.6% and 97.9%, respectively. Overall very major error (VME), major error (ME), and minor error (mE) rates were 1.0%, 0.7%, and 1.3%, respectively. Eight species of Gram-negative rods were evaluated against 15 antibiotics. From the 6,331 AST results, overall EA and CA were 95.4% and 94.3%, respectively. Overall VME, ME, and mE rates were 0.5%, 0.9%, and 4.8%, respectively. The Accelerate Pheno system has the unique ability to identify and provide phenotypic MIC and categorical AST results in a few hours directly from positive blood culture bottles and support accurate antimicrobial adjustment. PMID:29305546

Mutations in PIGY: expanding the phenotype of inherited glycosylphosphatidylinositol deficiencies

PubMed Central

Ilkovski, Biljana; Pagnamenta, Alistair T.; O'Grady, Gina L.; Kinoshita, Taroh; Howard, Malcolm F.; Lek, Monkol; Thomas, Brett; Turner, Anne; Christodoulou, John; Sillence, David; Knight, Samantha J.L.; Popitsch, Niko; Keays, David A.; Anzilotti, Consuelo; Goriely, Anne; Waddell, Leigh B.; Brilot, Fabienne; North, Kathryn N.; Kanzawa, Noriyuki; Macarthur, Daniel G.; Taylor, Jenny C.; Kini, Usha; Murakami, Yoshiko; Clarke, Nigel F.

2015-01-01

Glycosylphosphatidylinositol (GPI)-anchored proteins are ubiquitously expressed in the human body and are important for various functions at the cell surface. Mutations in many GPI biosynthesis genes have been described to date in patients with multi-system disease and together these constitute a subtype of congenital disorders of glycosylation. We used whole exome sequencing in two families to investigate the genetic basis of disease and used RNA and cellular studies to investigate the functional consequences of sequence variants in the PIGY gene. Two families with different phenotypes had homozygous recessive sequence variants in the GPI biosynthesis gene PIGY. Two sisters with c.137T>C (p.Leu46Pro) PIGY variants had multi-system disease including dysmorphism, seizures, severe developmental delay, cataracts and early death. There were significantly reduced levels of GPI-anchored proteins (CD55 and CD59) on the surface of patient-derived skin fibroblasts (∼20–50% compared with controls). In a second, consanguineous family, two siblings had moderate development delay and microcephaly. A homozygous PIGY promoter variant (c.-540G>A) was detected within a 7.7 Mb region of autozygosity. This variant was predicted to disrupt a SP1 consensus binding site and was shown to be associated with reduced gene expression. Mutations in PIGY can occur in coding and non-coding regions of the gene and cause variable phenotypes. This article contributes to understanding of the range of disease phenotypes and disease genes associated with deficiencies of the GPI-anchor biosynthesis pathway and also serves to highlight the potential importance of analysing variants detected in 5′-UTR regions despite their typically low coverage in exome data. PMID:26293662

Mutations in PIGY: expanding the phenotype of inherited glycosylphosphatidylinositol deficiencies.

PubMed

Ilkovski, Biljana; Pagnamenta, Alistair T; O'Grady, Gina L; Kinoshita, Taroh; Howard, Malcolm F; Lek, Monkol; Thomas, Brett; Turner, Anne; Christodoulou, John; Sillence, David; Knight, Samantha J L; Popitsch, Niko; Keays, David A; Anzilotti, Consuelo; Goriely, Anne; Waddell, Leigh B; Brilot, Fabienne; North, Kathryn N; Kanzawa, Noriyuki; Macarthur, Daniel G; Taylor, Jenny C; Kini, Usha; Murakami, Yoshiko; Clarke, Nigel F

2015-11-01

Glycosylphosphatidylinositol (GPI)-anchored proteins are ubiquitously expressed in the human body and are important for various functions at the cell surface. Mutations in many GPI biosynthesis genes have been described to date in patients with multi-system disease and together these constitute a subtype of congenital disorders of glycosylation. We used whole exome sequencing in two families to investigate the genetic basis of disease and used RNA and cellular studies to investigate the functional consequences of sequence variants in the PIGY gene. Two families with different phenotypes had homozygous recessive sequence variants in the GPI biosynthesis gene PIGY. Two sisters with c.137T>C (p.Leu46Pro) PIGY variants had multi-system disease including dysmorphism, seizures, severe developmental delay, cataracts and early death. There were significantly reduced levels of GPI-anchored proteins (CD55 and CD59) on the surface of patient-derived skin fibroblasts (∼20-50% compared with controls). In a second, consanguineous family, two siblings had moderate development delay and microcephaly. A homozygous PIGY promoter variant (c.-540G>A) was detected within a 7.7 Mb region of autozygosity. This variant was predicted to disrupt a SP1 consensus binding site and was shown to be associated with reduced gene expression. Mutations in PIGY can occur in coding and non-coding regions of the gene and cause variable phenotypes. This article contributes to understanding of the range of disease phenotypes and disease genes associated with deficiencies of the GPI-anchor biosynthesis pathway and also serves to highlight the potential importance of analysing variants detected in 5'-UTR regions despite their typically low coverage in exome data. © The Author 2015. Published by Oxford University Press.

Monte Carlo simulation of a simple gene network yields new evolutionary insights.

PubMed

Andrecut, M; Cloud, D; Kauffman, S A

2008-02-07

Monte Carlo simulations of a genetic toggle switch show that its behavior can be more complex than analytic models would suggest. We show here that as a result of the interplay between frequent and infrequent reaction events, such a switch can have more stable states than an analytic model would predict, and that the number and character of these states depend to a large extent on the propensity of transcription factors to bind to and dissociate from promoters. The effects of gene duplications differ even more; in analytic models, these seem to result in the disappearance of bi-stability and thus a loss of the switching function, but a Monte Carlo simulation shows that they can result in the appearance of new stable states without the loss of old ones, and thus in an increase of the complexity of the switch's behavior which may facilitate the evolution of new cellular functions. These differences are of interest with respect to the evolution of gene networks, particularly in clonal lines of cancer cells, where the duplication of active genes is an extremely common event, and often seems to result in the appearance of viable new cellular phenotypes.

Untargeted Metabolomics Strategies—Challenges and Emerging Directions

NASA Astrophysics Data System (ADS)

Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

2016-12-01

Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

Archimedes' principle for characterisation of recombinant whole cell biocatalysts.

PubMed

Schmitt, Steven; Walser, Marcel; Rehmann, Michael; Oesterle, Sabine; Panke, Sven; Held, Martin

2018-02-14

The ability of whole cells to catalyse multistep reactions, often yielding synthetically demanding compounds later used by industrial biotech or pharma, makes them an indispensable tool of synthetic chemistry. The complex reaction network employed by cellular catalysts and the still only moderate predictive power of modelling approaches leaves this tool challenging to engineer. Frequently, large libraries of semi-rationally generated variants are sampled in high-throughput mode in order to then identify improved catalysts. We present a method for space- and time-efficient processing of very large libraries (10 7 ) of recombinant cellular catalysts, in which the phenotypic characterisation and the isolation of positive variants for the entire library is done within one minute in a single, highly parallelized operation. Specifically, product formation in nanolitre-sized cultivation vessels is sensed and translated into the formation of catalase as a reporter protein. Exposure to hydrogen peroxide leads to oxygen gas formation and thus to a density shift of the cultivation vessel. Exploiting Archimedes' principle, this density shift and the resulting upward buoyancy force can be used for batch-wise library sampling. We demonstrate the potential of the method for both, screening and selection protocols, and envision a wide applicability of the system for biosensor-based assays.

Systemic deregulation of autophagy upon loss of ALS- and FTD-linked C9orf72.

PubMed

Ji, Yon Ju; Ugolino, Janet; Brady, Nathan Ryan; Hamacher-Brady, Anne; Wang, Jiou

2017-07-03

A genetic mutation in the C9orf72 gene causes the most common forms of neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The C9orf72 protein, predicted to be a DENN-family protein, is reduced in ALS and FTD, but its functions remain poorly understood. Using a 3110043O21Rik/C9orf72 knockout mouse model, as well as cellular analysis, we have found that loss of C9orf72 causes alterations in the signaling states of central autophagy regulators. In particular, C9orf72 depletion leads to reduced activity of MTOR, a negative regulator of macroautophagy/autophagy, and concomitantly increased TFEB levels and nuclear translocation. Consistent with these alterations, cells exhibit enlarged lysosomal compartments and enhanced autophagic flux. Loss of the C9orf72 interaction partner SMCR8 results in similar phenotypes. Our findings suggest that C9orf72 functions as a potent negative regulator of autophagy, with a central role in coupling the cellular metabolic state with autophagy regulation. We thus propose C9orf72 as a fundamental component of autophagy signaling with implications in basic cell physiology and pathophysiology, including neurodegeneration.

Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model.

PubMed

Aridhi, Sabeur; Sghaier, Haïtham; Zoghlami, Manel; Maddouri, Mondher; Nguifo, Engelbert Mephu

2016-01-01

Ionizing-radiation-resistant bacteria (IRRB) are important in biotechnology. In this context, in silico methods of phenotypic prediction and genotype-phenotype relationship discovery are limited. In this work, we analyzed basal DNA repair proteins of most known proteome sequences of IRRB and ionizing-radiation-sensitive bacteria (IRSB) in order to learn a classifier that correctly predicts this bacterial phenotype. We formulated the problem of predicting bacterial ionizing radiation resistance (IRR) as a multiple-instance learning (MIL) problem, and we proposed a novel approach for this purpose. We provide a MIL-based prediction system that classifies a bacterium to either IRRB or IRSB. The experimental results of the proposed system are satisfactory with 91.5% of successful predictions.

A genome-scale metabolic flux model of Escherichia coli K–12 derived from the EcoCyc database

PubMed Central

2014-01-01

Background Constraint-based models of Escherichia coli metabolic flux have played a key role in computational studies of cellular metabolism at the genome scale. We sought to develop a next-generation constraint-based E. coli model that achieved improved phenotypic prediction accuracy while being frequently updated and easy to use. We also sought to compare model predictions with experimental data to highlight open questions in E. coli biology. Results We present EcoCyc–18.0–GEM, a genome-scale model of the E. coli K–12 MG1655 metabolic network. The model is automatically generated from the current state of EcoCyc using the MetaFlux software, enabling the release of multiple model updates per year. EcoCyc–18.0–GEM encompasses 1445 genes, 2286 unique metabolic reactions, and 1453 unique metabolites. We demonstrate a three-part validation of the model that breaks new ground in breadth and accuracy: (i) Comparison of simulated growth in aerobic and anaerobic glucose culture with experimental results from chemostat culture and simulation results from the E. coli modeling literature. (ii) Essentiality prediction for the 1445 genes represented in the model, in which EcoCyc–18.0–GEM achieves an improved accuracy of 95.2% in predicting the growth phenotype of experimental gene knockouts. (iii) Nutrient utilization predictions under 431 different media conditions, for which the model achieves an overall accuracy of 80.7%. The model’s derivation from EcoCyc enables query and visualization via the EcoCyc website, facilitating model reuse and validation by inspection. We present an extensive investigation of disagreements between EcoCyc–18.0–GEM predictions and experimental data to highlight areas of interest to E. coli modelers and experimentalists, including 70 incorrect predictions of gene essentiality on glucose, 80 incorrect predictions of gene essentiality on glycerol, and 83 incorrect predictions of nutrient utilization. Conclusion Significant advantages can be derived from the combination of model organism databases and flux balance modeling represented by MetaFlux. Interpretation of the EcoCyc database as a flux balance model results in a highly accurate metabolic model and provides a rigorous consistency check for information stored in the database. PMID:24974895

Ascites-induced shift along epithelial-mesenchymal spectrum in ovarian cancer cells: enhancement of their invasive behavior partly dependant on αv integrins.

PubMed

Carduner, L; Leroy-Dudal, J; Picot, C R; Gallet, O; Carreiras, F; Kellouche, S

2014-08-01

At least one-third of patients with epithelial ovarian cancer (OC) present ascites at diagnosis and almost all have ascites at recurrence. The presence of ascites, which acts as a dynamic reservoir of active molecules and cellular components, correlates with the OC peritoneal metastasis and is associated with poor prognosis. Since epithelial-mesenchymal transition (EMT) is involved in different phases of OC progression, we have investigated the effect of the unique ascitic tumor microenvironment on the EMT status and the behavior of OC cells. The exposure of three OC cell lines to ascites leads to changes in cellular morphologies. Within ascites, OC cells harboring an initial intermediate epithelial phenotype are characterized by marked dislocation of epithelial markers (E-cadherin, ZO-1 staining) while OC cells initially harboring an intermediate mesenchymal phenotype strengthen their mesenchymal markers (N-cadherin, vimentin). Ascites differentially triggers a dissemination phenotype related to the initial cell features by either allowing the proliferation and the formation of spheroids and the extension of colonies for cells that present an initial epithelial intermediate phenotype, or favoring the migration of cells with a mesenchymal intermediate phenotype. In an ascitic microenvironment, a redeployment of αv integrins into cells was observed and the ascites-induced accentuation of the two different invasive phenotypes (i.e. spheroids formation or migration) was shown to involve αv integrins. Thus, ascites induces a shift toward an unstable intermediate state of the epithelial-mesenchymal spectrum and confers a more aggressive cell behavior that takes on a different pathway based on the initial epithelial-mesenchymal cell features.

Notch3 Maintains Luminal Phenotype and Suppresses Tumorigenesis and Metastasis of Breast Cancer via Trans-Activating Estrogen Receptor-α.

PubMed

Dou, Xiao-Wei; Liang, Yuan-Ke; Lin, Hao-Yu; Wei, Xiao-Long; Zhang, Yong-Qu; Bai, Jing-Wen; Chen, Chun-Fa; Chen, Min; Du, Cai-Wen; Li, Yao-Chen; Tian, Jie; Man, Kwan; Zhang, Guo-Jun

2017-01-01

The luminal A phenotype is the most common breast cancer subtype and is characterized by estrogen receptor α expression (ERα). Identification of the key regulator that governs the luminal phenotype of breast cancer will clarify the pathogenic mechanism and provide novel therapeutic strategies for this subtype of cancer. ERα signaling pathway sustains the epithelial phenotype and inhibits the epithelial-mesenchymal transition (EMT) of breast cancer. In this study, we demonstrate that Notch3 positively associates with ERα in both breast cancer cell lines and human breast cancer tissues. We found that overexpression of Notch3 intra-cellular domain, a Notch3 active form (N3ICD), in ERα negative breast cancer cells re-activated ERα, while knock-down of Notch3 reduced ERα transcript and proteins, with alteration of down-stream genes, suggesting its ability to regulate ERα. Mechanistically, our results show that Notch3 specifically binds to the CSL binding element of the ERα promoter and activates ERα expression. Moreover, Notch3 suppressed EMT, while suppression of Notch3 promoted EMT in cellular assay. Overexpressing N3ICD in triple-negative breast cancer suppressed tumorigenesis and metastasis in vivo . Conversely, depletion of Notch3 in luminal breast cancer promoted metastasis in vivo . Furthermore, Notch3 transcripts were significantly associated with prolonged relapse-free survival in breast cancer, in particular in ERα positive breast cancer patients. Our observations demonstrate that Notch3 governs the luminal phenotype via trans-activating ERα expression in breast cancer. These findings delineate the role of a Notch3/ERα axis in maintaining the luminal phenotype and inhibiting tumorigenesis and metastasis in breast cancer, providing a novel strategy to re-sensitize ERα negative or low-expressing breast cancers to hormone therapy.

Notch3 Maintains Luminal Phenotype and Suppresses Tumorigenesis and Metastasis of Breast Cancer via Trans-Activating Estrogen Receptor-α

PubMed Central

Dou, Xiao-Wei; Liang, Yuan-Ke; Lin, Hao-Yu; Wei, Xiao-Long; Zhang, Yong-Qu; Bai, Jing-Wen; Chen, Chun-Fa; Chen, Min; Du, Cai-Wen; Li, Yao-Chen; Tian, Jie; Man, Kwan; Zhang, Guo-Jun

2017-01-01

The luminal A phenotype is the most common breast cancer subtype and is characterized by estrogen receptor α expression (ERα). Identification of the key regulator that governs the luminal phenotype of breast cancer will clarify the pathogenic mechanism and provide novel therapeutic strategies for this subtype of cancer. ERα signaling pathway sustains the epithelial phenotype and inhibits the epithelial-mesenchymal transition (EMT) of breast cancer. In this study, we demonstrate that Notch3 positively associates with ERα in both breast cancer cell lines and human breast cancer tissues. We found that overexpression of Notch3 intra-cellular domain, a Notch3 active form (N3ICD), in ERα negative breast cancer cells re-activated ERα, while knock-down of Notch3 reduced ERα transcript and proteins, with alteration of down-stream genes, suggesting its ability to regulate ERα. Mechanistically, our results show that Notch3 specifically binds to the CSL binding element of the ERα promoter and activates ERα expression. Moreover, Notch3 suppressed EMT, while suppression of Notch3 promoted EMT in cellular assay. Overexpressing N3ICD in triple-negative breast cancer suppressed tumorigenesis and metastasis in vivo. Conversely, depletion of Notch3 in luminal breast cancer promoted metastasis in vivo. Furthermore, Notch3 transcripts were significantly associated with prolonged relapse-free survival in breast cancer, in particular in ERα positive breast cancer patients. Our observations demonstrate that Notch3 governs the luminal phenotype via trans-activating ERα expression in breast cancer. These findings delineate the role of a Notch3/ERα axis in maintaining the luminal phenotype and inhibiting tumorigenesis and metastasis in breast cancer, providing a novel strategy to re-sensitize ERα negative or low-expressing breast cancers to hormone therapy. PMID:29109797

Single-cell protein secretomic signatures as potential correlates to tumor cell lineage evolution and cell–cell interaction

PubMed Central

Kwak, Minsuk; Mu, Luye; Lu, Yao; Chen, Jonathan J.; Brower, Kara; Fan, Rong

2013-01-01

Secreted proteins including cytokines, chemokines, and growth factors represent important functional regulators mediating a range of cellular behavior and cell–cell paracrine/autocrine signaling, e.g., in the immunological system (Rothenberg, 2007), tumor microenvironment (Hanahan and Weinberg, 2011), or stem cell niche (Gnecchi etal., 2008). Detection of these proteins is of great value not only in basic cell biology but also for diagnosis and therapeutic monitoring of human diseases such as cancer. However, due to co-production of multiple effector proteins from a single cell, referred to as polyfunctionality, it is biologically informative to measure a panel of secreted proteins, or secretomic signature, at the level of single cells. Recent evidence further indicates that a genetically identical cell population can give rise to diverse phenotypic differences (Niepel etal., 2009). Non-genetic heterogeneity is also emerging as a potential barrier to accurate monitoring of cellular immunity and effective pharmacological therapies (Cohen etal., 2008; Gascoigne and Taylor, 2008), but can hardly assessed using conventional approaches that do not examine cellular phenotype at the functional level. It is known that cytokines, for example, in the immune system define the effector functions and lineage differentiation of immune cells. In this article, we hypothesize that protein secretion profile may represent a universal measure to identify the definitive correlate in the larger context of cellular functions to dissect cellular heterogeneity and evolutionary lineage relationship in human cancer. PMID:23390614

Slug is upregulated during wound healing and regulates cellular phenotypes in corneal epithelial cells.

PubMed

Aomatsu, Keiichi; Arao, Tokuzo; Abe, Kosuke; Kodama, Aya; Sugioka, Koji; Matsumoto, Kazuko; Kudo, Kanae; Kimura, Hideharu; Fujita, Yoshihiko; Hayashi, Hidetoshi; Nagai, Tomoyuki; Shimomura, Yoshikazu; Nishio, Kazuto

2012-02-16

The involvement of the epithelial mesenchymal transition (EMT) in the process of corneal wound healing remains largely unclear. The purpose of the present study was to gain insight into Slug expression and corneal wound healing. Slug expression during wound healing in the murine cornea was evaluated using fluorescence staining in vivo. Slug or Snail was stably introduced into human corneal epithelial cells (HCECs). These stable transfectants were evaluated for the induction of the EMT, cellular growth, migration activity, and expression changes in differentiation-related molecules. Slug, but not Snail, was clearly expressed in the nuclei of corneal epithelial cells in basal lesion of the corneal epithelium during wound healing in vivo. The overexpression of Slug or Snail induced an EMT-like cellular morphology and cadherin switching in HCECs, indicating that these transcription factors were able to mediate the typical EMT in HCECs. The overexpression of Slug or Snail suppressed cellular proliferation but enhanced the migration activity. Furthermore, ABCG2, TP63, and keratin 19, which are known as stemness-related molecules, were downregulated in these transfectants. It was found that Slug is upregulated during corneal wound healing in vivo. The overexpression of Slug mediated a change in the cellular phenotype affecting proliferation, migration, and expression levels of differentiation-related molecules. This is the first evidence that Slug is regulated during the process of corneal wound healing in the corneal epithelium in vivo, providing a novel insight into the EMT and Slug expression in corneal wound healing.

Recurrent gene loss correlates with the evolution of stomach phenotypes in gnathostome history

PubMed Central

Castro, L. Filipe C.; Gonçalves, Odete; Mazan, Sylvie; Tay, Boon-Hui; Venkatesh, Byrappa; Wilson, Jonathan M.

2014-01-01

The stomach, a hallmark of gnathostome evolution, represents a unique anatomical innovation characterized by the presence of acid- and pepsin-secreting glands. However, the occurrence of these glands in gnathostome species is not universal; in the nineteenth century the French zoologist Cuvier first noted that some teleosts lacked a stomach. Strikingly, Holocephali (chimaeras), dipnoids (lungfish) and monotremes (egg-laying mammals) also lack acid secretion and a gastric cellular phenotype. Here, we test the hypothesis that loss of the gastric phenotype is correlated with the loss of key gastric genes. We investigated species from all the main gnathostome lineages and show the specific contribution of gene loss to the widespread distribution of the agastric condition. We establish that the stomach loss correlates with the persistent and complete absence of the gastric function gene kit—H+/K+-ATPase (Atp4A and Atp4B) and pepsinogens (Pga, Pgc, Cym)—in the analysed species. We also find that in gastric species the pepsinogen gene complement varies significantly (e.g. two to four in teleosts and tens in some mammals) with multiple events of pseudogenization identified in various lineages. We propose that relaxation of purifying selection in pepsinogen genes and possibly proton pump genes in response to dietary changes led to the numerous independent events of stomach loss in gnathostome history. Significantly, the absence of the gastric genes predicts that reinvention of the stomach in agastric lineages would be highly improbable, in line with Dollo's principle. PMID:24307675

Recurrent gene loss correlates with the evolution of stomach phenotypes in gnathostome history.

PubMed

Castro, L Filipe C; Gonçalves, Odete; Mazan, Sylvie; Tay, Boon-Hui; Venkatesh, Byrappa; Wilson, Jonathan M

2014-01-22

The stomach, a hallmark of gnathostome evolution, represents a unique anatomical innovation characterized by the presence of acid- and pepsin-secreting glands. However, the occurrence of these glands in gnathostome species is not universal; in the nineteenth century the French zoologist Cuvier first noted that some teleosts lacked a stomach. Strikingly, Holocephali (chimaeras), dipnoids (lungfish) and monotremes (egg-laying mammals) also lack acid secretion and a gastric cellular phenotype. Here, we test the hypothesis that loss of the gastric phenotype is correlated with the loss of key gastric genes. We investigated species from all the main gnathostome lineages and show the specific contribution of gene loss to the widespread distribution of the agastric condition. We establish that the stomach loss correlates with the persistent and complete absence of the gastric function gene kit--H(+)/K(+)-ATPase (Atp4A and Atp4B) and pepsinogens (Pga, Pgc, Cym)--in the analysed species. We also find that in gastric species the pepsinogen gene complement varies significantly (e.g. two to four in teleosts and tens in some mammals) with multiple events of pseudogenization identified in various lineages. We propose that relaxation of purifying selection in pepsinogen genes and possibly proton pump genes in response to dietary changes led to the numerous independent events of stomach loss in gnathostome history. Significantly, the absence of the gastric genes predicts that reinvention of the stomach in agastric lineages would be highly improbable, in line with Dollo's principle.

3D-3-culture: A tool to unveil macrophage plasticity in the tumour microenvironment.

PubMed

Rebelo, Sofia P; Pinto, Catarina; Martins, Tatiana R; Harrer, Nathalie; Estrada, Marta F; Loza-Alvarez, Pablo; Cabeçadas, José; Alves, Paula M; Gualda, Emilio J; Sommergruber, Wolfgang; Brito, Catarina

2018-05-01

The tumour microenvironment (TME) shapes disease progression and influences therapeutic response. Most aggressive solid tumours have high levels of myeloid cell infiltration, namely tumour associated macrophages (TAM). Recapitulation of the interaction between the different cellular players of the TME, along with the extracellular matrix (ECM), is critical for understanding the mechanisms underlying disease progression. This particularly holds true for prediction of therapeutic response(s) to standard therapies and interrogation of efficacy of TME-targeting agents. In this work, we explored a culture platform based on alginate microencapsulation and stirred culture systems to develop the 3D-3-culture, which entails the co-culture of tumour cell spheroids of non-small cell lung carcinoma (NSCLC), cancer associated fibroblasts (CAF) and monocytes. We demonstrate that the 3D-3-culture recreates an invasive and immunosuppressive TME, with accumulation of cytokines/chemokines (IL4, IL10, IL13, CCL22, CCL24, CXCL1), ECM elements (collagen type I, IV and fibronectin) and matrix metalloproteinases (MMP1/9), supporting cell migration and promoting cell-cell interactions within the alginate microcapsules. Importantly, we show that both the monocytic cell line THP-1 and peripheral blood-derived monocytes infiltrate the tumour tissue and transpolarize into an M2-like macrophage phenotype expressing CD68, CD163 and CD206, resembling the TAM phenotype in NSCLC. The 3D-3-culture was challenged with chemo- and immunotherapeutic agents and the response to therapy was assessed in each cellular component. Specifically, the macrophage phenotype was modulated upon treatment with the CSF1R inhibitor BLZ945, resulting in a decrease of the M2-like macrophages. In conclusion, the crosstalk between the ECM and tumour, stromal and immune cells in microencapsulated 3D-3-culture promotes the activation of monocytes into TAM, mimicking aggressive tumour stages. The 3D-3-culture constitutes a novel tool to study tumour-immune interaction and macrophage plasticity in response to external stimuli, such as chemotherapeutic and immunomodulatory drugs. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2016-01-01

The hypertriglyceridemic waist (HW) phenotype is strongly associated with type 2 diabetes; however, to date, no study has assessed the predictive power of phenotypes based on individual anthropometric measurements and triglyceride (TG) levels. The aims of the present study were to assess the association between the HW phenotype and type 2 diabetes in Korean adults and to evaluate the predictive power of various phenotypes consisting of combinations of individual anthropometric measurements and TG levels. Between November 2006 and August 2013, 11,937 subjects participated in this retrospective cross-sectional study. We measured fasting plasma glucose and TG levels and performed anthropometric measurements. We employed binary logistic regression (LR) to examine statistically significant differences between normal subjects and those with type 2 diabetes using HW and individual anthropometric measurements. For more reliable prediction results, two machine learning algorithms, naive Bayes (NB) and LR, were used to evaluate the predictive power of various phenotypes. All prediction experiments were performed using a tenfold cross validation method. Among all of the variables, the presence of HW was most strongly associated with type 2 diabetes (p < 0.001, adjusted odds ratio (OR) = 2.07 [95% CI, 1.72-2.49] in men; p < 0.001, adjusted OR = 2.09 [1.79-2.45] in women). When comparing waist circumference (WC) and TG levels as components of the HW phenotype, the association between WC and type 2 diabetes was greater than the association between TG and type 2 diabetes. The phenotypes tended to have higher predictive power in women than in men. Among the phenotypes, the best predictors of type 2 diabetes were waist-to-hip ratio + TG in men (AUC by NB = 0.653, AUC by LR = 0.661) and rib-to-hip ratio + TG in women (AUC by NB = 0.73, AUC by LR = 0.735). Although the presence of HW demonstrated the strongest association with type 2 diabetes, the predictive power of the combined measurements of the actual WC and TG values may not be the best manner of predicting type 2 diabetes. Our findings may provide clinical information concerning the development of clinical decision support systems for the initial screening of type 2 diabetes.

Phenotypic screening in cancer drug discovery - past, present and future.

PubMed

Moffat, John G; Rudolph, Joachim; Bailey, David

2014-08-01

There has been a resurgence of interest in the use of phenotypic screens in drug discovery as an alternative to target-focused approaches. Given that oncology is currently the most active therapeutic area, and also one in which target-focused approaches have been particularly prominent in the past two decades, we investigated the contribution of phenotypic assays to oncology drug discovery by analysing the origins of all new small-molecule cancer drugs approved by the US Food and Drug Administration (FDA) over the past 15 years and those currently in clinical development. Although the majority of these drugs originated from target-based discovery, we identified a significant number whose discovery depended on phenotypic screening approaches. We postulate that the contribution of phenotypic screening to cancer drug discovery has been hampered by a reliance on 'classical' nonspecific drug effects such as cytotoxicity and mitotic arrest, exacerbated by a paucity of mechanistically defined cellular models for therapeutically translatable cancer phenotypes. However, technical and biological advances that enable such mechanistically informed phenotypic models have the potential to empower phenotypic drug discovery in oncology.

Cell surface physiology and outer cell envelope impermeability for hydrophobic substances in Burkholderia multivorans.

PubMed

Ruskoski, Sallie A; Champlin, Franklin R

2017-07-01

The purpose of the present study was to obtain a better understanding of the relationship between cell surface physiology and outer cellular envelope permeability for hydrophobic substances in mucoid and non-mucoid B. multivorans strains, as well as in two capsule-deficient derivatives of a mucoid parental strain. Cell surface hydrophobicity properties were determined using the hydrocarbon adherence method, while outer cell envelope accessibility and permeability for non-polar compounds were measured using hydrophobic antimicrobial agent susceptibility and fluorescent probe assays. Extracellular polysaccharide (EPS) production was assessed by cultivating strains of disparate origin on yeast extract agar (YEA) containing different sugars, while the resultant colonial and cellular morphological parameters were assessed macro- and microscopically, respectively.Results/Key findings. The cell surfaces of all the strains were hydrophilic, impermeable to mechanistically disparate hydrophobic antibacterial agents and inaccessible to the hydrophobic probe N-phenyl-1-napthylamine, regardless of EPS phenotype. Supplementation of basal YEA with eight different sugars enhanced macroscopic EPS expression for all but one non-mucoid strain, with mannose potentiating the greatest effect. Despite acquisition of the mucoid phenotype, non-mucoid strains remained non-capsulated and capsulation of a hyper-mucoid strain and its two non-mucoid derivative strains was unaffected, as judged by microscopic observation. These data support the conclusion that EPS expression and the consistent mucoid phenotype are not necessarily associated with the ability of the outer cell surface to associate with non-polar substances or cellular capsulation.

Genome wide selection in Citrus breeding.

PubMed

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

Explaining the disease phenotype of intergenic SNP through predicted long range regulation

PubMed Central

Chen, Jingqi; Tian, Weidong

2016-01-01

Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes. PMID:27280978

A quantitative study of shape descriptors from glioblastoma multiforme phenotypes for predicting survival outcome

PubMed Central

Desrosiers, Christian; Hassan, Lama; Tanougast, Camel

2016-01-01

Objective: Predicting the survival outcome of patients with glioblastoma multiforme (GBM) is of key importance to clinicians for selecting the optimal course of treatment. The goal of this study was to evaluate the usefulness of geometric shape features, extracted from MR images, as a potential non-invasive way to characterize GBM tumours and predict the overall survival times of patients with GBM. Methods: The data of 40 patients with GBM were obtained from the Cancer Genome Atlas and Cancer Imaging Archive. The T1 weighted post-contrast and fluid-attenuated inversion-recovery volumes of patients were co-registered and segmented into delineate regions corresponding to three GBM phenotypes: necrosis, active tumour and oedema/invasion. A set of two-dimensional shape features were then extracted slicewise from each phenotype region and combined over slices to describe the three-dimensional shape of these phenotypes. Thereafter, a Kruskal–Wallis test was employed to identify shape features with significantly different distributions across phenotypes. Moreover, a Kaplan–Meier analysis was performed to find features strongly associated with GBM survival. Finally, a multivariate analysis based on the random forest model was used for predicting the survival group of patients with GBM. Results: Our analysis using the Kruskal–Wallis test showed that all but one shape feature had statistically significant differences across phenotypes, with p-value < 0.05, following Holm–Bonferroni correction, justifying the analysis of GBM tumour shapes on a per-phenotype basis. Furthermore, the survival analysis based on the Kaplan–Meier estimator identified three features derived from necrotic regions (i.e. Eccentricity, Extent and Solidity) that were significantly correlated with overall survival (corrected p-value < 0.05; hazard ratios between 1.68 and 1.87). In the multivariate analysis, features from necrotic regions gave the highest accuracy in predicting the survival group of patients, with a mean area under the receiver-operating characteristic curve (AUC) of 63.85%. Combining the features of all three phenotypes increased the mean AUC to 66.99%, suggesting that shape features from different phenotypes can be used in a synergic manner to predict GBM survival. Conclusion: Results show that shape features, in particular those extracted from necrotic regions, can be used effectively to characterize GBM tumours and predict the overall survival of patients with GBM. Advances in knowledge: Simple volumetric features have been largely used to characterize the different phenotypes of a GBM tumour (i.e. active tumour, oedema and necrosis). This study extends previous work by considering a wide range of shape features, extracted in different phenotypes, for the prediction of survival in patients with GBM. PMID:27781499

Behavioural phenotypes predict disease susceptibility and infectiousness

PubMed Central

Araujo, Alessandra; Kirschman, Lucas

2016-01-01

Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans. PMID:27555652

Behavioural phenotypes predict disease susceptibility and infectiousness.

PubMed

Araujo, Alessandra; Kirschman, Lucas; Warne, Robin W

2016-08-01

Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans. © 2016 The Author(s).

The role of NDR1 in pathogen perception and plant defense signaling.

PubMed

Knepper, Caleb; Savory, Elizabeth A; Day, Brad

2011-08-01

The biochemical and cellular function of NDR1 in plant immunity and defense signaling has long remained elusive. Herein, we describe a novel role for NDR1 in both pathogen perception and plant defense signaling, elucidated by exploring a broader, physiological role for NDR1 in general stress responses and cell wall adhesion. Based on our predictive homology modeling, coupled with a structure-function approach, we found that NDR1 shares a striking similarity to mammalian integrins, well-characterized for their role in mediating the interaction between the extracellular matrix and stress signaling. ndr1-1 mutant plants exhibit higher electrolyte leakage following pathogen infection, compared to wild type Col-0. In addition, we observed an altered plasmolysis phenotype, supporting a role for NDR1 in maintaining cell wall-plasma membrane adhesions through mediating fluid loss under stress. 

Prediction accuracy of direct and indirect approaches, and their relationships with prediction ability of calibration models.

PubMed

Belay, T K; Dagnachew, B S; Boison, S A; Ådnøy, T

2018-03-28

Milk infrared spectra are routinely used for phenotyping traits of interest through links developed between the traits and spectra. Predicted individual traits are then used in genetic analyses for estimated breeding value (EBV) or for phenotypic predictions using a single-trait mixed model; this approach is referred to as indirect prediction (IP). An alternative approach [direct prediction (DP)] is a direct genetic analysis of (a reduced dimension of) the spectra using a multitrait model to predict multivariate EBV of the spectral components and, ultimately, also to predict the univariate EBV or phenotype for the traits of interest. We simulated 3 traits under different genetic (low: 0.10 to high: 0.90) and residual (zero to high: ±0.90) correlation scenarios between the 3 traits and assumed the first trait is a linear combination of the other 2 traits. The aim was to compare the IP and DP approaches for predictions of EBV and phenotypes under the different correlation scenarios. We also evaluated relationships between performances of the 2 approaches and the accuracy of calibration equations. Moreover, the effect of using different regression coefficients estimated from simulated phenotypes (β p ), true breeding values (β g ), and residuals (β r ) on performance of the 2 approaches were evaluated. The simulated data contained 2,100 parents (100 sires and 2,000 cows) and 8,000 offspring (4 offspring per cow). Of the 8,000 observations, 2,000 were randomly selected and used to develop links between the first and the other 2 traits using partial least square (PLS) regression analysis. The different PLS regression coefficients, such as β p , β g , and β r , were used in subsequent predictions following the IP and DP approaches. We used BLUP analyses for the remaining 6,000 observations using the true (co)variance components that had been used for the simulation. Accuracy of prediction (of EBV and phenotype) was calculated as a correlation between predicted and true values from the simulations. The results showed that accuracies of EBV prediction were higher in the DP than in the IP approach. The reverse was true for accuracy of phenotypic prediction when using β p but not when using β g and β r , where accuracy of phenotypic prediction in the DP was slightly higher than in the IP approach. Within the DP approach, accuracies of EBV when using β g were higher than when using β p only at the low genetic correlation scenario. However, we found no differences in EBV prediction accuracy between the β p and β g in the IP approach. Accuracy of the calibration models increased with an increase in genetic and residual correlations between the traits. Performance of both approaches increased with an increase in accuracy of the calibration models. In conclusion, the DP approach is a good strategy for EBV prediction but not for phenotypic prediction, where the classical PLS regression-based equations or the IP approach provided better results. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

PubMed

Pearlstein, Robert A; McKay, Daniel J J; Hornak, Viktor; Dickson, Callum; Golosov, Andrei; Harrison, Tyler; Velez-Vega, Camilo; Duca, José

2017-01-01

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

‘Particle genetics’: treating every cell as unique

PubMed Central

Yvert, Gaël

2014-01-01

Genotype-phenotype relations are usually inferred from a deterministic point of view. For example, quantitative trait loci (QTL), which describe regions of the genome associated with a particular phenotype, are based on a mean trait difference between genotype categories. However, living systems comprise huge numbers of cells (the ‘particles’ of biology). Each cell can exhibit substantial phenotypic individuality, which can have dramatic consequences at the organismal level. Now, with technology capable of interrogating individual cells, it is time to consider how genotypes shape the probability laws of single cell traits. The possibility of mapping single cell probabilistic trait loci (PTL), which link genomic regions to probabilities of cellular traits, is a promising step in this direction. This approach requires thinking about phenotypes in probabilistic terms, a concept that statistical physicists have been applying to particles for a century. Here, I describe PTL and discuss their potential to enlarge our understanding of genotype-phenotype relations. PMID:24315431

Genome-wide screen for inositol auxotrophy in Saccharomyces cerevisiae implicates lipid metabolism in stress response signaling.

PubMed

Villa-García, Manuel J; Choi, Myung Sun; Hinz, Flora I; Gaspar, María L; Jesch, Stephen A; Henry, Susan A

2011-02-01

Inositol auxotrophy (Ino(-) phenotype) in budding yeast has classically been associated with misregulation of INO1 and other genes involved in lipid metabolism. To identify all non-essential yeast genes that are necessary for growth in the absence of inositol, we carried out a genome-wide phenotypic screening for deletion mutants exhibiting Ino(-) phenotypes under one or more growth conditions. We report the identification of 419 genes, including 385 genes not previously reported, which exhibit this phenotype when deleted. The identified genes are involved in a wide range of cellular processes, but are particularly enriched in those affecting transcription, protein modification, membrane trafficking, diverse stress responses, and lipid metabolism. Among the Ino(-) mutants involved in stress response, many exhibited phenotypes that are strengthened at elevated temperature and/or when choline is present in the medium. The role of inositol in regulation of lipid metabolism and stress response signaling is discussed.

Some Like It Hot, Some Like It Warm: Phenotyping to Explore Thermotolerance Diversity

PubMed Central

Yeh, Ching-Hui; Kaplinsky, Nicholas J.; Hu, Catherine; Charng, Yee-yung

2012-01-01

Plants have evolved overlapping but distinct cellular responses to different aspects of high temperature stress. These responses include basal thermotolerance, short- and long-term acquired thermotolerance, and thermotolerance to moderately high temperatures. This thermotolerance diversity’ means that multiple phenotypic assays are essential for fully describing the functions of genes involved in heat stress responses. A large number of genes with potential roles in heat stress responses have been identified using genetic screens and genome wide expression studies. We examine the range of phenotypic assays that have been used to characterize thermotolerance phenotypes in both Arabidopsis and crop plants. Three major variables differentiate thermotolerance assays: 1) the heat stress regime used, 2) the developmental stage of the plants being studied, and 3) the actual phenotype which is scored. Consideration of these variables will be essential for deepening our understanding of the molecular genetics of plant thermotolerance. PMID:22920995

Mammalian synthetic biology for studying the cell

PubMed Central

Mathur, Melina; Xiang, Joy S.

2017-01-01

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. PMID:27932576

RRM2 induces NF-{kappa}B-dependent MMP-9 activation and enhances cellular invasiveness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duxbury, Mark S.; Whang, Edward E.

2007-03-02

Ribonucleotide reductase is a dimeric enzyme that catalyzes conversion of ribonucleotide 5'-diphosphates to their 2'-deoxynucleotide forms, a rate-limiting step in the production of 2'-deoxyribonucleoside 5'-triphosphates required for DNA synthesis. The ribonucleotide reductase M2 subunit (RRM2) is a determinant of malignant cellular behavior in a range of human cancers. We examined the effect of RRM2 overexpression on pancreatic adenocarcinoma cellular invasiveness and nuclear factor-{kappa}B (NF-{kappa}B) transcription factor activity. RRM2 overexpression increases pancreatic adenocarcinoma cellular invasiveness and MMP-9 expression in a NF-{kappa}B-dependent manner. RNA interference (RNAi)-mediated silencing of RRM2 expression attenuates cellular invasiveness and NF-{kappa}B activity. NF-{kappa}B is a key mediator ofmore » the invasive phenotypic changes induced by RRM2 overexpression.« less

Mutations in SNX14 Cause a Distinctive Autosomal-Recessive Cerebellar Ataxia and Intellectual Disability Syndrome

PubMed Central

Thomas, Anna C.; Williams, Hywel; Setó-Salvia, Núria; Bacchelli, Chiara; Jenkins, Dagan; O’Sullivan, Mary; Mengrelis, Konstantinos; Ishida, Miho; Ocaka, Louise; Chanudet, Estelle; James, Chela; Lescai, Francesco; Anderson, Glenn; Morrogh, Deborah; Ryten, Mina; Duncan, Andrew J.; Pai, Yun Jin; Saraiva, Jorge M.; Ramos, Fabiana; Farren, Bernadette; Saunders, Dawn; Vernay, Bertrand; Gissen, Paul; Straatmaan-Iwanowska, Anna; Baas, Frank; Wood, Nicholas W.; Hersheson, Joshua; Houlden, Henry; Hurst, Jane; Scott, Richard; Bitner-Glindzicz, Maria; Moore, Gudrun E.; Sousa, Sérgio B.; Stanier, Philip

2014-01-01

Intellectual disability and cerebellar atrophy occur together in a large number of genetic conditions and are frequently associated with microcephaly and/or epilepsy. Here we report the identification of causal mutations in Sorting Nexin 14 (SNX14) found in seven affected individuals from three unrelated consanguineous families who presented with recessively inherited moderate-severe intellectual disability, cerebellar ataxia, early-onset cerebellar atrophy, sensorineural hearing loss, and the distinctive association of progressively coarsening facial features, relative macrocephaly, and the absence of seizures. We used homozygosity mapping and whole-exome sequencing to identify a homozygous nonsense mutation and an in-frame multiexon deletion in two families. A homozygous splice site mutation was identified by Sanger sequencing of SNX14 in a third family, selected purely by phenotypic similarity. This discovery confirms that these characteristic features represent a distinct and recognizable syndrome. SNX14 encodes a cellular protein containing Phox (PX) and regulator of G protein signaling (RGS) domains. Weighted gene coexpression network analysis predicts that SNX14 is highly coexpressed with genes involved in cellular protein metabolism and vesicle-mediated transport. All three mutations either directly affected the PX domain or diminished SNX14 levels, implicating a loss of normal cellular function. This manifested as increased cytoplasmic vacuolation as observed in cultured fibroblasts. Our findings indicate an essential role for SNX14 in neural development and function, particularly in development and maturation of the cerebellum. PMID:25439728

Mutations in SNX14 cause a distinctive autosomal-recessive cerebellar ataxia and intellectual disability syndrome.

PubMed

Thomas, Anna C; Williams, Hywel; Setó-Salvia, Núria; Bacchelli, Chiara; Jenkins, Dagan; O'Sullivan, Mary; Mengrelis, Konstantinos; Ishida, Miho; Ocaka, Louise; Chanudet, Estelle; James, Chela; Lescai, Francesco; Anderson, Glenn; Morrogh, Deborah; Ryten, Mina; Duncan, Andrew J; Pai, Yun Jin; Saraiva, Jorge M; Ramos, Fabiana; Farren, Bernadette; Saunders, Dawn; Vernay, Bertrand; Gissen, Paul; Straatmaan-Iwanowska, Anna; Baas, Frank; Wood, Nicholas W; Hersheson, Joshua; Houlden, Henry; Hurst, Jane; Scott, Richard; Bitner-Glindzicz, Maria; Moore, Gudrun E; Sousa, Sérgio B; Stanier, Philip

2014-11-06

Intellectual disability and cerebellar atrophy occur together in a large number of genetic conditions and are frequently associated with microcephaly and/or epilepsy. Here we report the identification of causal mutations in Sorting Nexin 14 (SNX14) found in seven affected individuals from three unrelated consanguineous families who presented with recessively inherited moderate-severe intellectual disability, cerebellar ataxia, early-onset cerebellar atrophy, sensorineural hearing loss, and the distinctive association of progressively coarsening facial features, relative macrocephaly, and the absence of seizures. We used homozygosity mapping and whole-exome sequencing to identify a homozygous nonsense mutation and an in-frame multiexon deletion in two families. A homozygous splice site mutation was identified by Sanger sequencing of SNX14 in a third family, selected purely by phenotypic similarity. This discovery confirms that these characteristic features represent a distinct and recognizable syndrome. SNX14 encodes a cellular protein containing Phox (PX) and regulator of G protein signaling (RGS) domains. Weighted gene coexpression network analysis predicts that SNX14 is highly coexpressed with genes involved in cellular protein metabolism and vesicle-mediated transport. All three mutations either directly affected the PX domain or diminished SNX14 levels, implicating a loss of normal cellular function. This manifested as increased cytoplasmic vacuolation as observed in cultured fibroblasts. Our findings indicate an essential role for SNX14 in neural development and function, particularly in development and maturation of the cerebellum. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Phenotypes from ancient DNA: approaches, insights and prospects.

PubMed

Fortes, Gloria G; Speller, Camilla F; Hofreiter, Michael; King, Turi E

2013-08-01

The great majority of phenotypic characteristics are complex traits, complicating the identification of the genes underlying their expression. However, both methodological and theoretical progress in genome-wide association studies have resulted in a much better understanding of the underlying genetics of many phenotypic traits, including externally visible characteristics (EVCs) such as eye and hair color. Consequently, it has become possible to predict EVCs from human samples lacking phenotypic information. Predicting EVCs from genetic evidence is clearly appealing for forensic applications involving the personal identification of human remains. Now, a recent paper has reported the genetic determination of eye and hair color in samples up to 800 years old. The ability to predict EVCs from ancient human remains opens up promising perspectives for ancient DNA research, as this could allow studies to directly address archaeological and evolutionary questions related to the temporal and geographical origins of the genetic variants underlying phenotypes. © 2013 WILEY Periodicals, Inc.

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

PubMed Central

Schellenberger, Jan; Que, Richard; Fleming, Ronan M. T.; Thiele, Ines; Orth, Jeffrey D.; Feist, Adam M.; Zielinski, Daniel C.; Bordbar, Aarash; Lewis, Nathan E.; Rahmanian, Sorena; Kang, Joseph; Hyduke, Daniel R.; Palsson, Bernhard Ø.

2012-01-01

Over the past decade, a growing community of researchers has emerged around the use of COnstraint-Based Reconstruction and Analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a significant update of this in silico ToolBox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include: (1) network gap filling, (2) 13C analysis, (3) metabolic engineering, (4) omics-guided analysis, and (5) visualization. As with the first version, the COBRA Toolbox reads and writes Systems Biology Markup Language formatted models. In version 2.0, we improved performance, usability, and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the Toolbox and validate results. This Toolbox lowers the barrier of entry to use powerful COBRA methods. PMID:21886097

Reinforcement learning in depression: A review of computational research.

PubMed

Chen, Chong; Takahashi, Taiki; Nakagawa, Shin; Inoue, Takeshi; Kusumi, Ichiro

2015-08-01

Despite being considered primarily a mood disorder, major depressive disorder (MDD) is characterized by cognitive and decision making deficits. Recent research has employed computational models of reinforcement learning (RL) to address these deficits. The computational approach has the advantage in making explicit predictions about learning and behavior, specifying the process parameters of RL, differentiating between model-free and model-based RL, and the computational model-based functional magnetic resonance imaging and electroencephalography. With these merits there has been an emerging field of computational psychiatry and here we review specific studies that focused on MDD. Considerable evidence suggests that MDD is associated with impaired brain signals of reward prediction error and expected value ('wanting'), decreased reward sensitivity ('liking') and/or learning (be it model-free or model-based), etc., although the causality remains unclear. These parameters may serve as valuable intermediate phenotypes of MDD, linking general clinical symptoms to underlying molecular dysfunctions. We believe future computational research at clinical, systems, and cellular/molecular/genetic levels will propel us toward a better understanding of the disease. Copyright © 2015 Elsevier Ltd. All rights reserved.

Upper gastrointestinal tract phenotype of Crohn's disease is associated with early surgery and further hospitalization.

PubMed

Chow, Dorothy K L; Sung, Joseph J Y; Wu, Justin C Y; Tsoi, Kelvin K F; Leong, Rupert W L; Chan, Francis K L

2009-04-01

According to the Montreal Classification, upper gastrointestinal tract phenotype L4 is uncommon in Caucasian patients with Crohn's disease (CD) but carries excess risk of recurrence. We studied the clinical course of CD in Chinese patients presenting with the L4 phenotype and factors predicting its occurrence upon longitudinal follow-up. This prospective cohort study included 132 Chinese CD patients (median age at diagnosis, 30.0 years, range: 14.0-77.0 years) who were followed for 770 person-years. Demographic data including disease behavior and location, details of surgery, and hospitalization were collected. The Kaplan-Meier method was used to estimate the probabilities of further hospitalization and major surgery followed by Cox proportional hazards regression to determine if clinical variables independently predicted the endpoints. The L4 phenotype was found in 30 (22.7%) patients at presentation. There were significantly more stricturing (46.7% versus 18.6%) and penetrating (30.0% versus 3.9%) phenotypes in the L4 group than in the non-L4 group (P < 0.0001). The 3-year cumulative probability of further hospitalization was 86.9% (95% confidence interval [CI]: 73.8%-100.0%) in the L4 group as compared with 49.3% (95% CI: 39.3%-59.3%) in the non-L4 group (log-rank test, P < 0.0001). The L4 phenotype independently predicted further hospitalization (adjusted hazards ratio [HR]: 2.1; 95% CI: 1.3-3.5). The cumulative probability of major surgery was significantly higher in the L4 than in the non-L4 group (P < 0.0001). Eighteen (17.6%) patients developed the L4 phenotype on follow-up and the stricturing phenotype predicted its occurrence (adjusted HR: 5.5; 95% CI: 2.2-14.0). Chinese CD patients more often had the L4 phenotype, which predicted the need of subsequent hospitalization.

Prediction of whole-genome risk for selection and management of hyperketonemia in Holstein dairy cattle.

PubMed

Weigel, K A; Pralle, R S; Adams, H; Cho, K; Do, C; White, H M

2017-06-01

Hyperketonemia (HYK), a common early postpartum health disorder characterized by elevated blood concentrations of β-hydroxybutyrate (BHB), affects millions of dairy cows worldwide and leads to significant economic losses and animal welfare concerns. In this study, blood concentrations of BHB were assessed for 1,453 Holstein cows using electronic handheld meters at four time points between 5 and 18 days postpartum. Incidence rates of subclinical (1.2 ≤ maximum BHB ≤ 2.9 mmol/L) and clinical ketosis (maximum BHB ≥ 3.0 mmol/L) were 24.0 and 2.4%, respectively. Variance components, estimated breeding values, and predicted HYK phenotypes were computed on the original, square-root, and binary scales. Heritability estimates for HYK ranged from 0.058 to 0.072 in pedigree-based analyses, as compared to estimates that ranged from 0.071 to 0.093 when pedigrees were augmented with 60,671 single nucleotide polymorphism genotypes of 959 cows and 801 male ancestors. On average, predicted HYK phenotypes from the genome-enhanced analysis ranged from 0.55 mmol/L for first-parity cows in the best contemporary group to 1.40 mmol/L for fourth-parity cows in the worst contemporary group. Genome-enhanced predictions of HYK phenotypes were more closely associated with actual phenotypes than pedigree-based predictions in five-fold cross-validation, and transforming phenotypes to reduce skewness and kurtosis also improved predictive ability. This study demonstrates the feasibility of using repeated cowside measurement of blood BHB concentration in early lactation to construct a reference population that can be used to estimate HYK breeding values for genomic selection programmes and predict HYK phenotypes for genome-guided management decisions. © 2017 Blackwell Verlag GmbH.

A grammar inference approach for predicting kinase specific phosphorylation sites.

PubMed

Datta, Sutapa; Mukhopadhyay, Subhasis

2015-01-01

Kinase mediated phosphorylation site detection is the key mechanism of post translational mechanism that plays an important role in regulating various cellular processes and phenotypes. Many diseases, like cancer are related with the signaling defects which are associated with protein phosphorylation. Characterizing the protein kinases and their substrates enhances our ability to understand the mechanism of protein phosphorylation and extends our knowledge of signaling network; thereby helping us to treat such diseases. Experimental methods for predicting phosphorylation sites are labour intensive and expensive. Also, manifold increase of protein sequences in the databanks over the years necessitates the improvement of high speed and accurate computational methods for predicting phosphorylation sites in protein sequences. Till date, a number of computational methods have been proposed by various researchers in predicting phosphorylation sites, but there remains much scope of improvement. In this communication, we present a simple and novel method based on Grammatical Inference (GI) approach to automate the prediction of kinase specific phosphorylation sites. In this regard, we have used a popular GI algorithm Alergia to infer Deterministic Stochastic Finite State Automata (DSFA) which equally represents the regular grammar corresponding to the phosphorylation sites. Extensive experiments on several datasets generated by us reveal that, our inferred grammar successfully predicts phosphorylation sites in a kinase specific manner. It performs significantly better when compared with the other existing phosphorylation site prediction methods. We have also compared our inferred DSFA with two other GI inference algorithms. The DSFA generated by our method performs superior which indicates that our method is robust and has a potential for predicting the phosphorylation sites in a kinase specific manner.

Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods.

PubMed

Notaro, Marco; Schubach, Max; Robinson, Peter N; Valentini, Giorgio

2017-10-12

The prediction of human gene-abnormal phenotype associations is a fundamental step toward the discovery of novel genes associated with human disorders, especially when no genes are known to be associated with a specific disease. In this context the Human Phenotype Ontology (HPO) provides a standard categorization of the abnormalities associated with human diseases. While the problem of the prediction of gene-disease associations has been widely investigated, the related problem of gene-phenotypic feature (i.e., HPO term) associations has been largely overlooked, even if for most human genes no HPO term associations are known and despite the increasing application of the HPO to relevant medical problems. Moreover most of the methods proposed in literature are not able to capture the hierarchical relationships between HPO terms, thus resulting in inconsistent and relatively inaccurate predictions. We present two hierarchical ensemble methods that we formally prove to provide biologically consistent predictions according to the hierarchical structure of the HPO. The modular structure of the proposed methods, that consists in a "flat" learning first step and a hierarchical combination of the predictions in the second step, allows the predictions of virtually any flat learning method to be enhanced. The experimental results show that hierarchical ensemble methods are able to predict novel associations between genes and abnormal phenotypes with results that are competitive with state-of-the-art algorithms and with a significant reduction of the computational complexity. Hierarchical ensembles are efficient computational methods that guarantee biologically meaningful predictions that obey the true path rule, and can be used as a tool to improve and make consistent the HPO terms predictions starting from virtually any flat learning method. The implementation of the proposed methods is available as an R package from the CRAN repository.

Using ToxCast data to reconstruct dynamic cell state ...

EPA Pesticide Factsheets

AbstractBackground. High-throughput in vitro screening is an important tool for evaluating the potential biological activity of the thousands of existing chemicals in commerce and the hundreds more introduced each year. Among the assay technologies available, high-content imaging (HCI) allows multiplexed measurements of cellular phenotypic changes induced by chemical exposures. For a large chemical inventory having limited concentration-time series data, the deconvolution of cellular response profiles into transitive or irrevocable state trajectories is an important consideration. Objectives. Our goal was to analyze temporal and concentration-related cellular changes measured using HCI to identify the “tipping point” at which the cells did not show recovery towards a normal phenotypic state. Methods. The effects of 976 chemicals (ToxCast Phase I and II) were evaluated using HCI as a function of concentration and time in HepG2 cells over a 72-hr exposure period to concentrations ranging from 0.4- to 200 µM. The cellular endpoints included nuclear p53 accumulation, JNK, markers of oxidative stress, cytoskeletal changes, mitochondrial energization and density, cell viability and cell cycle progression. A novel computational model was developed to interpret dynamic multidimensional system responses as cell-state trajectories. Results. Analysis of cell-state trajectories showed that HepG2 cells were resilient to the effects of 178 chemicals up to the highest co

Understanding the cellular and molecular mechanisms of dominant and recessive inheritance in genetics course.

PubMed

Wanjin, Xing; Morigen, Morigen

2015-01-01

In Mendellian genetics, the dominance and recessiveness are used to describe the functional relationship between two alleles of one gene in a heterozygote. The allele which constitutes a phenotypical character over the other is named dominant and the one functionally masked is called recessive. The definitions thereby led to the creation of Mendel's laws on segregation and independent assortment and subsequent classic genetics. The discrimination of dominance and recessiveness originally is a requirement for Mendel's logical reasoning, but now it should be explained by cellular and molecular principles in the modern genetics. To answer the question raised by students of how the dominance and recessiveness are controlled, we reviewed the recent articles and tried to summarize the cellular and molecular basis of dominant and recessive inheritance. Clearly, understanding the essences of dominant and recessive inheritance requires us to know the dissimilarity of the alleles and their products (RNA and/or proteins), and the way of their function in cells. The alleles spatio-temporally play different roles on offering cells, tissues or organs with discernible phenotypes, namely dominant or recessive. Here, we discuss the changes of allele dominance and recessiveness at the cellular and molecular levels based on the variation of gene structure, gene regulation, function and types of gene products, in order to make students understand gene mutation and function more comprehensively and concretely.

Integrated MicroRNA and mRNA Signatures Associated with Survival in Triple Negative Breast Cancer

PubMed Central

Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M.; Shapiro, Charles L.; Huebner, Kay

2013-01-01

Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways. Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis. PMID:23405235

Integrated microRNA and mRNA signatures associated with survival in triple negative breast cancer.

PubMed

Cascione, Luciano; Gasparini, Pierluigi; Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M; Shapiro, Charles L; Huebner, Kay

2013-01-01

Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways.Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis.

A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line.

PubMed

Collins, Adam; Huett, Alan

2018-05-15

We present a high-content screen (HCS) for the simultaneous analysis of multiple phenotypes in HeLa cells expressing an autophagy reporter (mcherry-LC3) and one of 224 GFP-fused proteins from the Crohn's Disease (CD)-associated bacterium, Adherent Invasive E. coli (AIEC) strain LF82. Using automated confocal microscopy and image analysis (CellProfiler), we localised GFP fusions within cells, and monitored their effects upon autophagy (an important innate cellular defence mechanism), cellular and nuclear morphology, and the actin cytoskeleton. This data will provide an atlas for the localisation of 224 AIEC proteins within human cells, as well as a dataset to analyse their effects upon many aspects of host cell morphology. We also describe an open-source, automated, image-analysis workflow to identify bacterial effectors and their roles via the perturbations induced in reporter cell lines when candidate effectors are exogenously expressed.

Optimization of industrial microorganisms: recent advances in synthetic dynamic regulators.

PubMed

Min, Byung Eun; Hwang, Hyun Gyu; Lim, Hyun Gyu; Jung, Gyoo Yeol

2017-01-01

Production of biochemicals by industrial fermentation using microorganisms requires maintaining cellular production capacity, because maximal productivity is economically important. High-productivity microbial strains can be developed using static engineering, but these may not maintain maximal productivity throughout the culture period as culture conditions and cell states change dynamically. Additionally, economic reasons limit heterologous protein expression using inducible promoters to prevent metabolic burden for commodity chemical and biofuel production. Recently, synthetic and systems biology has been used to design genetic circuits, precisely controlling gene expression or influencing genetic behavior toward a desired phenotype. Development of dynamic regulators can maintain cellular phenotype in a maximum production state in response to factors including cell concentration, oxygen, temperature, pH, and metabolites. Herein, we introduce dynamic regulators of industrial microorganism optimization and discuss metabolic flux fine control by dynamic regulators in response to metabolites or extracellular stimuli, robust production systems, and auto-induction systems using quorum sensing.

The GARP complex is required for cellular sphingolipid homeostasis.

PubMed

Fröhlich, Florian; Petit, Constance; Kory, Nora; Christiano, Romain; Hannibal-Bach, Hans-Kristian; Graham, Morven; Liu, Xinran; Ejsing, Christer S; Farese, Robert V; Walther, Tobias C

2015-09-10

Sphingolipids are abundant membrane components and important signaling molecules in eukaryotic cells. Their levels and localization are tightly regulated. However, the mechanisms underlying this regulation remain largely unknown. In this study, we identify the Golgi-associated retrograde protein (GARP) complex, which functions in endosome-to-Golgi retrograde vesicular transport, as a critical player in sphingolipid homeostasis. GARP deficiency leads to accumulation of sphingolipid synthesis intermediates, changes in sterol distribution, and lysosomal dysfunction. A GARP complex mutation analogous to a VPS53 allele causing progressive cerebello-cerebral atrophy type 2 (PCCA2) in humans exhibits similar, albeit weaker, phenotypes in yeast, providing mechanistic insights into disease pathogenesis. Inhibition of the first step of de novo sphingolipid synthesis is sufficient to mitigate many of the phenotypes of GARP-deficient yeast or mammalian cells. Together, these data show that GARP is essential for cellular sphingolipid homeostasis and suggest a therapeutic strategy for the treatment of PCCA2.

Identification of a Gene That Reverses the Immortal Phenotype of a Subset of Cells and Is a Member of a Novel Family of Transcription Factor-Like Genes†

PubMed Central

Bertram, M. J.; Bérubé, N. G.; Hang-Swanson, X.; Ran, Q.; Leung, J. K.; Bryce, S.; Spurgers, K.; Bick, R. J.; Baldini, A.; Ning, Y.; Clark, L. J.; Parkinson, E. K.; Barrett, J. C.; Smith, J. R.; Pereira-Smith, O. M.

1999-01-01

Based on the dominance of cellular senescence over immortality, immortal human cell lines have been assigned to four complementation groups for indefinite division. Human chromosomes carrying senescence genes have been identified, including chromosome 4. We report the cloning and identification of a gene, mortality factor 4 (MORF 4), which induces a senescent-like phenotype in immortal cell lines assigned to complementation group B with concomitant changes in two markers for senescence. MORF 4 is a member of a novel family of genes with transcription factor-like motifs. We present here the sequences of the seven family members, their chromosomal locations, and a partial characterization of the three members that are expressed. Elucidation of the mechanism of action of these genes should enhance our understanding of growth regulation and cellular aging. PMID:9891081

Unfolding the relationship between secreted molecular chaperones and macrophage activation states

PubMed Central

Henderson, Samantha

2008-01-01

Over the last 20 years, it has emerged that many molecular chaperones and protein-folding catalysts are secreted from cells and function, somewhat in the manner of cytokines, as pleiotropic signals for a variety of cells, with much attention being focused on the macrophage. During the last decade, it has become clear that macrophages respond to bacterial, protozoal, parasitic and host signals to generate phenotypically distinct states of activation. These activation states have been termed ‘classical’ and ‘alternative’ and represent not a simple bifurcation in response to external signals but a range of cellular phenotypes. From an examination of the literature, the hypothesis is propounded that mammalian molecular chaperones are able to induce a wide variety of alternative macrophage activation states, and this may be a system for relating cellular or tissue stress to appropriate macrophage responses to restore homeostatic equilibrium. PMID:18958583

Phenotypic correction of Fanconi anemia cells in the murine bone marrow after carrier cell mediated delivery of lentiviral vector.

PubMed

Chakkaramakkil Verghese, Santhosh; Goloviznina, Natalya A; Kurre, Peter

2016-11-19

Fanconi anemia (FA) is an autosomal-recessive disorder associated with hematopoietic failure and it is a candidate for hematopoietic stem cell (HSC)-directed gene therapy. However, the characteristically reduced HSC numbers found in FA patients, their ineffective mobilization from the marrow, and re-oxygenation damage during ex vivo manipulation have precluded clinical success using conventional in vitro approaches. We previously demonstrated that lentiviral vector (LV) particles reversibly attach to the cell surface where they gain protection from serum complement neutralization. We reasoned that cellular delivery of LV to the bone marrow niche could avoid detrimental losses during FA HSC mobilization and in vitro modification. Here, we demonstrate that a VSV-G pseudotyped lentivector, carrying the FANCC transgene, can be transmitted from carrier to bystander cells. In cell culture and transplantation models of FA, we further demonstrate that LV carrier cells migrate along SDF-1α gradients and transfer vector particles that stably integrate and phenotypically correct the characteristic DNA alkylator sensitivity in murine and human FA-deficient target bystander cells. Altogether, we demonstrate that cellular homing mechanisms can be harnessed for the functional phenotype correction in murine FA hematopoietic cells.

Genetic analysis of indefinite division in human cells: Evidence for a cell senescence-related gene(s) on human chromosome 4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yi Ning; Ledbetter, D.H.; Smith, J.R.

1991-07-01

Earlier studies had demonstrated that fusion of normal with immortal human cells yielded hybrids having limited division potential. This indicated that the phenotype of limited proliferation (cellular senescence) is dominant and that immortal cells result from recessive changes in normal growth-regulatory genes. In additional studies, the authors exploited the fact that the immortal phenotype is recessive and, by fusing various immortal human cell lines with each other, identified four complementation groups for indefinite division. Assignment of cell lines to specific groups allowed us to take a focused approach to identify the chromosomes and genes involved in growth regulation that havemore » been modified in immortal cells. They report here that introduction of a normal human chromosome 4 into three immortal cell lines (HeLa, J82, T98G) assigned to complementation group B resulted in loss of proliferation and reversal of the immortal phenotype. No effect on the proliferation potential of cell lines representative of the other complementation groups was observed. This result suggests that a gene(s) involved in cellular senescence and normal growth regulation resides on chromosome 4.« less

Single nucleotide polymorphism coverage and inference of N-acetyltransferase-2 acetylator phenotypes in wordwide population groups.

PubMed

Suarez-Kurtz, Guilherme; Fuchshuber-Moraes, Mateus; Struchiner, Claudio J; Parra, Esteban J

2016-08-01

Several algorithms have been proposed to reduce the genotyping effort and cost, while retaining the accuracy of N-acetyltransferase-2 (NAT2) phenotype prediction. Data from the 1000 Genomes (1KG) project and an admixed cohort of Black Brazilians were used to assess the accuracy of NAT2 phenotype prediction using algorithms based on paired single nucleotide polymorphisms (SNPs) (rs1041983 and rs1801280) or a tag SNP (rs1495741). NAT2 haplotypes comprising SNPs rs1801279, rs1041983, rs1801280, rs1799929, rs1799930, rs1208 and rs1799931 were assigned according to the arylamine N-acetyltransferases database. Contingency tables were used to visualize the agreement between the NAT2 acetylator phenotypes on the basis of these haplotypes versus phenotypes inferred by the prediction algorithms. The paired and tag SNP algorithms provided more than 96% agreement with the 7-SNP derived phenotypes in Europeans, East Asians, South Asians and Admixed Americans, but discordance of phenotype prediction occurred in 30.2 and 24.8% 1KG Africans and in 14.4 and 18.6% Black Brazilians, respectively. Paired SNP panel misclassification occurs in carriers of NATs haplotypes *13A (282T alone), *12B (282T and 803G), *6B (590A alone) and *14A (191A alone), whereas haplotype *14, defined by the 191A allele, is the major culprit of misclassification by the tag allele. Both the paired SNP and the tag SNP algorithms may be used, with economy of scale, to infer NAT2 acetylator phenotypes, including the ultra-slow phenotype, in European, East Asian, South Asian and American populations represented in the 1KG cohort. Both algorithms, however, perform poorly in populations of predominant African descent, including admixed African-Americans, African Caribbeans and Black Brazilians.

Immediate Administration of Intraarticular Triamcinolone Acetonide after Joint Injury Modulates Molecular Outcomes Associated with Early Synovitis

PubMed Central

Sieker, Jakob T.; Ayturk, Ugur M.; Proffen, Benedikt L.; Weissenberger, Manuela H.; Kiapour, Ata M.; Murray, Martha M.

2016-01-01

Objective To test if intraarticular corticosteroid injection mitigates injury-induced synovitis and collagen degradation after anterior cruciate ligament (ACL) transection and characterize the synovial response using a functional genomics approach in a preclinical model of post- traumatic osteoarthritis. Methods Yorkshire pigs received untreated unilateral ACL transection (ACLT, n=6) or transection with immediate injection of 20mg triamcinolone acetonide (STEROID, n=6). Total synovial membrane cellularity and synovial fluid concentration of COL-2 3/4C short neoepitope bearing collagen fragments at 14 days post-injury were primary endpoints and compared between ACLT, STEROID and INTACT (n=6 uninjured knees). Cells were differentiated by histological phenotype and counted, while RNA-seq was used to quantify transcriptome-wide gene expression, monocyte, macrophage and lymphocyte markers. Results Total cellularity of 13% (95% confidence interval of 9–16) and COL-2 3/4C short levels of 0.24 Kg/ml (0.08–0.39) were determined in INTACT. Significant increases in total cellularity to 21% (16–27) and COL-2 3/4C short to 0.49 Kg/ml (0.39–0.59) were observed in ACLT. Compared to ACLT, total cellularity was non-significantly and COL-2 3/4C short was significantly decreased in STEROID to 17% (15–18, p=0.26) and 0.29 Kg/ml (0.23–0.35). Between ACLT and INTACT, 255 genes were differentially expressed and enriched pathways related to cellular immune response and proteolysis. Mononuclear leukocytes were the dominant cell type in cell dense areas. MARCO, SOCS3, CCR1, IL4R and MMP2 expression was significantly associated with COL-2 3/4C short levels. Conclusions Early intraarticular immunosuppression mitigated the injury-induced increase of collagen fragments, an outcome better predicted by specific marker expression than histological measures of synovitis. PMID:26866935

Explaining the disease phenotype of intergenic SNP through predicted long range regulation.

PubMed

Chen, Jingqi; Tian, Weidong

2016-10-14

Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Stapled peptide inhibitors of RAB25 target context-specific phenotypes in cancer | Office of Cancer Genomics

Cancer.gov

Recent evidence has established a role for the small GTPase RAB25, as well as related effector proteins, in enacting both pro-oncogenic and anti-oncogenic phenotypes in specific cellular contexts. Here we report the development of all-hydrocarbon stabilized peptides derived from the RAB-binding FIP-family of proteins to target RAB25. Relative to unmodified peptides, optimized stapled peptides exhibit increased structural stability, binding affinity, cell permeability, and inhibition of RAB25:FIP complex formation.

In situ macrophage phenotypic transition is affected by altered cellular composition prior to acute sterile muscle injury.

PubMed

Patsalos, Andreas; Pap, Attila; Varga, Tamas; Trencsenyi, Gyorgy; Contreras, Gerardo Alvarado; Garai, Ildiko; Papp, Zoltan; Dezso, Balazs; Pintye, Eva; Nagy, Laszlo

2017-09-01

The in situ phenotypic switch of macrophages is delayed in acute injury following irradiation. The combination of bone marrow transplantation and local muscle radiation protection allows for the identification of a myeloid cell contribution to tissue repair. PET-MRI allows monitoring of myeloid cell invasion and metabolism. Altered cellular composition prior to acute sterile injury affects the in situ phenotypic transition of invading myeloid cells to repair macrophages. There is reciprocal intercellular communication between local muscle cell compartments, such as PAX7 positive cells, and recruited macrophages during skeletal muscle regeneration. Skeletal muscle regeneration is a complex interplay between various cell types including invading macrophages. Their recruitment to damaged tissues upon acute sterile injuries is necessary for clearance of necrotic debris and for coordination of tissue regeneration. This highly dynamic process is characterized by an in situ transition of infiltrating monocytes from an inflammatory (Ly6C high ) to a repair (Ly6C low ) macrophage phenotype. The importance of the macrophage phenotypic shift and the cross-talk of the local muscle tissue with the infiltrating macrophages during tissue regeneration upon injury are not fully understood and their study lacks adequate methodology. Here, using an acute sterile skeletal muscle injury model combined with irradiation, bone marrow transplantation and in vivo imaging, we show that preserved muscle integrity and cell composition prior to the injury is necessary for the repair macrophage phenotypic transition and subsequently for proper and complete tissue regeneration. Importantly, by using a model of in vivo ablation of PAX7 positive cells, we show that this radiosensitive skeletal muscle progenitor pool contributes to macrophage phenotypic transition following acute sterile muscle injury. In addition, local muscle tissue radioprotection by lead shielding during irradiation preserves normal macrophage transition dynamics and subsequently muscle tissue regeneration. Taken together, our data suggest the existence of a more extensive and reciprocal cross-talk between muscle tissue compartments, including satellite cells, and infiltrating myeloid cells upon tissue damage. These interactions shape the macrophage in situ phenotypic shift, which is indispensable for normal muscle tissue repair dynamics. © 2017 The Authors. The Journal of Physiology © 2017 The Physiological Society.

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

PubMed Central

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-01-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays. PMID:27452732

Proteomics in Heart Failure: Top-down or Bottom-up?

PubMed Central

Gregorich, Zachery R.; Chang, Ying-Hua; Ge, Ying

2014-01-01

Summary The pathophysiology of heart failure (HF) is diverse, owing to multiple etiologies and aberrations in a number of cellular processes. Therefore, it is essential to understand how defects in the molecular pathways that mediate cellular responses to internal and external stressors function as a system to drive the HF phenotype. Mass spectrometry (MS)-based proteomics strategies have great potential for advancing our understanding of disease mechanisms at the systems level because proteins are the effector molecules for all cell functions and, thus, are directly responsible for determining cell phenotype. Two MS-based proteomics strategies exist: peptide-based bottom-up and protein-based top-down proteomics—each with its own unique strengths and weaknesses for interrogating the proteome. In this review, we will discuss the advantages and disadvantages of bottom-up and top-down MS for protein identification, quantification, and the analysis of post-translational modifications, as well as highlight how both of these strategies have contributed to our understanding of the molecular and cellular mechanisms underlying HF. Additionally, the challenges associated with both proteomics approaches will be discussed and insights will be offered regarding the future of MS-based proteomics in HF research. PMID:24619480

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

NASA Astrophysics Data System (ADS)

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-07-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays.

Mammalian synthetic biology for studying the cell.

PubMed

Mathur, Melina; Xiang, Joy S; Smolke, Christina D

2017-01-02

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.

Linking transcriptional responses to organismal tolerance reveals mechanisms of thermal sensitivity in a mesothermal endangered fish.

PubMed

Komoroske, Lisa M; Connon, Richard E; Jeffries, Ken M; Fangue, Nann A

2015-10-01

Forecasting species' responses to climate change requires understanding the underlying mechanisms governing environmental stress tolerance, including acclimation capacity and acute stress responses. Current knowledge of these physiological processes in aquatic ectotherms is largely drawn from eurythermal or extreme stenothermal species. Yet many species of conservation concern exhibit tolerance windows and acclimation capacities in between these extremes. We linked transcriptome profiles to organismal tolerance in a mesothermal endangered fish, the delta smelt (Hypomesus transpacificus), to quantify the cellular processes, sublethal thresholds and effects of thermal acclimation on acute stress responses. Delta smelt initiated rapid molecular changes in line with expectations of theoretical thermal limitation models, but also exhibited diminished capacity to modify the expression of some genes and cellular mechanisms key to coping with acute thermal stress found in eurytherms. Sublethal critical thresholds occurred 4-6 °C below their upper tolerance limits, and thermal acclimation shifted the onset of acute thermal stress and tolerance as predicted. However, we found evidence that delta smelt's limited thermal plasticity may be partially due to an inability of individuals to effectively make physiological adjustments to truly achieve new homoeostasis under heightened temperatures, resulting in chronic thermal stress. These findings provide insight into the physiological basis of the diverse patterns of thermal tolerances observed in nature. Moreover, understanding how underlying molecular mechanisms shape thermal acclimation capacity, acute stress responses and ultimately differential phenotypes contributes to a predictive framework to deduce species' responses in situ to changes in selective pressures due to climate change. © 2015 John Wiley & Sons Ltd.

Dynamic Finite Element Predictions for Mars Sample Return Cellular Impact Test #4

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Billings, Marcus D.

2001-01-01

The nonlinear, transient dynamic finite element code, MSC.Dytran, was used to simulate an impact test of an energy absorbing Earth Entry Vehicle (EEV) that will impact without a parachute. EEVOs are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite-epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the center of the EEVOs cellular structure. Pre-test analytical predictions were compared with the test results from a bungee accelerator. The model used to represent the foam and the proper failure criteria for the cell walls were critical in predicting the impact loads of the cellular structure. It was determined that a FOAM1 model for the foam and a 20% failure strain criteria for the cell walls gave an accurate prediction of the acceleration pulse for cellular impact.

Adaptive therapy.

PubMed

Gatenby, Robert A; Silva, Ariosto S; Gillies, Robert J; Frieden, B Roy

2009-06-01

A number of successful systemic therapies are available for treatment of disseminated cancers. However, tumor response is often transient, and therapy frequently fails due to emergence of resistant populations. The latter reflects the temporal and spatial heterogeneity of the tumor microenvironment as well as the evolutionary capacity of cancer phenotypes to adapt to therapeutic perturbations. Although cancers are highly dynamic systems, cancer therapy is typically administered according to a fixed, linear protocol. Here we examine an adaptive therapeutic approach that evolves in response to the temporal and spatial variability of tumor microenvironment and cellular phenotype as well as therapy-induced perturbations. Initial mathematical models find that when resistant phenotypes arise in the untreated tumor, they are typically present in small numbers because they are less fit than the sensitive population. This reflects the "cost" of phenotypic resistance such as additional substrate and energy used to up-regulate xenobiotic metabolism, and therefore not available for proliferation, or the growth inhibitory nature of environments (i.e., ischemia or hypoxia) that confer resistance on phenotypically sensitive cells. Thus, in the Darwinian environment of a cancer, the fitter chemosensitive cells will ordinarily proliferate at the expense of the less fit chemoresistant cells. The models show that, if resistant populations are present before administration of therapy, treatments designed to kill maximum numbers of cancer cells remove this inhibitory effect and actually promote more rapid growth of the resistant populations. We present an alternative approach in which treatment is continuously modulated to achieve a fixed tumor population. The goal of adaptive therapy is to enforce a stable tumor burden by permitting a significant population of chemosensitive cells to survive so that they, in turn, suppress proliferation of the less fit but chemoresistant subpopulations. Computer simulations show that this strategy can result in prolonged survival that is substantially greater than that of high dose density or metronomic therapies. The feasibility of adaptive therapy is supported by in vivo experiments. [Cancer Res 2009;69(11):4894-903] Major FindingsWe present mathematical analysis of the evolutionary dynamics of tumor populations with and without therapy. Analytic solutions and numerical simulations show that, with pretreatment, therapy-resistant cancer subpopulations are present due to phenotypic or microenvironmental factors; maximum dose density chemotherapy hastens rapid expansion of resistant populations. The models predict that host survival can be maximized if "treatment-for-cure strategy" is replaced by "treatment-for-stability." Specifically, the models predict that an optimal treatment strategy will modulate therapy to maintain a stable population of chemosensitive cells that can, in turn, suppress the growth of resistant populations under normal tumor conditions (i.e., when therapy-induced toxicity is absent). In vivo experiments using OVCAR xenografts treated with carboplatin show that adaptive therapy is feasible and, in this system, can produce long-term survival.

Intracellular Localization and Cellular Factors Interaction of HTLV-1 and HTLV-2 Tax Proteins: Similarities and Functional Differences

PubMed Central

Bertazzoni, Umberto; Turci, Marco; Avesani, Francesca; Di Gennaro, Gianfranco; Bidoia, Carlo; Romanelli, Maria Grazia

2011-01-01

Human T-lymphotropic viruses type 1 (HTLV-1) and type 2 (HTLV-2) present very similar genomic structures but HTLV-1 is more pathogenic than HTLV-2. Is this difference due to their transactivating Tax proteins, Tax-1 and Tax-2, which are responsible for viral and cellular gene activation? Do Tax-1 and Tax-2 differ in their cellular localization and in their interaction pattern with cellular factors? In this review, we summarize Tax-1 and Tax-2 structural and phenotypic properties, their interaction with factors involved in signal transduction and their localization-related behavior within the cell. Special attention will be given to the distinctions between Tax-1 and Tax-2 that likely play an important role in their transactivation activity. PMID:21994745

Mitochondria targeting by environmental stressors: Implications for redox cellular signaling.

PubMed

Blajszczak, Chuck; Bonini, Marcelo G

2017-11-01

Mitochondria are cellular powerhouses as well as metabolic and signaling hubs regulating diverse cellular functions, from basic physiology to phenotypic fate determination. It is widely accepted that reactive oxygen species (ROS) generated in mitochondria participate in the regulation of cellular signaling, and that some mitochondria chronically operate at a high ROS baseline. However, it is not completely understood how mitochondria adapt to persistently high ROS states and to environmental stressors that disturb the redox balance. Here we will review some of the current concepts regarding how mitochondria resist oxidative damage, how they are replaced when excessive oxidative damage compromises function, and the effect of environmental toxicants (i.e. heavy metals) on the regulation of mitochondrial ROS (mtROS) production and subsequent impact. Copyright © 2017 Elsevier B.V. All rights reserved.

Gene regulatory networks and the underlying biology of developmental toxicity

EPA Science Inventory

Embryonic cells are specified by large-scale networks of functionally linked regulatory genes. Knowledge of the relevant gene regulatory networks is essential for understanding phenotypic heterogeneity that emerges from disruption of molecular functions, cellular processes or sig...

GABAB-mediated rescue of altered excitatory-inhibitory balance, gamma synchrony and behavioral deficits following constitutive NMDAR-hypofunction.

PubMed

Gandal, M J; Sisti, J; Klook, K; Ortinski, P I; Leitman, V; Liang, Y; Thieu, T; Anderson, R; Pierce, R C; Jonak, G; Gur, R E; Carlson, G; Siegel, S J

2012-07-17

Reduced N-methyl-D-aspartate-receptor (NMDAR) signaling has been associated with schizophrenia, autism and intellectual disability. NMDAR-hypofunction is thought to contribute to social, cognitive and gamma (30-80 Hz) oscillatory abnormalities, phenotypes common to these disorders. However, circuit-level mechanisms underlying such deficits remain unclear. This study investigated the relationship between gamma synchrony, excitatory-inhibitory (E/I) signaling, and behavioral phenotypes in NMDA-NR1(neo-/-) mice, which have constitutively reduced expression of the obligate NR1 subunit to model disrupted developmental NMDAR function. Constitutive NMDAR-hypofunction caused a loss of E/I balance, with an increase in intrinsic pyramidal cell excitability and a selective disruption of parvalbumin-expressing interneurons. Disrupted E/I coupling was associated with deficits in auditory-evoked gamma signal-to-noise ratio (SNR). Gamma-band abnormalities predicted deficits in spatial working memory and social preference, linking cellular changes in E/I signaling to target behaviors. The GABA(B)-receptor agonist baclofen improved E/I balance, gamma-SNR and broadly reversed behavioral deficits. These data demonstrate a clinically relevant, highly translatable neural-activity-based biomarker for preclinical screening and therapeutic development across a broad range of disorders that share common endophenotypes and disrupted NMDA-receptor signaling.

Shifting behaviour: epigenetic reprogramming in eusocial insects.

PubMed

Patalano, Solenn; Hore, Timothy A; Reik, Wolf; Sumner, Seirian

2012-06-01

Epigenetic modifications are ancient and widely utilised mechanisms that have been recruited across fungi, plants and animals for diverse but fundamental biological functions, such as cell differentiation. Recently, a functional DNA methylation system was identified in the honeybee, where it appears to underlie queen and worker caste differentiation. This discovery, along with other insights into the epigenetics of social insects, allows provocative analogies to be drawn between insect caste differentiation and cellular differentiation, particularly in mammals. Developing larvae in social insect colonies are totipotent: they retain the ability to specialise as queens or workers, in a similar way to the totipotent cells of early embryos before they differentiate into specific cell lineages. Further, both differentiating cells and insect castes lose phenotypic plasticity by committing to their lineage, losing the ability to be readily reprogrammed. Hence, a comparison of the epigenetic mechanisms underlying lineage differentiation (and reprogramming) between cells and social insects is worthwhile. Here we develop a conceptual model of how loss and regain of phenotypic plasticity might be conserved for individual specialisation in both cells and societies. This framework forges a novel link between two fields of biological research, providing predictions for a unified approach to understanding the molecular mechanisms underlying biological complexity. Copyright © 2012 Elsevier Ltd. All rights reserved.

Insights in connecting phenotypes in bacteria to coevolutionary information

NASA Astrophysics Data System (ADS)

Cheng, Ryan; Morcos, Faruck; Hayes, Ryan; Helm, Rodney; Levine, Herbert; Onuchic, Jose

It has long been known that protein sequences are far from random. These sequences have been evolutionarily selected to maintain their ability to fold into stable, three-dimensional folded structures as well as their ability to form macromolecular assemblies, perform catalytic functions, etc. For these reasons, there exist quantifiable mutational patterns in the collection of sequence data for a protein family arising from the need to maintain favorable residue-residue interactions to facilitate folding as well as cellular function. Here, we focus on studying the correlated mutational patterns that give rise to interaction specificity in bacterial two-component signaling (TCS) systems. TCS proteins have evolved to be able to preferentially bind and transfer a phosphate group to their signaling partner while avoiding phosphotransfer with non-partners. We infer a Potts model Hamiltonian governing the correlated mutational patterns that are observed in the sequence data of TCS partners and apply this model to recently published in vivo mutational data. Our findings further support the notion that statistical models built from sequence data can be used to predict bacterial phenotypes as well as engineer interaction specificity between non-partner TCS proteins. This research has been supported by the NSF INSPIRE Award (MCB-1241332) and by the CTBP sponsored by the NSF (Grant PHY- 1427654).

Deletion of Lipoteichoic Acid Synthase Impacts Expression of Genes Encoding Cell Surface Proteins in Lactobacillus acidophilus

PubMed Central

Selle, Kurt; Goh, Yong J.; Johnson, Brant R.; O’Flaherty, Sarah; Andersen, Joakim M.; Barrangou, Rodolphe; Klaenhammer, Todd R.

2017-01-01

Lactobacillus acidophilus NCFM is a well-characterized probiotic microorganism, supported by a decade of genomic and functional phenotypic investigations. L. acidophilus deficient in lipoteichoic acid (LTA), a major immunostimulant in Gram-positive bacteria, has been shown to shift immune system responses in animal disease models. However, the pleiotropic effects of removing LTA from the cell surface in lactobacilli are unknown. In this study, we surveyed the global transcriptional and extracellular protein profiles of two strains of L. acidophilus deficient in LTA. Twenty-four differentially expressed genes specific to the LTA-deficient strains were identified, including a predicted heavy metal resistance operon and several putative peptidoglycan hydrolases. Cell morphology and manganese sensitivity phenotypes were assessed in relation to the putative functions of differentially expressed genes. LTA-deficient L. acidophilus exhibited elongated cellular morphology and their growth was severely inhibited by elevated manganese concentrations. Exoproteomic surveys revealed distinct changes in the composition and relative abundances of several extracellular proteins and showed a bias of intracellular proteins in LTA-deficient strains of L. acidophilus. Taken together, these results elucidate the impact of ltaS deletion on the transcriptome and extracellular proteins of L. acidophilus, suggesting roles of LTA in cell morphology and ion homeostasis as a structural component of the Gram positive cell wall. PMID:28443071

Deletion of Lipoteichoic Acid Synthase Impacts Expression of Genes Encoding Cell Surface Proteins in Lactobacillus acidophilus.

PubMed

Selle, Kurt; Goh, Yong J; Johnson, Brant R; O'Flaherty, Sarah; Andersen, Joakim M; Barrangou, Rodolphe; Klaenhammer, Todd R

2017-01-01

Lactobacillus acidophilus NCFM is a well-characterized probiotic microorganism, supported by a decade of genomic and functional phenotypic investigations. L. acidophilus deficient in lipoteichoic acid (LTA), a major immunostimulant in Gram-positive bacteria, has been shown to shift immune system responses in animal disease models. However, the pleiotropic effects of removing LTA from the cell surface in lactobacilli are unknown. In this study, we surveyed the global transcriptional and extracellular protein profiles of two strains of L. acidophilus deficient in LTA. Twenty-four differentially expressed genes specific to the LTA-deficient strains were identified, including a predicted heavy metal resistance operon and several putative peptidoglycan hydrolases. Cell morphology and manganese sensitivity phenotypes were assessed in relation to the putative functions of differentially expressed genes. LTA-deficient L. acidophilus exhibited elongated cellular morphology and their growth was severely inhibited by elevated manganese concentrations. Exoproteomic surveys revealed distinct changes in the composition and relative abundances of several extracellular proteins and showed a bias of intracellular proteins in LTA-deficient strains of L. acidophilus . Taken together, these results elucidate the impact of ltaS deletion on the transcriptome and extracellular proteins of L. acidophilus , suggesting roles of LTA in cell morphology and ion homeostasis as a structural component of the Gram positive cell wall.

Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines.

PubMed

Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just

2016-01-01

Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families.

Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines

PubMed Central

Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just

2016-01-01

Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families. PMID:27783639

Literature-based prediction of novel drug indications considering relationships between entities.

PubMed

Jang, Giup; Lee, Taekeon; Lee, Byung Mun; Yoon, Youngmi

2017-06-27

There have been many attempts to identify and develop new uses for existing drugs, which is known as drug repositioning. Among these efforts, text mining is an effective means of discovering novel knowledge from a large amount of literature data. We identify a gene regulation by a drug and a phenotype based on the biomedical literature. Drugs or phenotypes can activate or inhibit gene regulation. We calculate the therapeutic possibility that a drug acts on a phenotype by means of these two types of regulation. We assume that a drug treats a phenotype if the genes regulated by the phenotype are inversely correlated with the genes regulated by the drug. Based on this hypothesis, we identify drug-phenotype associations with therapeutic possibility. To validate the drug-phenotype associations predicted by our method, we make an enrichment comparison with known drug-phenotype associations. We also identify candidate drugs for drug repositioning from novel associations and thus reveal that our method is a novel approach to drug repositioning.

Identification and validation of distinct biological phenotypes in patients with acute respiratory distress syndrome by cluster analysis.

PubMed

Bos, L D; Schouten, L R; van Vught, L A; Wiewel, M A; Ong, D S Y; Cremer, O; Artigas, A; Martin-Loeches, I; Hoogendijk, A J; van der Poll, T; Horn, J; Juffermans, N; Calfee, C S; Schultz, M J

2017-10-01

We hypothesised that patients with acute respiratory distress syndrome (ARDS) can be clustered based on concentrations of plasma biomarkers and that the thereby identified biological phenotypes are associated with mortality. Consecutive patients with ARDS were included in this prospective observational cohort study. Cluster analysis of 20 biomarkers of inflammation, coagulation and endothelial activation provided the phenotypes in a training cohort, not taking any outcome data into account. Logistic regression with backward selection was used to select the most predictive biomarkers, and these predicted phenotypes were validated in a separate cohort. Multivariable logistic regression was used to quantify the independent association with mortality. Two phenotypes were identified in 454 patients, which we named 'uninflamed' (N=218) and 'reactive' (N=236). A selection of four biomarkers (interleukin-6, interferon gamma, angiopoietin 1/2 and plasminogen activator inhibitor-1) could be used to accurately predict the phenotype in the training cohort (area under the receiver operating characteristics curve: 0.98, 95% CI 0.97 to 0.99). Mortality rates were 15.6% and 36.4% (p<0.001) in the training cohort and 13.6% and 37.5% (p<0.001) in the validation cohort (N=207). The 'reactive phenotype' was independent from confounders associated with intensive care unit mortality (training cohort: OR 1.13, 95% CI 1.04 to 1.23; validation cohort: OR 1.18, 95% CI 1.06 to 1.31). Patients with ARDS can be clustered into two biological phenotypes, with different mortality rates. Four biomarkers can be used to predict the phenotype with high accuracy. The phenotypes were very similar to those found in cohorts derived from randomised controlled trials, and these results may improve patient selection for future clinical trials targeting host response in patients with ARDS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Differential cellular responses by oncogenic levels of c-Myc expression in long-term confluent retinal pigment epithelial cells.

PubMed

Wang, Yiping; Cheng, Xiangdong; Samma, Muhammad Kaleem; Kung, Sam K P; Lee, Clement M; Chiu, Sung Kay

2018-06-01

c-Myc is a highly pleiotropic transcription factor known to control cell cycle progression, apoptosis, and cellular transformation. Normally, ectopic expression of c-Myc is associated with promoting cell proliferation or triggering cell death via activating p53. However, it is not clear how the levels of c-Myc lead to different cellular responses. Here, we generated a series of stable RPE cell clones expressing c-Myc at different levels, and found that consistent low level of c-Myc induced cellular senescence by activating AP4 in post-confluent RPE cells, while the cells underwent cell death at high level of c-Myc. In addition, high level of c-Myc could override the effect of AP4 on cellular senescence. Further knockdown of AP4 abrogated senescence-like phenotype in cells expressing low level of c-Myc, and accelerated cell death in cells with medium level of c-Myc, indicating that AP4 was required for cellular senescence induced by low level of c-Myc.

Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.

PubMed

Hamilton, Joshua J; Dwivedi, Vivek; Reed, Jennifer L

2013-07-16

Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Phenotypic Diagnosis of Lineage and Differentiation During Sake Yeast Breeding

PubMed Central

Ohnuki, Shinsuke; Okada, Hiroki; Friedrich, Anne; Kanno, Yoichiro; Goshima, Tetsuya; Hasuda, Hirokazu; Inahashi, Masaaki; Okazaki, Naoto; Tamura, Hiroyasu; Nakamura, Ryo; Hirata, Dai; Fukuda, Hisashi; Shimoi, Hitoshi; Kitamoto, Katsuhiko; Watanabe, Daisuke; Schacherer, Joseph; Akao, Takeshi; Ohya, Yoshikazu

2017-01-01

Sake yeast was developed exclusively in Japan. Its diversification during breeding remains largely uncharacterized. To evaluate the breeding processes of the sake lineage, we thoroughly investigated the phenotypes and differentiation of 27 sake yeast strains using high-dimensional, single-cell, morphological phenotyping. Although the genetic diversity of the sake yeast lineage is relatively low, its morphological diversity has expanded substantially compared to that of the Saccharomyces cerevisiae species as a whole. Evaluation of the different types of breeding processes showed that the generation of hybrids (crossbreeding) has more profound effects on cell morphology than the isolation of mutants (mutation breeding). Analysis of phenotypic robustness revealed that some sake yeast strains are more morphologically heterogeneous, possibly due to impairment of cellular network hubs. This study provides a new perspective for studying yeast breeding genetics and micro-organism breeding strategies. PMID:28642365

miRNA profiling of high, low and non-producing CHO cells during biphasic fed-batch cultivation reveals process relevant targets for host cell engineering.

PubMed

Stiefel, Fabian; Fischer, Simon; Sczyrba, Alexander; Otte, Kerstin; Hesse, Friedemann

2016-05-10

Fed-batch cultivation of recombinant Chinese hamster ovary (CHO) cell lines is one of the most widely used production modes for commercial manufacturing of recombinant protein therapeutics. Furthermore, fed-batch cultivations are often conducted as biphasic processes where the culture temperature is decreased to maximize volumetric product yields. However, it remains to be elucidated which intracellular regulatory elements actually control the observed pro-productive phenotypes. Recently, several studies have revealed microRNAs (miRNAs) to be important molecular switches of cell phenotypes. In this study, we analyzed miRNA profiles of two different recombinant CHO cell lines (high and low producer), and compared them to a non-producing CHO DG44 host cell line during fed-batch cultivation at 37°C versus a temperature shift to 30°C. Taking advantage of next-generation sequencing combined with cluster, correlation and differential expression analyses, we could identify 89 different miRNAs, which were differentially expressed in the different cell lines and cultivation phases. Functional validation experiments using 19 validated target miRNAs confirmed that these miRNAs indeed induced changes in process relevant phenotypes. Furthermore, computational miRNA target prediction combined with functional clustering identified putative target genes and cellular pathways, which might be regulated by these miRNAs. This study systematically identified novel target miRNAs during different phases and conditions of a biphasic fed-batch production process and functionally evaluated their potential for host cell engineering. Copyright © 2016. Published by Elsevier B.V.

Canine Models of Duchenne Muscular Dystrophy and Their Use in Therapeutic Strategies

PubMed Central

Kornegay, Joe N.; Bogan, Janet R.; Bogan, Daniel J.; Childers, Martin K.; Li, Juan; Nghiem, Peter; Detwiler, David A.; Larsen, C. Aaron; Grange, Robert W.; Bhavaraju-Sanka, Ratna K.; Tou, Sandra; Keene, Bruce P.; Howard, James F.; Wang, Jiahui; Fan, Zheng; Schatzberg, Scott J.; Styner, Martin A.; Flanigan, Kevin M.; Xiao, Xiao; Hoffman, Eric P.

2013-01-01

Duchenne muscular dystrophy (DMD) is an X-linked recessive disorder in which the loss of dystrophin causes progressive degeneration of skeletal and cardiac muscle. Potential therapies that carry substantial risk, such as gene and cell-based approaches, must first be tested in animal models, notably the mdx mouse and several dystrophin-deficient breeds of dogs, including golden retriever muscular dystrophy (GRMD). Affected dogs have a more severe phenotype, in keeping with that of DMD, so may better predict disease pathogenesis and treatment efficacy. We and others have developed various phenotypic tests to characterize disease progression in the GRMD model. These biomarkers range from measures of strength and joint contractures to magnetic resonance imaging. Some of these tests are routinely used in clinical veterinary practice, while others require specialized equipment and expertise. By comparing serial measurements from treated and untreated groups, one can document improvement or delayed progression of disease. Potential treatments for DMD may be broadly categorized as molecular, cellular, or pharmacologic. The GRMD model has increasingly been used to assess efficacy of a range of these therapies. While some of these studies have largely provided general proof-of-concept for the treatment under study, others have demonstrated efficacy using the biomarkers discussed. Importantly, just as symptoms in DMD vary among patients, GRMD dogs display remarkable phenotypic variation. While confounding statistical analysis in preclinical trials, this variation offers insight regarding the role that modifier genes play in disease pathogenesis. By correlating functional and mRNA profiling results, gene targets for therapy development can be identified. PMID:22218699

Induction of appropriate Th-cell phenotypes: cellular decision-making in heterogeneous environments.

PubMed

van den Ham, H-J; Andeweg, A C; de Boer, R J

2013-11-01

Helper T (Th)-cell differentiation is a key event in the development of the adaptive immune response. By the production of a range of cytokines, Th cells determine the type of immune response that is raised against an invading pathogen. Th cells can adopt many different phenotypes, and Th-cell phenotype decision-making is crucial in mounting effective host responses. This review discusses the different Th-cell phenotypes that have been identified and how Th cells adopt a particular phenotype. The regulation of Th-cell phenotypes has been studied extensively using mathematical models, which have explored the role of regulatory mechanisms such as autocrine cytokine signalling and cross-inhibition between self-activating transcription factors. At the single cell level, Th responses tend to be heterogeneous, but corrections can be made soon after T-cell activation. Although pathogens and the innate immune system provide signals that direct the induction of Th-cell phenotypes, these instructive mechanisms could be easily subverted by pathogens. We discuss that a model of success-driven feedback would select the most appropriate phenotype for clearing a pathogen. Given the heterogeneity in the induction phase of the Th response, such a success-driven feedback loop would allow the selection of effective Th-cell phenotypes while terminating incorrect responses. © 2013 John Wiley & Sons Ltd.

Defects in lymphocyte telomere homeostasis contribute to cellular immune phenotype in patients with cartilage-hair hypoplasia.

PubMed

Aubert, Geraldine; Strauss, Kevin A; Lansdorp, Peter M; Rider, Nicholas L

2017-10-01

Mutations in the long noncoding RNA RNase component of the mitochondrial RNA processing endoribonuclease (RMRP) give rise to the autosomal recessive condition cartilage-hair hypoplasia (CHH). The CHH disease phenotype has some overlap with dyskeratosis congenita, a well-known "telomere disorder." RMRP binds the telomerase reverse transcriptase (catalytic subunit) in some cell lines, raising the possibility that RMRP might play a role in telomere biology. We sought to determine whether a telomere phenotype is present in immune cells from patients with CHH and explore mechanisms underlying these observations. We assessed proliferative capacity and telomere length using flow-fluorescence in situ hybridization (in situ hybridization and flow cytometry) of primary lymphocytes from patients with CHH, carrier relatives, and control subjects. The role of telomerase holoenzyme components in gene expression and activity were assessed by using quantitative PCR and the telomere repeat amplification protocol from PBMCs and enriched lymphocyte cultures. Lymphocyte cultures from patients with CHH display growth defects in vitro, which is consistent with an immune deficiency cellular phenotype. Here we show that telomere length and telomerase activity are impaired in primary lymphocyte subsets from patients with CHH. Notably, telomerase activity is affected in a gene dose-dependent manner when comparing heterozygote RMRP carriers with patients with CHH. Telomerase deficiency in patients with CHH is not mediated by abnormal telomerase gene transcript levels relative to those of endogenous genes. These findings suggest that telomere deficiency is implicated in the CHH disease phenotype through an as yet unidentified mechanism. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Superoxide dismutating molecules rescue the toxic effects of PINK1 and parkin loss.

PubMed

Biosa, Alice; Sanchez-Martinez, Alvaro; Filograna, Roberta; Terriente-Felix, Ana; Alam, Sarah M; Beltramini, Mariano; Bubacco, Luigi; Bisaglia, Marco; Whitworth, Alexander J

2018-05-01

Reactive oxygen species exert important functions in regulating several cellular signalling pathways. However, an excessive accumulation of reactive oxygen species can perturb the redox homeostasis leading to oxidative stress, a condition which has been associated to many neurodegenerative disorders. Accordingly, alterations in the redox state of cells and mitochondrial homeostasis are established hallmarks in both familial and sporadic Parkinson's disease cases. PINK1 and Parkin are two genes which account for a large fraction of autosomal recessive early-onset forms of Parkinson's disease and are now firmly associated to both mitochondria and redox homeostasis. In this study we explored the hypothesis that superoxide anions participate in the generation of the Parkin and PINK1 associated phenotypic effect by testing the capacity of endogenous and exogenous superoxide dismutating molecules to rescue the toxic effects induced by loss of PINK1 or Parkin, in both cellular and fly models. Our results demonstrate the positive effect of an increased level of superoxide dismutase proteins on the pathological phenotypes, both in vitro and in vivo. A more pronounced effectiveness for mitochondrial SOD2 activity points to the superoxide radicals generated in the mitochondrial matrix as the prime suspect in the definition of the observed phenotypes. Moreover, we also demonstrate the efficacy of a SOD-mimetic compound, M40403, to partially ameliorate PINK1/Parkin phenotypes in vitro and in vivo. These results support the further exploration of SOD-mimetic compounds as a therapeutic strategy against Parkinson's disease.

Point Mutations in the Stem Region and the Fourth AAA Domain of Cytoplasmic Dynein Heavy Chain Partially Suppress the Phenotype of NUDF/LIS1 Loss in Aspergillus nidulans

PubMed Central

Zhuang, Lei; Zhang, Jun; Xiang, Xin

2007-01-01

Cytoplasmic dynein performs multiple cellular tasks but its regulation remains unclear. The dynein heavy chain has a N-terminal stem that binds to other subunits and a C-terminal motor unit that contains six AAA (ATPase associated with cellular activities) domains and a microtubule-binding site located between AAA4 and AAA5. In Aspergillus nidulans, NUDF (a LIS1 homolog) functions in the dynein pathway, and two nudF6 partial suppressors were mapped to the nudA dynein heavy chain locus. Here we identified these two mutations. The nudAL1098F mutation resides in the stem region, and nudAR3086C is in the end of AAA4. These mutations partially suppress the phenotype of nudF deletion but do not suppress the phenotype exhibited by mutants of dynein intermediate chain and Arp1. Surprisingly, the stronger ΔnudF suppressor, nudAR3086C, causes an obvious decrease in the basal level of dynein's ATPase activity and an increase in dynein's distribution along microtubules. Thus, suppression of the ΔnudF phenotype may result from mechanisms other than simply the enhancement of dynein's ATPase activity. The fact that a mutation in the end of AAA4 negatively regulates dynein's ATPase activity but partially compensates for NUDF loss indicates the importance of the AAA4 domain in dynein regulation in vivo. PMID:17237507

Noise-Driven Phenotypic Heterogeneity with Finite Correlation Time in Clonal Populations.

PubMed

Lee, UnJin; Skinner, John J; Reinitz, John; Rosner, Marsha Rich; Kim, Eun-Jin

2015-01-01

There has been increasing awareness in the wider biological community of the role of clonal phenotypic heterogeneity in playing key roles in phenomena such as cellular bet-hedging and decision making, as in the case of the phage-λ lysis/lysogeny and B. Subtilis competence/vegetative pathways. Here, we report on the effect of stochasticity in growth rate, cellular memory/intermittency, and its relation to phenotypic heterogeneity. We first present a linear stochastic differential model with finite auto-correlation time, where a randomly fluctuating growth rate with a negative average is shown to result in exponential growth for sufficiently large fluctuations in growth rate. We then present a non-linear stochastic self-regulation model where the loss of coherent self-regulation and an increase in noise can induce a shift from bounded to unbounded growth. An important consequence of these models is that while the average change in phenotype may not differ for various parameter sets, the variance of the resulting distributions may considerably change. This demonstrates the necessity of understanding the influence of variance and heterogeneity within seemingly identical clonal populations, while providing a mechanism for varying functional consequences of such heterogeneity. Our results highlight the importance of a paradigm shift from a deterministic to a probabilistic view of clonality in understanding selection as an optimization problem on noise-driven processes, resulting in a wide range of biological implications, from robustness to environmental stress to the development of drug resistance.

Genetic Complexity and Quantitative Trait Loci Mapping of Yeast Morphological Traits

PubMed Central

Nogami, Satoru; Ohya, Yoshikazu; Yvert, Gaël

2007-01-01

Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes. PMID:17319748

Genome-enabled prediction models for yield related traits in chickpea

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped...

Epigenetic mechanisms of nutrient-induced modulation of gene expression and cellular functions

USDA-ARS?s Scientific Manuscript database

Utilizing next-generation sequencing technology in combination with chromatin immunoprecipitation (ChIP) technology, our study provides systematic and novel insights into the relationships between nutrition and epigenetics. One paradigmatic example of nutrient-epigenetic-phenotype relationship is th...

Disease models for the development of therapies for lysosomal storage diseases.

PubMed

Xu, Miao; Motabar, Omid; Ferrer, Marc; Marugan, Juan J; Zheng, Wei; Ottinger, Elizabeth A

2016-05-01

Lysosomal storage diseases (LSDs) are a group of rare diseases in which the function of the lysosome is disrupted by the accumulation of macromolecules. The complexity underlying the pathogenesis of LSDs and the small, often pediatric, population of patients make the development of therapies for these diseases challenging. Current treatments are only available for a small subset of LSDs and have not been effective at treating neurological symptoms. Disease-relevant cellular and animal models with high clinical predictability are critical for the discovery and development of new treatments for LSDs. In this paper, we review how LSD patient primary cells and induced pluripotent stem cell-derived cellular models are providing novel assay systems in which phenotypes are more similar to those of the human LSD physiology. Furthermore, larger animal disease models are providing additional tools for evaluation of the efficacy of drug candidates. Early predictors of efficacy and better understanding of disease biology can significantly affect the translational process by focusing efforts on those therapies with the higher probability of success, thus decreasing overall time and cost spent in clinical development and increasing the overall positive outcomes in clinical trials. © 2016 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.

Large-Scale Comparative Phenotypic and Genomic Analyses Reveal Ecological Preferences of Shewanella Species and Identify Metabolic Pathways Conserved at the Genus Level ▿ †

PubMed Central

Rodrigues, Jorge L. M.; Serres, Margrethe H.; Tiedje, James M.

2011-01-01

The use of comparative genomics for the study of different microbiological species has increased substantially as sequence technologies become more affordable. However, efforts to fully link a genotype to its phenotype remain limited to the development of one mutant at a time. In this study, we provided a high-throughput alternative to this limiting step by coupling comparative genomics to the use of phenotype arrays for five sequenced Shewanella strains. Positive phenotypes were obtained for 441 nutrients (C, N, P, and S sources), with N-based compounds being the most utilized for all strains. Many genes and pathways predicted by genome analyses were confirmed with the comparative phenotype assay, and three degradation pathways believed to be missing in Shewanella were confirmed as missing. A number of previously unknown gene products were predicted to be parts of pathways or to have a function, expanding the number of gene targets for future genetic analyses. Ecologically, the comparative high-throughput phenotype analysis provided insights into niche specialization among the five different strains. For example, Shewanella amazonensis strain SB2B, isolated from the Amazon River delta, was capable of utilizing 60 C compounds, whereas Shewanella sp. strain W3-18-1, isolated from deep marine sediment, utilized only 25 of them. In spite of the large number of nutrient sources yielding positive results, our study indicated that except for the N sources, they were not sufficiently informative to predict growth phenotypes from increasing evolutionary distances. Our results indicate the importance of phenotypic evaluation for confirming genome predictions. This strategy will accelerate the functional discovery of genes and provide an ecological framework for microbial genome sequencing projects. PMID:21642407

Deregulation of obesity-relevant genes is associated with progression in BMI and the amount of adipose tissue in pigs.

PubMed

Mentzel, Caroline M Junker; Cardoso, Tainã Figueiredo; Pipper, Christian Bressen; Jacobsen, Mette Juul; Jørgensen, Claus Bøttcher; Cirera, Susanna; Fredholm, Merete

2018-02-01

The aim of this study was to elucidate the relative impact of three phenotypes often used to characterize obesity on perturbation of molecular pathways involved in obesity. The three obesity-related phenotypes are (1) body mass index (BMI), (2) amount of subcutaneous adipose tissue (SATa), and (3) amount of retroperitoneal adipose tissue (RPATa). Although it is generally accepted that increasing amount of RPATa is 'unhealthy', a direct comparison of the relative impact of the three obesity-related phenotypes on gene expression has, to our knowledge, not been performed previously. We have used multiple linear models to analyze altered gene expression of selected obesity-related genes in tissues collected from 19 female pigs phenotypically characterized with respect to the obesity-related phenotypes. Gene expression was assessed by high-throughput qPCR in RNA from liver, skeletal muscle and abdominal adipose tissue. The stringent statistical approach used in the study has increased the power of the analysis compared to the classical approach of analysis in divergent groups of individuals. Our approach led to the identification of key components of cellular pathways that are modulated in the three tissues in association with changes in the three obesity-relevant phenotypes (BMI, SATa and RPATa). The deregulated pathways are involved in biosynthesis and transcript regulation in adipocytes, in lipid transport, lipolysis and metabolism, and in inflammatory responses. Deregulation seemed more comprehensive in liver (23 genes) compared to abdominal adipose tissue (10 genes) and muscle (3 genes). Notably, the study supports the notion that excess amount of intra-abdominal adipose tissue is associated with a greater metabolic disease risk. Our results provide molecular support for this notion by demonstrating that increasing amount of RPATa has a higher impact on perturbation of cellular pathways influencing obesity and obesity-related metabolic traits compared to increase in BMI and amount of SATa.

Correlation of RNA secondary structure and attenuation of Sabin vaccine strains of poliovirus in tissue culture.

PubMed

Macadam, A J; Ferguson, G; Burlison, J; Stone, D; Skuce, R; Almond, J W; Minor, P D

1992-08-01

Part of the 5' noncoding regions of all three Sabin vaccine strains of poliovirus contains determinants of attenuation that are shown here to influence the ability of these strains to grow at elevated temperatures in BGM cells. The predicted RNA secondary structure of this region (nt 464-542 in P3/Sabin) suggests that both phenotypes are due to perturbation of base-paired stems. Ts phenotypes of site-directed mutants with defined changes in this region correlated well with predicted secondary structure stabilities. Reversal of base-pair orientation had little effect whereas stem disruption led to marked increases in temperature sensitivity. Phenotypic revertants of such viruses displayed mutations on either side of the stem. Mutations destabilizing stems led to intermediate phenotypes. These results provided evidence for the biological significance of the predicted RNA secondary structure.

On the role of mid-infrared predicted phenotypes in fertility and health dairy breeding programs.

PubMed

Bastin, C; Théron, L; Lainé, A; Gengler, N

2016-05-01

Fertility and health traits are of prime importance in dairy breeding programs. However, these traits are generally complex, difficult to record, and lowly heritable (<0.10), thereby hampering genetic improvement in disease resistance and fertility. Hence, indicators are useful in the prediction of genetic merit for fertility and health traits as long as they are easier to measure than direct fitness traits, heritable, and genetically correlated. Considering that changes in (fine) milk composition over a lactation reflect the physiological status of the cow, mid-infrared (MIR) analysis of milk opens the door to a wide range of potential indicator traits of fertility and health. Previous studies investigated the phenotypic and genetic relationships between fertility and MIR-predicted phenotypes, most being related to negative postpartum energy balance and body fat mobilization (e.g., fat:protein ratio, urea, fatty acids profile). Results showed that a combination of various fatty acid traits (e.g., C18:1 cis-9 and C10:0) could be used to improve fertility. Furthermore, occurrence of (sub)clinical ketosis has been related to milk-based phenotypes such as fat:protein ratio, fatty acids, and ketone bodies. Hence, MIR-predicted acetone and β-hydroxybutyrate contents in milk could be useful for breeding cows less susceptible to ketosis. Although studies investigating the genetic association among mastitis and MIR-predicted phenotypes are scarce, a wide range of traits, potentially predicted by MIR spectrometry, are worthy of consideration. These include traits related to the disease response of the cow (e.g., lactoferrin), reduced secretory activity (e.g., casein), and the alteration of the blood-milk barrier (e.g., minerals). Moreover, direct MIR prediction of fertility and health traits should be further considered. To conclude, MIR-predicted phenotypes have a role to play in the improvement of dairy cow fertility and health. However, further studies are warranted to (1) grasp underlying associations among MIR-predicted indicator and fitness traits, (2) estimate the genetic parameters, and (3) include these traits in broader breeding strategies. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Automatic analysis of dividing cells in live cell movies to detect mitotic delays and correlate phenotypes in time.

PubMed

Harder, Nathalie; Mora-Bermúdez, Felipe; Godinez, William J; Wünsche, Annelie; Eils, Roland; Ellenberg, Jan; Rohr, Karl

2009-11-01

Live-cell imaging allows detailed dynamic cellular phenotyping for cell biology and, in combination with small molecule or drug libraries, for high-content screening. Fully automated analysis of live cell movies has been hampered by the lack of computational approaches that allow tracking and recognition of individual cell fates over time in a precise manner. Here, we present a fully automated approach to analyze time-lapse movies of dividing cells. Our method dynamically categorizes cells into seven phases of the cell cycle and five aberrant morphological phenotypes over time. It reliably tracks cells and their progeny and can thus measure the length of mitotic phases and detect cause and effect if mitosis goes awry. We applied our computational scheme to annotate mitotic phenotypes induced by RNAi gene knockdown of CKAP5 (also known as ch-TOG) or by treatment with the drug nocodazole. Our approach can be readily applied to comparable assays aiming at uncovering the dynamic cause of cell division phenotypes.

Image-guided genomics of phenotypically heterogeneous populations reveals vascular signalling during symbiotic collective cancer invasion

PubMed Central

Konen, J.; Summerbell, E.; Dwivedi, B.; Galior, K.; Hou, Y.; Rusnak, L.; Chen, A.; Saltz, J.; Zhou, W.; Boise, L. H.; Vertino, P.; Cooper, L.; Salaita, K.; Kowalski, J.; Marcus, A. I.

2017-01-01

Phenotypic heterogeneity is widely observed in cancer cell populations. Here, to probe this heterogeneity, we developed an image-guided genomics technique termed spatiotemporal genomic and cellular analysis (SaGA) that allows for precise selection and amplification of living and rare cells. SaGA was used on collectively invading 3D cancer cell packs to create purified leader and follower cell lines. The leader cell cultures are phenotypically stable and highly invasive in contrast to follower cultures, which show phenotypic plasticity over time and minimally invade in a sheet-like pattern. Genomic and molecular interrogation reveals an atypical VEGF-based vasculogenesis signalling that facilitates recruitment of follower cells but not for leader cell motility itself, which instead utilizes focal adhesion kinase-fibronectin signalling. While leader cells provide an escape mechanism for followers, follower cells in turn provide leaders with increased growth and survival. These data support a symbiotic model of collective invasion where phenotypically distinct cell types cooperate to promote their escape. PMID:28497793

In Vitro Assays for Mouse Müller Cell Phenotyping Through microRNA Profiling in the Damaged Retina.

PubMed

Reyes-Aguirre, Luis I; Quintero, Heberto; Estrada-Leyva, Brenda; Lamas, Mónica

2018-01-01

microRNA profiling has identified cell-specific expression patterns that could represent molecular signatures triggering the acquisition of a specific phenotype; in other words, of cellular identity and its associated function. Several groups have hypothesized that retinal cell phenotyping could be achieved through the determination of the global pattern of miRNA expression across specific cell types in the adult retina. This is especially relevant for Müller glia in the context of retinal damage, as these cells undergo dramatic changes of gene expression in response to injury, that render them susceptible to acquire a progenitor-like phenotype and be a source of new neurons.We describe a method that combines an experimental protocol for excitotoxic-induced retinal damage through N-methyl-D-aspartate subretinal injection with magnetic-activated cell sorting (MACS) of Müller cells and RNA isolation for microRNA profiling. Comparison of microRNA patterns of expression should allow Müller cell phenotyping under different experimental conditions.

Development of a population of cancer cells: Observation and modeling by a Mixed Spatial Evolutionary Games approach.

PubMed

Świerniak, Andrzej; Krześlak, Michał; Student, Sebastian; Rzeszowska-Wolny, Joanna

2016-09-21

Living cells, like whole living organisms during evolution, communicate with their neighbors, interact with the environment, divide, change their phenotypes, and eventually die. The development of specific ways of communication (through signaling molecules and receptors) allows some cellular subpopulations to survive better, to coordinate their physiological status, and during embryonal development to create tissues and organs or in some conditions to become tumors. Populations of cells cultured in vitro interact similarly, also competing for space and nutrients and stimulating each other to better survive or to die. The results of these intercellular interactions of different types seem to be good examples of biological evolutionary games, and have been the subjects of simulations by the methods of evolutionary game theory where individual cells are treated as players. Here we present examples of intercellular contacts in a population of living human cancer HeLa cells cultured in vitro and propose an evolutionary game theory approach to model the development of such populations. We propose a new technique termed Mixed Spatial Evolutionary Games (MSEG) which are played on multiple lattices corresponding to the possible cellular phenotypes which gives the possibility of simulating and investigating the effects of heterogeneity at the cellular level in addition to the population level. Analyses performed with MSEG suggested different ways in which cellular populations develop in the case of cells communicating directly and through factors released to the environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mutations in the NHEJ Component XRCC4 Cause Primordial Dwarfism

PubMed Central

Murray, Jennie E.; van der Burg, Mirjam; IJspeert, Hanna; Carroll, Paula; Wu, Qian; Ochi, Takashi; Leitch, Andrea; Miller, Edward S.; Kysela, Boris; Jawad, Alireza; Bottani, Armand; Brancati, Francesco; Cappa, Marco; Cormier-Daire, Valerie; Deshpande, Charu; Faqeih, Eissa A.; Graham, Gail E.; Ranza, Emmanuelle; Blundell, Tom L.; Jackson, Andrew P.; Stewart, Grant S.; Bicknell, Louise S.

2015-01-01

Non-homologous end joining (NHEJ) is a key cellular process ensuring genome integrity. Mutations in several components of the NHEJ pathway have been identified, often associated with severe combined immunodeficiency (SCID), consistent with the requirement for NHEJ during V(D)J recombination to ensure diversity of the adaptive immune system. In contrast, we have recently found that biallelic mutations in LIG4 are a common cause of microcephalic primordial dwarfism (MPD), a phenotype characterized by prenatal-onset extreme global growth failure. Here we provide definitive molecular genetic evidence supported by biochemical, cellular, and immunological data for mutations in XRCC4, encoding the obligate binding partner of LIG4, causing MPD. We report the identification of biallelic mutations in XRCC4 in five families. Biochemical and cellular studies demonstrate that these alterations substantially decrease XRCC4 protein levels leading to reduced cellular ligase IV activity. Consequently, NHEJ-dependent repair of ionizing-radiation-induced DNA double-strand breaks is compromised in XRCC4 cells. Similarly, immunoglobulin junctional diversification is impaired in cells. However, immunoglobulin levels are normal, and individuals lack overt signs of immunodeficiency. Additionally, in contrast to individuals with LIG4 mutations, pancytopenia leading to bone marrow failure has not been observed. Hence, alterations that alter different NHEJ proteins give rise to a phenotypic spectrum, from SCID to extreme growth failure, with deficiencies in certain key components of this repair pathway predominantly exhibiting growth deficits, reflecting differential developmental requirements for NHEJ proteins to support growth and immune maturation. PMID:25728776

Self-reported pigmentary phenotypes and race are significant but incomplete predictors of Fitzpatrick skin phototype in an ethnically diverse population.

PubMed

He, Steven Y; McCulloch, Charles E; Boscardin, W John; Chren, Mary-Margaret; Linos, Eleni; Arron, Sarah T

2014-10-01

Fitzpatrick skin phototype (FSPT) is the most common method used to assess sunburn risk and is an independent predictor of skin cancer risk. Because of a conventional assumption that FSPT is predictable based on pigmentary phenotypes, physicians frequently estimate FSPT based on patient appearance. We sought to determine the degree to which self-reported race and pigmentary phenotypes are predictive of FSPT in a large, ethnically diverse population. A cross-sectional survey collected responses from 3386 individuals regarding self-reported FSPT, pigmentary phenotypes, race, age, and sex. Univariate and multivariate logistic regression analyses were performed to determine variables that significantly predict FSPT. Race, sex, skin color, eye color, and hair color are significant but weak independent predictors of FSPT (P<.0001). A multivariate model constructed using all independent predictors of FSPT only accurately predicted FSPT to within 1 point on the Fitzpatrick scale with 92% accuracy (weighted kappa statistic 0.53). Our study enriched for responses from ethnic minorities and does not fully represent the demographics of the US population. Patient self-reported race and pigmentary phenotypes are inaccurate predictors of sun sensitivity as defined by FSPT. There are limitations to using patient-reported race and appearance in predicting individual sunburn risk. Copyright © 2014 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Complementation of non-tumorigenicity of HPV18-positive cervical carcinoma cells involves differential mRNA expression of cellular genes including potential tumor suppressor genes on chromosome 11q13.

PubMed

Kehrmann, Angela; Truong, Ha; Repenning, Antje; Boger, Regina; Klein-Hitpass, Ludger; Pascheberg, Ulrich; Beckmann, Alf; Opalka, Bertram; Kleine-Lowinski, Kerstin

2013-01-01

The fusion between human tumorigenic cells and normal human diploid fibroblasts results in non-tumorigenic hybrid cells, suggesting a dominant role for tumor suppressor genes in the generated hybrid cells. After long-term cultivation in vitro, tumorigenic segregants may arise. The loss of tumor suppressor genes on chromosome 11q13 has been postulated to be involved in the induction of the tumorigenic phenotype of human papillomavirus (HPV)18-positive cervical carcinoma cells and their derived tumorigenic hybrid cells after subcutaneous injection in immunocompromised mice. The aim of this study was the identification of novel cellular genes that may contribute to the suppression of the tumorigenic phenotype of non-tumorigenic hybrid cells in vivo. We used cDNA microarray technology to identify differentially expressed cellular genes in tumorigenic HPV18-positive hybrid and parental HeLa cells compared to non-tumorigenic HPV18-positive hybrid cells. We detected several as yet unknown cellular genes that play a role in cell differentiation, cell cycle progression, cell-cell communication, metastasis formation, angiogenesis, antigen presentation, and immune response. Apart from the known differentially expressed genes on 11q13 (e.g., phosphofurin acidic cluster sorting protein 1 (PACS1) and FOS ligand 1 (FOSL1 or Fra-1)), we detected novel differentially expressed cellular genes located within the tumor suppressor gene region (e.g., EGF-containing fibulin-like extracellular matrix protein 2 (EFEMP2) and leucine rich repeat containing 32 (LRRC32) (also known as glycoprotein-A repetitions predominant (GARP)) that may have potential tumor suppressor functions in this model system of non-tumorigenic and tumorigenic HeLa x fibroblast hybrid cells. Copyright © 2013 Elsevier Inc. All rights reserved.

Mild intermittent hypoxemia in neonatal mice causes permanent neurofunctional deficit and white matter hypomyelination.

PubMed

Juliano, Courtney; Sosunov, Sergey; Niatsetskaya, Zoya; Isler, Joseph A; Utkina-Sosunova, Irina; Jang, Isaac; Ratner, Veniamin; Ten, Vadim

2015-02-01

Very low birth weight (VLBW) premature infants experience numerous, often self-limited non-bradycardic episodes of intermittent hypoxemia (IH). We hypothesized that these episodes of IH affect postnatal white matter (WM) development causing hypomyelination and neurological handicap in the absence of cellular degeneration. Based on clinical data from ten VLBW neonates; a severity, daily duration and frequency of non-bradycardic IH episodes were reproduced in neonatal mice. Changes in heart rate and cerebral blood flow during IH were recorded. A short-term and long-term neurofunctional performance, cerebral content of myelin basic protein (MBP), 2'3' cyclic-nucleotide 3-phosphodiesterase (CNPase), electron microscopy of axonal myelination and the extent of cellular degeneration were examined. Neonatal mice exposed to IH exhibited no signs of cellular degeneration, yet demonstrated significantly poorer olfactory discrimination, wire holding, beam and bridge crossing, and walking-initiation tests performance compared to controls. In adulthood, IH-mice demonstrated no alteration in navigational memory. However, sensorimotor performance on rota-rod, wire-holding and beam tests was significantly worse compared to naive littermates. Both short- and long-term neurofunctional deficits were coupled with decreased MBP, CNPase content and poorer axonal myelination compared to controls. In neonatal mice mild, non-ischemic IH stress, mimicking that in VLBW preterm infants, replicates a key phenotype of non-cystic WM injury: permanent hypomyelination and sensorimotor deficits. Because this phenotype has developed in the absence of cellular degeneration, our data suggest that cellular mechanisms of WM injury induced by mild IH differ from that of cystic periventricular leukomalacia where the loss of myelin-producing cells and axons is the major mechanism of injury. Copyright © 2014 Elsevier Inc. All rights reserved.

Early spatiotemporal-specific changes in intermediate signals are predictive of cytotoxic sensitivity to TNFα and co-treatments

NASA Astrophysics Data System (ADS)

Loo, Lit-Hsin; Bougen-Zhukov, Nicola Michelle; Tan, Wei-Ling Cecilia

2017-03-01

Signaling pathways can generate different cellular responses to the same cytotoxic agents. Current quantitative models for predicting these differential responses are usually based on large numbers of intracellular gene products or signals at different levels of signaling cascades. Here, we report a study to predict cellular sensitivity to tumor necrosis factor alpha (TNFα) using high-throughput cellular imaging and machine-learning methods. We measured and compared 1170 protein phosphorylation events in a panel of human lung cancer cell lines based on different signals, subcellular regions, and time points within one hour of TNFα treatment. We found that two spatiotemporal-specific changes in an intermediate signaling protein, p90 ribosomal S6 kinase (RSK), are sufficient to predict the TNFα sensitivity of these cell lines. Our models could also predict the combined effects of TNFα and other kinase inhibitors, many of which are not known to target RSK directly. Therefore, early spatiotemporal-specific changes in intermediate signals are sufficient to represent the complex cellular responses to these perturbations. Our study provides a general framework for the development of rapid, signaling-based cytotoxicity screens that may be used to predict cellular sensitivity to a cytotoxic agent, or identify co-treatments that may sensitize or desensitize cells to the agent.

Early spatiotemporal-specific changes in intermediate signals are predictive of cytotoxic sensitivity to TNFα and co-treatments

PubMed Central

Loo, Lit-Hsin; Bougen-Zhukov, Nicola Michelle; Tan, Wei-Ling Cecilia

2017-01-01

Signaling pathways can generate different cellular responses to the same cytotoxic agents. Current quantitative models for predicting these differential responses are usually based on large numbers of intracellular gene products or signals at different levels of signaling cascades. Here, we report a study to predict cellular sensitivity to tumor necrosis factor alpha (TNFα) using high-throughput cellular imaging and machine-learning methods. We measured and compared 1170 protein phosphorylation events in a panel of human lung cancer cell lines based on different signals, subcellular regions, and time points within one hour of TNFα treatment. We found that two spatiotemporal-specific changes in an intermediate signaling protein, p90 ribosomal S6 kinase (RSK), are sufficient to predict the TNFα sensitivity of these cell lines. Our models could also predict the combined effects of TNFα and other kinase inhibitors, many of which are not known to target RSK directly. Therefore, early spatiotemporal-specific changes in intermediate signals are sufficient to represent the complex cellular responses to these perturbations. Our study provides a general framework for the development of rapid, signaling-based cytotoxicity screens that may be used to predict cellular sensitivity to a cytotoxic agent, or identify co-treatments that may sensitize or desensitize cells to the agent. PMID:28272488

Accuracy of genomic prediction using deregressed breeding values estimated from purebred and crossbred offspring phenotypes in pigs.

PubMed

Hidalgo, A M; Bastiaansen, J W M; Lopes, M S; Veroneze, R; Groenen, M A M; de Koning, D-J

2015-07-01

Genomic selection is applied to dairy cattle breeding to improve the genetic progress of purebred (PB) animals, whereas in pigs and poultry the target is a crossbred (CB) animal for which a different strategy appears to be needed. The source of information used to estimate the breeding values, i.e., using phenotypes of CB or PB animals, may affect the accuracy of prediction. The objective of our study was to assess the direct genomic value (DGV) accuracy of CB and PB pigs using different sources of phenotypic information. Data used were from 3 populations: 2,078 Dutch Landrace-based, 2,301 Large White-based, and 497 crossbreds from an F1 cross between the 2 lines. Two female reproduction traits were analyzed: gestation length (GLE) and total number of piglets born (TNB). Phenotypes used in the analyses originated from offspring of genotyped individuals. Phenotypes collected on CB and PB animals were analyzed as separate traits using a single-trait model. Breeding values were estimated separately for each trait in a pedigree BLUP analysis and subsequently deregressed. Deregressed EBV for each trait originating from different sources (CB or PB offspring) were used to study the accuracy of genomic prediction. Accuracy of prediction was computed as the correlation between DGV and the DEBV of the validation population. Accuracy of prediction within PB populations ranged from 0.43 to 0.62 across GLE and TNB. Accuracies to predict genetic merit of CB animals with one PB population in the training set ranged from 0.12 to 0.28, with the exception of using the CB offspring phenotype of the Dutch Landrace that resulted in an accuracy estimate around 0 for both traits. Accuracies to predict genetic merit of CB animals with both parental PB populations in the training set ranged from 0.17 to 0.30. We conclude that prediction within population and trait had good predictive ability regardless of the trait being the PB or CB performance, whereas using PB population(s) to predict genetic merit of CB animals had zero to moderate predictive ability. We observed that the DGV accuracy of CB animals when training on PB data was greater than or equal to training on CB data. However, when results are corrected for the different levels of reliabilities in the PB and CB training data, we showed that training on CB data does outperform PB data for the prediction of CB genetic merit, indicating that more CB animals should be phenotyped to increase the reliability and, consequently, accuracy of DGV for CB genetic merit.

Flotillin proteins recruit sphingosine to membranes and maintain cellular sphingosine-1-phosphate levels

PubMed Central

Riento, Kirsi; Zhang, Qifeng; Clark, Jonathan; Begum, Farida; Stephens, Elaine; Wakelam, Michael J.

2018-01-01

Sphingosine-1-phosphate (S1P) is an important lipid signalling molecule. S1P is produced via intracellular phosphorylation of sphingosine (Sph). As a lipid with a single fatty alkyl chain, Sph may diffuse rapidly between cellular membranes and through the aqueous phase. Here, we show that the absence of microdomains generated by multimeric assemblies of flotillin proteins results in reduced S1P levels. Cellular phenotypes of flotillin knockout mice, including changes in histone acetylation and expression of Isg15, are recapitulated when S1P synthesis is perturbed. Flotillins bind to Sph in vitro and increase recruitment of Sph to membranes in cells. Ectopic re-localisation of flotillins within the cell causes concomitant redistribution of Sph. The data suggest that flotillins may directly or indirectly regulate cellular sphingolipid distribution and signalling. PMID:29787576

Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis.

PubMed

Lee, Jessica J Y; Gottlieb, Michael M; Lever, Jake; Jones, Steven J M; Blau, Nenad; van Karnebeek, Clara D M; Wasserman, Wyeth W

2018-05-01

Phenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze phenotypes. Such methods have allowed phenotypic data to be widely used in medical applications, from assisting clinical diagnoses to prioritizing genomic diagnoses. To channel the benefits of phenomics into the field of inborn errors of metabolism (IEM), we have recently launched IEMbase, an expert-curated knowledgebase of IEM and their disease-characterizing phenotypes. While our efforts with IEMbase have realized benefits, taking full advantage of phenomics requires a comprehensive curation of IEM phenotypes in core phenomics projects, which is dependent upon contributions from the IEM clinical and research community. Here, we assess the inclusion of IEM biochemical phenotypes in a core phenomics project, the Human Phenotype Ontology. We then demonstrate the utility of biochemical phenotypes using a text-based phenomics method to predict gene-disease relationships, showing that the prediction of IEM genes is significantly better using biochemical rather than clinical profiles. The findings herein provide a motivating goal for the IEM community to expand the computationally accessible descriptions of biochemical phenotypes associated with IEM in phenomics resources.

Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

USDA-ARS?s Scientific Manuscript database

The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...

Demographic and phenotypic responses of juvenile steelhead trout to spatial predictability of food resources

Treesearch

Matthew R. Sloat; Gordon H. Reeves

2014-01-01

We manipulated food inputs among patches within experimental streams to determine how variation in foraging behavior influenced demographic and phenotypic responses of juvenile steelhead trout (Oncorhynchus mykiss) to the spatial predictability of food resources. Demographic responses included compensatory adjustments in fish abundance, mean fish...

Not just black and white: pigment pattern development and evolution in vertebrates

PubMed Central

Mills, Margaret G.; Patterson, Larissa B.

2009-01-01

Animals display diverse colors and patterns that vary within and between species. Similar phenotypes appear in both closely related and widely divergent taxa. Pigment patterns thus provide an opportunity to explore how development is altered to produce differences in form and whether similar phenotypes share a common genetic basis. Understanding the development and evolution of pigment patterns requires knowledge of the cellular interactions and signaling pathways that produce those patterns. These complex traits provide unparalleled opportunities for integrating studies from ecology and behavior to molecular biology and biophysics. PMID:19073271

Effects of nanotopography on stem cell phenotypes.

PubMed

Ravichandran, Rajeswari; Liao, Susan; Ng, Clarisse Ch; Chan, Casey K; Raghunath, Michael; Ramakrishna, Seeram

2009-12-31

Stem cells are unspecialized cells that can self renew indefinitely and differentiate into several somatic cells given the correct environmental cues. In the stem cell niche, stem cell-extracellular matrix (ECM) interactions are crucial for different cellular functions, such as adhesion, proliferation, and differentiation. Recently, in addition to chemical surface modifications, the importance of nanometric scale surface topography and roughness of biomaterials has increasingly becoming recognized as a crucial factor for cell survival and host tissue acceptance in synthetic ECMs. This review describes the influence of nanotopography on stem cell phenotypes.

IRESPred: Web Server for Prediction of Cellular and Viral Internal Ribosome Entry Site (IRES)

PubMed Central

Kolekar, Pandurang; Pataskar, Abhijeet; Kulkarni-Kale, Urmila; Pal, Jayanta; Kulkarni, Abhijeet

2016-01-01

Cellular mRNAs are predominantly translated in a cap-dependent manner. However, some viral and a subset of cellular mRNAs initiate their translation in a cap-independent manner. This requires presence of a structured RNA element, known as, Internal Ribosome Entry Site (IRES) in their 5′ untranslated regions (UTRs). Experimental demonstration of IRES in UTR remains a challenging task. Computational prediction of IRES merely based on sequence and structure conservation is also difficult, particularly for cellular IRES. A web server, IRESPred is developed for prediction of both viral and cellular IRES using Support Vector Machine (SVM). The predictive model was built using 35 features that are based on sequence and structural properties of UTRs and the probabilities of interactions between UTR and small subunit ribosomal proteins (SSRPs). The model was found to have 75.51% accuracy, 75.75% sensitivity, 75.25% specificity, 75.75% precision and Matthews Correlation Coefficient (MCC) of 0.51 in blind testing. IRESPred was found to perform better than the only available viral IRES prediction server, VIPS. The IRESPred server is freely available at http://bioinfo.net.in/IRESPred/. PMID:27264539

Saccharomyces cerevisiae metabolism in ecological context.

PubMed

Jouhten, Paula; Ponomarova, Olga; Gonzalez, Ramon; Patil, Kiran R

2016-11-01

The architecture and regulation of Saccharomyces cerevisiae metabolic network are among the best studied owing to its widespread use in both basic research and industry. Yet, several recent studies have revealed notable limitations in explaining genotype-metabolic phenotype relations in this yeast, especially when concerning multiple genetic/environmental perturbations. Apparently unexpected genotype-phenotype relations may originate in the evolutionarily shaped cellular operating principles being hidden in common laboratory conditions. Predecessors of laboratory S. cerevisiae strains, the wild and the domesticated yeasts, have been evolutionarily shaped by highly variable environments, very distinct from laboratory conditions, and most interestingly by social life within microbial communities. Here we present a brief review of the genotypic and phenotypic peculiarities of S. cerevisiae in the context of its social lifestyle beyond laboratory environments. Accounting for this ecological context and the origin of the laboratory strains in experimental design and data analysis would be essential in improving the understanding of genotype-environment-phenotype relationships. © FEMS 2016.

Biological monitoring of environmental quality: The use of developmental instability

USGS Publications Warehouse

Freeman, D.C.; Emlen, J.M.; Graham, J.H.; Hough, R. A.; Bannon, T.A.

1994-01-01

Distributed robustness is thought to influence the buffering of random phenotypic variation through the scale-free topology of gene regulatory, metabolic, and protein-protein interaction networks. If this hypothesis is true, then the phenotypic response to the perturbation of particular nodes in such a network should be proportional to the number of links those nodes make with neighboring nodes. This suggests a probability distribution approximating an inverse power-law of random phenotypic variation. Zero phenotypic variation, however, is impossible, because random molecular and cellular processes are essential to normal development. Consequently, a more realistic distribution should have a y-intercept close to zero in the lower tail, a mode greater than zero, and a long (fat) upper tail. The double Pareto-lognormal (DPLN) distribution is an ideal candidate distribution. It consists of a mixture of a lognormal body and upper and lower power-law tails.

Saccharomyces cerevisiae metabolism in ecological context

PubMed Central

Jouhten, Paula; Ponomarova, Olga; Gonzalez, Ramon

2016-01-01

The architecture and regulation of Saccharomyces cerevisiae metabolic network are among the best studied owing to its widespread use in both basic research and industry. Yet, several recent studies have revealed notable limitations in explaining genotype–metabolic phenotype relations in this yeast, especially when concerning multiple genetic/environmental perturbations. Apparently unexpected genotype–phenotype relations may originate in the evolutionarily shaped cellular operating principles being hidden in common laboratory conditions. Predecessors of laboratory S. cerevisiae strains, the wild and the domesticated yeasts, have been evolutionarily shaped by highly variable environments, very distinct from laboratory conditions, and most interestingly by social life within microbial communities. Here we present a brief review of the genotypic and phenotypic peculiarities of S. cerevisiae in the context of its social lifestyle beyond laboratory environments. Accounting for this ecological context and the origin of the laboratory strains in experimental design and data analysis would be essential in improving the understanding of genotype–environment–phenotype relationships. PMID:27634775

Automated deep-phenotyping of the vertebrate brain

PubMed Central

Allalou, Amin; Wu, Yuelong; Ghannad-Rezaie, Mostafa; Eimon, Peter M; Yanik, Mehmet Fatih

2017-01-01

Here, we describe an automated platform suitable for large-scale deep-phenotyping of zebrafish mutant lines, which uses optical projection tomography to rapidly image brain-specific gene expression patterns in 3D at cellular resolution. Registration algorithms and correlation analysis are then used to compare 3D expression patterns, to automatically detect all statistically significant alterations in mutants, and to map them onto a brain atlas. Automated deep-phenotyping of a mutation in the master transcriptional regulator fezf2 not only detects all known phenotypes but also uncovers important novel neural deficits that were overlooked in previous studies. In the telencephalon, we show for the first time that fezf2 mutant zebrafish have significant patterning deficits, particularly in glutamatergic populations. Our findings reveal unexpected parallels between fezf2 function in zebrafish and mice, where mutations cause deficits in glutamatergic neurons of the telencephalon-derived neocortex. DOI: http://dx.doi.org/10.7554/eLife.23379.001 PMID:28406399

Assessment of Cell Line Models of Primary Human Cells by Raman Spectral Phenotyping

PubMed Central

Swain, Robin J.; Kemp, Sarah J.; Goldstraw, Peter; Tetley, Teresa D.; Stevens, Molly M.

2010-01-01

Abstract Researchers have previously questioned the suitability of cell lines as models for primary cells. In this study, we used Raman microspectroscopy to characterize live A549 cells from a unique molecular biochemical perspective to shed light on their suitability as a model for primary human pulmonary alveolar type II (ATII) cells. We also investigated a recently developed transduced type I (TT1) cell line as a model for alveolar type I (ATI) cells. Single-cell Raman spectra provide unique biomolecular fingerprints that can be used to characterize cellular phenotypes. A multivariate statistical analysis of Raman spectra indicated that the spectra of A549 and TT1 cells are characterized by significantly lower phospholipid content compared to ATII and ATI spectra because their cytoplasm contains fewer surfactant lamellar bodies. Furthermore, we found that A549 spectra are statistically more similar to ATI spectra than to ATII spectra. The spectral variation permitted phenotypic classification of cells based on Raman spectral signatures with >99% accuracy. These results suggest that A549 cells are not a good model for ATII cells, but TT1 cells do provide a reasonable model for ATI cells. The findings have far-reaching implications for the assessment of cell lines as suitable primary cellular models in live cultures. PMID:20409492

Cryopreservation of adenovirus-transfected dendritic cells (DCs) for clinical use.

PubMed

Gülen, D; Maas, S; Julius, H; Warkentin, P; Britton, H; Younos, I; Senesac, J; Pirruccello, Samuel M; Talmadge, J E

2012-05-01

In this study, we examined the effects of cryoprotectant, freezing and thawing, and adenovirus (Adv) transduction on the viability, transgene expression, phenotype, and function of human dendritic cells (DCs). DCs were differentiated from cultured peripheral blood (PB) monocytes following Elutra isolation using granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin-4 (IL-4) for 6 days and then transduced using an Adv vector with an IL-12 transgene. Fresh, cryopreserved, and thawed transduced immature DCs were examined for their: 1) cellular concentration and viability; 2) antigenicity using an allogeneic mixed lymphocyte reaction (MLR); 3) phenotype (HLA-DR and CD11c) and activation (CD83); and 4) transgene expression based on IL-12 secretion. Stability studies revealed that transduced DCs could be held in cryoprotectant for as long as 75 min at 2-8°C prior to freezing with little effect on their viability and cellularity. Further, cryopreservation, storage, and thawing reduced the viability of the transduced DCs by an average of 7.7%; and had no significant impact on DC phenotype and activation. In summary, cryopreservation, storage, and thawing had no significant effect on DC viability, function, and transgene expression by Adv-transduced DCs. Copyright © 2012 Elsevier B.V. All rights reserved.

Extracellular environment modulates the formation and propagation of particular amyloid structures

PubMed Central

Westergard, Laura; True, Heather L.

2016-01-01

Summary Amyloidogenic proteins, including prions, assemble into multiple forms of structurally distinct fibres. The [PSI+] prion, endogenous to the yeast Saccharomyces cerevisiae, is a dominantly inherited, epigenetic modifier of phenotypes. [PSI+] formation relies on the coexistence of another prion, [RNQ+]. Here, in order to better define the role of amyloid diversity on cellular phenotypes, we investigated how physiological and environmental changes impact the generation and propagation of diverse protein conformations from a single polypeptide. Utilizing the yeast model system, we defined extracellular factors that influence the formation of a spectrum of alternative self-propagating amyloid structures of the Sup35 protein, called [PSI+] variants. Strikingly, exposure to specific stressful environments dramatically altered the variants of [PSI+] that formed de novo. Additionally, we found that stress also influenced the association between the [PSI+] and [RNQ+] prions in a way that it superceded their typical relationship. Furthermore, changing the growth environment modified both the biochemical properties and [PSI+]-inducing capabilities of the [RNQ+] template. These data suggest that the cellular environment contributes to both the generation and the selective propagation of specific amyloid structures, providing insight into a key feature that impacts phenotypic diversity in yeast and the cross-species transmission barriers characteristic of prion diseases. PMID:24628771

Histone deacetylases regulate multicellular development in the social amoeba Dictyostelium discoideum.

PubMed

Sawarkar, Ritwick; Visweswariah, Sandhya S; Nellen, Wolfgang; Nanjundiah, Vidyanand

2009-09-04

Epigenetic modifications of histones regulate gene expression and lead to the establishment and maintenance of cellular phenotypes during development. Histone acetylation depends on a balance between the activities of histone acetyltransferases and histone deacetylases (HDACs) and influences transcriptional regulation. In this study, we analyse the roles of HDACs during growth and development of one of the cellular slime moulds, the social amoeba Dictyostelium discoideum. The inhibition of HDAC activity by trichostatin A results in histone hyperacetylation and a delay in cell aggregation and differentiation. Cyclic AMP oscillations are normal in starved amoebae treated with trichostatin A but the expression of a subset of cAMP-regulated genes is delayed. Bioinformatic analysis indicates that there are four genes encoding putative HDACs in D. discoideum. Using biochemical, genetic and developmental approaches, we demonstrate that one of these four genes, hdaB, is dispensable for growth and development under laboratory conditions. A knockout of the hdaB gene results in a social context-dependent phenotype: hdaB(-) cells develop normally but sporulate less efficiently than the wild type in chimeras. We infer that HDAC activity is important for regulating the timing of gene expression during the development of D. discoideum and for defining aspects of the phenotype that mediate social behaviour in genetically heterogeneous groups.

[Phenotypic heterogeneity of chronic obstructive pulmonary disease].

PubMed

Garcia-Aymerich, Judith; Agustí, Alvar; Barberà, Joan A; Belda, José; Farrero, Eva; Ferrer, Antoni; Ferrer, Jaume; Gáldiz, Juan B; Gea, Joaquim; Gómez, Federico P; Monsó, Eduard; Morera, Josep; Roca, Josep; Sauleda, Jaume; Antó, Josep M

2009-03-01

A functional definition of chronic obstructive pulmonary disease (COPD) based on airflow limitation has largely dominated the field. However, a view has emerged that COPD involves a complex array of cellular, organic, functional, and clinical events, with a growing interest in disentangling the phenotypic heterogeneity of COPD. The present review is based on the opinion of the authors, who have extensive research experience in several aspects of COPD. The starting assumption of the review is that current knowledge on the pathophysiology and clinical features of COPD allows us to classify phenotypic information in terms of the following dimensions: respiratory symptoms and health status, acute exacerbations, lung function, structural changes, local and systemic inflammation, and systemic effects. Twenty-six phenotypic traits were identified and assigned to one of the 6 dimensions. For each dimension, a summary is provided of the best evidence on the relationships among phenotypic traits, in particular among those corresponding to different dimensions, and on the relationship between these traits and relevant events in the natural history of COPD. The information has been organized graphically into a phenotypic matrix where each cell representing a pair of phenotypic traits is linked to relevant references. The information provided has the potential to increase our understanding of the heterogeneity of COPD phenotypes and help us plan future studies on aspects that are as yet unexplored.

Engineering yeast transcription machinery for improved ethanol tolerance and production.

PubMed

Alper, Hal; Moxley, Joel; Nevoigt, Elke; Fink, Gerald R; Stephanopoulos, Gregory

2006-12-08

Global transcription machinery engineering (gTME) is an approach for reprogramming gene transcription to elicit cellular phenotypes important for technological applications. Here we show the application of gTME to Saccharomyces cerevisiae for improved glucose/ethanol tolerance, a key trait for many biofuels programs. Mutagenesis of the transcription factor Spt15p and selection led to dominant mutations that conferred increased tolerance and more efficient glucose conversion to ethanol. The desired phenotype results from the combined effect of three separate mutations in the SPT15 gene [serine substituted for phenylalanine (Phe(177)Ser) and, similarly, Tyr(195)His, and Lys(218)Arg]. Thus, gTME can provide a route to complex phenotypes that are not readily accessible by traditional methods.

Behavioral Phenotyping and Pathological Indicators of Parkinson's Disease in C. elegans Models

PubMed Central

Maulik, Malabika; Mitra, Swarup; Bult-Ito, Abel; Taylor, Barbara E.; Vayndorf, Elena M.

2017-01-01

Parkinson's disease (PD) is a neurodegenerative disorder with symptoms that progressively worsen with age. Pathologically, PD is characterized by the aggregation of α-synuclein in cells of the substantia nigra in the brain and loss of dopaminergic neurons. This pathology is associated with impaired movement and reduced cognitive function. The etiology of PD can be attributed to a combination of environmental and genetic factors. A popular animal model, the nematode roundworm Caenorhabditis elegans, has been frequently used to study the role of genetic and environmental factors in the molecular pathology and behavioral phenotypes associated with PD. The current review summarizes cellular markers and behavioral phenotypes in transgenic and toxin-induced PD models of C. elegans. PMID:28659967

Discovery of a Chemical Probe Bisamide (CCT251236): An Orally Bioavailable Efficacious Pirin Ligand from a Heat Shock Transcription Factor 1 (HSF1) Phenotypic Screen

PubMed Central

2016-01-01

Phenotypic screens, which focus on measuring and quantifying discrete cellular changes rather than affinity for individual recombinant proteins, have recently attracted renewed interest as an efficient strategy for drug discovery. In this article, we describe the discovery of a new chemical probe, bisamide (CCT251236), identified using an unbiased phenotypic screen to detect inhibitors of the HSF1 stress pathway. The chemical probe is orally bioavailable and displays efficacy in a human ovarian carcinoma xenograft model. By developing cell-based SAR and using chemical proteomics, we identified pirin as a high affinity molecular target, which was confirmed by SPR and crystallography. PMID:28004573

Mycobacterium tuberculosis toxin Rv2872 is an RNase involved in vancomycin stress response and biofilm development.

PubMed

Wang, Xiaoyu; Zhao, Xiaokang; Wang, Hao; Huang, Xue; Duan, Xiangke; Gu, Yinzhong; Lambert, Nzungize; Zhang, Ke; Kou, Zhenhao; Xie, Jianping

2018-06-11

Bacterial toxin-antitoxin (TA) systems are emerging important regulators of multiple cellular physiological events and candidates for novel antibiotic targets. To explore the role of Mycobacterium tuberculosis function, unknown toxin gene Rv2872 was heterologously expressed in Mycobacterium smegmatis (MS_Rv2872). Upon induction, MS_Rv2872 phenotype differed significantly from the control, such as increased vancomycin resistance, retarded growth, cell wall, and biofilm structure. This phenotype change might result from the RNase activity of Rv2872 as purified Rv2872 toxin protein can cleave the products of several key genes involved in abovementioned phenotypes. In summary, toxin Rv2872 was firstly reported to be a endonuclease involved in antibiotic stress responses, cell wall structure, and biofilm development.

Protocols for Migration and Invasion Studies in Prostate Cancer.

PubMed

van de Merbel, Arjanneke F; van der Horst, Geertje; Buijs, Jeroen T; van der Pluijm, Gabri

2018-01-01

Prostate cancer is the most common malignancy diagnosed in men in the western world. The development of distant metastases and therapy resistance are major clinical problems in the management of prostate cancer patients. In order for prostate cancer to metastasize to distant sites in the human body, prostate cancer cells have to migrate and invade neighboring tissue. Cancer cells can acquire a migratory and invasive phenotype in several ways, including single cell and collective migration. As a requisite for migration, epithelial prostate cancer cells often need to acquire a motile, mesenchymal-like phenotype. This way prostate cancer cells often lose polarity and epithelial characteristics (e.g., expression of E-cadherin homotypic adhesion receptor), and acquire mesenchymal phenotype (for example, cytoskeletal rearrangements, enhanced expression of proteolytic enzymes and other repertory of integrins). This process is referred to as epithelial-to-mesenchymal transition (EMT). Cellular invasion, one of the hallmarks of cancer, is characterized by the movement of cells through a three-dimensional matrix, resulting in remodeling of the cellular environment. Cellular invasion requires adhesion, proteolysis of the extracellular matrix, and migration of cells. Studying the migratory and invasive ability of cells in vitro represents a useful tool to assess the aggressiveness of solid cancers, including those of the prostate.This chapter provides a comprehensive description of the Transwell migration assay, a commonly used technique to investigate the migratory behavior of prostate cancer cells in vitro. Furthermore, we will provide an overview of the adaptations to the Transwell migration protocol to study the invasive capacity of prostate cancer cells, i.e., the Transwell invasion assay. Finally, we will present a detailed description of the procedures required to stain the Transwell filter inserts and quantify the migration and/or invasion.

Phenotypic diversity in autosomal-dominant cone-rod dystrophy elucidated by adaptive optics retinal imaging

PubMed Central

Song, Hongxin; Rossi, Ethan A; Stone, Edwin; Latchney, Lisa; Williams, David; Dubra, Alfredo; Chung, Mina

2018-01-01

Purpose Several genes causing autosomal-dominant cone-rod dystrophy (AD-CRD) have been identified. However, the mechanisms by which genetic mutations lead to cellular loss in human disease remain poorly understood. Here we combine genotyping with high-resolution adaptive optics retinal imaging to elucidate the retinal phenotype at a cellular level in patients with AD-CRD harbouring a defect in the GUCA1A gene. Methods Nine affected members of a four-generation AD-CRD pedigree and three unaffected first-degree relatives underwent clinical examinations including visual acuity, fundus examination, Goldmann perimetry, spectral domain optical coherence tomography and electroretinography. Genome-wide scan followed by bidirectional sequencing was performed on all affected participants. High-resolution imaging using a custom adaptive optics scanning light ophthalmoscope (AOSLO) was performed for selected participants. Results Clinical evaluations showed a range of disease severity from normal fundus appearance in teenaged patients to pronounced macular atrophy in older patients. Molecular genetic testing showed a mutation in in GUCA1A segregating with disease. AOSLO imaging revealed that of the two teenage patients with mild disease, one had severe disruption of the photoreceptor mosaic while the other had a normal cone mosaic. Conclusions AOSLO imaging demonstrated variability in the pattern of cone and rod cell loss between two teenage cousins with early AD-CRD, who had similar clinical features and had the identical disease-causing mutation in GUCA1A. This finding suggests that a mutation in GUCA1A does not lead to the same degree of AD-CRD in all patients. Modifying factors may mitigate or augment disease severity, leading to different retinal cellular phenotypes. PMID:29074494

Formation of human hepatocyte-like cells with different cellular phenotypes by human umbilical cord blood-derived cells in the human-rat chimeras

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Yan; Xiao, Dong; Zhang, Ruo-Shuang

2007-06-15

We took advantage of the proliferative and permissive environment of the developing pre-immune fetus to develop a noninjury human-rat xenograft small animal model, in which the in utero transplantation of low-density mononuclear cells (MNCs) from human umbilical cord blood (hUCB) into fetal rats at 9-11 days of gestation led to the formation of human hepatocyte-like cells (hHLCs) with different cellular phenotypes, as revealed by positive immunostaining for human-specific alpha-fetoprotein (AFP), cytokeratin 19 (CK19), cytokeratin 8 (CK8), cytokeratin 18 (CK18), and albumin (Alb), and with some animals exhibiting levels as high as 10.7% of donor-derived human cells in the recipient liver.more » More interestingly, donor-derived human cells stained positively for CD34 and CD45 in the liver of 2-month-old rat. Human hepatic differentiation appeared to partially follow the process of hepatic ontogeny, as evidenced by the expression of AFP gene at an early stage and albumin gene at a later stage. Human hepatocytes generated in this model retained functional properties of normal hepatocytes. In this xenogeneic system, the engrafted donor-derived human cells persisted in the recipient liver for at least 6 months after birth. Taken together, these findings suggest that the donor-derived human cells with different cellular phenotypes are found in the recipient liver and hHLCs hold biological activity. This humanized small animal model, which offers an in vivo environment more closely resembling the situations in human, provides an invaluable approach for in vivo investigating human stem cell behaviors, and further in vivo examining fundamental mechanisms controlling human stem cell fates in the future.« less

Phenotypic diversity in autosomal-dominant cone-rod dystrophy elucidated by adaptive optics retinal imaging.

PubMed

Song, Hongxin; Rossi, Ethan A; Stone, Edwin; Latchney, Lisa; Williams, David; Dubra, Alfredo; Chung, Mina

2018-01-01

Several genes causing autosomal-dominant cone-rod dystrophy (AD-CRD) have been identified. However, the mechanisms by which genetic mutations lead to cellular loss in human disease remain poorly understood. Here we combine genotyping with high-resolution adaptive optics retinal imaging to elucidate the retinal phenotype at a cellular level in patients with AD-CRD harbouring a defect in the GUCA1A gene. Nine affected members of a four-generation AD-CRD pedigree and three unaffected first-degree relatives underwent clinical examinations including visual acuity, fundus examination, Goldmann perimetry, spectral domain optical coherence tomography and electroretinography. Genome-wide scan followed by bidirectional sequencing was performed on all affected participants. High-resolution imaging using a custom adaptive optics scanning light ophthalmoscope (AOSLO) was performed for selected participants. Clinical evaluations showed a range of disease severity from normal fundus appearance in teenaged patients to pronounced macular atrophy in older patients. Molecular genetic testing showed a mutation in in GUCA1A segregating with disease. AOSLO imaging revealed that of the two teenage patients with mild disease, one had severe disruption of the photoreceptor mosaic while the other had a normal cone mosaic. AOSLO imaging demonstrated variability in the pattern of cone and rod cell loss between two teenage cousins with early AD-CRD, who had similar clinical features and had the identical disease-causing mutation in GUCA1A . This finding suggests that a mutation in GUCA1A does not lead to the same degree of AD-CRD in all patients. Modifying factors may mitigate or augment disease severity, leading to different retinal cellular phenotypes. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Enabling phenotypic big data with PheNorm.

PubMed

Yu, Sheng; Ma, Yumeng; Gronsbell, Jessica; Cai, Tianrun; Ananthakrishnan, Ashwin N; Gainer, Vivian S; Churchill, Susanne E; Szolovits, Peter; Murphy, Shawn N; Kohane, Isaac S; Liao, Katherine P; Cai, Tianxi

2018-01-01

Electronic health record (EHR)-based phenotyping infers whether a patient has a disease based on the information in his or her EHR. A human-annotated training set with gold-standard disease status labels is usually required to build an algorithm for phenotyping based on a set of predictive features. The time intensiveness of annotation and feature curation severely limits the ability to achieve high-throughput phenotyping. While previous studies have successfully automated feature curation, annotation remains a major bottleneck. In this paper, we present PheNorm, a phenotyping algorithm that does not require expert-labeled samples for training. The most predictive features, such as the number of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes or mentions of the target phenotype, are normalized to resemble a normal mixture distribution with high area under the receiver operating curve (AUC) for prediction. The transformed features are then denoised and combined into a score for accurate disease classification. We validated the accuracy of PheNorm with 4 phenotypes: coronary artery disease, rheumatoid arthritis, Crohn's disease, and ulcerative colitis. The AUCs of the PheNorm score reached 0.90, 0.94, 0.95, and 0.94 for the 4 phenotypes, respectively, which were comparable to the accuracy of supervised algorithms trained with sample sizes of 100-300, with no statistically significant difference. The accuracy of the PheNorm algorithms is on par with algorithms trained with annotated samples. PheNorm fully automates the generation of accurate phenotyping algorithms and demonstrates the capacity for EHR-driven annotations to scale to the next level - phenotypic big data. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Connecting genes, coexpression modules, and molecular signatures to environmental stress phenotypes in plants

PubMed Central

Weston, David J; Gunter, Lee E; Rogers, Alistair; Wullschleger, Stan D

2008-01-01

Background One of the eminent opportunities afforded by modern genomic technologies is the potential to provide a mechanistic understanding of the processes by which genetic change translates to phenotypic variation and the resultant appearance of distinct physiological traits. Indeed much progress has been made in this area, particularly in biomedicine where functional genomic information can be used to determine the physiological state (e.g., diagnosis) and predict phenotypic outcome (e.g., patient survival). Ecology currently lacks an analogous approach where genomic information can be used to diagnose the presence of a given physiological state (e.g., stress response) and then predict likely phenotypic outcomes (e.g., stress duration and tolerance, fitness). Results Here, we demonstrate that a compendium of genomic signatures can be used to classify the plant abiotic stress phenotype in Arabidopsis according to the architecture of the transcriptome, and then be linked with gene coexpression network analysis to determine the underlying genes governing the phenotypic response. Using this approach, we confirm the existence of known stress responsive pathways and marker genes, report a common abiotic stress responsive transcriptome and relate phenotypic classification to stress duration. Conclusion Linking genomic signatures to gene coexpression analysis provides a unique method of relating an observed plant phenotype to changes in gene expression that underlie that phenotype. Such information is critical to current and future investigations in plant biology and, in particular, to evolutionary ecology, where a mechanistic understanding of adaptive physiological responses to abiotic stress can provide researchers with a tool of great predictive value in understanding species and population level adaptation to climate change. PMID:18248680

Forensic DNA Phenotyping: Predicting human appearance from crime scene material for investigative purposes.

PubMed

Kayser, Manfred

2015-09-01

Forensic DNA Phenotyping refers to the prediction of appearance traits of unknown sample donors, or unknown deceased (missing) persons, directly from biological materials found at the scene. "Biological witness" outcomes of Forensic DNA Phenotyping can provide investigative leads to trace unknown persons, who are unidentifiable with current comparative DNA profiling. This intelligence application of DNA marks a substantially different forensic use of genetic material rather than that of current DNA profiling presented in the courtroom. Currently, group-specific pigmentation traits are already predictable from DNA with reasonably high accuracies, while several other externally visible characteristics are under genetic investigation. Until individual-specific appearance becomes accurately predictable from DNA, conventional DNA profiling needs to be performed subsequent to appearance DNA prediction. Notably, and where Forensic DNA Phenotyping shows great promise, this is on a (much) smaller group of potential suspects, who match the appearance characteristics DNA-predicted from the crime scene stain or from the deceased person's remains. Provided sufficient funding being made available, future research to better understand the genetic basis of human appearance will expectedly lead to a substantially more detailed description of an unknown person's appearance from DNA, delivering increased value for police investigations in criminal and missing person cases involving unknowns. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Genetic Analyses of a Three Generation Family Segregating Hirschsprung Disease and Iris Heterochromia

PubMed Central

Cheng, Guo; Firmato de Almeida, Manoel; So, Man-Ting; Sham, Pak-Chung; Cherny, Stacey S.; Tam, Paul Kwong-Hang; Garcia-Barceló, Maria-Mercè

2013-01-01

We present the genetic analyses conducted on a three-generation family (14 individuals) with three members affected with isolated-Hirschsprung disease (HSCR) and one with HSCR and heterochromia iridum (syndromic-HSCR), a phenotype reminiscent of Waardenburg-Shah syndrome (WS4). WS4 is characterized by pigmentary abnormalities of the skin, eyes and/or hair, sensorineural deafness and HSCR. None of the members had sensorineural deafness. The family was screened for copy number variations (CNVs) using Illumina-HumanOmni2.5-Beadchip and for coding sequence mutations in WS4 genes (EDN3, EDNRB, or SOX10) and in the main HSCR gene (RET). Confocal microscopy and immunoblotting were used to assess the functional impact of the mutations. A heterozygous A/G transition in EDNRB was identified in 4 affected and 3 unaffected individuals. While in EDNRB isoforms 1 and 2 (cellular receptor) the transition results in the abolishment of translation initiation (M1V), in isoform 3 (only in the cytosol) the replacement occurs at Met91 (M91V) and is predicted benign. Another heterozygous transition (c.-248G/A; -predicted to affect translation efficiency-) in the 5′-untranslated region of EDN3 (EDNRB ligand) was detected in all affected individuals but not in healthy carriers of the EDNRB mutation. Also, a de novo CNVs encompassing DACH1 was identified in the patient with heterochromia iridum and HSCR Since the EDNRB and EDN3 variants only coexist in affected individuals, HSCR could be due to the joint effect of mutations in genes of the same pathway. Iris heterochromia could be due to an independent genetic event and would account for the additional phenotype within the family. PMID:23840513

Genes located in a chromosomal inversion are correlated with territorial song in white-throated sparrows.

PubMed

Zinzow-Kramer, W M; Horton, B M; McKee, C D; Michaud, J M; Tharp, G K; Thomas, J W; Tuttle, E M; Yi, S; Maney, D L

2015-11-01

The genome of the white-throated sparrow (Zonotrichia albicollis) contains an inversion polymorphism on chromosome 2 that is linked to predictable variation in a suite of phenotypic traits including plumage color, aggression and parental behavior. Differences in gene expression between the two color morphs, which represent the two common inversion genotypes (ZAL2/ZAL2 and ZAL2/ZAL2(m) ), may therefore advance our understanding of the molecular underpinnings of these phenotypes. To identify genes that are differentially expressed between the two morphs and correlated with behavior, we quantified gene expression and terrirorial aggression, including song, in a population of free-living white-throated sparrows. We analyzed gene expression in two brain regions, the medial amygdala (MeA) and hypothalamus. Both regions are part of a 'social behavior network', which is rich in steroid hormone receptors and previously linked with territorial behavior. Using weighted gene co-expression network analyses, we identified modules of genes that were correlated with both morph and singing behavior. The majority of these genes were located within the inversion, showing the profound effect of the inversion on the expression of genes captured by the rearrangement. These modules were enriched with genes related to retinoic acid signaling and basic cellular functioning. In the MeA, the most prominent pathways were those related to steroid hormone receptor activity. Within these pathways, the only gene encoding such a receptor was ESR1 (estrogen receptor 1), a gene previously shown to predict song rate in this species. The set of candidate genes we identified may mediate the effects of a chromosomal inversion on territorial behavior. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Chronic innate immune activation of TBK1 suppresses mTORC1 activity and dysregulates cellular metabolism.

PubMed

Hasan, Maroof; Gonugunta, Vijay K; Dobbs, Nicole; Ali, Aktar; Palchik, Guillermo; Calvaruso, Maria A; DeBerardinis, Ralph J; Yan, Nan

2017-01-24

Three-prime repair exonuclease 1 knockout (Trex1 -/- ) mice suffer from systemic inflammation caused largely by chronic activation of the cyclic GMP-AMP synthase-stimulator of interferon genes-TANK-binding kinase-interferon regulatory factor 3 (cGAS-STING-TBK1-IRF3) signaling pathway. We showed previously that Trex1-deficient cells have reduced mammalian target of rapamycin complex 1 (mTORC1) activity, although the underlying mechanism is unclear. Here, we performed detailed metabolic analysis in Trex1 -/- mice and cells that revealed both cellular and systemic metabolic defects, including reduced mitochondrial respiration and increased glycolysis, energy expenditure, and fat metabolism. We also genetically separated the inflammatory and metabolic phenotypes by showing that Sting deficiency rescued both inflammatory and metabolic phenotypes, whereas Irf3 deficiency only rescued inflammation on the Trex1 -/- background, and many metabolic defects persist in Trex1 -/- Irf3 -/- cells and mice. We also showed that Leptin deficiency (ob/ob) increased lipogenesis and prolonged survival of Trex1 -/- mice without dampening inflammation. Mechanistically, we identified TBK1 as a key regulator of mTORC1 activity in Trex1 -/- cells. Together, our data demonstrate that chronic innate immune activation of TBK1 suppresses mTORC1 activity, leading to dysregulated cellular metabolism.

Spectral Monitoring of Surfactant Clearance during Alveolar Epithelial Type II Cell Differentiation

PubMed Central

Swain, Robin J.; Kemp, Sarah J.; Goldstraw, Peter; Tetley, Teresa D.; Stevens, Molly M.

2008-01-01

In this study, we report on the noninvasive identification of spectral markers of alveolar type II (ATII) cell differentiation in vitro using Raman microspectroscopy. ATII cells are progenitor cells for alveolar type I (ATI) cells in vivo, and spontaneously differentiate toward an ATI-like phenotype in culture. We analyzed undifferentiated and differentiated primary human ATII cells, and correlated Raman spectral changes to cellular changes in morphology and marker protein synthesis (surfactant protein C, alkaline phosphatase, caveolin-1). Undifferentiated ATII cells demonstrated spectra with strong phospholipid vibrations, arising from alveolar surfactant stored within cytoplasmic lamellar bodies (Lbs). Differentiated ATI-like cells yielded spectra with significantly less lipid content. Factor analysis revealed a phospholipid-dominated spectral component as the main discriminator between the ATII and ATI-like phenotypes. Spectral modeling of the data revealed a significant decrease in the spectral contribution of cellular lipids—specifically phosphatidyl choline, the main constituent of surfactant, as ATII cells differentiate. These observations were consistent with the clearance of surfactant from Lbs as ATII cells differentiate, and were further supported by cytochemical staining for Lbs. These results demonstrate the first spectral characterization of primary human ATII cells, and provide insight into the biochemical properties of alveolar surfactant in its unperturbed cellular environment. PMID:18820234

Glycolysis is the primary bioenergetic pathway for cell motility and cytoskeletal remodeling in human prostate and breast cancer cells.

PubMed

Shiraishi, Takumi; Verdone, James E; Huang, Jessie; Kahlert, Ulf D; Hernandez, James R; Torga, Gonzalo; Zarif, Jelani C; Epstein, Tamir; Gatenby, Robert; McCartney, Annemarie; Elisseeff, Jennifer H; Mooney, Steven M; An, Steven S; Pienta, Kenneth J

2015-01-01

The ability of a cancer cell to detach from the primary tumor and move to distant sites is fundamental to a lethal cancer phenotype. Metabolic transformations are associated with highly motile aggressive cellular phenotypes in tumor progression. Here, we report that cancer cell motility requires increased utilization of the glycolytic pathway. Mesenchymal cancer cells exhibited higher aerobic glycolysis compared to epithelial cancer cells while no significant change was observed in mitochondrial ATP production rate. Higher glycolysis was associated with increased rates of cytoskeletal remodeling, greater cell traction forces and faster cell migration, all of which were blocked by inhibition of glycolysis, but not by inhibition of mitochondrial ATP synthesis. Thus, our results demonstrate that cancer cell motility and cytoskeleton rearrangement is energetically dependent on aerobic glycolysis and not oxidative phosphorylation. Mitochondrial derived ATP is insufficient to compensate for inhibition of the glycolytic pathway with regard to cellular motility and CSK rearrangement, implying that localization of ATP derived from glycolytic enzymes near sites of active CSK rearrangement is more important for cell motility than total cellular ATP production rate. These results extend our understanding of cancer cell metabolism, potentially providing a target metabolic pathway associated with aggressive disease.

Glycolysis is the primary bioenergetic pathway for cell motility and cytoskeletal remodeling in human prostate and breast cancer cells

PubMed Central

Shiraishi, Takumi; Verdone, James E.; Huang, Jessie; Kahlert, Ulf D.; Hernandez, James R.; Torga, Gonzalo; Zarif, Jelani C.; Epstein, Tamir; Gatenby, Robert; McCartney, Annemarie; Elisseeff, Jennifer H.; Mooney, Steven M.; An, Steven S.; Pienta, Kenneth J.

2015-01-01

The ability of a cancer cell to detach from the primary tumor and move to distant sites is fundamental to a lethal cancer phenotype. Metabolic transformations are associated with highly motile aggressive cellular phenotypes in tumor progression. Here, we report that cancer cell motility requires increased utilization of the glycolytic pathway. Mesenchymal cancer cells exhibited higher aerobic glycolysis compared to epithelial cancer cells while no significant change was observed in mitochondrial ATP production rate. Higher glycolysis was associated with increased rates of cytoskeletal remodeling, greater cell traction forces and faster cell migration, all of which were blocked by inhibition of glycolysis, but not by inhibition of mitochondrial ATP synthesis. Thus, our results demonstrate that cancer cell motility and cytoskeleton rearrangement is energetically dependent on aerobic glycolysis and not oxidative phosphorylation. Mitochondrial derived ATP is insufficient to compensate for inhibition of the glycolytic pathway with regard to cellular motility and CSK rearrangement, implying that localization of ATP derived from glycolytic enzymes near sites of active CSK rearrangement is more important for cell motility than total cellular ATP production rate. These results extend our understanding of cancer cell metabolism, potentially providing a target metabolic pathway associated with aggressive disease. PMID:25426557

Phenotypic screening for developmental neurotoxicity ...

EPA Pesticide Factsheets

There are large numbers of environmental chemicals with little or no available information on their toxicity, including developmental neurotoxicity. Because of the resource-intensive nature of traditional animal tests, high-throughput (HTP) methods that can rapidly evaluate chemicals for the potential to affect the developing brain are being explored. Typically, HTP screening uses biochemical and molecular assays to detect the interaction of a chemical with a known target or molecular initiating event (e.g., the mechanism of action). For developmental neurotoxicity, however, the mechanism(s) is often unknown. Thus, we have developed assays for detecting chemical effects on the key events of neurodevelopment at the cellular level (e.g., proliferation, differentiation, neurite growth, synaptogenesis, network formation). Cell-based assays provide a test system at a level of biological complexity that encompasses many potential neurotoxic mechanisms. For example, phenotypic assessment of neurite outgrowth at the cellular level can detect chemicals that target kinases, ion channels, or esterases at the molecular level. The results from cell-based assays can be placed in a conceptual framework using an Adverse Outcome Pathway (AOP) which links molecular, cellular, and organ level effects with apical measures of developmental neurotoxicity. Testing a wide range of concentrations allows for the distinction between selective effects on neurodevelopmental and non-specific

Multi-layered mutation in hedgehog-related genes in Gorlin syndrome may affect the phenotype.

PubMed

Onodera, Shoko; Saito, Akiko; Hasegawa, Daigo; Morita, Nana; Watanabe, Katsuhito; Nomura, Takeshi; Shibahara, Takahiko; Ohba, Shinsuke; Yamaguchi, Akira; Azuma, Toshifumi

2017-01-01

Gorlin syndrome is a genetic disorder of autosomal dominant inheritance that predisposes the affected individual to a variety of disorders that are attributed largely to heterozygous germline patched1 (PTCH1) mutations. PTCH1 is a hedgehog (Hh) receptor as well as a repressor, mutation of which leads to constitutive activation of Hh pathway. Hh pathway encompasses a wide variety of cellular signaling cascades, which involve several molecules; however, no associated genotype-phenotype correlations have been reported. Recently, mutations in Suppressor of fused homolog (SUFU) or PTCH2 were reported in patients with Gorlin syndrome. These facts suggest that multi-layered mutations in Hh pathway may contribute to the development of Gorlin syndrome. We demonstrated multiple mutations of Hh-related genes in addition to PTCH1, which possibly act in an additive or multiplicative manner and lead to Gorlin syndrome. High-throughput sequencing was performed to analyze exome sequences in four unrelated Gorlin syndrome patient genomes. Mutations in PTCH1 gene were detected in all four patients. Specific nucleotide variations or frameshift variations of PTCH1 were identified along with the inferred amino acid changes in all patients. We further filtered 84 different genes which are closely related to Hh signaling. Fifty three of these had enough coverage of over ×30. The sequencing results were filtered and compared to reduce the number of sequence variants identified in each of the affected individuals. We discovered three genes, PTCH2, BOC, and WNT9b, with mutations with a predicted functional impact assessed by MutationTaster2 or PolyPhen-2 (Polymorphism Phenotyping v2) analysis. It is noticeable that PTCH2 and BOC are Hh receptor molecules. No significant mutations were observed in SUFU. Multi-layered mutations in Hh pathway may change the activation level of the Hh signals, which may explain the wide phenotypic variability of Gorlin syndrome.

The "Transport Specificity Ratio": a structure-function tool to search the protein fold for loci that control transition state stability in membrane transport catalysis

PubMed Central

King, Steven C

2004-01-01

Background In establishing structure-function relationships for membrane transport proteins, the interpretation of phenotypic changes can be problematic, owing to uncertainties in protein expression levels, sub-cellular localization, and protein-folding fidelity. A dual-label competitive transport assay called "Transport Specificity Ratio" (TSR) analysis has been developed that is simple to perform, and circumvents the "expression problem," providing a reliable TSR phenotype (a constant) for comparison to other transporters. Results Using the Escherichia coli GABA (4-aminobutyrate) permease (GabP) as a model carrier, it is demonstrated that the TSR phenotype is largely independent of assay conditions, exhibiting: (i) indifference to the particular substrate concentrations used, (ii) indifference to extreme changes (40-fold) in transporter expression level, and within broad limits (iii) indifference to assay duration. The theoretical underpinnings of TSR analysis predict all of the above observations, supporting that TSR has (i) applicability in the analysis of membrane transport, and (ii) particular utility in the face of incomplete information on protein expression levels and initial reaction rate intervals (e.g., in high-throughput screening situations). The TSR was used to identify gab permease (GabP) variants that exhibit relative changes in catalytic specificity (kcat/Km) for [14C]GABA (4-aminobutyrate) versus [3H]NA (nipecotic acid). Conclusions The TSR phenotype is an easily measured constant that reflects innate molecular properties of the transition state, and provides a reliable index of the difference in catalytic specificity that a carrier exhibits toward a particular pair of substrates. A change in the TSR phenotype, called a Δ(TSR), represents a specificity shift attributable to underlying changes in the intrinsic substrate binding energy (ΔGb) that translocation catalysts rely upon to decrease activation energy (). TSR analysis is therefore a structure-function tool that enables parsimonious scanning for positions in the protein fold that couple to the transition state, creating stability and thereby serving as functional determinants of catalytic power (efficiency, or specificity). PMID:15548327

Genome-wide identification of translationally inhibited and degraded miR-155 targets using RNA-interacting protein-IP

PubMed Central

Meier, Jan; Hovestadt, Volker; Zapatka, Marc; Pscherer, Armin; Lichter, Peter; Seiffert, Martina

2013-01-01

MicroRNAs (miRNAs) are single-stranded, small, non-coding RNAs, which fine-tune protein expression by degrading and/or translationally inhibiting mRNAs. Manipulation of miRNA expression in animal models frequently results in severe phenotypes indicating their relevance in controlling cellular functions, most likely by interacting with multiple targets. To better understand the effect of miRNA activities, genome-wide analysis of their targets are required. MicroRNA profiling as well as transcriptome analysis upon enforced miRNA expression were frequently used to investigate their relevance. However, these approaches often fail to identify relevant miRNAs targets. Therefore, we tested the precision of RNA-interacting protein immunoprecipitation (RIP) using AGO2-specific antibodies, a core component of the “RNA-induced silencing complex” (RISC), followed by RNA sequencing (Seq) in a defined cellular system, the HEK293T cells with stable, ectopic expression of miR-155. Thereby, we identified 100 AGO2-associated mRNAs in miR-155-expressing cells, of which 67 were in silico predicted miR-155 target genes. An integrated analysis of the corresponding expression profiles indicated that these targets were either regulated by mRNA decay or by translational repression. Of the identified miR-155 targets, 17 were related to cell cycle control, suggesting their involvement in the observed increase in cell proliferation of HEK293T cells upon miR-155 expression. Additional, secondary changes within the gene expression profile were detected and might contribute to this phenotype as well. Interestingly, by analyzing RIP-Seq data of HEK-293T cells and two B-cell lines we identified a recurrent disproportional enrichment of several miRNAs, including miR-155 and miRNAs of the miR-17-92 cluster, in the AGO2-associated precipitates, suggesting discrepancies in miRNA expression and activity. PMID:23673373

Decrease of reactive oxygen species-related biomarkers in the tissue-mimic 3D spheroid culture of human lung cells exposed to zinc oxide nanoparticles.

PubMed

Kim, Eunjoo; Jeon, Won Bae; Kim, Soonhyun; Lee, Soo-Keun

2014-05-01

Common 2-dimensional (2D) cell cultures do not adequately represent cell-cell and cell-matrix signaling and substantially different diffusion/transport pathways. To obtain tissue-mimic information on nanoparticle toxicity from in vitro cell tests, we used a 3-dimensional (3D) culture of human lung cells (A549) prepared with elastin-like peptides modified with an arginine-glycine-aspartate motif. The 3D cells showed different cellular phenotypes, gene expression profiles, and functionalities compared to the 2D cultured cells. In gene array analysis, 3D cells displayed the induced extracellular matrix (ECM)-related biological functions such as cell-to-cell signaling and interaction, cellular function and maintenance, connective tissue development and function, molecular transport, and tissue morphology. Additionally, the expression of ECM-related molecules, such as laminin, fibronectin, and insulin-like growth factor binding protein 3 (IGFBP3), was simultaneously induced at both mRNA and protein levels. When 0.08-50 microg/ml zinc oxide nanoparticles (ZnO-NPs) were administered to 2D and 3D cells, the cell proliferation was not significantly changed. The level of molecular markers for oxidative stress, such as superoxide dismutase (SOD), Bcl-2, ATP synthase, and Complex IV (cytochrome C oxidase), was significantly reduced in 2D culture when exposed to 10 microg/ml ZnO-NPs, but no significant decrease was detected in 3D culture when exposed to the same concentration of ZnO-NPs. In conclusion, the tissue-mimic phenotype and functionality of 3D cells could be achieved through the elevated expression of ECM components. The 3D cells were expected to help to better predict the nanotoxicity of ZnO-NPs at tissue-level by increased cell-cell and cell-ECM adhesion and signaling. The tissue-mimic morphology would also be useful to simulate the diffusion/transport of the nanoparticles in vitro.

The structural effects of mutations can aid in differential phenotype prediction of beta-myosin heavy chain (Myosin-7) missense variants.

PubMed

Al-Numair, Nouf S; Lopes, Luis; Syrris, Petros; Monserrat, Lorenzo; Elliott, Perry; Martin, Andrew C R

2016-10-01

High-throughput sequencing platforms are increasingly used to screen patients with genetic disease for pathogenic mutations, but prediction of the effects of mutations remains challenging. Previously we developed SAAPdap (Single Amino Acid Polymorphism Data Analysis Pipeline) and SAAPpred (Single Amino Acid Polymorphism Predictor) that use a combination of rule-based structural measures to predict whether a missense genetic variant is pathogenic. Here we investigate whether the same methodology can be used to develop a differential phenotype predictor, which, once a mutation has been predicted as pathogenic, is able to distinguish between phenotypes-in this case the two major clinical phenotypes (hypertrophic cardiomyopathy, HCM and dilated cardiomyopathy, DCM) associated with mutations in the beta-myosin heavy chain (MYH7) gene product (Myosin-7). A random forest predictor trained on rule-based structural analyses together with structural clustering data gave a Matthews' correlation coefficient (MCC) of 0.53 (accuracy, 75%). A post hoc removal of machine learning models that performed particularly badly, increased the performance (MCC = 0.61, Acc = 79%). This proof of concept suggests that methods used for pathogenicity prediction can be extended for use in differential phenotype prediction. Analyses were implemented in Perl and C and used the Java-based Weka machine learning environment. Please contact the authors for availability. andrew@bioinf.org.uk or andrew.martin@ucl.ac.uk Supplementary data are available at Bioinformatics online. © The Authors 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Semi-automated confocal imaging of fungal pathogenesis on plants: microscopic analysis of macroscopic specimens

USDA-ARS?s Scientific Manuscript database

Contextualizing natural genetic variation in plant disease resistance in terms of pathogenesis can provide information about the function of causal genes. Cellular mechanisms associated with pathogenesis can be elucidated with confocal microscopy, but systematic phenotyping platforms—from sample pro...

Modeling Fanconi Anemia pathogenesis and therapeutics using integration-free patient-derived iPSCs

PubMed Central

Montserrat, Nuria; Tarantino, Carolina; Gu, Ying; Yi, Fei; Xu, Xiuling; Zhang, Weiqi; Ruiz, Sergio; Plongthongkum, Nongluk; Zhang, Kun; Masuda, Shigeo; Nivet, Emmanuel; Tsunekawa, Yuji; Soligalla, Rupa Devi; Goebl, April; Aizawa, Emi; Kim, Na Young; Kim, Jessica; Dubova, Ilir; Li, Ying; Ren, Ruotong; Benner, Chris; del Sol, Antonio; Bueren, Juan; Trujillo, Juan Pablo; Surralles, Jordi; Cappelli, Enrico; Dufour, Carlo; Esteban, Concepcion Rodriguez; Belmonte, Juan Carlos Izpisua

2014-01-01

Fanconi Anemia (FA) is a recessive disorder characterized by genomic instability, congenital abnormalities, cancer predisposition and bone marrow failure. However, the pathogenesis of FA is not fully understood partly due to the limitations of current disease models. Here, we derive integration-free induced pluripotent stem cells (iPSCs) from an FA patient without genetic complementation and report in situ gene correction in FA-iPSCs as well as the generation of isogenic FANCA deficient human embryonic stem cell (ESC) lines. FA cellular phenotypes are recapitulated in iPSCs/ESCs and their adult stem/progenitor cell derivatives. By using isogenic pathogenic mutation-free controls as well as cellular and genomic tools, our model serves to facilitate the discovery of novel disease features. We validate our model as a drug-screening platform by identifying several compounds that improve hematopoietic differentiation of FA-iPSCs. These compounds are also able to rescue the hematopoietic phenotype of FA-patient bone marrow cells. PMID:24999918

Ablation of Prion Protein in Wild Type Human Amyloid Precursor Protein (APP) Transgenic Mice Does Not Alter The Proteolysis of APP, Levels of Amyloid-β or Pathologic Phenotype

PubMed Central

Baybutt, Herbert; Diack, Abigail B.; Kellett, Katherine A. B.; Piccardo, Pedro; Manson, Jean C.

2016-01-01

The cellular prion protein (PrPC) has been proposed to play an important role in the pathogenesis of Alzheimer’s disease. In cellular models PrPC inhibited the action of the β-secretase BACE1 on wild type amyloid precursor protein resulting in a reduction in amyloid-β (Aβ) peptides. Here we have assessed the effect of genetic ablation of PrPC in transgenic mice expressing human wild type amyloid precursor protein (line I5). Deletion of PrPC had no effect on the α- and β-secretase proteolysis of the amyloid precursor protein (APP) nor on the amount of Aβ38, Aβ40 or Aβ42 in the brains of the mice. In addition, ablation of PrPC did not alter Aβ deposition or histopathology phenotype in this transgenic model. Thus using this transgenic model we could not provide evidence to support the hypothesis that PrPC regulates Aβ production. PMID:27447728

Electric-field driven assembly of live bacterial cell microarrays for rapid phenotypic assessment and cell viability testing.

PubMed

Goel, Meenal; Verma, Abhishek; Gupta, Shalini

2018-07-15

Microarray technology to isolate living cells using external fields is a facile way to do phenotypic analysis at the cellular level. We have used alternating current dielectrophoresis (AC-DEP) to drive the assembly of live pathogenic Salmonella typhi (S.typhi) and Escherichia coli (E.coli) bacteria into miniaturized single cell microarrays. The effects of voltage and frequency were optimized to identify the conditions for maximum cell capture which gave an entrapment efficiency of 90% in 60 min. The chip was used for calibration-free estimation of cellular loads in binary mixtures and further applied for rapid and enhanced testing of cell viability in the presence of drug via impedance spectroscopy. Our results using a model antimicrobial sushi peptide showed that the cell viability could be tested down to 5 μg/mL drug concentration under an hour, thus establishing the utility of our system for ultrafast and sensitive detection. Copyright © 2018 Elsevier B.V. All rights reserved.

Modelling Fanconi anemia pathogenesis and therapeutics using integration-free patient-derived iPSCs.

PubMed

Liu, Guang-Hui; Suzuki, Keiichiro; Li, Mo; Qu, Jing; Montserrat, Nuria; Tarantino, Carolina; Gu, Ying; Yi, Fei; Xu, Xiuling; Zhang, Weiqi; Ruiz, Sergio; Plongthongkum, Nongluk; Zhang, Kun; Masuda, Shigeo; Nivet, Emmanuel; Tsunekawa, Yuji; Soligalla, Rupa Devi; Goebl, April; Aizawa, Emi; Kim, Na Young; Kim, Jessica; Dubova, Ilir; Li, Ying; Ren, Ruotong; Benner, Chris; Del Sol, Antonio; Bueren, Juan; Trujillo, Juan Pablo; Surralles, Jordi; Cappelli, Enrico; Dufour, Carlo; Esteban, Concepcion Rodriguez; Belmonte, Juan Carlos Izpisua

2014-07-07

Fanconi anaemia (FA) is a recessive disorder characterized by genomic instability, congenital abnormalities, cancer predisposition and bone marrow (BM) failure. However, the pathogenesis of FA is not fully understood partly due to the limitations of current disease models. Here, we derive integration free-induced pluripotent stem cells (iPSCs) from an FA patient without genetic complementation and report in situ gene correction in FA-iPSCs as well as the generation of isogenic FANCA-deficient human embryonic stem cell (ESC) lines. FA cellular phenotypes are recapitulated in iPSCs/ESCs and their adult stem/progenitor cell derivatives. By using isogenic pathogenic mutation-free controls as well as cellular and genomic tools, our model serves to facilitate the discovery of novel disease features. We validate our model as a drug-screening platform by identifying several compounds that improve hematopoietic differentiation of FA-iPSCs. These compounds are also able to rescue the hematopoietic phenotype of FA patient BM cells.

Clinical Impact and Cellular Mechanisms of Iron Overload-Associated Bone Loss

PubMed Central

Jeney, Viktória

2017-01-01

Diseases/conditions with diverse etiology, such as hemoglobinopathies, hereditary hemochromatosis and menopause, could lead to chronic iron accumulation. This condition is frequently associated with a bone phenotype; characterized by low bone mass, osteoporosis/osteopenia, altered microarchitecture and biomechanics, and increased incidence of fractures. Osteoporotic bone phenotype constitutes a major complication in patients with iron overload. The purpose of this review is to summarize what we have learnt about iron overload-associated bone loss from clinical studies and animal models. Bone is a metabolically active tissue that undergoes continuous remodeling with the involvement of osteoclasts that resorb mineralized bone, and osteoblasts that form new bone. Growing evidence suggests that both increased bone resorption and decreased bone formation are involved in the pathological bone-loss in iron overload conditions. We will discuss the cellular and molecular mechanisms that are involved in this detrimental process. Fuller understanding of this complex mechanism may lead to the development of improved therapeutics meant to interrupt the pathologic effects of excess iron on bone. PMID:28270766

Mitochondria in lung disease

PubMed Central

Cloonan, Suzanne M.; Choi, Augustine M.K.

2016-01-01

Mitochondria are a distinguishing feature of eukaryotic cells. Best known for their critical function in energy production via oxidative phosphorylation (OXPHOS), mitochondria are essential for nutrient and oxygen sensing and for the regulation of critical cellular processes, including cell death and inflammation. Such diverse functional roles for organelles that were once thought to be simple may be attributed to their distinct heteroplasmic genome, exclusive maternal lineage of inheritance, and ability to generate signals to communicate with other cellular organelles. Mitochondria are now thought of as one of the cell’s most sophisticated and dynamic responsive sensing systems. Specific signatures of mitochondrial dysfunction that are associated with disease pathogenesis and/or progression are becoming increasingly important. In particular, the centrality of mitochondria in the pathological processes and clinical phenotypes associated with a range of lung diseases is emerging. Understanding the molecular mechanisms regulating the mitochondrial processes of lung cells will help to better define phenotypes and clinical manifestations associated with respiratory disease and to identify potential diagnostic and therapeutic targets. PMID:26928034

Engineering live cell surfaces with functional polymers via cytocompatible controlled radical polymerization

NASA Astrophysics Data System (ADS)

Niu, Jia; Lunn, David J.; Pusuluri, Anusha; Yoo, Justin I.; O'Malley, Michelle A.; Mitragotri, Samir; Soh, H. Tom; Hawker, Craig J.

2017-06-01

The capability to graft synthetic polymers onto the surfaces of live cells offers the potential to manipulate and control their phenotype and underlying cellular processes. Conventional grafting-to strategies for conjugating preformed polymers to cell surfaces are limited by low polymer grafting efficiency. Here we report an alternative grafting-from strategy for directly engineering the surfaces of live yeast and mammalian cells through cell surface-initiated controlled radical polymerization. By developing cytocompatible PET-RAFT (photoinduced electron transfer-reversible addition-fragmentation chain-transfer polymerization), synthetic polymers with narrow polydispersity (Mw/Mn < 1.3) could be obtained at room temperature in 5 minutes. This polymerization strategy enables chain growth to be initiated directly from chain-transfer agents anchored on the surface of live cells using either covalent attachment or non-covalent insertion, while maintaining high cell viability. Compared with conventional grafting-to approaches, these methods significantly improve the efficiency of grafting polymer chains and enable the active manipulation of cellular phenotypes.

Hematopoiesis: an evolving paradigm for stem cell biology.

PubMed

Orkin, Stuart H; Zon, Leonard I

2008-02-22

Establishment and maintenance of the blood system relies on self-renewing hematopoietic stem cells (HSCs) that normally reside in small numbers in the bone marrow niche of adult mammals. This Review describes the developmental origins of HSCs and the molecular mechanisms that regulate lineage-specific differentiation. Studies of hematopoiesis provide critical insights of general relevance to other areas of stem cell biology including the role of cellular interactions in development and tissue homeostasis, lineage programming and reprogramming by transcription factors, and stage- and age-specific differences in cellular phenotypes.

Visualizing Morphological Changes of Abscission Zone Cells in Arabidopsis by Scanning Electron Microscope.

PubMed

Shi, Chun-Lin; Butenko, Melinka A

2018-01-01

Scanning electron microscope (SEM) is a type of electron microscope which produces detailed images of surface structures. It has been widely used in plants and animals to study cellular structures. Here, we describe a detailed protocol to prepare samples of floral abscission zones (AZs) for SEM, as well as further image analysis. We show that it is a powerful tool to detect morphologic changes at the cellular level during the course of abscission in wild-type plants and to establish the details of phenotypic alteration in abscission mutants.

Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures

PubMed Central

Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.

2014-01-01

Parametric and nonparametric methods have been developed for purposes of predicting phenotypes. These methods are based on retrospective analyses of empirical data consisting of genotypic and phenotypic scores. Recent reports have indicated that parametric methods are unable to predict phenotypes of traits with known epistatic genetic architectures. Herein, we review parametric methods including least squares regression, ridge regression, Bayesian ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian LASSO, best linear unbiased prediction (BLUP), Bayes A, Bayes B, Bayes C, and Bayes Cπ. We also review nonparametric methods including Nadaraya-Watson estimator, reproducing kernel Hilbert space, support vector machine regression, and neural networks. We assess the relative merits of these 14 methods in terms of accuracy and mean squared error (MSE) using simulated genetic architectures consisting of completely additive or two-way epistatic interactions in an F2 population derived from crosses of inbred lines. Each simulated genetic architecture explained either 30% or 70% of the phenotypic variability. The greatest impact on estimates of accuracy and MSE was due to genetic architecture. Parametric methods were unable to predict phenotypic values when the underlying genetic architecture was based entirely on epistasis. Parametric methods were slightly better than nonparametric methods for additive genetic architectures. Distinctions among parametric methods for additive genetic architectures were incremental. Heritability, i.e., proportion of phenotypic variability, had the second greatest impact on estimates of accuracy and MSE. PMID:24727289

Integrating Milk Metabolite Profile Information for the Prediction of Traditional Milk Traits Based on SNP Information for Holstein Cows

PubMed Central

Melzer, Nina; Wittenburg, Dörte; Repsilber, Dirk

2013-01-01

In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs) enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced SNP subset (reduced classical approach). To enable a comparison between SNP subsets, a special invariable evaluation design was implemented. SNPs close to or within known quantitative trait loci (QTL) were determined. This enabled us to determine if detected important SNP subsets were enriched in these regions. The results show that our approach can lead to genetic value prediction, but requires less than 1% of the total amount of (40,317) SNPs., significantly more important SNPs in known QTL regions were detected using our approach compared to the reduced classical approach. Concluding, our approach allows a deeper insight into the associations between the different levels of the genotype-phenotype map (genotype-metabolome, metabolome-phenotype, genotype-phenotype). PMID:23990900

Comparing the predictive abilities of phenotypic and marker-assisted selection methods in a biparental lettuce population

USDA-ARS?s Scientific Manuscript database

Breeding and selection for the traits with polygenic inheritance is a challenging task that can be done by phenotypic selection, by marker-assisted selection or by genome wide selection. We tested predictive ability of four selection models in a biparental population genotyped with 95 SNP markers an...

Multitrait, random regression, or simple repeatability model in high-throughput phenotyping data improve genomic prediction for wheat grain yield

USDA-ARS?s Scientific Manuscript database

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat (Triticum aestivum L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect s...

[Cell signaling pathways interaction in cellular proliferation: Potential target for therapeutic interventionism].

PubMed

Valdespino-Gómez, Víctor Manuel; Valdespino-Castillo, Patricia Margarita; Valdespino-Castillo, Víctor Edmundo

2015-01-01

Nowadays, cellular physiology is best understood by analysing their interacting molecular components. Proteins are the major components of the cells. Different proteins are organised in the form of functional clusters, pathways or networks. These molecules are ordered in clusters of receptor molecules of extracellular signals, transducers, sensors and biological response effectors. The identification of these intracellular signaling pathways in different cellular types has required a long journey of experimental work. More than 300 intracellular signaling pathways have been identified in human cells. They participate in cell homeostasis processes for structural and functional maintenance. Some of them participate simultaneously or in a nearly-consecutive progression to generate a cellular phenotypic change. In this review, an analysis is performed on the main intracellular signaling pathways that take part in the cellular proliferation process, and the potential use of some components of these pathways as target for therapeutic interventionism are also underlined. Copyright © 2015 Academia Mexicana de Cirugía A.C. Published by Masson Doyma México S.A. All rights reserved.

Terminal addition in a cellular world.

PubMed

Torday, J S; Miller, William B

2018-07-01

Recent advances in our understanding of evolutionary development permit a reframed appraisal of Terminal Addition as a continuous historical process of cellular-environmental complementarity. Within this frame of reference, evolutionary terminal additions can be identified as environmental induction of episodic adjustments to cell-cell signaling patterns that yield the cellular-molecular pathways that lead to differing developmental forms. Phenotypes derive, thereby, through cellular mutualistic/competitive niche constructions in reciprocating responsiveness to environmental stresses and epigenetic impacts. In such terms, Terminal Addition flows according to a logic of cellular needs confronting environmental challenges over space-time. A reconciliation of evolutionary development and Terminal Addition can be achieved through a combined focus on cell-cell signaling, molecular phylogenies and a broader understanding of epigenetic phenomena among eukaryotic organisms. When understood in this manner, Terminal Addition has an important role in evolutionary development, and chronic disease might be considered as a form of 'reverse evolution' of the self-same processes. Copyright © 2017. Published by Elsevier Ltd.

Heterogeneity of Metazoan Cells and Beyond: To Integrative Analysis of Cellular Populations at Single-Cell Level.

PubMed

Barteneva, Natasha S; Vorobjev, Ivan A

2018-01-01

In this paper, we review some of the recent advances in cellular heterogeneity and single-cell analysis methods. In modern research of cellular heterogeneity, there are four major approaches: analysis of pooled samples, single-cell analysis, high-throughput single-cell analysis, and lately integrated analysis of cellular population at a single-cell level. Recently developed high-throughput single-cell genetic analysis methods such as RNA-Seq require purification step and destruction of an analyzed cell often are providing a snapshot of the investigated cell without spatiotemporal context. Correlative analysis of multiparameter morphological, functional, and molecular information is important for differentiation of more uniform groups in the spectrum of different cell types. Simplified distributions (histograms and 2D plots) can underrepresent biologically significant subpopulations. Future directions may include the development of nondestructive methods for dissecting molecular events in intact cells, simultaneous correlative cellular analysis of phenotypic and molecular features by hybrid technologies such as imaging flow cytometry, and further progress in supervised and non-supervised statistical analysis algorithms.

Non-additive genetic variation in growth, carcass and fertility traits of beef cattle.

PubMed

Bolormaa, Sunduimijid; Pryce, Jennie E; Zhang, Yuandan; Reverter, Antonio; Barendse, William; Hayes, Ben J; Goddard, Michael E

2015-04-02

A better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have been mainly used to map additive effects for quantitative traits, but they can also be used to investigate non-additive effects. We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation. Genotype data (729 068 real or imputed SNPs) and phenotypes on up to 16 traits of 10 191 individuals from Bos taurus, Bos indicus and composite breeds were used. A genome-wide association study was performed by fitting the additive and dominance effects of single SNPs. The dominance variance was estimated by fitting a dominance relationship matrix constructed from the 729 068 SNPs. The accuracy of predicted phenotypic values was evaluated by best linear unbiased prediction using the additive and dominance relationship matrices. Epistatic interactions (additive × additive) were tested between each of the 28 SNPs that are known to have additive effects on multiple traits, and each of the other remaining 729 067 SNPs. The number of significant dominance effects was greater than expected by chance and most of them were in the direction that is presumed to increase fitness and in the opposite direction to inbreeding depression. Estimates of dominance variance explained by SNPs varied widely between traits, but had large standard errors. The median dominance variance across the 16 traits was equal to 5% of the phenotypic variance. Including a dominance deviation in the prediction did not significantly increase its accuracy for any of the phenotypes. The number of additive × additive epistatic effects that were statistically significant was greater than expected by chance. Significant dominance and epistatic effects occur for growth, carcass and fertility traits in beef cattle but they are difficult to estimate precisely and including them in phenotype prediction does not increase its accuracy.

Tissue Chips to aid drug development and modeling for rare diseases

PubMed Central

Low, Lucie A.; Tagle, Danilo A.

2016-01-01

Introduction The technologies used to design, create and use microphysiological systems (MPS, “tissue chips” or “organs-on-chips”) have progressed rapidly in the last 5 years, and validation studies of the functional relevance of these platforms to human physiology, and response to drugs for individual model organ systems, are well underway. These studies are paving the way for integrated multi-organ systems that can model diseases and predict drug efficacy and toxicology of multiple organs in real-time, improving the potential for diagnostics and development of novel treatments of rare diseases in the future. Areas covered This review will briefly summarize the current state of tissue chip research and highlight model systems where these microfabricated (or bioengineered) devices are already being used to screen therapeutics, model disease states, and provide potential treatments in addition to helping elucidate the basic molecular and cellular phenotypes of rare diseases. Expert opinion Microphysiological systems hold great promise and potential for modeling rare disorders, as well as for their potential use to enhance the predictive power of new drug therapeutics, plus potentially increase the statistical power of clinical trials while removing the inherent risks of these trials in rare disease populations. PMID:28626620

Could the Extended Phenotype Extend to the Cellular and Subcellular Levels in Insect-Induced Galls?

PubMed Central

Carneiro, Renê Gonçalves da Silva; Pacheco, Priscilla; Isaias, Rosy Mary dos Santos

2015-01-01

Neo-ontogenesis of plant galls involves redifferentiation of host plant tissues to express new phenotypes, when new cell properties are established via structural-functional remodeling. Herein, Psidium cattleianum leaves and Nothotrioza cattleiani galls are analyzed by developmental anatomy, cytometry and immunocytochemistry of cell walls. We address hypothesis-driven questions concerning the organogenesis of globoid galls in the association of P. cattleianum - N. cattleianum, and P. myrtoides - N. myrtoidis. These double co-generic systems represent good models for comparing final gall shapes and cell lineages functionalities under the perspective of convergent plant-dependent or divergent insect-induced characteristics. Gall induction, and growth and development are similar in both galls, but homologous cell lineages exhibit divergent degrees of cell hypertrophy and directions of elongation. Median cortical cells in P. cattleianum galls hypertrophy the most, while in P. myrtoides galls there is a centrifugal gradient of cell hypertrophy. Cortical cells in P. cattleianum galls tend to anisotropy, while P. myrtoidis galls have isotropically hypertrophied cells. Immunocytochemistry evidences the chemical identity and functional traits of cell lineages: epidermal cells walls have homogalacturonans (HGAs) and galactans, which confer rigidity to sites of enhanced cell division; oil gland cell walls have arabinogalactan proteins (AGPs) that help avoiding cell death; and parenchyma cell walls have HGAs, galactans and arabinans, which confer porosity. Variations in such chemical identities are related to specific sites of hypertrophy. Even though the double co-generic models have the same macroscopic phenotype, the globoid morphotype, current analyses indicate that the extended phenotype of N. cattleiani is substantiated by cellular and subcellular specificities. PMID:26053863

Degradation of Human PDZ-Proteins by Human Alphapapillomaviruses Represents an Evolutionary Adaptation to a Novel Cellular Niche.

PubMed

Van Doorslaer, Koenraad; DeSalle, Rob; Einstein, Mark H; Burk, Robert D

2015-06-01

In order to complete their life cycle, papillomaviruses have evolved to manipulate a plethora of cellular pathways. The products of the human Alphapapillomavirus E6 proteins specifically interact with and target PDZ containing proteins for degradation. This viral phenotype has been suggested to play a role in viral oncogenesis. To analyze the association of HPV E6 mediated PDZ-protein degradation with cervical oncogenesis, a high-throughput cell culture assay was developed. Degradation of an epitope tagged human MAGI1 isoform was visualized by immunoblot. The correlation between HPV E6-induced degradation of hMAGI1 and epidemiologically determined HPV oncogenicity was evaluated using a Bayesian approach within a phylogenetic context. All tested oncogenic types degraded the PDZ-containing protein hMAGI1d; however, E6 proteins isolated from several related albeit non-oncogenic viral types were equally efficient at degrading hMAGI1. The relationship between both traits (oncogenicity and PDZ degradation potential) is best explained by a model in which the potential to degrade PDZ proteins was acquired prior to the oncogenic phenotype. This analysis provides evidence that the ancestor of both oncogenic and non-oncogenic HPVs acquired the potential to degrade human PDZ-containing proteins. This suggests that HPV E6 directed degradation of PDZ-proteins represents an ancient ecological niche adaptation. Phylogenetic modeling indicates that this phenotype is not specifically correlated with oncogenic risk, but may act as an enabling phenotype. The role of PDZ protein degradation in HPV fitness and oncogenesis needs to be interpreted in the context of Alphapapillomavirus evolution.

Degradation of Human PDZ-Proteins by Human Alphapapillomaviruses Represents an Evolutionary Adaptation to a Novel Cellular Niche

PubMed Central

Van Doorslaer, Koenraad; DeSalle, Rob; Einstein, Mark H.; Burk, Robert D.

2015-01-01

In order to complete their life cycle, papillomaviruses have evolved to manipulate a plethora of cellular pathways. The products of the human Alphapapillomavirus E6 proteins specifically interact with and target PDZ containing proteins for degradation. This viral phenotype has been suggested to play a role in viral oncogenesis. To analyze the association of HPV E6 mediated PDZ-protein degradation with cervical oncogenesis, a high-throughput cell culture assay was developed. Degradation of an epitope tagged human MAGI1 isoform was visualized by immunoblot. The correlation between HPV E6-induced degradation of hMAGI1 and epidemiologically determined HPV oncogenicity was evaluated using a Bayesian approach within a phylogenetic context. All tested oncogenic types degraded the PDZ-containing protein hMAGI1d; however, E6 proteins isolated from several related albeit non-oncogenic viral types were equally efficient at degrading hMAGI1. The relationship between both traits (oncogenicity and PDZ degradation potential) is best explained by a model in which the potential to degrade PDZ proteins was acquired prior to the oncogenic phenotype. This analysis provides evidence that the ancestor of both oncogenic and non-oncogenic HPVs acquired the potential to degrade human PDZ-containing proteins. This suggests that HPV E6 directed degradation of PDZ-proteins represents an ancient ecological niche adaptation. Phylogenetic modeling indicates that this phenotype is not specifically correlated with oncogenic risk, but may act as an enabling phenotype. The role of PDZ protein degradation in HPV fitness and oncogenesis needs to be interpreted in the context of Alphapapillomavirus evolution. PMID:26086730

A knowledge based approach to matching human neurodegenerative disease and animal models

PubMed Central

Maynard, Sarah M.; Mungall, Christopher J.; Lewis, Suzanna E.; Imam, Fahim T.; Martone, Maryann E.

2013-01-01

Neurodegenerative diseases present a wide and complex range of biological and clinical features. Animal models are key to translational research, yet typically only exhibit a subset of disease features rather than being precise replicas of the disease. Consequently, connecting animal to human conditions using direct data-mining strategies has proven challenging, particularly for diseases of the nervous system, with its complicated anatomy and physiology. To address this challenge we have explored the use of ontologies to create formal descriptions of structural phenotypes across scales that are machine processable and amenable to logical inference. As proof of concept, we built a Neurodegenerative Disease Phenotype Ontology (NDPO) and an associated Phenotype Knowledge Base (PKB) using an entity-quality model that incorporates descriptions for both human disease phenotypes and those of animal models. Entities are drawn from community ontologies made available through the Neuroscience Information Framework (NIF) and qualities are drawn from the Phenotype and Trait Ontology (PATO). We generated ~1200 structured phenotype statements describing structural alterations at the subcellular, cellular and gross anatomical levels observed in 11 human neurodegenerative conditions and associated animal models. PhenoSim, an open source tool for comparing phenotypes, was used to issue a series of competency questions to compare individual phenotypes among organisms and to determine which animal models recapitulate phenotypic aspects of the human disease in aggregate. Overall, the system was able to use relationships within the ontology to bridge phenotypes across scales, returning non-trivial matches based on common subsumers that were meaningful to a neuroscientist with an advanced knowledge of neuroanatomy. The system can be used both to compare individual phenotypes and also phenotypes in aggregate. This proof of concept suggests that expressing complex phenotypes using formal ontologies provides considerable benefit for comparing phenotypes across scales and species. PMID:23717278

Predicting plant biomass accumulation from image-derived parameters

PubMed Central

Chen, Dijun; Shi, Rongli; Pape, Jean-Michel; Neumann, Kerstin; Graner, Andreas; Chen, Ming; Klukas, Christian

2018-01-01

Abstract Background Image-based high-throughput phenotyping technologies have been rapidly developed in plant science recently, and they provide a great potential to gain more valuable information than traditionally destructive methods. Predicting plant biomass is regarded as a key purpose for plant breeders and ecologists. However, it is a great challenge to find a predictive biomass model across experiments. Results In the present study, we constructed 4 predictive models to examine the quantitative relationship between image-based features and plant biomass accumulation. Our methodology has been applied to 3 consecutive barley (Hordeum vulgare) experiments with control and stress treatments. The results proved that plant biomass can be accurately predicted from image-based parameters using a random forest model. The high prediction accuracy based on this model will contribute to relieving the phenotyping bottleneck in biomass measurement in breeding applications. The prediction performance is still relatively high across experiments under similar conditions. The relative contribution of individual features for predicting biomass was further quantified, revealing new insights into the phenotypic determinants of the plant biomass outcome. Furthermore, methods could also be used to determine the most important image-based features related to plant biomass accumulation, which would be promising for subsequent genetic mapping to uncover the genetic basis of biomass. Conclusions We have developed quantitative models to accurately predict plant biomass accumulation from image data. We anticipate that the analysis results will be useful to advance our views of the phenotypic determinants of plant biomass outcome, and the statistical methods can be broadly used for other plant species. PMID:29346559

Genomic selection in a commercial winter wheat population.

PubMed

He, Sang; Schulthess, Albert Wilhelm; Mirdita, Vilson; Zhao, Yusheng; Korzun, Viktor; Bothe, Reiner; Ebmeyer, Erhard; Reif, Jochen C; Jiang, Yong

2016-03-01

Genomic selection models can be trained using historical data and filtering genotypes based on phenotyping intensity and reliability criterion are able to increase the prediction ability. We implemented genomic selection based on a large commercial population incorporating 2325 European winter wheat lines. Our objectives were (1) to study whether modeling epistasis besides additive genetic effects results in enhancement on prediction ability of genomic selection, (2) to assess prediction ability when training population comprised historical or less-intensively phenotyped lines, and (3) to explore the prediction ability in subpopulations selected based on the reliability criterion. We found a 5 % increase in prediction ability when shifting from additive to additive plus epistatic effects models. In addition, only a marginal loss from 0.65 to 0.50 in accuracy was observed using the data collected from 1 year to predict genotypes of the following year, revealing that stable genomic selection models can be accurately calibrated to predict subsequent breeding stages. Moreover, prediction ability was maximized when the genotypes evaluated in a single location were excluded from the training set but subsequently decreased again when the phenotyping intensity was increased above two locations, suggesting that the update of the training population should be performed considering all the selected genotypes but excluding those evaluated in a single location. The genomic prediction ability was substantially higher in subpopulations selected based on the reliability criterion, indicating that phenotypic selection for highly reliable individuals could be directly replaced by applying genomic selection to them. We empirically conclude that there is a high potential to assist commercial wheat breeding programs employing genomic selection approaches.

MicroRNAs associated with the efficacy of photodynamic therapy in biliary tract cancer cell lines.

PubMed

Wagner, Andrej; Mayr, Christian; Bach, Doris; Illig, Romana; Plaetzer, Kristjan; Berr, Frieder; Pichler, Martin; Neureiter, Daniel; Kiesslich, Tobias

2014-11-05

Photodynamic therapy (PDT) is a palliative treatment option for unresectable hilar biliary tract cancer (BTC) showing a considerable benefit for survival and quality of life with few side effects. Currently, factors determining the cellular response of BTC cells towards PDT are unknown. Due to their multifaceted nature, microRNAs (miRs) are a promising analyte to investigate the cellular mechanisms following PDT. For two photosensitizers, Photofrin® and Foscan®, the phototoxicity was investigated in eight BTC cell lines. Each cell line (untreated) was profiled for expression of n=754 miRs using TaqMan® Array Human MicroRNA Cards. Statistical analysis and bioinformatic tools were used to identify miRs associated with PDT efficiency and their putative targets, respectively. Twenty miRs correlated significantly with either high or low PDT efficiency. PDT was particularly effective in cells with high levels of clustered miRs 25-93*-106b and (in case of miR-106b) a phenotype characterized by high expression of the mesenchymal marker vimentin and high proliferation (cyclinD1 and Ki67 expression). Insensitivity towards PDT was associated with high miR-200 family expression and (for miR-cluster 200a/b-429) expression of differentiation markers Ck19 and Ck8/18. Predicted and validated downstream targets indicate plausible involvement of miRs 20a*, 25, 93*, 130a, 141, 200a, 200c and 203 in response mechanisms to PDT, suggesting that targeting these miRs could improve susceptibility to PDT in insensitive cell lines. Taken together, the miRNome pattern may provide a novel tool for predicting the efficiency of PDT and-following appropriate functional verification-may subsequently allow for optimization of the PDT protocol.

The Impact of the Emerging Genomics Data on the Management of Agerelated Phenotypes in the Context of Cellular Senescence.

PubMed

Montesanto, Alberto; Geracitano, Silvana; Garasto, Sabrina; Fusco, Sergio; Lattanzio, Fabrizia; Passarino, Giuseppe; Corsonello, Andrea

2016-01-01

Before the last decade, attempts to identify the genetic factors involved in the susceptibility to age-related complex diseases such as cardiovascular disease, diabetes and cancer had very limited success. Recently, two important advancements have provided new opportunities to improve our knowledge in this field. Firstly, it has emerged the concept of studying the molecular mechanisms underlying the age related decline of the organism (such as cellular senescence), rather than the genetics of single disorders. In addition, advances in DNA technology have uncovered an incredible number of common susceptibility variants for several complex traits. Despite these progresses, the translation of these discoveries into clinical practice has been very difficult. To date, several attempts in translating genomics to medicine are being carried out to look for the best way by which genomic discoveries may improve our understanding of fundamental issues in the prediction and prevention of some complex diseases. The successful strategy seems to be testing simultaneously multiple susceptibility variants in combination with traditional risk factors. In fact, such approach showed that genetic factors substantially improve the prediction of complex diseases especially for coronary heart disease and prostate cancer, making possible appropriate behavioural and medical interventions. In the future, the identification of new genetic variants and their inclusion into current risk profile models will probably improve the discrimination power of these models for other complex diseases such as type 2 diabetes mellitus and breast cancer. On the other hand, for traits with low heritability, this improvement will probably be negligible, and this will urge further researches on the role played by traditional and newly discovered non-genetic risk factors.

MicroRNAs Associated with the Efficacy of Photodynamic Therapy in Biliary Tract Cancer Cell Lines

PubMed Central

Wagner, Andrej; Mayr, Christian; Bach, Doris; Illig, Romana; Plaetzer, Kristjan; Berr, Frieder; Pichler, Martin; Neureiter, Daniel; Kiesslich, Tobias

2014-01-01

Photodynamic therapy (PDT) is a palliative treatment option for unresectable hilar biliary tract cancer (BTC) showing a considerable benefit for survival and quality of life with few side effects. Currently, factors determining the cellular response of BTC cells towards PDT are unknown. Due to their multifaceted nature, microRNAs (miRs) are a promising analyte to investigate the cellular mechanisms following PDT. For two photosensitizers, Photofrin® and Foscan®, the phototoxicity was investigated in eight BTC cell lines. Each cell line (untreated) was profiled for expression of n = 754 miRs using TaqMan® Array Human MicroRNA Cards. Statistical analysis and bioinformatic tools were used to identify miRs associated with PDT efficiency and their putative targets, respectively. Twenty miRs correlated significantly with either high or low PDT efficiency. PDT was particularly effective in cells with high levels of clustered miRs 25-93*-106b and (in case of miR-106b) a phenotype characterized by high expression of the mesenchymal marker vimentin and high proliferation (cyclinD1 and Ki67 expression). Insensitivity towards PDT was associated with high miR-200 family expression and (for miR-cluster 200a/b-429) expression of differentiation markers Ck19 and Ck8/18. Predicted and validated downstream targets indicate plausible involvement of miRs 20a*, 25, 93*, 130a, 141, 200a, 200c and 203 in response mechanisms to PDT, suggesting that targeting these miRs could improve susceptibility to PDT in insensitive cell lines. Taken together, the miRNome pattern may provide a novel tool for predicting the efficiency of PDT and—following appropriate functional verification—may subsequently allow for optimization of the PDT protocol. PMID:25380521

Smooth muscle architecture within cell-dense vascular tissues influences functional contractility.

PubMed

Win, Zaw; Vrla, Geoffrey D; Steucke, Kerianne E; Sevcik, Emily N; Hald, Eric S; Alford, Patrick W

2014-12-01

The role of vascular smooth muscle architecture in the function of healthy and dysfunctional vessels is poorly understood. We aimed at determining the relationship between vascular smooth muscle architecture and contractile output using engineered vascular tissues. We utilized microcontact printing and a microfluidic cell seeding technique to provide three different initial seeding conditions, with the aim of influencing the cellular architecture within the tissue. Cells seeded in each condition formed confluent and aligned tissues but within the tissues, the cellular architecture varied. Tissues with a more elongated cellular architecture had significantly elevated basal stress and produced more contractile stress in response to endothelin-1 stimulation. We also found a correlation between the contractile phenotype marker expression and the cellular architecture, contrary to our previous findings in non-confluent tissues. Taken with previous results, these data suggest that within cell-dense vascular tissues, smooth muscle contractility is strongly influenced by cell and tissue architectures.

Cellular complexity captured in durable silica biocomposites

PubMed Central

Kaehr, Bryan; Townson, Jason L.; Kalinich, Robin M.; Awad, Yasmine H.; Swartzentruber, B. S.; Dunphy, Darren R.; Brinker, C. Jeffrey

2012-01-01

Tissue-derived cultured cells exhibit a remarkable range of morphological features in vitro, depending on phenotypic expression and environmental interactions. Translation of these cellular architectures into inorganic materials would provide routes to generate hierarchical nanomaterials with stabilized structures and functions. Here, we describe the fabrication of cell/silica composites (CSCs) and their conversion to silica replicas using mammalian cells as scaffolds to direct complex structure formation. Under mildly acidic solution conditions, silica deposition is restricted to the molecularly crowded cellular template. Inter- and intracellular heterogeneity from the nano- to macroscale is captured and dimensionally preserved in CSCs following drying and subjection to extreme temperatures allowing, for instance, size and shape preserving pyrolysis of cellular architectures to form conductive carbon replicas. The structural and behavioral malleability of the starting material (cultured cells) provides opportunities to develop robust and economical biocomposites with programmed structures and functions. PMID:23045634

Activation of cellular death programs associated with immunosenescence-like phenotype in TPPII knockout mice

PubMed Central

Huai, Jisen; Firat, Elke; Nil, Ahmed; Million, Daniele; Gaedicke, Simone; Kanzler, Benoit; Freudenberg, Marina; van Endert, Peter; Kohler, Gabriele; Pahl, Heike L.; Aichele, Peter; Eichmann, Klaus; Niedermann, Gabriele

2008-01-01

The giant cytosolic protease tripeptidyl peptidase II (TPPII) has been implicated in the regulation of proliferation and survival of malignant cells, particularly lymphoma cells. To address its functions in normal cellular and systemic physiology we have generated TPPII-deficient mice. TPPII deficiency activates cell type-specific death programs, including proliferative apoptosis in several T lineage subsets and premature cellular senescence in fibroblasts and CD8+ T cells. This coincides with up-regulation of p53 and dysregulation of NF-κB. Prominent degenerative alterations at the organismic level were a decreased lifespan and symptoms characteristic of immunohematopoietic senescence. These symptoms include accelerated thymic involution, lymphopenia, impaired proliferative T cell responses, extramedullary hematopoiesis, and inflammation. Thus, TPPII is important for maintaining normal cellular and systemic physiology, which may be relevant for potential therapeutic applications of TPPII inhibitors. PMID:18362329

Chromatin organization as an indicator of glucocorticoid induced natural killer cell dysfunction.

PubMed

Misale, Michael S; Witek Janusek, Linda; Tell, Dina; Mathews, Herbert L

2018-01-01

It is well-established that psychological distress reduces natural killer cell immune function and that this reduction can be due to the stress-induced release of glucocorticoids. Glucocorticoids are known to alter epigenetic marks associated with immune effector loci, and are also known to influence chromatin organization. The purpose of this investigation was to assess the effect of glucocorticoids on natural killer cell chromatin organization and to determine the relationship of chromatin organization to natural killer cell effector function, e.g. interferon gamma production. Interferon gamma production is the prototypic cytokine produced by natural killer cells and is known to modulate both innate and adaptive immunity. Glucocorticoid treatment of human peripheral blood mononuclear cells resulted in a significant reduction in interferon gamma production. Glucocorticoid treatment also resulted in a demonstrable natural killer cell nuclear phenotype. This phenotype was localization of the histone, post-translational epigenetic mark, H3K27me3, to the nuclear periphery. Peripheral nuclear localization of H3K27me3 was directly related to cellular levels of interferon gamma. This nuclear phenotype was determined by direct visual inspection and by use of an automated, high through-put technology, the Amnis ImageStream. This technology combines the per-cell information content provided by standard microscopy with the statistical significance afforded by large sample sizes common to standard flow cytometry. Most importantly, this technology provides for a direct assessment of the localization of signal intensity within individual cells. The results demonstrate glucocorticoids to dysregulate natural killer cell function at least in part through altered H3K27me3 nuclear organization and demonstrate H3K27me3 chromatin organization to be a predictive indicator of glucocorticoid induced immune dysregulation of natural killer cells. Copyright © 2017 Elsevier Inc. All rights reserved.

Phenotypic Characterization of Toxic Compound Effects on Liver Spheroids Derived from iPSC Using Confocal Imaging and Three-Dimensional Image Analysis.

PubMed

Sirenko, Oksana; Hancock, Michael K; Hesley, Jayne; Hong, Dihui; Cohen, Avrum; Gentry, Jason; Carlson, Coby B; Mann, David A

2016-09-01

Cell models are becoming more complex to better mimic the in vivo environment and provide greater predictivity for compound efficacy and toxicity. There is an increasing interest in exploring the use of three-dimensional (3D) spheroids for modeling developmental and tissue biology with the goal of accelerating translational research in these areas. Accordingly, the development of high-throughput quantitative assays using 3D cultures is an active area of investigation. In this study, we have developed and optimized methods for the formation of 3D liver spheroids derived from human iPS cells and used those for toxicity assessment. We used confocal imaging and 3D image analysis to characterize cellular information from a 3D matrix to enable a multi-parametric comparison of different spheroid phenotypes. The assay enables characterization of compound toxicities by spheroid size (volume) and shape, cell number and spatial distribution, nuclear characterization, number and distribution of cells expressing viability, apoptosis, mitochondrial potential, and viability marker intensities. In addition, changes in the content of live, dead, and apoptotic cells as a consequence of compound exposure were characterized. We tested 48 compounds and compared induced pluripotent stem cell (iPSC)-derived hepatocytes and HepG2 cells in both two-dimensional (2D) and 3D cultures. We observed significant differences in the pharmacological effects of compounds across the two cell types and between the different culture conditions. Our results indicate that a phenotypic assay using 3D model systems formed with human iPSC-derived hepatocytes is suitable for high-throughput screening and can be used for hepatotoxicity assessment in vitro.

Endogenous molecular network reveals two mechanisms of heterogeneity within gastric cancer.

PubMed

Li, Site; Zhu, Xiaomei; Liu, Bingya; Wang, Gaowei; Ao, Ping

2015-05-30

Intratumor heterogeneity is a common phenomenon and impedes cancer therapy and research. Gastric cancer (GC) cells have generally been classified into two heterogeneous cellular phenotypes, the gastric and intestinal types, yet the mechanisms of maintaining two phenotypes and controlling phenotypic transition are largely unknown. A qualitative systematic framework, the endogenous molecular network hypothesis, has recently been proposed to understand cancer genesis and progression. Here, a minimal network corresponding to such framework was found for GC and was quantified via a stochastic nonlinear dynamical system. We then further extended the framework to address the important question of intratumor heterogeneity quantitatively. The working network characterized main known features of normal gastric epithelial and GC cell phenotypes. Our results demonstrated that four positive feedback loops in the network are critical for GC cell phenotypes. Moreover, two mechanisms that contribute to GC cell heterogeneity were identified: particular positive feedback loops are responsible for the maintenance of intestinal and gastric phenotypes; GC cell progression routes that were revealed by the dynamical behaviors of individual key components are heterogeneous. In this work, we constructed an endogenous molecular network of GC that can be expanded in the future and would broaden the known mechanisms of intratumor heterogeneity.

Molecular Mechanisms Modulating the Phenotype of Macrophages and Microglia

PubMed Central

Amici, Stephanie A.; Dong, Joycelyn; Guerau-de-Arellano, Mireia

2017-01-01

Macrophages and microglia play crucial roles during central nervous system development, homeostasis and acute events such as infection or injury. The diverse functions of tissue macrophages and microglia are mirrored by equally diverse phenotypes. A model of inflammatory/M1 versus a resolution phase/M2 macrophages has been widely used. However, the complexity of macrophage function can only be achieved by the existence of varied, plastic and tridimensional macrophage phenotypes. Understanding how tissue macrophages integrate environmental signals via molecular programs to define pathogen/injury inflammatory responses provides an opportunity to better understand the multilayered nature of macrophages, as well as target and modulate cellular programs to control excessive inflammation. This is particularly important in MS and other neuroinflammatory diseases, where chronic inflammatory macrophage and microglial responses may contribute to pathology. Here, we perform a comprehensive review of our current understanding of how molecular pathways modulate tissue macrophage phenotype, covering both classic pathways and the emerging role of microRNAs, receptor-tyrosine kinases and metabolism in macrophage phenotype. In addition, we discuss pathway parallels in microglia, novel markers helpful in the identification of peripheral macrophages versus microglia and markers linked to their phenotype. PMID:29176977

Single-cell mechanical phenotype is an intrinsic marker of reprogramming and differentiation along the mouse neural lineage.

PubMed

Urbanska, Marta; Winzi, Maria; Neumann, Katrin; Abuhattum, Shada; Rosendahl, Philipp; Müller, Paul; Taubenberger, Anna; Anastassiadis, Konstantinos; Guck, Jochen

2017-12-01

Cellular reprogramming is a dedifferentiation process during which cells continuously undergo phenotypical remodeling. Although the genetic and biochemical details of this remodeling are fairly well understood, little is known about the change in cell mechanical properties during the process. In this study, we investigated changes in the mechanical phenotype of murine fetal neural progenitor cells (fNPCs) during reprogramming to induced pluripotent stem cells (iPSCs). We find that fNPCs become progressively stiffer en route to pluripotency, and that this stiffening is mirrored by iPSCs becoming more compliant during differentiation towards the neural lineage. Furthermore, we show that the mechanical phenotype of iPSCs is comparable with that of embryonic stem cells. These results suggest that mechanical properties of cells are inherent to their developmental stage. They also reveal that pluripotent cells can differentiate towards a more compliant phenotype, which challenges the view that pluripotent stem cells are less stiff than any cells more advanced developmentally. Finally, our study indicates that the cell mechanical phenotype might be utilized as an inherent biophysical marker of pluripotent stem cells. © 2017. Published by The Company of Biologists Ltd.

Endogenous molecular network reveals two mechanisms of heterogeneity within gastric cancer

PubMed Central

Li, Site; Zhu, Xiaomei; Liu, Bingya; Wang, Gaowei; Ao, Ping

2015-01-01

Intratumor heterogeneity is a common phenomenon and impedes cancer therapy and research. Gastric cancer (GC) cells have generally been classified into two heterogeneous cellular phenotypes, the gastric and intestinal types, yet the mechanisms of maintaining two phenotypes and controlling phenotypic transition are largely unknown. A qualitative systematic framework, the endogenous molecular network hypothesis, has recently been proposed to understand cancer genesis and progression. Here, a minimal network corresponding to such framework was found for GC and was quantified via a stochastic nonlinear dynamical system. We then further extended the framework to address the important question of intratumor heterogeneity quantitatively. The working network characterized main known features of normal gastric epithelial and GC cell phenotypes. Our results demonstrated that four positive feedback loops in the network are critical for GC cell phenotypes. Moreover, two mechanisms that contribute to GC cell heterogeneity were identified: particular positive feedback loops are responsible for the maintenance of intestinal and gastric phenotypes; GC cell progression routes that were revealed by the dynamical behaviors of individual key components are heterogeneous. In this work, we constructed an endogenous molecular network of GC that can be expanded in the future and would broaden the known mechanisms of intratumor heterogeneity. PMID:25962957

Computational Model of Secondary Palate Fusion and Disruption

EPA Science Inventory

Morphogenetic events are driven by cell-generated physical forces and complex cellular dynamics. To improve our capacity to predict developmental effects from cellular alterations, we built a multi-cellular agent-based model in CompuCell3D that recapitulates the cellular networks...

Mutations in the NHEJ component XRCC4 cause primordial dwarfism.

PubMed

Murray, Jennie E; van der Burg, Mirjam; IJspeert, Hanna; Carroll, Paula; Wu, Qian; Ochi, Takashi; Leitch, Andrea; Miller, Edward S; Kysela, Boris; Jawad, Alireza; Bottani, Armand; Brancati, Francesco; Cappa, Marco; Cormier-Daire, Valerie; Deshpande, Charu; Faqeih, Eissa A; Graham, Gail E; Ranza, Emmanuelle; Blundell, Tom L; Jackson, Andrew P; Stewart, Grant S; Bicknell, Louise S

2015-03-05

Non-homologous end joining (NHEJ) is a key cellular process ensuring genome integrity. Mutations in several components of the NHEJ pathway have been identified, often associated with severe combined immunodeficiency (SCID), consistent with the requirement for NHEJ during V(D)J recombination to ensure diversity of the adaptive immune system. In contrast, we have recently found that biallelic mutations in LIG4 are a common cause of microcephalic primordial dwarfism (MPD), a phenotype characterized by prenatal-onset extreme global growth failure. Here we provide definitive molecular genetic evidence supported by biochemical, cellular, and immunological data for mutations in XRCC4, encoding the obligate binding partner of LIG4, causing MPD. We report the identification of biallelic mutations in XRCC4 in five families. Biochemical and cellular studies demonstrate that these alterations substantially decrease XRCC4 protein levels leading to reduced cellular ligase IV activity. Consequently, NHEJ-dependent repair of ionizing-radiation-induced DNA double-strand breaks is compromised in XRCC4 cells. Similarly, immunoglobulin junctional diversification is impaired in cells. However, immunoglobulin levels are normal, and individuals lack overt signs of immunodeficiency. Additionally, in contrast to individuals with LIG4 mutations, pancytopenia leading to bone marrow failure has not been observed. Hence, alterations that alter different NHEJ proteins give rise to a phenotypic spectrum, from SCID to extreme growth failure, with deficiencies in certain key components of this repair pathway predominantly exhibiting growth deficits, reflecting differential developmental requirements for NHEJ proteins to support growth and immune maturation. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Astrocytes Can Adopt Endothelial Cell Fates in a p53-Dependent Manner.

PubMed

Brumm, Andrew J; Nunez, Stefanie; Doroudchi, Mehdi M; Kawaguchi, Riki; Duan, Jinhzu; Pellegrini, Matteo; Lam, Larry; Carmichael, S Thomas; Deb, Arjun; Hinman, Jason D

2017-08-01

Astrocytes respond to a variety of CNS injuries by cellular enlargement, process outgrowth, and upregulation of extracellular matrix proteins that function to prevent expansion of the injured region. This astrocytic response, though critical to the acute injury response, results in the formation of a glial scar that inhibits neural repair. Scar-forming cells (fibroblasts) in the heart can undergo mesenchymal-endothelial transition into endothelial cell fates following cardiac injury in a process dependent on p53 that can be modulated to augment cardiac repair. Here, we sought to determine whether astrocytes, as the primary scar-forming cell of the CNS, are able to undergo a similar cellular phenotypic transition and adopt endothelial cell fates. Serum deprivation of differentiated astrocytes resulted in a change in cellular morphology and upregulation of endothelial cell marker genes. In a tube formation assay, serum-deprived astrocytes showed a substantial increase in vessel-like morphology that was comparable to human umbilical vein endothelial cells and dependent on p53. RNA sequencing of serum-deprived astrocytes demonstrated an expression profile that mimicked an endothelial rather than astrocyte transcriptome and identified p53 and angiogenic pathways as specifically upregulated. Inhibition of p53 with genetic or pharmacologic strategies inhibited astrocyte-endothelial transition. Astrocyte-endothelial cell transition could also be modulated by miR-194, a microRNA downstream of p53 that affects expression of genes regulating angiogenesis. Together, these studies demonstrate that differentiated astrocytes retain a stimulus-dependent mechanism for cellular transition into an endothelial phenotype that may modulate formation of the glial scar and promote injury-induced angiogenesis.

Emended descriptions of Prevotella denticola, Prevotella loescheii, Prevotella veroralis, and Prevotella melaninogenica.

PubMed

Wu, C C; Johnson, J L; Moore, W E; Moore, L V

1992-10-01

During studies of human periodontal disease, a number of bacterial strains were encountered that, on the basis of results of standard biochemical tests, appeared to be Prevotella buccalis, Prevotella denticola, Prevotella melaninogenica, or Prevotella loescheii. However, use of the standard biochemical tests, cellular fatty acid analyses, and the polyacrylamide gel electrophoresis patterns of soluble proteins resulted in conflicting identifications of these strains. The results of tests for cellobiose fermentation, inulin fermentation, and pigment production were responsible for most of the discordant results. Cellular fatty acid analyses in which the Microbial Identification System was used did not differentiate these strains from validly described species, even though separate library entries were created for them. DNA reassociation determinations in which the S1 nuclease procedure was used showed that cellobiose fermentation and pigment production are variable among strains of P. melaninogenica and P. denticola and that fermentation of xylan is not a reliable characteristic for differentiating P. buccalis from Prevotella veroralis. In contrast to previous indications, most strains of P. veroralis do not ferment xylan. These species can be differentiated by DNA-DNA reassociation and by cellular fatty acid analysis, using the Microbial Identification System, but differentiation by currently described phenotypic characteristics is not reliable. Similarly, P. loescheii and the genetically distinct (but closely related) D1C-20 group cannot be distinguished reliably from each other or from P. veroralis, P. denticola, and P. melaninogenica on the basis of currently described phenotypic tests other than cellular fatty acid composition or, for some species, electrophoretic patterns of soluble whole-cell proteins.

Tumor evolution in space: the effects of competition colonization tradeoffs on tumor invasion dynamics.

PubMed

Orlando, Paul A; Gatenby, Robert A; Brown, Joel S

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations.

Tumor Evolution in Space: The Effects of Competition Colonization Tradeoffs on Tumor Invasion Dynamics

PubMed Central

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations. PMID:23508890

Identification of cancer-cytotoxic modulators of PDE3A by predictive chemogenomics | Office of Cancer Genomics

Cancer.gov

High cancer death rates indicate the need for new anticancer therapeutic agents. Approaches to discovering new cancer drugs include target-based drug discovery and phenotypic screening. Here, we identified phosphodiesterase 3A modulators as cell-selective cancer cytotoxic compounds through phenotypic compound library screening and target deconvolution by predictive chemogenomics.

Cpd-1 Null Mice Display a Subtle Neurological Phenotype

PubMed Central

Kular, Rupinder K.; Gogliotti, Rocky G.; Opal, Puneet

2010-01-01

Background CPD1 (also known as ANP32-E) belongs to a family of evolutionarily conserved acidic proteins with leucine rich repeats implicated in a variety of cellular processes regulating gene expression, vesicular trafficking, intracellular signaling and apoptosis. Because of its spatiotemporal expression pattern, CPD1 has been proposed to play an important role in brain morphogenesis and synaptic development. Methodology/Principal Findings We have generated CPD1 knock-out mice that we have subsequently characterized. These mice are viable and fertile. However, they display a subtle neurological clasping phenotype and mild motor deficits. Conclusions/Significance CPD1 is not essential for normal development; however, it appears to play a role in the regulation of fine motor functions. The minimal phenotype suggests compensatory biological mechanisms. PMID:20844742

Real-time detection of antibiotic activity by measuring nanometer-scale bacterial deformation

NASA Astrophysics Data System (ADS)

Iriya, Rafael; Syal, Karan; Jing, Wenwen; Mo, Manni; Yu, Hui; Haydel, Shelley E.; Wang, Shaopeng; Tao, Nongjian

2017-12-01

Diagnosing antibiotic-resistant bacteria currently requires sensitive detection of phenotypic changes associated with antibiotic action on bacteria. Here, we present an optical imaging-based approach to quantify bacterial membrane deformation as a phenotypic feature in real-time with a nanometer scale (˜9 nm) detection limit. Using this approach, we found two types of antibiotic-induced membrane deformations in different bacterial strains: polymyxin B induced relatively uniform spatial deformation of Escherichia coli O157:H7 cells leading to change in cellular volume and ampicillin-induced localized spatial deformation leading to the formation of bulges or protrusions on uropathogenic E. coli CFT073 cells. We anticipate that the approach will contribute to understanding of antibiotic phenotypic effects on bacteria with a potential for applications in rapid antibiotic susceptibility testing.

HDAC4 and HDAC6 sustain DNA double strand break repair and stem-like phenotype by promoting radioresistance in glioblastoma cells.

PubMed

Marampon, Francesco; Megiorni, Francesca; Camero, Simona; Crescioli, Clara; McDowell, Heather P; Sferra, Roberta; Vetuschi, Antonella; Pompili, Simona; Ventura, Luca; De Felice, Francesca; Tombolini, Vincenzo; Dominici, Carlo; Maggio, Roberto; Festuccia, Claudio; Gravina, Giovanni Luca

2017-07-01

The role of histone deacetylase (HDAC) 4 and 6 in glioblastoma (GBM) radioresistance was investigated. We found that tumor samples from 31 GBM patients, who underwent temozolomide and radiotherapy combined treatment, showed HDAC4 and HDAC6 expression in 93.5% and 96.7% of cases, respectively. Retrospective clinical data analysis demonstrated that high-intensity HDAC4 and/or HDAC6 immunostaining was predictive of poor clinical outcome. In vitro experiments revealed that short hairpin RNA-mediated silencing of HDAC4 or HDAC6 radiosensitized U87MG and U251MG GBM cell lines by promoting DNA double-strand break (DSBs) accumulation and by affecting DSBs repair molecular machinery. We found that HDAC6 knock-down predisposes to radiation therapy-induced U251MG apoptosis- and U87MG autophagy-mediated cell death. HDAC4 silencing promoted radiation therapy-induced senescence, independently by the cellular context. Finally, we showed that p53 WT expression contributed to the radiotherapy lethal effects and that HDAC4 or HDAC6 sustained GBM stem-like radioresistant phenotype. Altogether, these observations suggest that HDAC4 and HDAC6 are guardians of irradiation-induced DNA damages and stemness, thus promoting radioresistance, and may represent potential prognostic markers and therapeutic targets in GBM. Copyright © 2017 Elsevier B.V. All rights reserved.

Expression of c-Fes protein isoforms correlates with differentiation in myeloid leukemias.

PubMed

Carlson, Anne; Berkowitz, Jeanne McAdara; Browning, Damaris; Slamon, Dennis J; Gasson, Judith C; Yates, Karen E

2005-05-01

The cellular fes gene encodes a 93-kilodalton protein-tyrosine kinase (p93) that is expressed in both normal and neoplastic myeloid cells. Increased c-Fes expression is associated with differentiation in normal myeloid cells and cell lines. Our hypothesis was that primary leukemia cells would show a similar pattern of increased expression in more differentiated cells. Therefore, we compared c-Fes expression in cells with an undifferentiated, blast phenotype (acute myelogenous leukemia--AML) to cells with a differentiated phenotype (chronic myelogenous leukemia--CML). Instead of differences in p93 expression levels, we found complex patterns of c-Fes immunoreactive proteins that corresponded with differentiation in normal and leukemic myeloid cells. The "blast" pattern consisted of c-Fes immunoreactive proteins p93, p74, and p70; the "differentiated" pattern showed two additional c-Fes immunoreactive proteins, p67 and p62. Using mRNA from mouse and human cell lines, we found deletion of one or more exons in the c-fes mRNA. Those deletions predicted truncation of conserved domains (CDC15/FCH and SH2) involved in protein-protein interactions. No deletions were found, however, within the kinase domain. We infer that alternative splicing generates a family of c-Fes proteins. This may be a mechanism to direct the c-Fes kinase domain to different subcellular locations and/or substrates at specific stages of myeloid cell differentiation.

Genetic Determinants Influencing Human Serum Metabolome among African Americans

PubMed Central

Yu, Bing; Zheng, Yan; Alexander, Danny; Morrison, Alanna C.; Coresh, Josef; Boerwinkle, Eric

2014-01-01

Phenotypes proximal to gene action generally reflect larger genetic effect sizes than those that are distant. The human metabolome, a result of multiple cellular and biological processes, are functional intermediate phenotypes proximal to gene action. Here, we present a genome-wide association study of 308 untargeted metabolite levels among African Americans from the Atherosclerosis Risk in Communities (ARIC) Study. Nineteen significant common variant-metabolite associations were identified, including 13 novel loci (p<1.6×10−10). These loci were associated with 7–50% of the difference in metabolite levels per allele, and the variance explained ranged from 4% to 20%. Fourteen genes were identified within the nineteen loci, and four of them contained non-synonymous substitutions in four enzyme-encoding genes (KLKB1, SIAE, CPS1, and NAT8); the other significant loci consist of eight other enzyme-encoding genes (ACE, GATM, ACY3, ACSM2B, THEM4, ADH4, UGT1A, TREH), a transporter gene (SLC6A13) and a polycystin protein gene (PKD2L1). In addition, four potential disease-associated paths were identified, including two direct longitudinal predictive relationships: NAT8 with N-acetylornithine, N-acetyl-1-methylhistidine and incident chronic kidney disease, and TREH with trehalose and incident diabetes. These results highlight the value of using endophenotypes proximal to gene function to discover new insights into biology and disease pathology. PMID:24625756

Performance of in silico tools for the evaluation of p16INK4a (CDKN2A) variants in CAGI.

PubMed

Carraro, Marco; Minervini, Giovanni; Giollo, Manuel; Bromberg, Yana; Capriotti, Emidio; Casadio, Rita; Dunbrack, Roland; Elefanti, Lisa; Fariselli, Pietro; Ferrari, Carlo; Gough, Julian; Katsonis, Panagiotis; Leonardi, Emanuela; Lichtarge, Olivier; Menin, Chiara; Martelli, Pier Luigi; Niroula, Abhishek; Pal, Lipika R; Repo, Susanna; Scaini, Maria Chiara; Vihinen, Mauno; Wei, Qiong; Xu, Qifang; Yang, Yuedong; Yin, Yizhou; Zaucha, Jan; Zhao, Huiying; Zhou, Yaoqi; Brenner, Steven E; Moult, John; Tosatto, Silvio C E

2017-09-01

Correct phenotypic interpretation of variants of unknown significance for cancer-associated genes is a diagnostic challenge as genetic screenings gain in popularity in the next-generation sequencing era. The Critical Assessment of Genome Interpretation (CAGI) experiment aims to test and define the state of the art of genotype-phenotype interpretation. Here, we present the assessment of the CAGI p16INK4a challenge. Participants were asked to predict the effect on cellular proliferation of 10 variants for the p16INK4a tumor suppressor, a cyclin-dependent kinase inhibitor encoded by the CDKN2A gene. Twenty-two pathogenicity predictors were assessed with a variety of accuracy measures for reliability in a medical context. Different assessment measures were combined in an overall ranking to provide more robust results. The R scripts used for assessment are publicly available from a GitHub repository for future use in similar assessment exercises. Despite a limited test-set size, our findings show a variety of results, with some methods performing significantly better. Methods combining different strategies frequently outperform simpler approaches. The best predictor, Yang&Zhou lab, uses a machine learning method combining an empirical energy function measuring protein stability with an evolutionary conservation term. The p16INK4a challenge highlights how subtle structural effects can neutralize otherwise deleterious variants. © 2017 Wiley Periodicals, Inc.

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments

PubMed Central

Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

2015-01-01

The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141

The alignment between phenotypic plasticity, the major axis of genetic variation and the response to selection.

PubMed

Lind, Martin I; Yarlett, Kylie; Reger, Julia; Carter, Mauricio J; Beckerman, Andrew P

2015-10-07

Phenotypic plasticity is the ability of a genotype to produce more than one phenotype in order to match the environment. Recent theory proposes that the major axis of genetic variation in a phenotypically plastic population can align with the direction of selection. Therefore, theory predicts that plasticity directly aids adaptation by increasing genetic variation in the direction favoured by selection and reflected in plasticity. We evaluated this theory in the freshwater crustacean Daphnia pulex, facing predation risk from two contrasting size-selective predators. We estimated plasticity in several life-history traits, the G matrix of these traits, the selection gradients on reproduction and survival, and the predicted responses to selection. Using these data, we tested whether the genetic lines of least resistance and the predicted response to selection aligned with plasticity. We found predator environment-specific G matrices, but shared genetic architecture across environments resulted in more constraint in the G matrix than in the plasticity of the traits, sometimes preventing alignment of the two. However, as the importance of survival selection increased, the difference between environments in their predicted response to selection increased and resulted in closer alignment between the plasticity and the predicted selection response. Therefore, plasticity may indeed aid adaptation to new environments. © 2015 The Authors.

Network motifs that stabilize the hybrid epithelial/mesenchymal phenotype

NASA Astrophysics Data System (ADS)

Jolly, Mohit Kumar; Jia, Dongya; Tripathi, Satyendra; Hanash, Samir; Mani, Sendurai; Ben-Jacob, Eshel; Levine, Herbert

Epithelial to Mesenchymal Transition (EMT) and its reverse - MET - are hallmarks of cancer metastasis. While transitioning between E and M phenotypes, cells can also attain a hybrid epithelial/mesenchymal (E/M) phenotype that enables collective cell migration as a cluster of Circulating Tumor Cells (CTCs). These clusters can form 50-times more tumors than individually migrating CTCs, underlining their importance in metastasis. However, this hybrid E/M phenotype has been hypothesized to be only a transient one that is attained en route EMT. Here, via mathematically modeling, we identify certain `phenotypic stability factors' that couple with the core three-way decision-making circuit (miR-200/ZEB) and can maintain or stabilize the hybrid E/M phenotype. Further, we show experimentally that this phenotype can be maintained stably at a single-cell level, and knockdown of these factors impairs collective cell migration. We also show that these factors enable the association of hybrid E/M with high stemness or tumor-initiating potential. Finally, based on these factors, we deduce specific network motifs that can maintain the E/M phenotype. Our framework can be used to elucidate the effect of other players in regulating cellular plasticity during metastasis. This work was supported by NSF PHY-1427654 (Center for Theoretical Biological Physics) and the CPRIT Scholar in Cancer Research of the State of Texas at Rice University.

Prospects for Genomic Selection in Cassava Breeding.

PubMed

Wolfe, Marnin D; Del Carpio, Dunia Pino; Alabi, Olumide; Ezenwaka, Lydia C; Ikeogu, Ugochukwu N; Kayondo, Ismail S; Lozano, Roberto; Okeke, Uche G; Ozimati, Alfred A; Williams, Esuma; Egesi, Chiedozie; Kawuki, Robert S; Kulakow, Peter; Rabbi, Ismail Y; Jannink, Jean-Luc

2017-11-01

Cassava ( Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on previous analyses by assessing the accuracy of seven prediction models for seven traits in three prediction scenarios: cross-validation within populations, cross-population prediction and cross-generation prediction. We also evaluated the impact of increasing the training population (TP) size by phenotyping progenies selected either at random or with a genetic algorithm. Cross-validation results were mostly consistent across programs, with nonadditive models predicting of 10% better on average. Cross-population accuracy was generally low (mean = 0.18) but prediction of cassava mosaic disease increased up to 57% in one Nigerian population when data from another related population were combined. Accuracy across generations was poorer than within-generation accuracy, as expected, but accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling GS. Selection of a prediction model made some difference across generations, but increasing TP size was more important. With a genetic algorithm, selection of one-third of progeny could achieve an accuracy equivalent to phenotyping all progeny. We are in the early stages of GS for this crop but the results are promising for some traits. General guidelines that are emerging are that TPs need to continue to grow but phenotyping can be done on a cleverly selected subset of individuals, reducing the overall phenotyping burden. Copyright © 2017 Crop Science Society of America.

Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems

PubMed Central

Lomnitz, Jason G.; Savageau, Michael A.

2016-01-01

Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment, and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1) enumeration of the repertoire of model phenotypes, (2) prediction of values for the parameters for any model phenotype, and (3) analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3, and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between three stable states by transient stimulation through one of two input channels: a positive channel that increases the count, and a negative channel that decreases the count. This example shows the power of these new automated methods to rapidly identify behaviors of interest and efficiently predict parameter values for their realization. These tools may be applied to understand complex natural circuitry and to aid in the rational design of synthetic circuits. PMID:27462346

Epigenetics and the Biological Definition of Gene X Environment Interactions

ERIC Educational Resources Information Center

Meaney, Michael J.

2010-01-01

Variations in phenotype reflect the influence of environmental conditions during development on cellular functions, including that of the genome. The recent integration of epigenetics into developmental psychobiology illustrates the processes by which environmental conditions in early life structurally alter DNA, providing a physical basis for the…

The power of yeast to model diseases of the powerhouse of the cell

PubMed Central

Baile, Matthew G.; Claypool, Steven M

2013-01-01

Mitochondria participate in a variety of cellular functions. As such, mitochondrial diseases exhibit numerous clinical phenotypes. Because mitochondrial functions are highly conserved between humans and Saccharomyces cerevisiae, yeast are an excellent model to study mitochondrial disease, providing insight into both physiological and pathophysiological processes. PMID:23276920

Bioenergetic phenotypes and metabolic stress responses in cells derived from ecologically and commercially important fish species

USDA-ARS?s Scientific Manuscript database

As organisms intimately associated with their environment, fish are sensitive to numerous environmental insults which can negatively affect their cellular physiology. For our purposes, fish subject to intensive farming practices can experience a host of acute and chronic stressors such as changes in...

The common occurrence of epistasis in the determination of human pigmentation and its impact on DNA-based pigmentation phenotype prediction.

PubMed

Pośpiech, Ewelina; Wojas-Pelc, Anna; Walsh, Susan; Liu, Fan; Maeda, Hitoshi; Ishikawa, Takaki; Skowron, Małgorzata; Kayser, Manfred; Branicki, Wojciech

2014-07-01

The role of epistatic effects in the determination of complex traits is often underlined but its significance in the prediction of pigmentation phenotypes has not been evaluated so far. The prediction of pigmentation from genetic data can be useful in forensic science to describe the physical appearance of an unknown offender, victim, or missing person who cannot be identified via conventional DNA profiling. Available forensic DNA prediction systems enable the reliable prediction of several eye and hair colour categories. However, there is still space for improvement. Here we verified the association of 38 candidate DNA polymorphisms from 13 genes and explored the extent to which interactions between them may be involved in human pigmentation and their impact on forensic DNA prediction in particular. The model-building set included 718 Polish samples and the model-verification set included 307 independent Polish samples and additional 72 samples from Japan. In total, 29 significant SNP-SNP interactions were found with 5 of them showing an effect on phenotype prediction. For predicting green eye colour, interactions between HERC2 rs12913832 and OCA2 rs1800407 as well as TYRP1 rs1408799 raised the prediction accuracy expressed by AUC from 0.667 to 0.697 and increased the prediction sensitivity by >3%. Interaction between MC1R 'R' variants and VDR rs731236 increased the sensitivity for light skin by >1% and by almost 3% for dark skin colour prediction. Interactions between VDR rs1544410 and TYR rs1042602 as well as between MC1R 'R' variants and HERC2 rs12913832 provided an increase in red/non-red hair prediction accuracy from an AUC of 0.902-0.930. Our results thus underline epistasis as a common phenomenon in human pigmentation genetics and demonstrate that considering SNP-SNP interactions in forensic DNA phenotyping has little impact on eye, hair and skin colour prediction. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Periostin differentially induces proliferation, contraction and apoptosis of primary Dupuytren's disease and adjacent palmar fascia cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vi, Linda; Feng, Lucy; Zhu, Rebecca D.

2009-12-10

Dupuytren's disease, (DD), is a fibroproliferative condition of the palmar fascia in the hand, typically resulting in permanent contracture of one or more fingers. This fibromatosis is similar to scarring and other fibroses in displaying excess collagen secretion and contractile myofibroblast differentiation. In this report we expand on previous data demonstrating that POSTN mRNA, which encodes the extra-cellular matrix protein periostin, is up-regulated in Dupuytren's disease cord tissue relative to phenotypically normal palmar fascia. We demonstrate that the protein product of POSTN, periostin, is abundant in Dupuytren's disease cord tissue while little or no periostin immunoreactivity is evident in patient-matchedmore » control tissues. The relevance of periostin up-regulation in DD was assessed in primary cultures of cells derived from diseased and phenotypically unaffected palmar fascia from the same patients. These cells were grown in type-1 collagen-enriched culture conditions with or without periostin addition to more closely replicate the in vivo environment. Periostin was found to differentially regulate the apoptosis, proliferation, {alpha} smooth muscle actin expression and stressed Fibroblast Populated Collagen Lattice contraction of these cell types. We hypothesize that periostin, secreted by disease cord myofibroblasts into the extra-cellular matrix, promotes the transition of resident fibroblasts in the palmar fascia toward a myofibroblast phenotype, thereby promoting disease progression.« less

Culture on electrospun polyurethane scaffolds decreases atrial natriuretic peptide expression by cardiomyocytes in vitro.

PubMed

Rockwood, Danielle N; Akins, Robert E; Parrag, Ian C; Woodhouse, Kimberly A; Rabolt, John F

2008-12-01

The function of the mammalian heart depends on the functional alignment of cardiomyocytes, and controlling cell alignment is an important consideration in biomaterial design for cardiac tissue engineering and research. The physical cues that guide functional cell alignment in vitro and the impact of substrate-imposed alignment on cell phenotype, however, are only partially understood. In this report, primary cardiac ventricular cells were grown on electrospun, biodegradable polyurethane (ES-PU) with either aligned or unaligned microfibers. ES-PU scaffolds supported high-density cultures and cell subpopulations remained intact over two weeks in culture. ES-PU cultures contained electrically-coupled cardiomyocytes with connexin-43 localized to points of cell:cell contact. Multi-cellular organization correlated with microfiber orientation and aligned materials yielded highly oriented cardiomyocyte groupings. Atrial natriuretic peptide, a molecular marker that shows decreasing expression during ventricular cell maturation, was significantly lower in cultures grown on ES-PU scaffolds than in those grown on tissue culture polystyrene. Cells grown on aligned ES-PU had significantly lower steady state levels of ANP and constitutively released less ANP over time indicating that scaffold-imposed cell organization resulted in a shift in cell phenotype to a more mature state. We conclude that the physical organization of microfibers in ES-PU scaffolds impacts both multi-cellular architecture and cardiac cell phenotype in vitro.

Alterations of overused supraspinatus tendon: a possible role of glycosaminoglycans and HARP/pleiotrophin in early tendon pathology.

PubMed

Attia, Mohamed; Scott, Alexander; Duchesnay, Arlette; Carpentier, Gilles; Soslowsky, Louis J; Huynh, Minh Bao; Van Kuppevelt, Toin H; Gossard, Camille; Courty, José; Tassoni, Marie-Claude; Martelly, Isabelle

2012-01-01

Supraspinatus tendon overuse injuries lead to significant pain and disability in athletes and workers. Despite the prevalence and high social cost of these injuries, the early pathological events are not well known. We analyzed the potential relation between glycosaminoglycan (GAG) composition and phenotypic cellular alteration using a rat model of rotator cuff overuse. Total sulfated GAGs increased after 4 weeks of overuse and remained elevated up to 16 weeks. GAG accumulation was preceded by up-regulation of decorin, versican, and aggrecan proteoglycans (PGs) mRNAs and proteins and biglycan PG mRNA after 2 weeks. At 2 weeks, collagen 1 transcript decreased whereas mRNAs for collagen 2, collagen 3, collagen 6, and the transcription factor Sox9 were increased. Protein levels of heparin affine regulatory peptide (HARP)/pleiotrophin, a cytokine known to regulate developmental chondrocyte formation, were enhanced especially at 4 weeks, without up-regulation of HARP/pleiotrophin mRNA. Further results suggest that the increased GAGs present in early lesions may sequester HARP/pleiotrophin, which could contribute to a loss of tenocyte's phenotype. All these modifications are characteristic of a shift towards the chondrocyte phenotype. Identification of these early changes in the extra-cellular matrix may help to prevent the progression of the pathology to more disabling, degenerative alterations. Copyright © 2011 Orthopaedic Research Society.

Impairment of ntcA gene revealed its role in regulating iron homeostasis, ROS production and cellular phenotype under iron deficiency in cyanobacterium Anabaena sp. PCC 7120.

PubMed

Kaushik, Manish Singh; Srivastava, Meenakshi; Singh, Anumeha; Mishra, Arun Kumar

2017-08-01

Iron deficiency ends up into several unavoidable consequences including damaging oxidative stress in cyanobacteria. NtcA is a global nitrogen regulator controls wide range of metabolisms in addition to regulation of nitrogen metabolism. In present communication, NtcA based regulation of iron homeostasis, ROS production and cellular phenotype under iron deficiency in Anabaena 7120 has been investigated. NtcA regulates the concentration dependent iron uptake by controlling the expression of furA gene. NtcA also regulated pigment synthesis and phenotypic alterations in Anabaena 7120. A significant increase in ROS production and corresponding reduction in the activities of antioxidative enzymes (SOD, CAT, APX and GR) in CSE2 mutant strain in contrast to wild type Anabaena 7120 also suggested the possible involvement of NtcA in protection against oxidative stress in iron deficiency. NtcA has no impact on the expression of furB and furC in spite of presence of consensus NtcA binding site (NBS) and -10 boxes in their promoter. NtcA also regulates the thylakoid arrangement as well as related photosynthetic and respiration rates under iron deficiency in Anabaena 7120. Overall results suggested that NtcA regulates iron acquisition and in turn protect Anabaena cells from the damaging effects of oxidative stress induced under iron deficiency.

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat

PubMed Central

Rutkoski, Jessica; Poland, Jesse; Mondal, Suchismita; Autrique, Enrique; Pérez, Lorena González; Crossa, José; Reynolds, Matthew; Singh, Ravi

2016-01-01

Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots. PMID:27402362

Xenopus laevis oocyte maturation is affected by metal chlorides.

PubMed

Marin, Matthieu; Slaby, Sylvain; Marchand, Guillaume; Demuynck, Sylvain; Friscourt, Noémie; Gelaude, Armance; Lemière, Sébastien; Bodart, Jean-François

2015-08-01

Few studies have been conducted using Xenopus laevis germ cells as oocytes, though these cells offer many advantages allowing both electrophysiological studies and morphological examination. Our aim was to investigate the effects of metal (cadmium, lead, cobalt and zinc) exposures using cell biology approaches. First, cell survival was evaluated with both phenotypical and electrophysiological approaches. Secondly, the effect of metals on oocyte maturation was assessed with morphological observations and electrophysiological recordings. From survival experiments, our results showed that metal chlorides did not affect cell morphology but strongly depolarized X. laevis oocyte resting potential. In addition, cadmium chloride was able to inhibit progesterone-induced oocyte maturation. By contrast, zinc, but also to a lesser extent cadmium, cobalt and lead, were able to enhance spontaneous oocyte maturation in the absence of progesterone stimulation. Finally, electrophysiological recordings revealed that some metal chlorides (lead, cadmium) exposures could disturb calcium signaling in X. laevis oocyte by modifying calcium-activated chloride currents. Our results demonstrated the high sensitivity of X. laevis oocytes toward exogenous metals such as lead and cadmium. In addition, the cellular events recorded might have a predictive value of effects occurring later on the ability of oocytes to be fertilized. Together, these results suggest a potential use of this cellular lab model as a tool for ecotoxicological assessment of contaminated fresh waters. Copyright © 2015 Elsevier Ltd. All rights reserved.

Delineation of the Clinical, Molecular and Cellular Aspects of Novel JAM3 Mutations Underlying the Autosomal Recessive Hemorrhagic Destruction of the Brain, Subependymal Calcification and Congenital Cataracts

PubMed Central

Akawi, Nadia A.; Canpolat, Fuat E.; White, Susan M.; Quilis-Esquerra, Josep; Sanchez, Martin Morales; Gamundi, Maria José; Mochida, Ganeshwaran H.; Walsh, Christopher A.; Ali, Bassam R.; Al-Gazali, Lihadh

2014-01-01

We have recently shown that the hemorrhagic destruction of the brain, subependymal calcification and congenital cataracts is caused by biallelic mutations in the gene encoding junctional adhesion molecule 3 (JAM3) protein. Affected members from three new families underwent detailed clinical examination including imaging of the brain. Affected individuals presented with a distinctive phenotype comprising hemorrhagic destruction of the brain, subependymal calcification and congenital cataracts. All patients had a catastrophic clinical course resulting in death in 7 out of 10 affected individuals. Sequencing the coding exons of JAM3 revealed three novel homozygous mutations: c.2T>G (p.M1R), c.346G>A (p.E116K) and c.656G>A (p.C219Y). The p.M1R mutation affects the start codon and therefore is predicted to impair protein synthesis. Cellular studies showed that the p.C219Y mutation resulted in a significant retention of the mutated protein in the endoplasmic reticulum, suggesting a trafficking defect. The p.E116K mutant traffics normally to the plasma membrane as the wild type and may have lost its function due to the lack of interaction with an interacting partner. Our data further support the importance of JAM3 in the development and function of the vascular system and the brain. PMID:23255084

A modular cell-based biosensor using engineered genetic logic circuits to detect and integrate multiple environmental signals

PubMed Central

Wang, Baojun; Barahona, Mauricio; Buck, Martin

2013-01-01

Cells perceive a wide variety of cellular and environmental signals, which are often processed combinatorially to generate particular phenotypic responses. Here, we employ both single and mixed cell type populations, pre-programmed with engineered modular cell signalling and sensing circuits, as processing units to detect and integrate multiple environmental signals. Based on an engineered modular genetic AND logic gate, we report the construction of a set of scalable synthetic microbe-based biosensors comprising exchangeable sensory, signal processing and actuation modules. These cellular biosensors were engineered using distinct signalling sensory modules to precisely identify various chemical signals, and combinations thereof, with a quantitative fluorescent output. The genetic logic gate used can function as a biological filter and an amplifier to enhance the sensing selectivity and sensitivity of cell-based biosensors. In particular, an Escherichia coli consortium-based biosensor has been constructed that can detect and integrate three environmental signals (arsenic, mercury and copper ion levels) via either its native two-component signal transduction pathways or synthetic signalling sensors derived from other bacteria in combination with a cell-cell communication module. We demonstrate how a modular cell-based biosensor can be engineered predictably using exchangeable synthetic gene circuit modules to sense and integrate multiple-input signals. This study illustrates some of the key practical design principles required for the future application of these biosensors in broad environmental and healthcare areas. PMID:22981411

Analysis of Putative Apoplastic Effectors from the Nematode, Globodera rostochiensis, and Identification of an Expansin-Like Protein That Can Induce and Suppress Host Defenses

PubMed Central

Ali, Shawkat; Magne, Maxime; Chen, Shiyan; Côté, Olivier; Stare, Barbara Gerič; Obradovic, Natasa; Jamshaid, Lubna; Wang, Xiaohong; Bélair, Guy; Moffett, Peter

2015-01-01

The potato cyst nematode, Globodera rostochiensis, is an important pest of potato. Like other pathogens, plant parasitic nematodes are presumed to employ effector proteins, secreted into the apoplast as well as the host cytoplasm, to alter plant cellular functions and successfully infect their hosts. We have generated a library of ORFs encoding putative G. rostochiensis putative apoplastic effectors in vectors for expression in planta. These clones were assessed for morphological and developmental effects on plants as well as their ability to induce or suppress plant defenses. Several CLAVATA3/ESR-like proteins induced developmental phenotypes, whereas predicted cell wall-modifying proteins induced necrosis and chlorosis, consistent with roles in cell fate alteration and tissue invasion, respectively. When directed to the apoplast with a signal peptide, two effectors, an ubiquitin extension protein (GrUBCEP12) and an expansin-like protein (GrEXPB2), suppressed defense responses including NB-LRR signaling induced in the cytoplasm. GrEXPB2 also elicited defense response in species- and sequence-specific manner. Our results are consistent with the scenario whereby potato cyst nematodes secrete effectors that modulate host cell fate and metabolism as well as modifying host cell walls. Furthermore, we show a novel role for an apoplastic expansin-like protein in suppressing intra-cellular defense responses. PMID:25606855

Analysis of putative apoplastic effectors from the nematode, Globodera rostochiensis, and identification of an expansin-like protein that can induce and suppress host defenses.

PubMed

Ali, Shawkat; Magne, Maxime; Chen, Shiyan; Côté, Olivier; Stare, Barbara Gerič; Obradovic, Natasa; Jamshaid, Lubna; Wang, Xiaohong; Bélair, Guy; Moffett, Peter

2015-01-01

The potato cyst nematode, Globodera rostochiensis, is an important pest of potato. Like other pathogens, plant parasitic nematodes are presumed to employ effector proteins, secreted into the apoplast as well as the host cytoplasm, to alter plant cellular functions and successfully infect their hosts. We have generated a library of ORFs encoding putative G. rostochiensis putative apoplastic effectors in vectors for expression in planta. These clones were assessed for morphological and developmental effects on plants as well as their ability to induce or suppress plant defenses. Several CLAVATA3/ESR-like proteins induced developmental phenotypes, whereas predicted cell wall-modifying proteins induced necrosis and chlorosis, consistent with roles in cell fate alteration and tissue invasion, respectively. When directed to the apoplast with a signal peptide, two effectors, an ubiquitin extension protein (GrUBCEP12) and an expansin-like protein (GrEXPB2), suppressed defense responses including NB-LRR signaling induced in the cytoplasm. GrEXPB2 also elicited defense response in species- and sequence-specific manner. Our results are consistent with the scenario whereby potato cyst nematodes secrete effectors that modulate host cell fate and metabolism as well as modifying host cell walls. Furthermore, we show a novel role for an apoplastic expansin-like protein in suppressing intra-cellular defense responses.

Cell kinetics and genetic instabilities in differentiated type early gastric cancers with different mucin phenotype.

PubMed

Shibata, Naomi; Watari, Jiro; Fujiya, Mikihiro; Tanno, Satoshi; Saitoh, Yusuke; Kohgo, Yutaka

2003-01-01

To clarify the biological impact and molecular pathogenesis of cellular phenotype in differentiated-type gastric cancers (DGCs), we investigated cell kinetics and genetic instabilities in early stage of DGCs. A total of 43 early gastric cancers (EGCs) were studied. EGCs were divided into 3 phenotypic categories: gastric (G type, n = 11), ordinary (O type, n = 20), and complete intestinal (CI type, n = 12) based on the combination of HGM, ConA, MUC2, and CD10. Proliferative index (PI), apoptotic index (AI), and p53 overexpression were investigated by immunohistochemical staining with anti-Ki-67, the terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick-end labeling method, and p53 antibody, respectively. Using a high-resolution fluorescent microsatellite analysis system, microsatellite instability (MSI) and loss of heterozygosity (LOH) were examined. Frameshift mutation analysis of transforming growth factor-beta type II receptor (TGF-betaRII) and bcl-2-associated X (BAX) in cancers with MSI was also performed. The mean AI/PI ratio values were 0.04 for G-type, 0.10 for O-type, and 0.13 for CI-type cancers--significantly lower in G type than in O and CI types (P = 0.02 and P = 0.001, respectively). No difference in the incidence of MSI and LOH was seen among the 3 cellular phenotypes. However, the major pattern of MSI, which showed drastic and widely dispersed changes and is related to an increased risk for cancer, was significantly higher in G and O types than in CI type (P <0.005). No frame shift mutations of TGF-betaRII or BAX were found in CI-type cancers. These results indicate that G-type cancers are likely to show more aggressive behaviors than CI-type cancers, and that O-type cancers show the intermediate characteristics of both types. However, the molecular pathogenesis of each phenotypic cancer is not associated with microsatellite alterations. Copyright 2003, Elsevier Science (USA). All rights reserved.

Systematic bias of correlation coefficient may explain negative accuracy of genomic prediction.

PubMed

Zhou, Yao; Vales, M Isabel; Wang, Aoxue; Zhang, Zhiwu

2017-09-01

Accuracy of genomic prediction is commonly calculated as the Pearson correlation coefficient between the predicted and observed phenotypes in the inference population by using cross-validation analysis. More frequently than expected, significant negative accuracies of genomic prediction have been reported in genomic selection studies. These negative values are surprising, given that the minimum value for prediction accuracy should hover around zero when randomly permuted data sets are analyzed. We reviewed the two common approaches for calculating the Pearson correlation and hypothesized that these negative accuracy values reflect potential bias owing to artifacts caused by the mathematical formulas used to calculate prediction accuracy. The first approach, Instant accuracy, calculates correlations for each fold and reports prediction accuracy as the mean of correlations across fold. The other approach, Hold accuracy, predicts all phenotypes in all fold and calculates correlation between the observed and predicted phenotypes at the end of the cross-validation process. Using simulated and real data, we demonstrated that our hypothesis is true. Both approaches are biased downward under certain conditions. The biases become larger when more fold are employed and when the expected accuracy is low. The bias of Instant accuracy can be corrected using a modified formula. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower.

PubMed

Thorwarth, Patrick; Yousef, Eltohamy A A; Schmid, Karl J

2018-02-02

Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS) and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower ( Brassica oleracea var. botrytis ) by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS) and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding. Copyright © 2018 Thorwarth et al.

Developmental disruption of amygdala transcriptome and socioemotional behavior in rats exposed to valproic acid prenatally.

PubMed

Barrett, Catherine E; Hennessey, Thomas M; Gordon, Katelyn M; Ryan, Steve J; McNair, Morgan L; Ressler, Kerry J; Rainnie, Donald G

2017-01-01

The amygdala controls socioemotional behavior and has consistently been implicated in the etiology of autism spectrum disorder (ASD). Precocious amygdala development is commonly reported in ASD youth with the degree of overgrowth positively correlated to the severity of ASD symptoms. Prenatal exposure to VPA leads to an ASD phenotype in both humans and rats and has become a commonly used tool to model the complexity of ASD symptoms in the laboratory. Here, we examined abnormalities in gene expression in the amygdala and socioemotional behavior across development in the valproic acid (VPA) rat model of ASD. Rat dams received oral gavage of VPA (500 mg/kg) or saline daily between E11 and 13. Socioemotional behavior was tracked across development in both sexes. RNA sequencing and proteomics were performed on amygdala samples from male rats across development. Effects of VPA on time spent in social proximity and anxiety-like behavior were sex dependent, with social abnormalities presenting in males and heightened anxiety in females. Across time VPA stunted developmental and immune, but enhanced cellular death and disorder, pathways in the amygdala relative to saline controls. At postnatal day 10, gene pathways involved in nervous system and cellular development displayed predicted activations in prenatally exposed VPA amygdala samples. By juvenile age, however, transcriptomic and proteomic pathways displayed reductions in cellular growth and neural development. Alterations in immune pathways, calcium signaling, Rho GTPases, and protein kinase A signaling were also observed. As behavioral, developmental, and genomic alterations are similar to those reported in ASD, these results lend support to prenatal exposure to VPA as a useful tool for understanding how developmental insults to molecular pathways in the amygdala give rise to ASD-related syndromes.

Antimicrobial Resistance Prediction in PATRIC and RAST.

PubMed

Davis, James J; Boisvert, Sébastien; Brettin, Thomas; Kenyon, Ronald W; Mao, Chunhong; Olson, Robert; Overbeek, Ross; Santerre, John; Shukla, Maulik; Wattam, Alice R; Will, Rebecca; Xia, Fangfang; Stevens, Rick

2016-06-14

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88-99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71-88%. This set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.

Dynamic Finite Element Predictions for Mars Sample Return Cellular Impact Test #4

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Billings, Marcus D.

2001-01-01

The nonlinear finite element program MSC.Dytran was used to predict the impact pulse for (he drop test of an energy absorbing cellular structure. This pre-test simulation was performed to aid in the design of an energy absorbing concept for a highly reliable passive Earth Entry Vehicle (EEV) that will directly impact the Earth without a parachute. In addition, a goal of the simulation was to bound the acceleration pulse produced and delivered to the simulated space cargo container. EEV's are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite-epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the enter of the EEV's cellular structure. The material models and failure criteria were varied to determine their effect on the resulting acceleration pulse. Pre-test analytical predictions using MSC.Dytran were compared with the test results obtained from impact test #4 using bungee accelerator located at the NASA Langley Research Center Impact Dynamics Research Facility. The material model used to represent the foam and the proper failure criteria for the cell walls were critical in predicting the impact loads of the cellular structure. It was determined that a FOAMI model for the foam and a 20% failure strain criteria for the cell walls gave an accurate prediction of the acceleration pulse for drop test #4.

Cellular mechanisms of estradiol-mediated sexual differentiation of the brain.

PubMed

Wright, Christopher L; Schwarz, Jaclyn S; Dean, Shannon L; McCarthy, Margaret M

2010-09-01

Gonadal steroids organize the developing brain during a perinatal sensitive period and have enduring consequences for adult behavior. In male rodents testicular androgens are aromatized in neurons to estrogens and initiate multiple distinct cellular processes that ultimately determine the masculine phenotype. Within specific brain regions, overall cell number and dendritic morphology are the principal targets for hormonal organization. Recent advances have been made in elucidating the cellular mechanisms by which the neurological underpinnings of sexually dimorphic physiology and behavior are determined. These include estradiol-mediated prostaglandin synthesis, presynaptic release of glutamate, postsynaptic changes in glutamate receptors and changes in cell adhesion molecules. Sex differences in cell death are mediated by hormonal modulation of survival and death factors such as TNFalpha and Bcl-2/BAX. Copyright 2010 Elsevier Ltd. All rights reserved.

Phenotypic interactions between tree hosts and invasive forest pathogens in the light of globalization and climate change

PubMed Central

2016-01-01

Invasive pathogens can cause considerable damage to forest ecosystems. Lack of coevolution is generally thought to enable invasive pathogens to bypass the defence and/or recognition systems in the host. Although mostly true, this argument fails to predict intermittent outcomes in space and time, underlining the need to include the roles of the environment and the phenotype in host–pathogen interactions when predicting disease impacts. We emphasize the need to consider host–tree imbalances from a phenotypic perspective, considering the lack of coevolutionary and evolutionary history with the pathogen and the environment, respectively. We describe how phenotypic plasticity and plastic responses to environmental shifts may become maladaptive when hosts are faced with novel pathogens. The lack of host–pathogen and environmental coevolution are aligned with two global processes currently driving forest damage: globalization and climate change, respectively. We suggest that globalization and climate change act synergistically, increasing the chances of both genotypic and phenotypic imbalances. Short moves on the same continent are more likely to be in balance than if the move is from another part of the world. We use Gremmeniella abietina outbreaks in Sweden to exemplify how host–pathogen phenotypic interactions can help to predict the impacts of specific invasive and emergent diseases. This article is part of the themed issue ‘Tackling emerging fungal threats to animal health, food security and ecosystem resilience’. PMID:28080981

Phenotypic interactions between tree hosts and invasive forest pathogens in the light of globalization and climate change.

PubMed

Stenlid, Jan; Oliva, Jonàs

2016-12-05

Invasive pathogens can cause considerable damage to forest ecosystems. Lack of coevolution is generally thought to enable invasive pathogens to bypass the defence and/or recognition systems in the host. Although mostly true, this argument fails to predict intermittent outcomes in space and time, underlining the need to include the roles of the environment and the phenotype in host-pathogen interactions when predicting disease impacts. We emphasize the need to consider host-tree imbalances from a phenotypic perspective, considering the lack of coevolutionary and evolutionary history with the pathogen and the environment, respectively. We describe how phenotypic plasticity and plastic responses to environmental shifts may become maladaptive when hosts are faced with novel pathogens. The lack of host-pathogen and environmental coevolution are aligned with two global processes currently driving forest damage: globalization and climate change, respectively. We suggest that globalization and climate change act synergistically, increasing the chances of both genotypic and phenotypic imbalances. Short moves on the same continent are more likely to be in balance than if the move is from another part of the world. We use Gremmeniella abietina outbreaks in Sweden to exemplify how host-pathogen phenotypic interactions can help to predict the impacts of specific invasive and emergent diseases.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Author(s).

Transgressive Hybrids as Hopeful Monsters.

PubMed

Dittrich-Reed, Dylan R; Fitzpatrick, Benjamin M

2013-06-01

The origin of novelty is a critical subject for evolutionary biologists. Early geneticists speculated about the sudden appearance of new species via special macromutations, epitomized by Goldschmidt's infamous "hopeful monster". Although these ideas were easily dismissed by the insights of the Modern Synthesis, a lingering fascination with the possibility of sudden, dramatic change has persisted. Recent work on hybridization and gene exchange suggests an underappreciated mechanism for the sudden appearance of evolutionary novelty that is entirely consistent with the principles of modern population genetics. Genetic recombination in hybrids can produce transgressive phenotypes, "monstrous" phenotypes beyond the range of parental populations. Transgressive phenotypes can be products of epistatic interactions or additive effects of multiple recombined loci. We compare several epistatic and additive models of transgressive segregation in hybrids and find that they are special cases of a general, classic quantitative genetic model. The Dobzhansky-Muller model predicts "hopeless" monsters, sterile and inviable transgressive phenotypes. The Bateson model predicts "hopeful" monsters with fitness greater than either parental population. The complementation model predicts both. Transgressive segregation after hybridization can rapidly produce novel phenotypes by recombining multiple loci simultaneously. Admixed populations will also produce many similar recombinant phenotypes at the same time, increasing the probability that recombinant "hopeful monsters" will establish true-breeding evolutionary lineages. Recombination is not the only (or even most common) process generating evolutionary novelty, but might be the most credible mechanism for sudden appearance of new forms.

Resolving phylogenetic incongruence to articulate homology and phenotypic evolution: a case study from Nematoda

PubMed Central

Ragsdale, Erik J.; Baldwin, James G.

2010-01-01

Modern morphology-based systematics, including questions of incongruence with molecular data, emphasizes analysis over similarity criteria to assess homology. Yet detailed examination of a few key characters, using new tools and processes such as computerized, three-dimensional ultrastructural reconstruction of cell complexes, can resolve apparent incongruence by re-examining primary homologies. In nematodes of Tylenchomorpha, a parasitic feeding phenotype is thus reconciled with immediate free-living outgroups. Closer inspection of morphology reveals phenotypes congruent with molecular-based phylogeny and points to a new locus of homology in mouthparts. In nematode models, the study of individually homologous cells reveals a conserved modality of evolution among dissimilar feeding apparati adapted to divergent lifestyles. Conservatism of cellular components, consistent with that of other body systems, allows meaningful comparative morphology in difficult groups of microscopic organisms. The advent of phylogenomics is synergistic with morphology in systematics, providing an honest test of homology in the evolution of phenotype. PMID:20106846

Multiplexed precision genome editing with trackable genomic barcodes in yeast.

PubMed

Roy, Kevin R; Smith, Justin D; Vonesch, Sibylle C; Lin, Gen; Tu, Chelsea Szu; Lederer, Alex R; Chu, Angela; Suresh, Sundari; Nguyen, Michelle; Horecka, Joe; Tripathi, Ashutosh; Burnett, Wallace T; Morgan, Maddison A; Schulz, Julia; Orsley, Kevin M; Wei, Wu; Aiyar, Raeka S; Davis, Ronald W; Bankaitis, Vytas A; Haber, James E; Salit, Marc L; St Onge, Robert P; Steinmetz, Lars M

2018-07-01

Our understanding of how genotype controls phenotype is limited by the scale at which we can precisely alter the genome and assess the phenotypic consequences of each perturbation. Here we describe a CRISPR-Cas9-based method for multiplexed accurate genome editing with short, trackable, integrated cellular barcodes (MAGESTIC) in Saccharomyces cerevisiae. MAGESTIC uses array-synthesized guide-donor oligos for plasmid-based high-throughput editing and features genomic barcode integration to prevent plasmid barcode loss and to enable robust phenotyping. We demonstrate that editing efficiency can be increased more than fivefold by recruiting donor DNA to the site of breaks using the LexA-Fkh1p fusion protein. We performed saturation editing of the essential gene SEC14 and identified amino acids critical for chemical inhibition of lipid signaling. We also constructed thousands of natural genetic variants, characterized guide mismatch tolerance at the genome scale, and ascertained that cryptic Pol III termination elements substantially reduce guide efficacy. MAGESTIC will be broadly useful to uncover the genetic basis of phenotypes in yeast.

Large-scale image-based profiling of single-cell phenotypes in arrayed CRISPR-Cas9 gene perturbation screens.

PubMed

de Groot, Reinoud; Lüthi, Joel; Lindsay, Helen; Holtackers, René; Pelkmans, Lucas

2018-01-23

High-content imaging using automated microscopy and computer vision allows multivariate profiling of single-cell phenotypes. Here, we present methods for the application of the CISPR-Cas9 system in large-scale, image-based, gene perturbation experiments. We show that CRISPR-Cas9-mediated gene perturbation can be achieved in human tissue culture cells in a timeframe that is compatible with image-based phenotyping. We developed a pipeline to construct a large-scale arrayed library of 2,281 sequence-verified CRISPR-Cas9 targeting plasmids and profiled this library for genes affecting cellular morphology and the subcellular localization of components of the nuclear pore complex (NPC). We conceived a machine-learning method that harnesses genetic heterogeneity to score gene perturbations and identify phenotypically perturbed cells for in-depth characterization of gene perturbation effects. This approach enables genome-scale image-based multivariate gene perturbation profiling using CRISPR-Cas9. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Overexpression of the base excision repair NTHL1 glycosylase causes genomic instability and early cellular hallmarks of cancer

PubMed Central

Limpose, Kristin L; Trego, Kelly S; Li, Zhentian; Leung, Sara W; Sarker, Altaf H; Shah, Jason A; Ramalingam, Suresh S; Werner, Erica M; Dynan, William S; Cooper, Priscilla K; Corbett, Anita H; Doetsch, Paul W

2018-01-01

Abstract Base excision repair (BER), which is initiated by DNA N-glycosylase proteins, is the frontline for repairing potentially mutagenic DNA base damage. The NTHL1 glycosylase, which excises DNA base damage caused by reactive oxygen species, is thought to be a tumor suppressor. However, in addition to NTHL1 loss-of-function mutations, our analysis of cancer genomic datasets reveals that NTHL1 frequently undergoes amplification or upregulation in some cancers. Whether NTHL1 overexpression could contribute to cancer phenotypes has not yet been explored. To address the functional consequences of NTHL1 overexpression, we employed transient overexpression. Both NTHL1 and a catalytically-dead NTHL1 (CATmut) induce DNA damage and genomic instability in non-transformed human bronchial epithelial cells (HBEC) when overexpressed. Strikingly, overexpression of either NTHL1 or CATmut causes replication stress signaling and a decrease in homologous recombination (HR). HBEC cells that overexpress NTHL1 or CATmut acquire the ability to grow in soft agar and exhibit loss of contact inhibition, suggesting that a mechanism independent of NTHL1 catalytic activity contributes to acquisition of cancer-related cellular phenotypes. We provide evidence that NTHL1 interacts with the multifunctional DNA repair protein XPG suggesting that interference with HR is a possible mechanism that contributes to acquisition of early cellular hallmarks of cancer. PMID:29522130

Tension Monitoring during Epithelial-to-Mesenchymal Transition Links the Switch of Phenotype to Expression of Moesin and Cadherins in NMuMG Cells

PubMed Central

Schneider, David; Baronsky, Thilo; Pietuch, Anna; Rother, Jan; Oelkers, Marieelen; Fichtner, Dagmar; Wedlich, Doris; Janshoff, Andreas

2013-01-01

Structural alterations during epithelial-to-mesenchymal transition (EMT) pose a substantial challenge to the mechanical response of cells and are supposed to be key parameters for an increased malignancy during metastasis. Herein, we report that during EMT, apical tension of the epithelial cell line NMuMG is controlled by cell-cell contacts and the architecture of the underlying actin structures reflecting the mechanistic interplay between cellular structure and mechanics. Using force spectroscopy we find that tension in NMuMG cells slightly increases 24 h after EMT induction, whereas upon reaching the final mesenchymal-like state characterized by a complete loss of intercellular junctions and a concerted down-regulation of the adherens junction protein E-cadherin, the overall tension becomes similar to that of solitary adherent cells and fibroblasts. Interestingly, the contribution of the actin cytoskeleton on apical tension increases significantly upon EMT induction, most likely due to the formation of stable and highly contractile stress fibers which dominate the elastic properties of the cells after the transition. The structural alterations lead to the formation of single, highly motile cells rendering apical tension a good indicator for the cellular state during phenotype switching. In summary, our study paves the way towards a more profound understanding of cellular mechanics governing fundamental morphological programs such as the EMT. PMID:24339870

High-Content, High-Throughput Screening for the Identification of Cytotoxic Compounds Based on Cell Morphology and Cell Proliferation Markers

PubMed Central

Martin, Heather L.; Adams, Matthew; Higgins, Julie; Bond, Jacquelyn; Morrison, Ewan E.; Bell, Sandra M.; Warriner, Stuart; Nelson, Adam; Tomlinson, Darren C.

2014-01-01

Toxicity is a major cause of failure in drug discovery and development, and whilst robust toxicological testing occurs, efficiency could be improved if compounds with cytotoxic characteristics were identified during primary compound screening. The use of high-content imaging in primary screening is becoming more widespread, and by utilising phenotypic approaches it should be possible to incorporate cytotoxicity counter-screens into primary screens. Here we present a novel phenotypic assay that can be used as a counter-screen to identify compounds with adverse cellular effects. This assay has been developed using U2OS cells, the PerkinElmer Operetta high-content/high-throughput imaging system and Columbus image analysis software. In Columbus, algorithms were devised to identify changes in nuclear morphology, cell shape and proliferation using DAPI, TOTO-3 and phosphohistone H3 staining, respectively. The algorithms were developed and tested on cells treated with doxorubicin, taxol and nocodazole. The assay was then used to screen a novel, chemical library, rich in natural product-like molecules of over 300 compounds, 13.6% of which were identified as having adverse cellular effects. This assay provides a relatively cheap and rapid approach for identifying compounds with adverse cellular effects during screening assays, potentially reducing compound rejection due to toxicity in subsequent in vitro and in vivo assays. PMID:24505478

Stable isotope phenotyping via cluster analysis of NanoSIMS data as a method for characterizing distinct microbial ecophysiologies and sulfur-cycling in the environment

NASA Astrophysics Data System (ADS)

Dawson, K.; Scheller, S.; Dillon, J. G.; Orphan, V. J.

2016-12-01

Stable isotope probing (SIP) is a valuable tool for gaining insights into ecophysiology and biogeochemical cycling of environmental microbial communities by tracking isotopically labeled compounds into cellular macromolecules as well as into byproducts of respiration. SIP, in conjunction with nanoscale secondary ion mass spectrometry (NanoSIMS), allows for the visualization of isotope incorporation at the single cell level. In this manner, both active cells within a diverse population as well as heterogeneity in metabolism within a homogeneous population can be observed. The ecophysiological implications of these single cell stable isotope measurements are often limited to the taxonomic resolution of paired fluorescence in situ hybridization (FISH) microscopy. Here we introduce a taxonomy-independent method using multi-isotope SIP and NanoSIMS for identifying and grouping phenotypically similar microbial cells by their chemical and isotopic fingerprint. This method was applied to SIP experiments in a sulfur-cycling biofilm collected from sulfidic intertidal vents amended with 13C-acetate, 15N-ammonium, and 33S-sulfate. Using a cluster analysis technique based on fuzzy c-means to group cells according to their isotope (13C/12C, 15N/14N, and 33S/32S) and elemental ratio (C/CN and S/CN) profiles, our analysis partitioned 2200 cellular regions of interest (ROIs) into 5 distinct groups. These isotope phenotype groupings are reflective of the variation in labeled substrate uptake by cells in a multispecies metabolic network dominated by Gamma- and Deltaproteobacteria. Populations independently grouped by isotope phenotype were subsequently compared with paired FISH data, demonstrating a single coherent deltaproteobacterial cluster and multiple gammaproteobacterial groups, highlighting the distinct ecophysiologies of spatially-associated microbes within the sulfur-cycling biofilm from White Point Beach, CA.

Induction of CaSR expression circumvents the molecular features of malignant CaSR null colon cancer cells.

PubMed

Singh, Navneet; Chakrabarty, Subhas

2013-11-15

We recently reported on the isolation and characterization of calcium sensing receptor (CaSR) null human colon cancer cells (Singh et al., Int J Cancer 2013; 132: 1996-2005). CaSR null cells possess a myriad of molecular features that are linked to a highly malignant and drug resistant phenotype of colon cancer. The CaSR null phenotype can be maintained in defined human embryonic stem cell culture medium. We now show that the CaSR null cells can be induced to differentiate in conventional culture medium, regained the expression of CaSR with a concurrent reversal of the cellular and molecular features associated with the null phenotype. These features include cellular morphology, expression of colon cancer stem cell markers, expression of survivin and thymidylate synthase and sensitivity to fluorouracil. Other features include the expression of epithelial mesenchymal transition linked molecules and transcription factors, oncogenic miRNAs and tumor suppressive molecule and miRNA. With the exception of cancer stem cell markers, the reversal of molecular features, upon the induction of CaSR expression, is directly linked to the expression and function of CaSR because blocking CaSR induction by shRNA circumvented such reversal. We further report that methylation and demethylation of the CaSR gene promoter underlie CaSR expression. Due to the malignant nature of the CaSR null cells, inclusion of the CaSR null phenotype in disease management may improve on the mortality of this disease. Because CaSR is a robust promoter of differentiation and mediates its action through diverse mechanisms and pathways, inactivation of CaSR may serve as a new paradigm in colon carcinogenesis. Copyright © 2013 UICC.

Stable Isotope Phenotyping via Cluster Analysis of NanoSIMS Data As a Method for Characterizing Distinct Microbial Ecophysiologies and Sulfur-Cycling in the Environment

PubMed Central

Dawson, Katherine S.; Scheller, Silvan; Dillon, Jesse G.; Orphan, Victoria J.

2016-01-01

Stable isotope probing (SIP) is a valuable tool for gaining insights into ecophysiology and biogeochemical cycling of environmental microbial communities by tracking isotopically labeled compounds into cellular macromolecules as well as into byproducts of respiration. SIP, in conjunction with nanoscale secondary ion mass spectrometry (NanoSIMS), allows for the visualization of isotope incorporation at the single cell level. In this manner, both active cells within a diverse population as well as heterogeneity in metabolism within a homogeneous population can be observed. The ecophysiological implications of these single cell stable isotope measurements are often limited to the taxonomic resolution of paired fluorescence in situ hybridization (FISH) microscopy. Here we introduce a taxonomy-independent method using multi-isotope SIP and NanoSIMS for identifying and grouping phenotypically similar microbial cells by their chemical and isotopic fingerprint. This method was applied to SIP experiments in a sulfur-cycling biofilm collected from sulfidic intertidal vents amended with 13C-acetate, 15N-ammonium, and 33S-sulfate. Using a cluster analysis technique based on fuzzy c-means to group cells according to their isotope (13C/12C, 15N/14N, and 33S/32S) and elemental ratio (C/CN and S/CN) profiles, our analysis partitioned ~2200 cellular regions of interest (ROIs) into five distinct groups. These isotope phenotype groupings are reflective of the variation in labeled substrate uptake by cells in a multispecies metabolic network dominated by Gamma- and Deltaproteobacteria. Populations independently grouped by isotope phenotype were subsequently compared with paired FISH data, demonstrating a single coherent deltaproteobacterial cluster and multiple gammaproteobacterial groups, highlighting the distinct ecophysiologies of spatially-associated microbes within the sulfur-cycling biofilm from White Point Beach, CA. PMID:27303371

Early experiences mediate distinct adult gene expression and reproductive programs in Caenorhabditis elegans

PubMed Central

Ow, Maria C.; Nichitean, Alexandra M.; Dorus, Steve; Hall, Sarah E.

2018-01-01

Environmental stress during early development in animals can have profound effects on adult phenotypes via programmed changes in gene expression. Using the nematode C. elegans, we demonstrated previously that adults retain a cellular memory of their developmental experience that is manifested by differences in gene expression and life history traits; however, the sophistication of this system in response to different environmental stresses, and how it dictates phenotypic plasticity in adults that contribute to increased fitness in response to distinct environmental challenges, was unknown. Using transcriptional profiling, we show here that C. elegans adults indeed retain distinct cellular memories of different environmental conditions. We identified approximately 500 genes in adults that entered dauer due to starvation that exhibit significant opposite (“seesaw”) transcriptional phenotypes compared to adults that entered dauer due to crowding, and are distinct from animals that bypassed dauer. Moreover, we show that two-thirds of the genes in the genome experience a 2-fold or greater seesaw trend in gene expression, and based upon the direction of change, are enriched in large, tightly linked regions on different chromosomes. Importantly, these transcriptional programs correspond to significant changes in brood size depending on the experienced stress. In addition, we demonstrate that while the observed seesaw gene expression changes occur in both somatic and germline tissue, only starvation-induced changes require a functional GLP-4 protein necessary for germline development, and both programs require the Argonaute CSR-1. Thus, our results suggest that signaling between the soma and the germ line can generate phenotypic plasticity as a result of early environmental experience, and likely contribute to increased fitness in adverse conditions and the evolution of the C. elegans genome. PMID:29447162

The Twist Box Domain is Required for Twist1-induced Prostate Cancer Metastasis

PubMed Central

Gajula, Rajendra P.; Chettiar, Sivarajan T.; Williams, Russell D.; Thiyagarajan, Saravanan; Kato, Yoshinori; Aziz, Khaled; Wang, Ruoqi; Gandhi, Nishant; Wild, Aaron T.; Vesuna, Farhad; Ma, Jinfang; Salih, Tarek; Cades, Jessica; Fertig, Elana; Biswal, Shyam; Burns, Timothy F.; Chung, Christine H.; Rudin, Charles M.; Herman, Joseph M.; Hales, Russell K.; Raman, Venu; An, Steven S.; Tran, Phuoc T.

2013-01-01

Twist1, a basic helix-loop-helix transcription factor, plays a key role during development and is a master regulator of the epithelial-mesenchymal transition (EMT) that promotes cancer metastasis. Structure-function relationships of Twist1 to cancer-related phenotypes are underappreciated, so we studied the requirement of the conserved Twist box domain for metastatic phenotypes in prostate cancer (PCa). Evidence suggests that Twist1 is overexpressed in clinical specimens and correlated with aggressive/metastatic disease. Therefore, we examined a transactivation mutant, Twist1-F191G, in PCa cells using in vitro assays which mimic various stages of metastasis. Twist1 overexpression led to elevated cytoskeletal stiffness and cell traction forces at the migratory edge of cells based on biophysical single-cell measurements. Twist1 conferred additional cellular properties associated with cancer cell metastasis including increased migration, invasion, anoikis resistance, and anchorage-independent growth. The Twist box mutant was defective for these Twist1 phenotypes in vitro. Importantly, we observed a high frequency of Twist1-induced metastatic lung tumors and extra-thoracic metastases in vivo using the experimental lung metastasis assay. The Twist box was required for PCa cells to colonize metastatic lung lesions and extra-thoracic metastases. Comparative genomic profiling revealed transcriptional programs directed by the Twist box that were associated with cancer progression, such as Hoxa9. Mechanistically, Twist1 bound to the Hoxa9 promoter and positively regulated Hoxa9 expression in PCa cells. Finally, Hoxa9 was important for Twist1-induced cellular phenotypes associated with metastasis. These data suggest that the Twist box domain is required for Twist1 transcriptional programs and PCa metastasis. PMID:23982216

Analysis of the function of E. coli 23S rRNA helix-loop 69 by mutagenesis

PubMed Central

Liiv, Aivar; Karitkina, Diana; Maiväli, Ülo; Remme, Jaanus

2005-01-01

Background The ribosome is a two-subunit enzyme known to exhibit structural dynamism during protein synthesis. The intersubunit bridges have been proposed to play important roles in decoding, translocation, and the peptidyl transferase reaction; yet the physical nature of their contributions is ill understood. An intriguing intersubunit bridge, B2a, which contains 23S rRNA helix 69 as a major component, has been implicated by proximity in a number of catalytically important regions. In addition to contacting the small ribosomal subunit, helix 69 contacts both the A and P site tRNAs and several translation factors. Results We scanned the loop of helix 69 by mutagenesis and analyzed the mutant ribosomes using a plasmid-borne IPTG-inducible expression system. We assayed the effects of 23S rRNA mutations on cell growth, contribution of mutant ribosomes to cellular polysome pools and the ability of mutant ribosomes to function in cell-free translation. Mutations A1912G, and A1919G have very strong growth phenotypes, are inactive during in vitro protein synthesis, and under-represented in the polysomes. Mutation Ψ1917C has a very strong growth phenotype and leads to a general depletion of the cellular polysome pool. Mutation A1916G, having a modest growth phenotype, is apparently defective in the assembly of the 70S ribosome. Conclusion Mutations A1912G, A1919G, and Ψ1917C of 23S rRNA strongly inhibit translation. Mutation A1916G causes a defect in the 50S subunit or 70S formation. Mutations Ψ1911C, A1913G, C1914A, Ψ1915C, and A1918G lack clear phenotypes. PMID:16053518