yeast ppi network: Topics by Science.gov

Sample records for yeast ppi network

Prior knowledge based mining functional modules from Yeast PPI networks with gene ontology

PubMed Central

2010-01-01

Background In the literature, there are fruitful algorithmic approaches for identification functional modules in protein-protein interactions (PPI) networks. Because of accumulation of large-scale interaction data on multiple organisms and non-recording interaction data in the existing PPI database, it is still emergent to design novel computational techniques that can be able to correctly and scalably analyze interaction data sets. Indeed there are a number of large scale biological data sets providing indirect evidence for protein-protein interaction relationships. Results The main aim of this paper is to present a prior knowledge based mining strategy to identify functional modules from PPI networks with the aid of Gene Ontology. Higher similarity value in Gene Ontology means that two gene products are more functionally related to each other, so it is better to group such gene products into one functional module. We study (i) to encode the functional pairs into the existing PPI networks; and (ii) to use these functional pairs as pairwise constraints to supervise the existing functional module identification algorithms. Topology-based modularity metric and complex annotation in MIPs will be used to evaluate the identified functional modules by these two approaches. Conclusions The experimental results on Yeast PPI networks and GO have shown that the prior knowledge based learning methods perform better than the existing algorithms. PMID:21172053
MCL-CAw: a refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

PubMed Central

2010-01-01

Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly
Detecting complexes from edge-weighted PPI networks via genes expression analysis.

PubMed

Zhang, Zehua; Song, Jian; Tang, Jijun; Xu, Xinying; Guo, Fei

2018-04-24

Identifying complexes from PPI networks has become a key problem to elucidate protein functions and identify signal and biological processes in a cell. Proteins binding as complexes are important roles of life activity. Accurate determination of complexes in PPI networks is crucial for understanding principles of cellular organization. We propose a novel method to identify complexes on PPI networks, based on different co-expression information. First, we use Markov Cluster Algorithm with an edge-weighting scheme to calculate complexes on PPI networks. Then, we propose some significant features, such as graph information and gene expression analysis, to filter and modify complexes predicted by Markov Cluster Algorithm. To evaluate our method, we test on two experimental yeast PPI networks. On DIP network, our method has Precision and F-Measure values of 0.6004 and 0.5528. On MIPS network, our method has F-Measure and S n values of 0.3774 and 0.3453. Comparing to existing methods, our method improves Precision value by at least 0.1752, F-Measure value by at least 0.0448, S n value by at least 0.0771. Experiments show that our method achieves better results than some state-of-the-art methods for identifying complexes on PPI networks, with the prediction quality improved in terms of evaluation criteria.
Integrative network alignment reveals large regions of global network similarity in yeast and human.

PubMed

Kuchaiev, Oleksii; Przulj, Natasa

2011-05-15

High-throughput methods for detecting molecular interactions have produced large sets of biological network data with much more yet to come. Analogous to sequence alignment, efficient and reliable network alignment methods are expected to improve our understanding of biological systems. Unlike sequence alignment, network alignment is computationally intractable. Hence, devising efficient network alignment heuristics is currently a foremost challenge in computational biology. We introduce a novel network alignment algorithm, called Matching-based Integrative GRAph ALigner (MI-GRAAL), which can integrate any number and type of similarity measures between network nodes (e.g. proteins), including, but not limited to, any topological network similarity measure, sequence similarity, functional similarity and structural similarity. Hence, we resolve the ties in similarity measures and find a combination of similarity measures yielding the largest contiguous (i.e. connected) and biologically sound alignments. MI-GRAAL exposes the largest functional, connected regions of protein-protein interaction (PPI) network similarity to date: surprisingly, it reveals that 77.7% of proteins in the baker's yeast high-confidence PPI network participate in such a subnetwork that is fully contained in the human high-confidence PPI network. This is the first demonstration that species as diverse as yeast and human contain so large, continuous regions of global network similarity. We apply MI-GRAAL's alignments to predict functions of un-annotated proteins in yeast, human and bacteria validating our predictions in the literature. Furthermore, using network alignment scores for PPI networks of different herpes viruses, we reconstruct their phylogenetic relationship. This is the first time that phylogeny is exactly reconstructed from purely topological alignments of PPI networks. Supplementary files and MI-GRAAL executables: http://bio-nets.doc.ic.ac.uk/MI-GRAAL/.
Identifying protein complexes in PPI network using non-cooperative sequential game.

PubMed

Maulik, Ujjwal; Basu, Srinka; Ray, Sumanta

2017-08-21

Identifying protein complexes from protein-protein interaction (PPI) network is an important and challenging task in computational biology as it helps in better understanding of cellular mechanisms in various organisms. In this paper we propose a noncooperative sequential game based model for protein complex detection from PPI network. The key hypothesis is that protein complex formation is driven by mechanism that eventually optimizes the number of interactions within the complex leading to dense subgraph. The hypothesis is drawn from the observed network property named small world. The proposed multi-player game model translates the hypothesis into the game strategies. The Nash equilibrium of the game corresponds to a network partition where each protein either belong to a complex or form a singleton cluster. We further propose an algorithm to find the Nash equilibrium of the sequential game. The exhaustive experiment on synthetic benchmark and real life yeast networks evaluates the structural as well as biological significance of the network partitions.
Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

PubMed

Shen, Xianjun; Yi, Li; Jiang, Xingpeng; He, Tingting; Yang, Jincai; Xie, Wei; Hu, Po; Hu, Xiaohua

2017-01-01

How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI) data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment). It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.
Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction.

PubMed

Stojanova, Daniela; Ceci, Michelangelo; Malerba, Donato; Dzeroski, Saso

2013-09-26

Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers. This article demonstrates the benefits (in terms of predictive accuracy) of considering autocorrelation in multi-class gene function prediction. We develop a tree-based algorithm for considering network autocorrelation in the setting of Hierarchical Multi-label Classification (HMC). We empirically evaluate the proposed algorithm, called NHMC (Network Hierarchical Multi-label Classification), on 12 yeast datasets using each of the MIPS-FUN and GO annotation schemes and exploiting 2 different PPI networks. The results clearly show that taking autocorrelation into account improves the predictive performance of the learned models for predicting gene function. Our newly developed method for HMC takes into account network information in the learning phase: When used for gene function
Network topological analysis reveals the functional cohesiveness for the newly discovered links by Yeast 2 Hybrid approach

NASA Astrophysics Data System (ADS)

Ghiassian, Susan; Pevzner, Sam; Rolland, Thomas; Tassan, Murat; Barabasi, Albert Laszlo; Vidal, Mark; CCNR, Northeastern University Collaboration; Dana Farber Cancer Institute Collaboration

2014-03-01

Protein-protein interaction maps and interactomes are the blueprint of Network Medicine and systems biology and are being experimentally studied by different groups. Despite the wide usage of Literature Curated Interactome (LCI), these sources are biased towards different parameters such as highly studied proteins. Yeast two hybrid method is a high throughput experimental setup which screens proteins in an unbiased fashion. Current knowledge of protein interactions is far from complete. In fact the previous offered data from Y2H method (2005), is estimated to offer only 5% of all potential protein interactions. Currently this coverage has increased to 20% of what is known as reference HI In this work we study the topological properties of Y2H protein-protein interactions network with LCI and show although they both agree on some properties, LCI shows a clear unbiased nature of interaction selections. Most importantly, we assess the properties of PPI as it evolves with increasing the coverage. We show that, the newly discovered interactions tend to connect proteins that have been closer than average in the previous PPI release. reinforcing the modular structure of PPI. Furthermore, we show, some unseen effects on PPI (as opposed to LCI) can be explained by its incompleteness.
Discovering functional interdependence relationship in PPI networks for protein complex identification.

PubMed

Lam, Winnie W M; Chan, Keith C C

2012-04-01

Protein molecules interact with each other in protein complexes to perform many vital functions, and different computational techniques have been developed to identify protein complexes in protein-protein interaction (PPI) networks. These techniques are developed to search for subgraphs of high connectivity in PPI networks under the assumption that the proteins in a protein complex are highly interconnected. While these techniques have been shown to be quite effective, it is also possible that the matching rate between the protein complexes they discover and those that are previously determined experimentally be relatively low and the "false-alarm" rate can be relatively high. This is especially the case when the assumption of proteins in protein complexes being more highly interconnected be relatively invalid. To increase the matching rate and reduce the false-alarm rate, we have developed a technique that can work effectively without having to make this assumption. The name of the technique called protein complex identification by discovering functional interdependence (PCIFI) searches for protein complexes in PPI networks by taking into consideration both the functional interdependence relationship between protein molecules and the network topology of the network. The PCIFI works in several steps. The first step is to construct a multiple-function protein network graph by labeling each vertex with one or more of the molecular functions it performs. The second step is to filter out protein interactions between protein pairs that are not functionally interdependent of each other in the statistical sense. The third step is to make use of an information-theoretic measure to determine the strength of the functional interdependence between all remaining interacting protein pairs. Finally, the last step is to try to form protein complexes based on the measure of the strength of functional interdependence and the connectivity between proteins. For performance evaluation
Reinforce: An Ensemble Approach for Inferring PPI Network from AP-MS Data.

PubMed

Tian, Bo; Duan, Qiong; Zhao, Can; Teng, Ben; He, Zengyou

2017-05-17

Affinity Purification-Mass Spectrometry (AP-MS) is one of the most important technologies for constructing protein-protein interaction (PPI) networks. In this paper, we propose an ensemble method, Reinforce, for inferring PPI network from AP-MS data set. The new algorithm named Reinforce is based on rank aggregation and false discovery rate control. Under the null hypothesis that the interaction scores from different scoring methods are randomly generated, Reinforce follows three steps to integrate multiple ranking results from different algorithms or different data sets. The experimental results show that Reinforce can get more stable and accurate inference results than existing algorithms. The source codes of Reinforce and data sets used in the experiments are available at: https://sourceforge.net/projects/reinforce/.
MPact: the MIPS protein interaction resource on yeast.

PubMed

Güldener, Ulrich; Münsterkötter, Martin; Oesterheld, Matthias; Pagel, Philipp; Ruepp, Andreas; Mewes, Hans-Werner; Stümpflen, Volker

2006-01-01

In recent years, the Munich Information Center for Protein Sequences (MIPS) yeast protein-protein interaction (PPI) dataset has been used in numerous analyses of protein networks and has been called a gold standard because of its quality and comprehensiveness [H. Yu, N. M. Luscombe, H. X. Lu, X. Zhu, Y. Xia, J. D. Han, N. Bertin, S. Chung, M. Vidal and M. Gerstein (2004) Genome Res., 14, 1107-1118]. MPact and the yeast protein localization catalog provide information related to the proximity of proteins in yeast. Beside the integration of high-throughput data, information about experimental evidence for PPIs in the literature was compiled by experts adding up to 4300 distinct PPIs connecting 1500 proteins in yeast. As the interaction data is a complementary part of CYGD, interactive mapping of data on other integrated data types such as the functional classification catalog [A. Ruepp, A. Zollner, D. Maier, K. Albermann, J. Hani, M. Mokrejs, I. Tetko, U. Güldener, G. Mannhaupt, M. Münsterkötter and H. W. Mewes (2004) Nucleic Acids Res., 32, 5539-5545] is possible. A survey of signaling proteins and comparison with pathway data from KEGG demonstrates that based on these manually annotated data only an extensive overview of the complexity of this functional network can be obtained in yeast. The implementation of a web-based PPI-analysis tool allows analysis and visualization of protein interaction networks and facilitates integration of our curated data with high-throughput datasets. The complete dataset as well as user-defined sub-networks can be retrieved easily in the standardized PSI-MI format. The resource can be accessed through http://mips.gsf.de/genre/proj/mpact.
Completing sparse and disconnected protein-protein network by deep learning.

PubMed

Huang, Lei; Liao, Li; Wu, Cathy H

2018-03-22

Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of cellular and intracellular processes. Recently, an increasing number of computational methods have shifted from pair-wise prediction to network level prediction. Many of the existing network level methods predict PPIs under the assumption that the training network should be connected. However, this assumption greatly affects the prediction power and limits the application area because the current golden standard PPI networks are usually very sparse and disconnected. Therefore, how to effectively predict PPIs based on a training network that is sparse and disconnected remains a challenge. In this work, we developed a novel PPI prediction method based on deep learning neural network and regularized Laplacian kernel. We use a neural network with an autoencoder-like architecture to implicitly simulate the evolutionary processes of a PPI network. Neurons of the output layer correspond to proteins and are labeled with values (1 for interaction and 0 for otherwise) from the adjacency matrix of a sparse disconnected training PPI network. Unlike autoencoder, neurons at the input layer are given all zero input, reflecting an assumption of no a priori knowledge about PPIs, and hidden layers of smaller sizes mimic ancient interactome at different times during evolution. After the training step, an evolved PPI network whose rows are outputs of the neural network can be obtained. We then predict PPIs by applying the regularized Laplacian kernel to the transition matrix that is built upon the evolved PPI network. The results from cross-validation experiments show that the PPI prediction accuracies for yeast data and human data measured as AUC are increased by up to 8.4 and 14.9% respectively, as compared to the baseline. Moreover, the evolved PPI network can also help us leverage complementary information from the disconnected training network
Protein complex prediction in large ontology attributed protein-protein interaction networks.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

2013-01-01

Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.
The OncoPPi network of cancer-focused protein-protein interactions to inform biological insights and therapeutic strategies* | Office of Cancer Genomics

Cancer.gov

As genomics advances reveal the cancer gene landscape, a daunting task is to understand how these genes contribute to dysregulated oncogenic pathways. Integration of cancer genes into networks offers opportunities to reveal protein–protein interactions (PPIs) with functional and therapeutic significance. Here, we report the generation of a cancer-focused PPI network, termed OncoPPi, and identification of >260 cancer-associated PPIs not in other large-scale interactomes.
Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481
Yeast-assisted synthesis of polypyrrole: Quantification and influence on the mechanical properties of the cell wall.

PubMed

Andriukonis, Eivydas; Stirke, Arunas; Garbaras, Andrius; Mikoliunaite, Lina; Ramanaviciene, Almira; Remeikis, Vidmantas; Thornton, Barry; Ramanavicius, Arunas

2018-04-01

In this study, the metabolism of yeast cells (Saccharomyces cerevisiae) was utilized for the synthesis of the conducting polymer - polypyrrole (Ppy).Yeast cells were modified in situ by synthesized Ppy. The Ppy was formed in the cell wall by redox-cycling of [Fe(CN) 6 ] 3-/4- , performed by the yeast cells. Fluorescence microscopy, enzymatic digestions, atomic force microscopy and isotope ratio mass spectroscopy were applied to determine both the polymerization reaction itself and the polymer location in yeast cells. Ppy formation resulted in enhanced resistance to lytic enzymes, significant increase of elasticity and alteration of other mechanical cell wall properties evaluated by atomic force microscopy (AFM). The suggested method of polymer synthesis allows the introduction of polypyrrole structures within the cell wall, which is build up from polymers consisting of carbohydrates. This cell wall modification strategy could increase the usefulness of yeast as an alternative energy source in biofuel cells, and in cell based biosensors. Copyright © 2018 Elsevier B.V. All rights reserved.
Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.
Effects of the PPy layer thickness on Co-PPy composite films

NASA Astrophysics Data System (ADS)

Haciismailoglu, Murside

2015-11-01

Co-PPy composite films were electrodeposited on ITO substrate from two different solutions potentiostatically. Firstly, the PPy layers with the thicknesses changing from 20 to 5000 nm were produced on ITO. Then Co was electrodeposited on these PPy/ITO substrates with a charge density of 1000 mC cm-2. The electrochemical properties were investigated by the current density-time transients and the variation of the elapsed time for the Co deposition depending on the PPy layer thickness. X-ray photoelectron (XPS) spectra indicated the presence of both Co metal and its oxides on the surface. The weak reflections of the Co3O4, CoO and hcp Co were detected by the X-ray diffraction (XRD) technique. According to scanning electron microscopy (SEM) images, the thickness of the PPy layer strongly affects the Co nucleation. The composite films with the PPy layer thinner than 200 nm and thicker than 2000 nm have an isotropic magnetic behavior due to the symmetrical crystal field. The composite films with the PPy layer thicknesses between 200 and 2000 nm have an anisotropic magnetic behavior attributable to the deterioration of this symmetrical crystal field by the PPy bubbles on the surface. All films are hard magnetic material, since the coercivities are larger than 125 Oe.
Global Mapping of the Yeast Genetic Interaction Network

NASA Astrophysics Data System (ADS)

Tong, Amy Hin Yan; Lesage, Guillaume; Bader, Gary D.; Ding, Huiming; Xu, Hong; Xin, Xiaofeng; Young, James; Berriz, Gabriel F.; Brost, Renee L.; Chang, Michael; Chen, YiQun; Cheng, Xin; Chua, Gordon; Friesen, Helena; Goldberg, Debra S.; Haynes, Jennifer; Humphries, Christine; He, Grace; Hussein, Shamiza; Ke, Lizhu; Krogan, Nevan; Li, Zhijian; Levinson, Joshua N.; Lu, Hong; Ménard, Patrice; Munyana, Christella; Parsons, Ainslie B.; Ryan, Owen; Tonikian, Raffi; Roberts, Tania; Sdicu, Anne-Marie; Shapiro, Jesse; Sheikh, Bilal; Suter, Bernhard; Wong, Sharyl L.; Zhang, Lan V.; Zhu, Hongwei; Burd, Christopher G.; Munro, Sean; Sander, Chris; Rine, Jasper; Greenblatt, Jack; Peter, Matthias; Bretscher, Anthony; Bell, Graham; Roth, Frederick P.; Brown, Grant W.; Andrews, Brenda; Bussey, Howard; Boone, Charles

2004-02-01

A genetic interaction network containing ~1000 genes and ~4000 interactions was mapped by crossing mutations in 132 different query genes into a set of ~4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.
Identifying essential proteins based on sub-network partition and prioritization by integrating subcellular localization information.

PubMed

Li, Min; Li, Wenkai; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

2018-06-14

Essential proteins are important participants in various life activities and play a vital role in the survival and reproduction of living organisms. Identification of essential proteins from protein-protein interaction (PPI) networks has great significance to facilitate the study of human complex diseases, the design of drugs and the development of bioinformatics and computational science. Studies have shown that highly connected proteins in a PPI network tend to be essential. A series of computational methods have been proposed to identify essential proteins by analyzing topological structures of PPI networks. However, the high noise in the PPI data can degrade the accuracy of essential protein prediction. Moreover, proteins must be located in the appropriate subcellular localization to perform their functions, and only when the proteins are located in the same subcellular localization, it is possible that they can interact with each other. In this paper, we propose a new network-based essential protein discovery method based on sub-network partition and prioritization by integrating subcellular localization information, named SPP. The proposed method SPP was tested on two different yeast PPI networks obtained from DIP database and BioGRID database. The experimental results show that SPP can effectively reduce the effect of false positives in PPI networks and predict essential proteins more accurately compared with other existing computational methods DC, BC, CC, SC, EC, IC, NC. Copyright © 2018 Elsevier Ltd. All rights reserved.

Synthesis of polypyrrole within the cell wall of yeast by redox-cycling of [Fe(CN)6](3-)/[Fe(CN)6](4-).

PubMed

Ramanavicius, Arunas; Andriukonis, Eivydas; Stirke, Arunas; Mikoliunaite, Lina; Balevicius, Zigmas; Ramanaviciene, Almira

2016-02-01

Yeast cells are often used as a model system in various experiments. Moreover, due to their high metabolic activity, yeast cells have a potential to be applied as elements in the design of biofuel cells and biosensors. However a wider application of yeast cells in electrochemical systems is limited due to high electric resistance of their cell wall. In order to reduce this problem we have polymerized conducting polymer polypyrrole (Ppy) directly in the cell wall and/or within periplasmic membrane. In this research the formation of Ppy was induced by [Fe(CN)6](3-)ions, which were generated from K4[Fe(CN)6], which was initially added to polymerization solution. The redox process was catalyzed by oxido-reductases, which are present in the plasma membrane of yeast cells. The formation of Ppy was confirmed by spectrophotometry and atomic force microscopy. It was confirmed that the conducting polymer polypyrrole was formed within periplasmic space and/or within the cell wall of yeast cells, which were incubated in solution containing pyrrole, glucose and [Fe(CN)6](4-). After 24h drying at room temperature we have observed that Ppy-modified yeast cell walls retained their initial spherical form. In contrast to Ppy-modified cells, the walls of unmodified yeast have wrinkled after 24h drying. The viability of yeast cells in the presence of different pyrrole concentrations has been evaluated. Copyright © 2015 Elsevier Inc. All rights reserved.
GraphCrunch 2: Software tool for network modeling, alignment and clustering.

PubMed

Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

algorithm for clustering nodes within a network based solely on their topological similarities. Using GraphCrunch 2, we demonstrate that eukaryotic and viral PPI networks may belong to different graph model families and show that topology-based clustering can reveal important functional similarities between proteins within yeast and human PPI networks. GraphCrunch 2 is a software tool that implements the latest research on biological network analysis. It parallelizes computationally intensive tasks to fully utilize the potential of modern multi-core CPUs. It is open-source and freely available for research use. It runs under the Windows and Linux platforms.
Water-network percolation transitions in hydrated yeast

NASA Astrophysics Data System (ADS)

Sokołowska, Dagmara; Król-Otwinowska, Agnieszka; Mościcki, Józef K.

2004-11-01

We discovered two percolation processes in succession in dc conductivity of bulk baker’s yeast in the course of dehydration. Critical exponents characteristic for the three-dimensional network for heavily hydrated system, and two dimensions in the light hydration limit, evidenced a dramatic change of the water network dimensionality in the dehydration process.
Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273
A Proteome-wide Fission Yeast Interactome Reveals Network Evolution Principles from Yeasts to Human.

PubMed

Vo, Tommy V; Das, Jishnu; Meyer, Michael J; Cordero, Nicolas A; Akturk, Nurten; Wei, Xiaomu; Fair, Benjamin J; Degatano, Andrew G; Fragoza, Robert; Liu, Lisa G; Matsuyama, Akihisa; Trickey, Michelle; Horibata, Sachi; Grimson, Andrew; Yamano, Hiroyuki; Yoshida, Minoru; Roth, Frederick P; Pleiss, Jeffrey A; Xia, Yu; Yu, Haiyuan

2016-01-14

Here, we present FissionNet, a proteome-wide binary protein interactome for S. pombe, comprising 2,278 high-quality interactions, of which ∼ 50% were previously not reported in any species. FissionNet unravels previously unreported interactions implicated in processes such as gene silencing and pre-mRNA splicing. We developed a rigorous network comparison framework that accounts for assay sensitivity and specificity, revealing extensive species-specific network rewiring between fission yeast, budding yeast, and human. Surprisingly, although genes are better conserved between the yeasts, S. pombe interactions are significantly better conserved in human than in S. cerevisiae. Our framework also reveals that different modes of gene duplication influence the extent to which paralogous proteins are functionally repurposed. Finally, cross-species interactome mapping demonstrates that coevolution of interacting proteins is remarkably prevalent, a result with important implications for studying human disease in model organisms. Overall, FissionNet is a valuable resource for understanding protein functions and their evolution. Copyright © 2016 Elsevier Inc. All rights reserved.
Dynamical analysis of yeast protein interaction network during the sake brewing process.

PubMed

Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

2011-12-01

Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.
Functional complementation of yeast cytosolic pyrophosphatase by bacterial and plant H+-translocating pyrophosphatases.

PubMed

Perez-Castineira, Jose R; Lopez-Marques, Rosa L; Villalba, Jose M; Losada, Manuel; Serrano, Aurelio

2002-12-10

Two types of proteins that hydrolyze inorganic pyrophosphate (PPi), very different in both amino acid sequence and structure, have been characterized to date: soluble and membrane-bound proton-pumping pyrophosphatases (sPPases and H(+)-PPases, respectively). sPPases are ubiquitous proteins that hydrolyze PPi releasing heat, whereas H+-PPases, so far unidentified in animal and fungal cells, couple the energy of PPi hydrolysis to proton movement across biological membranes. The budding yeast Saccharomyces cerevisiae has two sPPases that are located in the cytosol and in the mitochondria. Previous attempts to knock out the gene coding for a cytosolic sPPase (IPP1) have been unsuccessful, thus suggesting that this protein is essential for growth. Here, we describe the generation of a conditional S. cerevisiae mutant (named YPC-1) whose functional IPP1 gene is under the control of a galactose-dependent promoter. Thus, YPC-1 cells become growth arrested in glucose but they regain the ability to grow on this carbon source when transformed with autonomous plasmids bearing diverse foreign H+-PPase genes under the control of a yeast constitutive promoter. The heterologously expressed H+-PPases are distributed among different yeast membranes, including the plasma membrane, functional complementation by these integral membrane proteins being consistently sensitive to external pH. These results demonstrate that hydrolysis of cytosolic PPi is essential for yeast growth and that this function is not substantially affected by the intrinsic characteristics of the PPase protein that accomplishes it. Moreover, this is, to our knowledge, the first direct evidence that H+-PPases can mediate net hydrolysis of PPi in vivo. YPC-1 mutant strain constitutes a convenient expression system to perform studies aimed at the elucidation of the structure-function relationships of this type of proton pumps.
The autophagy interaction network of the aging model Podospora anserina.

PubMed

Philipp, Oliver; Hamann, Andrea; Osiewacz, Heinz D; Koch, Ina

2017-03-27

Autophagy is a conserved molecular pathway involved in the degradation and recycling of cellular components. It is active either as response to starvation or molecular damage. Evidence is emerging that autophagy plays a key role in the degradation of damaged cellular components and thereby affects aging and lifespan control. In earlier studies, it was found that autophagy in the aging model Podospora anserina acts as a longevity assurance mechanism. However, only little is known about the individual components controlling autophagy in this aging model. Here, we report a biochemical and bioinformatics study to detect the protein-protein interaction (PPI) network of P. anserina combining experimental and theoretical methods. We constructed the PPI network of autophagy in P. anserina based on the corresponding networks of yeast and human. We integrated PaATG8 interaction partners identified in an own yeast two-hybrid analysis using ATG8 of P. anserina as bait. Additionally, we included age-dependent transcriptome data. The resulting network consists of 89 proteins involved in 186 interactions. We applied bioinformatics approaches to analyze the network topology and to prove that the network is not random, but exhibits biologically meaningful properties. We identified hub proteins which play an essential role in the network as well as seven putative sub-pathways, and interactions which are likely to be evolutionary conserved amongst species. We confirmed that autophagy-associated genes are significantly often up-regulated and co-expressed during aging of P. anserina. With the present study, we provide a comprehensive biological network of the autophagy pathway in P. anserina comprising PPI and gene expression data. It is based on computational prediction as well as experimental data. We identified sub-pathways, important hub proteins, and evolutionary conserved interactions. The network clearly illustrates the relation of autophagy to aging processes and enables
The role of HiPPI switches in mass storage systems: A five year prospective

NASA Technical Reports Server (NTRS)

Gilbert, T. A.

1992-01-01

New standards are evolving which provide the foundation for novel multi-gigabit per second data communication structures. The lowest layer protocols are so generalized that they encourage a wide range of application. Specifically, the ANSI High Performance Parallel Interface (HiPPI) is being applied to computer peripheral attachment as well as general data communication networks. This paper introduces the HiPPI standards suite and technology products which incorporate the standards. The use of simple HiPPI crosspoint switches to build potentially complex extended 'fabrics' is discussed in detail. Several near term applications of the HiPPI technology are briefly described with additional attention to storage systems. Finally, some related standards are mentioned which may further expand the concepts above.
The role of HiPPI switches in mass storage systems: A five year prospective

NASA Technical Reports Server (NTRS)

Gilbert, T. A.

1991-01-01

New standards are evolving which provide the foundation for multi-gigabit per second data communication structures. The lowest layer protocols are so generalized that they encourage a wide range of application. Specifically, the ANSI High Performance Parallel Interface (HiPPI) is being applied to computer peripheral attachment as well as general data communication networks. The HiPPI Standards suite and technology products which incorporate the standards are introduced. The use of simple HiPPI crosspoint switches to build potentially complex extended 'fabrics' is discussed in detail. Several near term applications of the HiPPI technology are briefly described with additional attention to storage systems. Finally, some related standards are mentioned which may further expand the concepts above.
Highly efficient near ultraviolet organic light-emitting diode based on a meta-linked donor–acceptor molecule† †Electronic supplementary information (ESI) available: The details of the synthesis; the ground state and excited state geometries in PPI, TPA–PPI and mTPA–PPI; absorption and emission properties of PPI, TPA–PPI and mTPA–PPI in the gas phase; detailed absorption peak positions, emission peak positions and ηPL values of PPI and mTPA–PPI in different solvents; HOMO and LUMO of mTPA–PPI at ground state; NTO for the S0 → S1 absorption transition in PPI, TPA–PPI and mTPA–PPI; NTO for S0 → Sn electronic transition character in mTPA–PPI; lifetime measurement, radiative transition rates and non-radiative transition rates of PPI and mTPA–PPI in hexane and THF solutions; low-temperature fluorescence and phosphorescence spectra of PPI and mTPA–PPI; CV curves of PPI and mTPA–PPI, and schematic diagram of design principle of mTPA–PPI; TGA and DSC graphs of PPI and mTPA–PPI; current efficiency–current density–power efficiency curves and EL spectra at different driving voltages of PPI and mTPA–PPI devices. See DOI: 10.1039/c5sc01131k

PubMed Central

Liu, Haichao; Bai, Qing; Yao, Liang; Zhang, Haiyan; Xu, Hai; Zhang, Shitong; Li, Weijun; Gao, Yu; Li, Jinyu; Lu, Ping; Wang, Hongyan; Ma, Yuguang

2015-01-01

A novel near ultraviolet (NUV) emitter with a meta-linked donor–acceptor (D–A) structure between triphenylamine (TPA) and phenanthroimidazole (PPI), mTPA–PPI, was designed and synthesized. This molecular design is expected to resolve the conflict between the non-red-shifted emission and the introduction of a charge-transfer (CT) state in the D–A system, aiming at NUV organic light-emitting diodes (OLEDs) with high-efficiency and colour-purity. Theoretical calculations and photophysical experiments were implemented to verify the unique excited state properties of mTPA–PPI. The mTPA–PPI device exhibited excellent NUV electroluminescence (EL) performance with an emission peak at 404 nm, a full width at half maximum (FWHM) of only 47 nm corresponding to a CIE coordinate of (0.161, 0.049), and a maximum external quantum efficiency (EQE) of 3.33%, which is among the best results for NUV OLEDs. This work not only demonstrates the promising potential of mTPA–PPI in NUV OLEDs, but also provides a valuable strategy for the rational design of NUV materials by using the meta-linked D–A architecture. PMID:29218149
Development and application of a DNA microarray-based yeast two-hybrid system

PubMed Central

Suter, Bernhard; Fontaine, Jean-Fred; Yildirimman, Reha; Raskó, Tamás; Schaefer, Martin H.; Rasche, Axel; Porras, Pablo; Vázquez-Álvarez, Blanca M.; Russ, Jenny; Rau, Kirstin; Foulle, Raphaele; Zenkner, Martina; Saar, Kathrin; Herwig, Ralf; Andrade-Navarro, Miguel A.; Wanker, Erich E.

2013-01-01

The yeast two-hybrid (Y2H) system is the most widely applied methodology for systematic protein–protein interaction (PPI) screening and the generation of comprehensive interaction networks. We developed a novel Y2H interaction screening procedure using DNA microarrays for high-throughput quantitative PPI detection. Applying a global pooling and selection scheme to a large collection of human open reading frames, proof-of-principle Y2H interaction screens were performed for the human neurodegenerative disease proteins huntingtin and ataxin-1. Using systematic controls for unspecific Y2H results and quantitative benchmarking, we identified and scored a large number of known and novel partner proteins for both huntingtin and ataxin-1. Moreover, we show that this parallelized screening procedure and the global inspection of Y2H interaction data are uniquely suited to define specific PPI patterns and their alteration by disease-causing mutations in huntingtin and ataxin-1. This approach takes advantage of the specificity and flexibility of DNA microarrays and of the existence of solid-related statistical methods for the analysis of DNA microarray data, and allows a quantitative approach toward interaction screens in human and in model organisms. PMID:23275563
Embedded Carbide-derived Carbon (CDC) particles in polypyrrole (PPy) for linear actuator

NASA Astrophysics Data System (ADS)

Zondaka, Zane; Valner, Robert; Aabloo, Alvo; Tamm, Tarmo; Kiefer, Rudolf

2016-04-01

Conducting polymer linear actuators, for example sodium dodecylbenzenesulfonate (NaDBS) doped polypyrrole (PPy/DBS), have shown moderate strain and stress. The goal of this work was to increase the obtainable strain and stress by adding additional active material to PPy/DBS. In recent year's carbide-derived carbon (CDC)-based materials have been applied in actuators; however, the obtained displacement and actuation speed has been low comparing to conducting polymer based actuators. In the present work, a CDC-PPy hybrid was synthesized electrochemically and polyoxometalate (POM) - phosphotungstic acid - was used to attach charge to CDC particles. The CDC-POM served in the presence of NaDBS as an additional electrolyte. Cyclic voltammetry and chronopotentiometric electrochemomechanical deformation (ECMD) measurements were performed in Lithium bis(trifluoromethanesulfonyl)- imide (LiTFSI) aqueous electrolyte. The ECMD measurements revealed that the hybrid CDC-PPy material exhibited higher force and strain in comparison to PPy/DBS films. The new material was investigated by scanning electron microscopy (SEM) to evaluate CDC particle embedding in the polymer network.
Version 6 of the consensus yeast metabolic network refines biochemical coverage and improves model performance

PubMed Central

Heavner, Benjamin D.; Smallbone, Kieran; Price, Nathan D.; Walker, Larry P.

2013-01-01

Updates to maintain a state-of-the art reconstruction of the yeast metabolic network are essential to reflect our understanding of yeast metabolism and functional organization, to eliminate any inaccuracies identified in earlier iterations, to improve predictive accuracy and to continue to expand into novel subsystems to extend the comprehensiveness of the model. Here, we present version 6 of the consensus yeast metabolic network (Yeast 6) as an update to the community effort to computationally reconstruct the genome-scale metabolic network of Saccharomyces cerevisiae S288c. Yeast 6 comprises 1458 metabolites participating in 1888 reactions, which are annotated with 900 yeast genes encoding the catalyzing enzymes. Compared with Yeast 5, Yeast 6 demonstrates improved sensitivity, specificity and positive and negative predictive values for predicting gene essentiality in glucose-limited aerobic conditions when analyzed with flux balance analysis. Additionally, Yeast 6 improves the accuracy of predicting the likelihood that a mutation will cause auxotrophy. The network reconstruction is available as a Systems Biology Markup Language (SBML) file enriched with Minimium Information Requested in the Annotation of Biochemical Models (MIRIAM)-compliant annotations. Small- and macromolecules in the network are referenced to authoritative databases such as Uniprot or ChEBI. Molecules and reactions are also annotated with appropriate publications that contain supporting evidence. Yeast 6 is freely available at http://yeast.sf.net/ as three separate SBML files: a model using the SBML level 3 Flux Balance Constraint package, a model compatible with the MATLAB® COBRA Toolbox for backward compatibility and a reconstruction containing only reactions for which there is experimental evidence (without the non-biological reactions necessary for simulating growth). Database URL: http://yeast.sf.net/ PMID:23935056
Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns

DOE PAGES

Tian, Wenhong; Samatova, Nagiza F.

2013-01-01

A number of tools for the alignment of protein-protein interaction (PPI) networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based onmore » a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast) and D. melanogaster (fly), E. coli K12 and S. typhimurium , E. coli K12 and C. crescenttus , we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO), and KEGG ortholog groups (KO). Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily.« less
An Improved, Bias-Reduced Probabilistic Functional Gene Network of Baker's Yeast, Saccharomyces cerevisiae

PubMed Central

Lee, Insuk; Li, Zhihua; Marcotte, Edward M.

2007-01-01

Background Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding specific gene functions and associations. Methodology/Principal Findings We report a significantly improved version (v. 2) of a probabilistic functional gene network [1] of the baker's yeast, Saccharomyces cerevisiae. We describe our optimization methods and illustrate their effects in three major areas: the reduction of functional bias in network training reference sets, the application of a probabilistic model for calculating confidences in pair-wise protein physical or genetic interactions, and the introduction of simple thresholds that eliminate many false positive mRNA co-expression relationships. Using the network, we predict and experimentally verify the function of the yeast RNA binding protein Puf6 in 60S ribosomal subunit biogenesis. Conclusions/Significance YeastNet v. 2, constructed using these optimizations together with additional data, shows significant reduction in bias and improvements in precision and recall, in total covering 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome). YeastNet is available from http://www.yeastnet.org. PMID:17912365
Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

PubMed Central

Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

2014-01-01

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891
Electrochemical and XPS study of LiFePO4 cathode nanocomposite with PPy/PEG conductive network

NASA Astrophysics Data System (ADS)

Fedorková, A.; Oriňáková, R.; Oriňák, A.; Kupková, M.; Wiemhöfer, H.-D.; Audinot, J. N.; Guillot, J.

2012-08-01

High performance PPy/PEG-LiFePO4 nanocomposites as cathode materials were synthesized by solvothermal method and simple chemical oxidative polymerization of pyrrole (Py) monomer on the surface of LiFePO4 particles. The samples were characterized by scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectrometry (XPS) and charge-discharge tests. PPyPEG hybrid layers decrease particle to particle contact resistance while the impedance measurements confirmed that the coating of PPy-PEG significantly decreases the charge transfer resistance of the electrode material. The initial discharge capacities of this sample at C/5 and 1C are 150 and 128 mAh/g, respectively. The results show that PPy/PEGLiFePO4 composites are more effective than bare LiFePO4 as cathode material.
Network thermodynamic curation of human and yeast genome-scale metabolic models.

PubMed

Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

2014-07-15

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.
A protein interaction network analysis for yeast integral membrane protein.

PubMed

Shi, Ming-Guang; Huang, De-Shuang; Li, Xue-Ling

2008-01-01

Although the yeast Saccharomyces cerevisiae is the best exemplified single-celled eukaryote, the vast number of protein-protein interactions of integral membrane proteins of Saccharomyces cerevisiae have not been characterized by experiments. Here, based on the kernel method of Greedy Kernel Principal Component analysis plus Linear Discriminant Analysis, we identify 300 protein-protein interactions involving 189 membrane proteins and get the outcome of a highly connected protein-protein interactions network. Furthermore, we study the global topological features of integral membrane proteins network of Saccharomyces cerevisiae. These results give the comprehensive description of protein-protein interactions of integral membrane proteins and reveal global topological and robustness of the interactome network at a system level. This work represents an important step towards a comprehensive understanding of yeast protein interactions.

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed Central

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-01-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. PMID:21666777
PPI, paradoxes and Plato: who's sailing the ship?

PubMed

Ives, Jonathan; Damery, Sarah; Redwod, Sabi

2013-03-01

Over the last decade, patient and public involvement (PPI) has become a requisite in applied health research. Some funding bodies demand explicit evidence of PPI, while others have made a commitment to developing PPI in the projects they fund. Despite being commonplace, there remains a dearth of engagement with the ethical and theoretical underpinnings of PPI processes and practices. More specifically, while there is a small (but growing) body of literature examining the effectiveness and impact of PPI, there has been relatively little reflection on whether the concept/practice of PPI is internally coherent. Here, the authors unpick a 'paradox' within PPI, which highlights a tension between its moral and pragmatic motivations and its implementation. The authors argue that this 'professionalisation paradox' means we need to rethink the practice, and purpose, of PPI in research.
L-GRAAL: Lagrangian graphlet-based network aligner.

PubMed

Malod-Dognin, Noël; Pržulj, Nataša

2015-07-01

Discovering and understanding patterns in networks of protein-protein interactions (PPIs) is a central problem in systems biology. Alignments between these networks aid functional understanding as they uncover important information, such as evolutionary conserved pathways, protein complexes and functional orthologs. A few methods have been proposed for global PPI network alignments, but because of NP-completeness of underlying sub-graph isomorphism problem, producing topologically and biologically accurate alignments remains a challenge. We introduce a novel global network alignment tool, Lagrangian GRAphlet-based ALigner (L-GRAAL), which directly optimizes both the protein and the interaction functional conservations, using a novel alignment search heuristic based on integer programming and Lagrangian relaxation. We compare L-GRAAL with the state-of-the-art network aligners on the largest available PPI networks from BioGRID and observe that L-GRAAL uncovers the largest common sub-graphs between the networks, as measured by edge-correctness and symmetric sub-structures scores, which allow transferring more functional information across networks. We assess the biological quality of the protein mappings using the semantic similarity of their Gene Ontology annotations and observe that L-GRAAL best uncovers functionally conserved proteins. Furthermore, we introduce for the first time a measure of the semantic similarity of the mapped interactions and show that L-GRAAL also uncovers best functionally conserved interactions. In addition, we illustrate on the PPI networks of baker's yeast and human the ability of L-GRAAL to predict new PPIs. Finally, L-GRAAL's results are the first to show that topological information is more important than sequence information for uncovering functionally conserved interactions. L-GRAAL is coded in C++. Software is available at: http://bio-nets.doc.ic.ac.uk/L-GRAAL/. n.malod-dognin@imperial.ac.uk Supplementary data are available at
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
Computational architecture of the yeast regulatory network

NASA Astrophysics Data System (ADS)

Maslov, Sergei; Sneppen, Kim

2005-12-01

The topology of regulatory networks contains clues to their overall design principles and evolutionary history. We find that while in- and out-degrees of a given protein in the regulatory network are not correlated with each other, there exists a strong negative correlation between the out-degree of a regulatory protein and in-degrees of its targets. Such correlation positions large regulatory modules on the periphery of the network and makes them rather well separated from each other. We also address the question of relative importance of different classes of proteins quantified by the lethality of null-mutants lacking one of them as well as by the level of their evolutionary conservation. It was found that in the yeast regulatory network highly connected proteins are in fact less important than their low-connected counterparts.
OncoPPi-informed discovery of mitogen-activated protein kinase kinase 3 as a novel binding partner of c-Myc | Office of Cancer Genomics

Cancer.gov

Mitogen-activated protein kinase kinase 3 (MKK3) is a dual threonine/tyrosine protein kinase that regulates inflammation, proliferation and apoptosis through specific phosphorylation and activation of the p38 mitogen-activated protein kinase. However, the role of MKK3 beyond p38-signaling remains elusive. Recently, we reported a protein-protein interaction (PPI) network of cancer-associated genes, termed OncoPPi, as a resource for the scientific community to generate new biological models. Analysis of the OncoPPi connectivity identified MKK3 as one of the major hub proteins in the network.
Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-06-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. © 2011 Elsevier Ltd. All rights reserved.
Discovering protein complexes in protein interaction networks via exploring the weak ties effect

PubMed Central

2012-01-01

Background Studying protein complexes is very important in biological processes since it helps reveal the structure-functionality relationships in biological networks and much attention has been paid to accurately predict protein complexes from the increasing amount of protein-protein interaction (PPI) data. Most of the available algorithms are based on the assumption that dense subgraphs correspond to complexes, failing to take into account the inherence organization within protein complex and the roles of edges. Thus, there is a critical need to investigate the possibility of discovering protein complexes using the topological information hidden in edges. Results To provide an investigation of the roles of edges in PPI networks, we show that the edges connecting less similar vertices in topology are more significant in maintaining the global connectivity, indicating the weak ties phenomenon in PPI networks. We further demonstrate that there is a negative relation between the weak tie strength and the topological similarity. By using the bridges, a reliable virtual network is constructed, in which each maximal clique corresponds to the core of a complex. By this notion, the detection of the protein complexes is transformed into a classic all-clique problem. A novel core-attachment based method is developed, which detects the cores and attachments, respectively. A comprehensive comparison among the existing algorithms and our algorithm has been made by comparing the predicted complexes against benchmark complexes. Conclusions We proved that the weak tie effect exists in the PPI network and demonstrated that the density is insufficient to characterize the topological structure of protein complexes. Furthermore, the experimental results on the yeast PPI network show that the proposed method outperforms the state-of-the-art algorithms. The analysis of detected modules by the present algorithm suggests that most of these modules have well biological significance in
Development and application of a recombination-based library versus library high- throughput yeast two-hybrid (RLL-Y2H) screening system.

PubMed

Yang, Fang; Lei, Yingying; Zhou, Meiling; Yao, Qili; Han, Yichao; Wu, Xiang; Zhong, Wanshun; Zhu, Chenghang; Xu, Weize; Tao, Ran; Chen, Xi; Lin, Da; Rahman, Khaista; Tyagi, Rohit; Habib, Zeshan; Xiao, Shaobo; Wang, Dang; Yu, Yang; Chen, Huanchun; Fu, Zhenfang; Cao, Gang

2018-02-16

Protein-protein interaction (PPI) network maintains proper function of all organisms. Simple high-throughput technologies are desperately needed to delineate the landscape of PPI networks. While recent state-of-the-art yeast two-hybrid (Y2H) systems improved screening efficiency, either individual colony isolation, library preparation arrays, gene barcoding or massive sequencing are still required. Here, we developed a recombination-based 'library vs library' Y2H system (RLL-Y2H), by which multi-library screening can be accomplished in a single pool without any individual treatment. This system is based on the phiC31 integrase-mediated integration between bait and prey plasmids. The integrated fragments were digested by MmeI and subjected to deep sequencing to decode the interaction matrix. We applied this system to decipher the trans-kingdom interactome between Mycobacterium tuberculosis and host cells and further identified Rv2427c interfering with the phagosome-lysosome fusion. This concept can also be applied to other systems to screen protein-RNA and protein-DNA interactions and delineate signaling landscape in cells.
ChiPPI: a novel method for mapping chimeric protein-protein interactions uncovers selection principles of protein fusion events in cancer.

PubMed

Frenkel-Morgenstern, Milana; Gorohovski, Alessandro; Tagore, Somnath; Sekar, Vaishnovi; Vazquez, Miguel; Valencia, Alfonso

2017-07-07

Fusion proteins, comprising peptides deriving from the translation of two parental genes, are produced in cancer by chromosomal aberrations. The expressed fusion protein incorporates domains of both parental proteins. Using a methodology that treats discrete protein domains as binding sites for specific domains of interacting proteins, we have cataloged the protein interaction networks for 11 528 cancer fusions (ChiTaRS-3.1). Here, we present our novel method, chimeric protein-protein interactions (ChiPPI) that uses the domain-domain co-occurrence scores in order to identify preserved interactors of chimeric proteins. Mapping the influence of fusion proteins on cell metabolism and pathways reveals that ChiPPI networks often lose tumor suppressor proteins and gain oncoproteins. Furthermore, fusions often induce novel connections between non-interactors skewing interaction networks and signaling pathways. We compared fusion protein PPI networks in leukemia/lymphoma, sarcoma and solid tumors finding distinct enrichment patterns for each disease type. While certain pathways are enriched in all three diseases (Wnt, Notch and TGF β), there are distinct patterns for leukemia (EGFR signaling, DNA replication and CCKR signaling), for sarcoma (p53 pathway and CCKR signaling) and solid tumors (FGFR and EGFR signaling). Thus, the ChiPPI method represents a comprehensive tool for studying the anomaly of skewed cellular networks produced by fusion proteins in cancer. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Quantitative analysis of chaperone network throughput in budding yeast

PubMed Central

Brownridge, Philip; Lawless, Craig; Payapilly, Aishwarya B; Lanthaler, Karin; Holman, Stephen W; Harman, Victoria M; Grant, Christopher M; Beynon, Robert J; Hubbard, Simon J

2013-01-01

The network of molecular chaperones mediates the folding and translocation of the many proteins encoded in the genome of eukaryotic organisms, as well as a response to stress. It has been particularly well characterised in the budding yeast, Saccharomyces cerevisiae, where 63 known chaperones have been annotated and recent affinity purification and MS/MS experiments have helped characterise the attendant network of chaperone targets to a high degree. In this study, we apply our QconCAT methodology to directly quantify the set of yeast chaperones in absolute terms (copies per cell) via SRM MS. Firstly, we compare these to existing quantitative estimates of these yeast proteins, highlighting differences between approaches. Secondly, we cast the results into the context of the chaperone target network and show a distinct relationship between abundance of individual chaperones and their targets. This allows us to characterise the ‘throughput’ of protein molecules passing through individual chaperones and their groups on a proteome-wide scale in an unstressed model eukaryote for the first time. The results demonstrate specialisations of the chaperone classes, which display different overall workloads, efficiencies and preference for the sub-cellular localisation of their targets. The novel integration of the interactome data with quantification supports re-estimates of the level of protein throughout going through molecular chaperones. Additionally, although chaperones target fewer than 40% of annotated proteins we show that they mediate the folding of the majority of protein molecules (∼62% of the total protein flux in the cell), highlighting their importance. PMID:23420633
PPI-IRO: a two-stage method for protein-protein interaction extraction based on interaction relation ontology.

PubMed

Li, Chuan-Xi; Chen, Peng; Wang, Ru-Jing; Wang, Xiu-Jie; Su, Ya-Ru; Li, Jinyan

2014-01-01

Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identification of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifies and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At first, IRO is applied in a binary classifier to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the significant performance of IRO on relation sentences classification and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and BioInfer, respectively, which are superior to most existing extraction methods.
Probing the Extent of Randomness in Protein Interaction Networks

DTIC Science & Technology

2008-07-11

other [54]. This characteristic is exemplified in Video S1, which contains a three-dimensional animation of the HT E . coli PPI network determined by...experiment using either yeast two-hybrid (Y2H) or tandem affinity purification (TAP) methodology: C. jejuni [18], E . coli (HT1) [12], E . coli (HT2...DCDWa C. jejuni [18] 1331 11664 0.095 0.095 2.91 2.85 E . coli (HT1) [12] 1289 5420 0.083 0.089 3.60 3.29 (HT2) [13] 3047 11477 0.064 0.085 3.37 3.27 C
Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2016-10-06

Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .
"Master-Slave" Biological Network Alignment

NASA Astrophysics Data System (ADS)

Ferraro, Nicola; Palopoli, Luigi; Panni, Simona; Rombo, Simona E.

Performing global alignment between protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform this task operate symmetrically, that is to say, they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how well the corresponding organism is biologically well-characterized. For well-characterized organisms the associated PPI network supposedly encode in a sound manner all the information about their proteins and associated interactions, which is far from being the case for not well characterized ones. Here the new idea is developed to devise a method for global alignment of PPI networks that in fact exploit differences in the characterization of organisms at hand. We assume that the PPI network (called Master) of the best characterized is used as a fingerprint to guide the alignment process to the second input network (called Slave), so that generated results preferably retain the structural characteristics of the Master (and using the Slave) network. We tested our method showing that the results it returns are biologically relevant.
Choice vs. voice? PPI policies and the re-positioning of the state in England and Wales.

PubMed

Hughes, David; Mullen, Caroline; Vincent-Jones, Peter

2009-09-01

CONTEXT AND THESIS: Changing patient and public involvement (PPI) policies in England and Wales are analysed against the background of wider National Health Service (NHS) reforms and regulatory frameworks. We argue that the growing divergence of health policies is accompanied by a re-positioning of the state vis-à-vis PPI, characterized by different mixes of centralized and decentralized regulatory instruments. Analysis of legislation and official documents, and interviews with policy makers. In England, continued hierarchical control is combined with the delegation of responsibilities for the oversight and organization of PPI to external institutions such as the Care Quality Commission and local involvement networks, in support of the government's policy agenda of increasing marketization. In Wales, which has rejected market reforms and economic regulation, decentralization is occurring through the use of mixed regulatory approaches and networks suited to the small-country governance model, and seeks to benefit from the close proximity of central and local actors by creating new forms of engagement while maintaining central steering of service planning. Whereas English PPI policies have emerged in tandem with a pluralistic supply-side market and combine new institutional arrangements for patient 'choice' with other forms of involvement, the Welsh policies focus on 'voice' within a largely publicly-delivered service. While the English reforms draw on theories of economic regulation and the experience of independent regulation in the utilities sector, the Welsh model of local service integration has been more influenced by reforms in local government. Such transfers of governance instruments from other public service sectors to the NHS may be problematic.
Clopidogrel and proton pump inhibitor (PPI) interaction: separate intake and a non-omeprazole PPI the solution?

PubMed

Kenngott, S; Olze, R; Kollmer, M; Bottheim, H; Laner, A; Holinski-Feder, E; Gross, M

2010-05-18

Dual therapy with aspirin and clopidogrel increases the risk of gastrointestinal bleeding. Therefore, co-therapy with a proton pump inhibitor (PPI) is recommended by most guidelines. However, there are warnings against combining PPIs with clopidogrel because of their interactions with cytochrome P450 isoenzyme 2C19 (CYP2C19). The effects of the combined or separate intake of 20 mg of omeprazole and 75 mg of clopidogrel on the clopidogrel-induced inhibition of platelet aggregation were measured in four healthy subjects whose CYP2C19 exon sequences were determined. The effects of co-therapy with 10 mg of rabeprazole were also examined. Two subjects showed the wild-type CYP2C19 sequence. The concurrent intake of omeprazole had no effect on clopidogrel-induced platelet inhibition in these subjects. Two subjects were heterozygous for the *2 allele, with predicted reduced CYP2C19 activity. One of them was a clopidogrel non-responder. In the second heterozygous subject, omeprazole co-therapy reduced the clopidogrel anti-platelet effect when taken simultaneously or separately. However, the simultaneous intake of rabeprazole did not reduce the clopidogrel effect. The clopidogrel-PPI interaction does not seem to be a PPI class effect. Rabeprazole did not affect the clopidogrel effect in a subject with a clear omeprazole-clopidogrel interaction. The separate intake of PPI and clopidogrel may not be sufficient to prevent their interaction.
PPy/PMMA/PEG-based sensor for low-concentration acetone detection

NASA Astrophysics Data System (ADS)

Daneshkhah, A.; Shrestha, S.; Agarwal, M.; Varahramyan, K.

2014-05-01

A polymer pellet-based sensor device comprised of polypyrrole (PPy), polymethyl methacrylate (PMMA) and polyethylene glycol (PEG), its fabrication methods, and the experimental results for low-concentration acetone detection are presented. The design consists of a double layer pellet, where the top layer consists of PPy/PMMA and the bottom layer is composed of PPy/PMMA/PEG. Both sets of material compositions are synthesized by readily realizable chemical polymerization techniques. The mechanism of the sensor operation is based on the change in resistance of PPy and the swelling of PMMA when exposed to acetone, thereby changing the resistance of the layers. The resistances measured on the two layers, and across the pellet, are taken as the three output signals of the sensor. Because the PPy/PMMA and PPy/PMMA/PEG layers respond differently to acetone, as well as to other volatile organic compounds, it is demonstrated that the three output signals can allow the presented sensor to have a better sensitivity and selectivity than previously reported devices. Materials characterizations show formation of new composite with PPy/PMMA/PEG. Material response at various concentrations of acetone was conducted using quartz crystal microbalance (QCM). It was observed that the frequency decreased by 98 Hz for 290 ppm of acetone and by 411 Hz for 1160 ppm. Experimental results with a double layer pellet of PPy/PMMA and PPy/PMMA/PEG show an improved selectivity of acetone over ethanol. The reported acetone sensor is applicable for biomedical and other applications.
PROPER: global protein interaction network alignment through percolation matching.

PubMed

Kazemi, Ehsan; Hassani, Hamed; Grossglauser, Matthias; Pezeshgi Modarres, Hassan

2016-12-12

The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological knowledge between species. Although different PPI-network alignment algorithms were introduced during the last decade, developing an accurate and scalable algorithm that can find alignments with high biological and structural similarities among PPI networks is still challenging. In this paper, we introduce a new global network alignment algorithm for PPI networks called PROPER. Compared to other global network alignment methods, our algorithm shows higher accuracy and speed over real PPI datasets and synthetic networks. We show that the PROPER algorithm can detect large portions of conserved biological pathways between species. Also, using a simple parsimonious evolutionary model, we explain why PROPER performs well based on several different comparison criteria. We highlight that PROPER has high potential in further applications such as detecting biological pathways, finding protein complexes and PPI prediction. The PROPER algorithm is available at http://proper.epfl.ch .
Neural network analysis of electrodynamic activity of yeast cells around 1 kHz

NASA Astrophysics Data System (ADS)

Janca, R.

2011-12-01

This paper deals with data analysis of electrodynamic activity of two mutants of yeast cells, cell cycle of which is synchronized and non-synchronized, respectively. We used data already published by Jelinek et al. and treat them with data mining method based on the multilayer neural network. Intersection of data mining and statistical distribution of the noise shows significant difference between synchronized and non-synchronized yeasts not only in total power, but also discrete frequencies.

Clopidogrel and proton pump inhibitor (PPI) interaction: separate intake and a non-omeprazole PPI the solution?

PubMed Central

2010-01-01

Background Dual therapy with aspirin and clopidogrel increases the risk of gastrointestinal bleeding. Therefore, co-therapy with a proton pump inhibitor (PPI) is recommended by most guidelines. However, there are warnings against combining PPIs with clopidogrel because of their interactions with cytochrome P450 isoenzyme 2C19 (CYP2C19). Methods The effects of the combined or separate intake of 20 mg of omeprazole and 75 mg of clopidogrel on the clopidogrel-induced inhibition of platelet aggregation were measured in four healthy subjects whose CYP2C19 exon sequences were determined. The effects of co-therapy with 10 mg of rabeprazole were also examined. Results Two subjects showed the wild-type CYP2C19 sequence. The concurrent intake of omeprazole had no effect on clopidogrel-induced platelet inhibition in these subjects. Two subjects were heterozygous for the *2 allele, with predicted reduced CYP2C19 activity. One of them was a clopidogrel non-responder. In the second heterozygous subject, omeprazole co-therapy reduced the clopidogrel anti-platelet effect when taken simultaneously or separately. However, the simultaneous intake of rabeprazole did not reduce the clopidogrel effect. Conclusion The clopidogrel-PPI interaction does not seem to be a PPI class effect. Rabeprazole did not affect the clopidogrel effect in a subject with a clear omeprazole-clopidogrel interaction. The separate intake of PPI and clopidogrel may not be sufficient to prevent their interaction. PMID:20562062
Choice vs. voice? PPI policies and the re‐positioning of the state in England and Wales

PubMed Central

Hughes, David; Mullen, Caroline; Vincent‐Jones, Peter

2009-01-01

Abstract Context and Thesis Changing patient and public involvement (PPI) policies in England and Wales are analysed against the background of wider National Health Service (NHS) reforms and regulatory frameworks. We argue that the growing divergence of health policies is accompanied by a re‐positioning of the state vis‐à‐vis PPI, characterized by different mixes of centralized and decentralized regulatory instruments. Method Analysis of legislation and official documents, and interviews with policy makers. Findings In England, continued hierarchical control is combined with the delegation of responsibilities for the oversight and organization of PPI to external institutions such as the Care Quality Commission and local involvement networks, in support of the government’s policy agenda of increasing marketization. In Wales, which has rejected market reforms and economic regulation, decentralization is occurring through the use of mixed regulatory approaches and networks suited to the small‐country governance model, and seeks to benefit from the close proximity of central and local actors by creating new forms of engagement while maintaining central steering of service planning. Whereas English PPI policies have emerged in tandem with a pluralistic supply‐side market and combine new institutional arrangements for patient ‘choice’ with other forms of involvement, the Welsh policies focus on ‘voice’ within a largely publicly‐delivered service. Discussion While the English reforms draw on theories of economic regulation and the experience of independent regulation in the utilities sector, the Welsh model of local service integration has been more influenced by reforms in local government. Such transfers of governance instruments from other public service sectors to the NHS may be problematic. PMID:19754688
PPi-dependent phosphofructotransferase (phosphofructokinase) activity in the mollicutes (mycoplasma) Acholeplasma laidlawii.

PubMed Central

Pollack, J D; Williams, M V

1986-01-01

A PPi-dependent phosphofructotransferase (PPi-fructose 6-phosphate 1-phosphotransferase, EC 2.7.1.90) which catalyzes the conversion of fructose 6 phosphate (F-6-P) to fructose 1,6-bisphosphate (F-1, 6-P2) was isolated from a cytoplasmic fraction of Acholeplasma laidlawii B-PG9 and partially purified (430-fold). PPi was required as the phosphate donor. ATP, dATP, CTP, dCTP, GTP, dGTP, UTP, dUTP, ITP, TTP, ADP, or Pi could not substitute for PPi. The PPi-dependent reaction (2.0 mM PPi) was not altered in the presence of any of these nucleotides (2.0 mM) or in the presence of smaller (less than or equal to 300 microM) amounts of fructose 2,6-bisphosphate, (NH4)2SO4, AMP, citrate, GDP, or phosphoenolpyruvate. Mg2+ and a pH of 7.4 were required for maximum activity. The partially purified enzyme in sucrose density gradient experiments had an approximate molecular weight of 74,000 and a sedimentation coefficient of 6.7. A second form of the enzyme (molecular weight, 37,000) was detected, although in relatively smaller amounts, by using Blue Sepharose matrix when performing electrophoresis experiments. The back reaction, F-1, 6-P2 to F-6-P, required Pi; arsenate could substitute for Pi, but not PPi or any other nucleotide tested. The computer-derived kinetic constants (+/- standard deviation) for the reaction in the PPi-driven direction of F-1, 6-P2 were as follows: v, 38.9 +/- 0.48 mM min-1; Ka(PPi), 0.11 +/- 0.04 mM; Kb(F-6-P), 0.65 +/- 0.15 mM; and Kia(PPi), 0.39 +/- 0.11 mM. A. laidlawii B-PG9 required PPi not only for the PPi-phosphofructotransferase reaction which we describe but also for purine nucleoside kinase activity. a dependency unknown in any other organism. In A. laidlawii B-PG9, the PPi requirement may be met by reactions in this organism already known to synthesize PPi (e.g., dUTPase and purine nucleobase phosphoribosyltransferases). In almost all other cells, the conversion of F-6-P to F-1,6-P2 is ATP dependent, and the reaction is generally considered
32 CFR 701.115 - Protected personal information (PPI).

Code of Federal Regulations, 2012 CFR

2012-07-01

... address, home telephone number, etc., must be strictly limited to individuals with an official need to know. It is inappropriate to use PPI in group/bulk orders. Activities must take action to protect PPI.... (c) Collection/maintenance. The collection and maintenance of information retrieved by an individual...
32 CFR 701.115 - Protected personal information (PPI).

Code of Federal Regulations, 2013 CFR

2013-07-01

... address, home telephone number, etc., must be strictly limited to individuals with an official need to know. It is inappropriate to use PPI in group/bulk orders. Activities must take action to protect PPI.... (c) Collection/maintenance. The collection and maintenance of information retrieved by an individual...
32 CFR 701.115 - Protected personal information (PPI).

Code of Federal Regulations, 2010 CFR

2010-07-01

... address, home telephone number, etc., must be strictly limited to individuals with an official need to know. It is inappropriate to use PPI in group/bulk orders. Activities must take action to protect PPI.... (c) Collection/maintenance. The collection and maintenance of information retrieved by an individual...
32 CFR 701.115 - Protected personal information (PPI).

Code of Federal Regulations, 2011 CFR

2011-07-01

... address, home telephone number, etc., must be strictly limited to individuals with an official need to know. It is inappropriate to use PPI in group/bulk orders. Activities must take action to protect PPI.... (c) Collection/maintenance. The collection and maintenance of information retrieved by an individual...
32 CFR 701.115 - Protected personal information (PPI).

Code of Federal Regulations, 2014 CFR

2014-07-01

... address, home telephone number, etc., must be strictly limited to individuals with an official need to know. It is inappropriate to use PPI in group/bulk orders. Activities must take action to protect PPI.... (c) Collection/maintenance. The collection and maintenance of information retrieved by an individual...
Clustering PPI data by combining FA and SHC method.

PubMed

Lei, Xiujuan; Ying, Chao; Wu, Fang-Xiang; Xu, Jin

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value.
Clustering PPI data by combining FA and SHC method

PubMed Central

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value. PMID:25707632
Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways

PubMed Central

Kawakami, Eiryo; Singh, Vivek K; Matsubara, Kazuko; Ishii, Takashi; Matsuoka, Yukiko; Hase, Takeshi; Kulkarni, Priya; Siddiqui, Kenaz; Kodilkar, Janhavi; Danve, Nitisha; Subramanian, Indhupriya; Katoh, Manami; Shimizu-Yoshida, Yuki; Ghosh, Samik; Jere, Abhay; Kitano, Hiroaki

2016-01-01

Cellular stress responses require exquisite coordination between intracellular signaling molecules to integrate multiple stimuli and actuate specific cellular behaviors. Deciphering the web of complex interactions underlying stress responses is a key challenge in understanding robust biological systems and has the potential to lead to the discovery of targeted therapeutics for diseases triggered by dysregulation of stress response pathways. We constructed large-scale molecular interaction maps of six major stress response pathways in Saccharomyces cerevisiae (baker’s or budding yeast). Biological findings from over 900 publications were converted into standardized graphical formats and integrated into a common framework. The maps are posted at http://www.yeast-maps.org/yeast-stress-response/ for browse and curation by the research community. On the basis of these maps, we undertook systematic analyses to unravel the underlying architecture of the networks. A series of network analyses revealed that yeast stress response pathways are organized in bow–tie structures, which have been proposed as universal sub-systems for robust biological regulation. Furthermore, we demonstrated a potential role for complexes in stabilizing the conserved core molecules of bow–tie structures. Specifically, complex-mediated reversible reactions, identified by network motif analyses, appeared to have an important role in buffering the concentration and activity of these core molecules. We propose complex-mediated reactions as a key mechanism mediating robust regulation of the yeast stress response. Thus, our comprehensive molecular interaction maps provide not only an integrated knowledge base, but also a platform for systematic network analyses to elucidate the underlying architecture in complex biological systems. PMID:28725465
Unified Alignment of Protein-Protein Interaction Networks.

PubMed

Malod-Dognin, Noël; Ban, Kristina; Pržulj, Nataša

2017-04-19

Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational intractability of the network alignment problem, aligners are heuristics providing divergent solutions and no consensus exists on a gold standard, or which scoring scheme should be used to evaluate them. We comprehensively evaluate the alignment scoring schemes and global network aligners on large scale PPI data and observe that three methods, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. We study the collective behaviour of network aligners and observe that PPI networks are almost entirely aligned with a handful of aligners that we unify into a new tool, Ulign. Ulign enables complete alignment of two networks, which traditional global and local aligners fail to do. Also, multiple mappings of Ulign define biologically relevant soft clusterings of proteins in PPI networks, which may be used for refining the transfer of annotations across networks. Hence, PPI networks are already well investigated by current aligners, so to gain additional biological insights, a paradigm shift is needed. We propose such a shift come from aligning all available data types collectively rather than any particular data type in isolation from others.
Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

PubMed Central

2012-01-01

Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Conclusions Yeast 5 expands and refines the computational reconstruction of yeast metabolism and improves the predictive accuracy of a
Competition-cooperation relationship networks characterize the competition and cooperation between proteins

PubMed Central

Li, Hong; Zhou, Yuan; Zhang, Ziding

2015-01-01

By analyzing protein-protein interaction (PPI) networks, one can find that a protein may have multiple binding partners. However, it is difficult to determine whether the interactions with these partners occur simultaneously from binary PPIs alone. Here, we construct the yeast and human competition-cooperation relationship networks (CCRNs) based on protein structural interactomes to clearly exhibit the relationship (competition or cooperation) between two partners of the same protein. If two partners compete for the same interaction interface, they would be connected by a competitive edge; otherwise, they would be connected by a cooperative edge. The properties of three kinds of hubs (i.e., competitive, modest, and cooperative hubs) are analyzed in the CCRNs. Our results show that competitive hubs have higher clustering coefficients and form clusters in the human CCRN, but these tendencies are not observed in the yeast CCRN. We find that the human-specific proteins contribute significantly to these differences. Subsequently, we conduct a series of computational experiments to investigate the regulatory mechanisms that avoid competition between proteins. Our comprehensive analyses reveal that for most yeast and human protein competitors, transcriptional regulation plays an important role. Moreover, the human-specific proteins have a particular preference for other regulatory mechanisms, such as alternative splicing. PMID:26108281
An insight into the complex prion-prion interaction network in the budding yeast Saccharomyces cerevisiae.

PubMed

Du, Zhiqiang; Valtierra, Stephanie; Li, Liming

2014-01-01

The budding yeast Saccharomyces cerevisiae is a valuable model system for studying prion-prion interactions as it contains multiple prion proteins. A recent study from our laboratory showed that the existence of Swi1 prion ([SWI(+)]) and overproduction of Swi1 can have strong impacts on the formation of 2 other extensively studied yeast prions, [PSI(+)] and [PIN(+)] ([RNQ(+)]) (Genetics, Vol. 197, 685-700). We showed that a single yeast cell is capable of harboring at least 3 heterologous prion elements and these prions can influence each other's appearance positively and/or negatively. We also showed that during the de novo [PSI(+)] formation process upon Sup35 overproduction, the aggregation patterns of a preexisting inducer ([RNQ(+)] or [SWI(+)]) can undergo significant remodeling from stably transmitted dot-shaped aggregates to aggregates that co-localize with the newly formed Sup35 aggregates that are ring/ribbon/rod- shaped. Such co-localization disappears once the newly formed [PSI(+)] prion stabilizes. Our finding provides strong evidence supporting the "cross-seeding" model for prion-prion interactions and confirms earlier reports that the interactions among different prions and their prion proteins mostly occur at the initiation stages of prionogenesis. Our results also highlight a complex prion interaction network in yeast. We believe that elucidating the mechanism underlying the yeast prion-prion interaction network will not only provide insight into the process of prion de novo generation and propagation in yeast but also shed light on the mechanisms that govern protein misfolding, aggregation, and amyloidogenesis in higher eukaryotes.
Chemically designed Pt/PPy nano-composite for effective LPG gas sensor.

PubMed

Gaikwad, Namrata; Bhanoth, Sreenu; More, Priyesh V; Jain, G H; Khanna, P K

2014-03-07

Simultaneous in situ reduction of hexachloroplatinic acid by the amine group in the pyrrole monomer and oxidation of pyrrole to form polypyrrole (PPy) was examined. The reactions were performed at various temperatures to understand the degree of reduction of platinum precursor as well as doping of polypyrrole with Pt(II) chloro-complex. Spectroscopic images revealed different morphologies for the Pt/PPy nano-composite prepared at various temperatures. The as-prepared Pt/PPy nano-composite samples were tested for their ability to sense liquefied petroleum gas (LPG) which resulted in excellent sensing at relatively low temperature. The porous nature and ohmic contact between the PPy and platinum nanoparticles makes the as-prepared Pt/PPy nano-composite highly useful for sensors as well as electronic applications.
A Fast Response Ammonia Sensor Based on Coaxial PPy-PAN Nanofiber Yarn.

PubMed

Liu, Penghong; Wu, Shaohua; Zhang, Yue; Zhang, Hongnan; Qin, Xiaohong

2016-06-23

Highly orientated polypyrrole (PPy)-coated polyacrylonitrile (PAN) (PPy-PAN) nanofiber yarn was prepared with an electrospinning technique and in-situ chemical polymerization. The morphology and chemical structure of PPy-PAN nanofiber yarn was characterized by scanning electron microscopy (SEM), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), and fourier transform infrared spectroscopy (FTIR), which indicated that the PPy as the shell layer was homogeneously and uniformly polymerized on the surface of PAN nanofiber. The effects of different concentration of doping acid on the responses of PPy-PAN nanofiber yarn sensor were investigated. The electrical responses of the gas sensor based on the PPy-PAN nanofiber yarn to ammonia were investigated at room temperature. The nanoyarn sensor composed of uniaxially aligned PPy-PAN nanofibers with a one-dimensional structure exhibited a transient response, and the response time was less than 1 s. The excellent sensing properties mentioned above give rise to good potential application prospects in the field of ammonia sensor.
[Phosphorescent effect of Ir (ppy)3 on the luminescent characteristic of Rubrene].

PubMed

Xu, Hong-Hua; Xu, Zheng; Zhang, Fu-Jun; Zhao, Su-Ling; Yuan, Guang-Cai; Chen, Yue-Ning

2008-07-01

Many organic matters including heavy metal ions can validly utilize the singlet and triplet for luminescence owiog to the spin-orbit coupling. As a result, the internal quantum efficiency can easily achieve a value higher than traditional organic light emitting diodes in theory. There is a strong luminescence of PVK in PVK : PBD : Rubrene system. PL spectra excited by 345 nm of PVK : PBD : Rubrene thin film has a 410 nm PVK luminescent peak and a 560 nm Rubrene peak. EL still has a PVK luminescent peak, which should be kept from happening. Excitons can not adequately transferred from the matrix solution to Rubrene. The doping with Ir(ppy)3 improves the PVK : PBD : Rubrene system performance. PL spectra excited by 345 nm of PVK : PBD : Ir(ppy)3 : Rubrene with low concentration of Rubrene has a 510 nm Ir(ppy)3 peak and a new 548 nm one. However, the Ir(ppy)3 peak is smaller and the Rubrene one is bigger in EL spectra. Notably a strong and single luminescence of Rubrene is obtained in EL and PL spectra excited by 345 nm of PVK : PBD : Ir(ppy)3 : Rubrene with high concentration of Rubrene. Meanwhile, the Ir(ppy)3 luminescent peak disappears. The mechanism originates from the phosphorescent effect of Ir (ppy)3. The singlet excitons can basically be transferred from PVK : PBD or Ir(ppy)3 to Rubrene. But most excitons from Ir (ppy)3 can directly tunnel to the fluorescent material and come into being singlet states that can return to ground states and cause luminescence. Rubrene can accept proportional excitons with low concentration. While the concentration of Rubrene is higher, excitons can be entirely accepted by Rubrene. The effect also restricts the luminescent intensity of Ir(ppy)3 and boosts up that of Rubrene. Furthermore, the energy transfer in PVK : PBD : Ir(ppy)3 : Rubrene system is primary the Forester energy transfer. Excitation spectra of Rubrene and emission spectra of Ir(ppy)3 have a large overlap revealing that there is a strong energy transfer and further
RNA sequencing confirms similarities between PPI-responsive oesophageal eosinophilia and eosinophilic oesophagitis.

PubMed

Peterson, K A; Yoshigi, M; Hazel, M W; Delker, D A; Lin, E; Krishnamurthy, C; Consiglio, N; Robson, J; Yandell, M; Clayton, F

2018-06-04

Although current American guidelines distinguish proton pump inhibitor-responsive oesophageal eosinophilia (PPI-REE) from eosinophilic oesophagitis (EoE), these entities are broadly similar. While two microarray studies showed that they have similar transcriptomes, more extensive RNA sequencing studies have not been done previously. To determine whether RNA sequencing identifies genetic markers distinguishing PPI-REE from EoE. We retrospectively examined 13 PPI-REE and 14 EoE biopsies, matched for tissue eosinophil content, and 14 normal controls. Patients and controls were not PPI-treated at the time of biopsy. We did RNA sequencing on formalin-fixed, paraffin-embedded tissue, with differential expression confirmation by quantitative polymerase chain reaction (PCR). We validated the use of formalin-fixed, paraffin-embedded vs RNAlater-preserved tissue, and compared our formalin-fixed, paraffin-embedded EoE results to a prior EoE study. By RNA sequencing, no genes were differentially expressed between the EoE and PPI-REE groups at the false discovery rate (FDR) ≤0.01 level. Compared to normal controls, 1996 genes were differentially expressed in the PPI-REE group and 1306 genes in the EoE group. By less stringent criteria, only MAPK8IP2 was differentially expressed between PPI-REE and EoE (FDR = 0.029, 2.2-fold less in EoE than in PPI-REE), with similar results by PCR. KCNJ2, which was differentially expressed in a prior study, was similar in the EoE and PPI-REE groups by both RNA sequencing and real-time PCR. Eosinophilic oesophagitis and PPI-REE have comparable transcriptomes, confirming that they are part of the same disease continuum. © 2018 John Wiley & Sons Ltd.
Oxadiazole-carbazole polymer (POC)-Ir(ppy)3 tunable emitting composites

NASA Astrophysics Data System (ADS)

Bruno, Annalisa; Borriello, Carmela; Di Luccio, Tiziana; Sessa, Lucia; Concilio, Simona; Haque, Saif A.; Minarini, Carla

2017-04-01

POC polymer is an oxadiazole-carbazole copolymer we have previously synthetized and established as light emitting material in Organic Light Emitting Devices (OLEDs), although POC quantum yield emission efficiency and color purity still need to be enhanced. On the other hand, tris[2-phenylpyridinato-C2,N]iridium(III) (Ir(ppy)3) complexes, namely Ir(ppy)3 are among the brightest luminophores employed in green light emitting devices. Our aim, in this work, is to take advantage of Ir(ppy)3 bright emission by combining the Ir complex with blue emitting POC to obtain tunable light emitting composites over a wide range of the visible spectrum. Here we have investigated the optical proprieties POC based nanocomposites with different concentrations of Ir(ppy)3, ranging from 1 to 10 wt%. Both spectral and time resolved fluorescence measurements show an efficient energy transfer from the polymer to the dopants, resulting in white-emitting composites. The most intense and stable emission has been found when POC was doped with about 5 wt% concentration of Ir(ppy)3.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.
Limited Effect of Rebamipide in Addition to Proton Pump Inhibitor (PPI) in the Treatment of Post-Endoscopic Submucosal Dissection Gastric Ulcers: A Randomized Controlled Trial Comparing PPI Plus Rebamipide Combination Therapy with PPI Monotherapy.

PubMed

Nakamura, Kazuhiko; Ihara, Eikichi; Akiho, Hirotada; Akahoshi, Kazuya; Harada, Naohiko; Ochiai, Toshiaki; Nakamura, Norimoto; Ogino, Haruei; Iwasa, Tsutomu; Aso, Akira; Iboshi, Yoichiro; Takayanagi, Ryoichi

2016-11-15

The ability of endoscopic submucosal dissection (ESD) to resect large early gastric cancers (EGCs) results in the need to treat large artificial gastric ulcers. This study assessed whether the combination therapy of rebamipide plus a proton pump inhibitor (PPI) offered benefits over PPI monotherapy. In this prospective, randomized, multicenter, open-label, and comparative study, patients who had undergone ESD for EGC or gastric adenoma were randomized into groups receiving either rabeprazole monotherapy (10 mg/day, n=64) or a combination of rabeprazole plus rebamipide (300 mg/day, n=66). The Scar stage (S stage) ratio after treatment was compared, and factors independently associated with ulcer healing were identified by using multivariate analyses. The S stage rates at 4 and 8 weeks were similar in the two groups, even in the subgroups of patients with large amounts of tissue resected and regardless of CYP2C19 genotype. Independent factors for ulcer healing were circumferential location of the tumor and resected tissue size; the type of treatment did not affect ulcer healing. Combination therapy with rebamipide and PPI had limited benefits compared with PPI monotherapy in the treatment of post-ESD gastric ulcer (UMIN Clinical Trials Registry, UMIN000007435).
Finding trans-regulatory genes and protein complexes modulating meiotic recombination hotspots of human, mouse and yeast.

PubMed

Wu, Min; Kwoh, Chee-Keong; Li, Xiaoli; Zheng, Jie

2014-09-11

The regulatory mechanism of recombination is one of the most fundamental problems in genomics, with wide applications in genome wide association studies (GWAS), birth-defect diseases, molecular evolution, cancer research, etc. Recombination events cluster into short genomic regions called "recombination hotspots". Recently, a zinc finger protein PRDM9 was reported to regulate recombination hotspots in human and mouse genomes. In addition, a 13-mer motif contained in the binding sites of PRDM9 is found to be enriched in human hotspots. However, this 13-mer motif only covers a fraction of hotspots, indicating that PRDM9 is not the only regulator of recombination hotspots. Therefore, the challenge of discovering other regulators of recombination hotspots becomes significant. Furthermore, recombination is a complex process. Hence, multiple proteins acting as machinery, rather than individual proteins, are more likely to carry out this process in a precise and stable manner. Therefore, the extension of the prediction of individual trans-regulators to protein complexes is also highly desired. In this paper, we introduce a pipeline to identify genes and protein complexes associated with recombination hotspots. First, we prioritize proteins associated with hotspots based on their preference of binding to hotspots and coldspots. Second, using the above identified genes as seeds, we apply the Random Walk with Restart algorithm (RWR) to propagate their influences to other proteins in protein-protein interaction (PPI) networks. Hence, many proteins without DNA-binding information will also be assigned a score to implicate their roles in recombination hotspots. Third, we construct sub-PPI networks induced by top genes ranked by RWR for various species (e.g., yeast, human and mouse) and detect protein complexes in those sub-PPI networks. The GO term analysis show that our prioritizing methods and the RWR algorithm are capable of identifying novel genes associated with
Limited Effect of Rebamipide in Addition to Proton Pump Inhibitor (PPI) in the Treatment of Post-Endoscopic Submucosal Dissection Gastric Ulcers: A Randomized Controlled Trial Comparing PPI Plus Rebamipide Combination Therapy with PPI Monotherapy

PubMed Central

Nakamura, Kazuhiko; Ihara, Eikichi; Akiho, Hirotada; Akahoshi, Kazuya; Harada, Naohiko; Ochiai, Toshiaki; Nakamura, Norimoto; Ogino, Haruei; Iwasa, Tsutomu; Aso, Akira; Iboshi, Yoichiro; Takayanagi, Ryoichi

2016-01-01

Background/Aims The ability of endoscopic submucosal dissection (ESD) to resect large early gastric cancers (EGCs) results in the need to treat large artificial gastric ulcers. This study assessed whether the combination therapy of rebamipide plus a proton pump inhibitor (PPI) offered benefits over PPI monotherapy. Methods In this prospective, randomized, multicenter, open-label, and comparative study, patients who had undergone ESD for EGC or gastric adenoma were randomized into groups receiving either rabeprazole monotherapy (10 mg/day, n=64) or a combination of rabeprazole plus rebamipide (300 mg/day, n=66). The Scar stage (S stage) ratio after treatment was compared, and factors independently associated with ulcer healing were identified by using multivariate analyses. Results The S stage rates at 4 and 8 weeks were similar in the two groups, even in the subgroups of patients with large amounts of tissue resected and regardless of CYP2C19 genotype. Independent factors for ulcer healing were circumferential location of the tumor and resected tissue size; the type of treatment did not affect ulcer healing. Conclusions Combination therapy with rebamipide and PPI had limited benefits compared with PPI monotherapy in the treatment of post-ESD gastric ulcer (UMIN Clinical Trials Registry, UMIN000007435). PMID:27282261
A Generalized Form of Context-Dependent Psychophysiological Interactions (gPPI): A Comparison to Standard Approaches

PubMed Central

McLaren, Donald G.; Ries, Michele L.; Xu, Guofan; Johnson, Sterling C.

2012-01-01

Functional MRI (fMRI) allows one to study task-related regional responses and task-dependent connectivity analysis using psychophysiological interaction (PPI) methods. The latter affords the additional opportunity to understand how brain regions interact in a task-dependent manner. The current implementation of PPI in Statistical Parametric Mapping (SPM8) is configured primarily to assess connectivity differences between two task conditions, when in practice fMRI tasks frequently employ more than two conditions. Here we evaluate how a generalized form of context-dependent PPI (gPPI; http://www.nitrc.org/projects/gppi), which is configured to automatically accommodate more than two task conditions in the same PPI model by spanning the entire experimental space, compares to the standard implementation in SPM8. These comparisons are made using both simulations and an empirical dataset. In the simulated dataset, we compare the interaction beta estimates to their expected values and model fit using the Akaike Information Criterion (AIC). We found that interaction beta estimates in gPPI were robust to different simulated data models, were not different from the expected beta value, and had better model fits than when using standard PPI (sPPI) methods. In the empirical dataset, we compare the model fit of the gPPI approach to sPPI. We found that the gPPI approach improved model fit compared to sPPI. There were several regions that became non-significant with gPPI. These regions all showed significantly better model fits with gPPI. Also, there were several regions where task-dependent connectivity was only detected using gPPI methods, also with improved model fit. Regions that were detected with all methods had more similar model fits. These results suggest that gPPI may have greater sensitivity and specificity than standard implementation in SPM. This notion is tempered slightly as there is no gold standard; however, data simulations with a known outcome support our
Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226
Statistical indicators of collective behavior and functional clusters in gene networks of yeast

NASA Astrophysics Data System (ADS)

Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

2006-03-01

We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.
A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.
A Global Protein Kinase and Phosphatase Interaction Network in Yeast

PubMed Central

Breitkreutz, Ashton; Choi, Hyungwon; Sharom, Jeffrey R.; Boucher, Lorrie; Neduva, Victor; Larsen, Brett; Lin, Zhen-Yuan; Breitkreutz, Bobby-Joe; Stark, Chris; Liu, Guomin; Ahn, Jessica; Dewar-Darch, Danielle; Reguly, Teresa; Tang, Xiaojing; Almeida, Ricardo; Qin, Zhaohui Steve; Pawson, Tony; Gingras, Anne-Claude; Nesvizhskii, Alexey I.; Tyers, Mike

2011-01-01

The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses. PMID:20489023
The feasibility and application of PPy in cathodic polarization antifouling.

PubMed

Jia, Meng-Yang; Zhang, Zhi-Ming; Yu, Liang-Min; Wang, Jia; Zheng, Tong-Tong

2018-04-01

Cathodic polarization antifouling deserves attention because of its environmentally friendly nature and good sustainability. It has been proven that cathodic voltages applied on metal substrates exhibit outstanding antifouling effects. However, most metals immersed in marine environment are protected by insulated anticorrosive coatings, restricting the cathodic polarization applied on metals. This study developed a conducting polypyrrole (PPy)/acrylic resin coating (σ = 0.18 Scm -1 ), which can be applied in cathodic polarization antifouling. The good stability and electro-activity of PPy in the negative polarity zone in alkalescent NaCl solution were verified by linear sweep voltammetry (LSV), chronoamperometry (CA), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), demonstrating the feasibility of PPy as cathodic polarization material. Furthermore, the antifouling effects of PPy/acrylicresin coating on 24-h old Escherichia coli bacteria (E. coli) which formed on PPy/acrylic resin-coated plastic plate were measured under different cathodic potentials and treatment time, characterized by fluorescent microscope. The results suggest that at cathodic potential around -0.5 V (vs. saturated calomel electrode (SCE)), there was little trace of attached bacteria on the substrate after 20 min of treatment. PPy/acrylicresin-coated substrates were also subjected to repeated cycles of biofilm formation and electrochemical removal, where high removal efficiencies were maintained throughout the total polarization process. Under these conditions, the generation of hydrogen peroxide is believed to be responsible for the antifouling effects because of causing oxidative damage to cells, suggesting the potential of the proposed technology for application on insulated surfaces in various industrial settings. Copyright © 2018 Elsevier B.V. All rights reserved.
Protein-protein interaction networks (PPI) and complex diseases

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Rezaei-Tavirani, Mostafa; Goliaei, Bahram

2014-01-01

The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic (and physiologic) mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network. PMID:25436094
The Functional Networks of Prepulse Inhibition: Neuronal Connectivity Analysis Based on FDG-PET in Awake and Unrestrained Rats.

PubMed

Rohleder, Cathrin; Wiedermann, Dirk; Neumaier, Bernd; Drzezga, Alexander; Timmermann, Lars; Graf, Rudolf; Leweke, F Markus; Endepols, Heike

2016-01-01

Prepulse inhibition (PPI) is a neuropsychological process during which a weak sensory stimulus ("prepulse") attenuates the motor response ("startle reaction") to a subsequent strong startling stimulus. It is measured as a surrogate marker of sensorimotor gating in patients suffering from neuropsychological diseases such as schizophrenia, as well as in corresponding animal models. A variety of studies has shown that PPI of the acoustical startle reaction comprises three brain circuitries for: (i) startle mediation, (ii) PPI mediation, and (iii) modulation of PPI mediation. While anatomical connections and information flow in the startle and PPI mediation pathways are well known, spatial and temporal interactions of the numerous regions involved in PPI modulation are incompletely understood. We therefore combined [(18)F]fluoro-2-deoxyglucose positron-emission-tomography (FDG-PET) with PPI and resting state control paradigms in awake rats. A battery of subtractive, correlative as well as seed-based functional connectivity analyses revealed a default mode-like network (DMN) active during resting state only. Furthermore, two functional networks were observed during PPI: Metabolic activity in the lateral circuitry was positively correlated with PPI effectiveness and involved the auditory system and emotional regions. The medial network was negatively correlated with PPI effectiveness, i.e., associated with startle, and recruited a spatial/cognitive network. Our study provides evidence for two distinct neuronal networks, whose continuous interplay determines PPI effectiveness in rats, probably by either protecting the prepulse or facilitating startle processing. Discovering similar networks affected in neuropsychological disorders may help to better understand mechanisms of sensorimotor gating deficits and provide new perspectives for therapeutic strategies.
Stabilizing Motifs in Autonomous Boolean Networks and the Yeast Cell Cycle Oscillator

NASA Astrophysics Data System (ADS)

Sevim, Volkan; Gong, Xinwei; Socolar, Joshua

2009-03-01

Synchronously updated Boolean networks are widely used to model gene regulation. Some properties of these model networks are known to be artifacts of the clocking in the update scheme. Autonomous updating is a less artificial scheme that allows one to introduce small timing perturbations and study stability of the attractors. We argue that the stabilization of a limit cycle in an autonomous Boolean network requires a combination of motifs such as feed-forward loops and auto-repressive links that can correct small fluctuations in the timing of switching events. A recently published model of the transcriptional cell-cycle oscillator in yeast contains the motifs necessary for stability under autonomous updating [1]. [1] D. A. Orlando, et al. Nature (London), 4530 (7197):0 944--947, 2008.
Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.

PubMed

Sable, Rushikesh; Jois, Seetharama

2015-06-23

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.
Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator

PubMed Central

Usaite, Renata; Jewett, Michael C; Oliveira, Ana Paula; Yates, John R; Olsson, Lisbeth; Nielsen, Jens

2009-01-01

Highly conserved among eukaryotic cells, the AMP-activated kinase (AMPK) is a central regulator of carbon metabolism. To map the complete network of interactions around AMPK in yeast (Snf1) and to evaluate the role of its regulatory subunit Snf4, we measured global mRNA, protein and metabolite levels in wild type, Δsnf1, Δsnf4, and Δsnf1Δsnf4 knockout strains. Using four newly developed computational tools, including novel DOGMA sub-network analysis, we showed the benefits of three-level ome-data integration to uncover the global Snf1 kinase role in yeast. We for the first time identified Snf1's global regulation on gene and protein expression levels, and showed that yeast Snf1 has a far more extensive function in controlling energy metabolism than reported earlier. Additionally, we identified complementary roles of Snf1 and Snf4. Similar to the function of AMPK in humans, our findings showed that Snf1 is a low-energy checkpoint and that yeast can be used more extensively as a model system for studying the molecular mechanisms underlying the global regulation of AMPK in mammals, failure of which leads to metabolic diseases. PMID:19888214
The gene for pancreatic polypeptide (PPY) and the anonymous marker D17S78 are within 45 kb of each other on chromosome 17q21

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

Chandrasekharappa, S.C.; King, S.E.; Lee, Y.H.

1994-05-15

A gene for early-onset breast and ovarian cancer (BRCA1) has been localized to a small region of chromosome 17q21. A combination of genetic linkage studies, radiation-reduced hybrid analysis, and physical mapping by FISH has identified several genes/markers that lie in this interval. Among these are the gene encoding pancreatic polypeptide (PPY) and a polymorphic marker at locus D17S78. Efforts to construct a physical map of this region by isolating a large number of yeast artificial chromosome (YAC) and cosmid clones demonstrate that PPY and D17S78 are present within the same cosmid clone, and therefore no farther than 45 kb apart.more » This observation takes on particular significance since it excludes a recently described BRCA1 candidate gene from the interval defined by meiotic mapping. Although PPY and D17S78 were found to be no farther than 45 kb apart, identification of a smaller fragment that hybridizes to both probes would indicate that these two are much closer. The probe p131 and the gene PPY were previously mapped to 17q21-q23 and to the proximal long arm of chromosome 17, respectively. The demonstration of the close proximity of these markers should allow them to be treated as a single locus in terms of long-range genomic mapping of this region, and the genomic clones isolated should serve as useful resources for the identification of the BRCA1 gene. Analysis of a large number of a familial and spordic breast and ovarian cancers has identified frequent loss of heterozygosity near the BRCA1 locus. A recent report has suggested the responsible interval lies just telomeric to PPY, and a suggested candidate gene (MCD) for BRCA1 was found to be somatically rearranged in two of several hundred sporadic breast tumors.« less
HomPPI: a class of sequence homology based protein-protein interface prediction methods

PubMed Central

2011-01-01

Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI), which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the
In silico modeling of the yeast protein and protein family interaction network

NASA Astrophysics Data System (ADS)

Goh, K.-I.; Kahng, B.; Kim, D.

2004-03-01

Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.
Association of Proton Pump Inhibitor (PPI) Use with Energy Intake, Physical Activity, and Weight Gain

PubMed Central

Czwornog, Jennifer L.; Austin, Gregory L.

2015-01-01

Studies suggest proton pump inhibitor (PPI) use impacts body weight regulation, though the effect of PPIs on energy intake, energy extraction, and energy expenditure is unknown. We used data on 3073 eligible adults from the National Health and Nutrition Examination Survey (NHANES). Medication use, energy intake, diet composition, and physical activity were extracted from NHANES. Multivariate regression models included confounding variables. Daily energy intake was similar between PPI users and non-users (p = 0.41). Diet composition was similar between the two groups, except that PPI users consumed a slightly greater proportion of calories from fat (34.5% vs. 33.2%; p = 0.02). PPI users rated themselves as being as physically active as their age/gender-matched peers and reported similar frequencies of walking or biking. However, PPI users were less likely to have participated in muscle-strengthening activities (OR: 0.53; 95% CI: 0.30–0.95). PPI users reported similar sedentary behaviors to non-users. Male PPI users had an increase in weight (of 1.52 ± 0.59 kg; p = 0.021) over the previous year compared to non-users, while female PPI users had a non-significant increase in weight. The potential mechanisms for PPI-associated weight gain are unclear as we did not find evidence for significant differences in energy intake or markers of energy expenditure. PMID:26492268
Dielectric and electrical studies of PVC-PPy blends in dilute solution of THF

NASA Astrophysics Data System (ADS)

Sharma, Deepika; Tripathi, Deepti

2018-05-01

An influence of adding Polypyrrole (PPy) which is an intrinsically conducting polymer (ICP), on the dielectric dispersion behavior of Polyvinyl chloride (PVC) in dilute solution of Tetrahydrofuran (THF) at low frequency is reported. The blends of PVC with PPy forms colloidal suspension in THF. The dielectric dispersion study of PVC-PPy blends in THF has been carried out in the frequency range of 20 Hz to 2 MHz at temperature of 303K. The effect of increasing PPy concentration on dielectric and electrical parameters such as complex dielectric function [ɛ*(ω)], loss tangent [tan δ], complex electric modulus [M*(ω)], ac conductivity [σac], and complex impedance [Z*(ω)] of PVC - PPy blends in THF solution were studied. The electrode polarization and ionic conduction appears to have dominant influence on the complex dielectric constant in the low frequency region. The relaxation time values corresponding to these two phenomena are also reported.

Heat Shock Partially Dissociates the Overlapping Modules of the Yeast Protein-Protein Interaction Network: A Systems Level Model of Adaptation

PubMed Central

Mihalik, Ágoston; Csermely, Peter

2011-01-01

Network analysis became a powerful tool giving new insights to the understanding of cellular behavior. Heat shock, the archetype of stress responses, is a well-characterized and simple model of cellular dynamics. S. cerevisiae is an appropriate model organism, since both its protein-protein interaction network (interactome) and stress response at the gene expression level have been well characterized. However, the analysis of the reorganization of the yeast interactome during stress has not been investigated yet. We calculated the changes of the interaction-weights of the yeast interactome from the changes of mRNA expression levels upon heat shock. The major finding of our study is that heat shock induced a significant decrease in both the overlaps and connections of yeast interactome modules. In agreement with this the weighted diameter of the yeast interactome had a 4.9-fold increase in heat shock. Several key proteins of the heat shock response became centers of heat shock-induced local communities, as well as bridges providing a residual connection of modules after heat shock. The observed changes resemble to a ‘stratus-cumulus’ type transition of the interactome structure, since the unstressed yeast interactome had a globally connected organization, similar to that of stratus clouds, whereas the heat shocked interactome had a multifocal organization, similar to that of cumulus clouds. Our results showed that heat shock induces a partial disintegration of the global organization of the yeast interactome. This change may be rather general occurring in many types of stresses. Moreover, other complex systems, such as single proteins, social networks and ecosystems may also decrease their inter-modular links, thus develop more compact modules, and display a partial disintegration of their global structure in the initial phase of crisis. Thus, our work may provide a model of a general, system-level adaptation mechanism to environmental changes. PMID:22022244
Pathway connectivity and signaling coordination in the yeast stress-activated signaling network

PubMed Central

Chasman, Deborah; Ho, Yi-Hsuan; Berry, David B; Nemec, Corey M; MacGilvray, Matthew E; Hose, James; Merrill, Anna E; Lee, M Violet; Will, Jessica L; Coon, Joshua J; Ansari, Aseem Z; Craven, Mark; Gasch, Audrey P

2014-01-01

Stressed cells coordinate a multi-faceted response spanning many levels of physiology. Yet knowledge of the complete stress-activated regulatory network as well as design principles for signal integration remains incomplete. We developed an experimental and computational approach to integrate available protein interaction data with gene fitness contributions, mutant transcriptome profiles, and phospho-proteome changes in cells responding to salt stress, to infer the salt-responsive signaling network in yeast. The inferred subnetwork presented many novel predictions by implicating new regulators, uncovering unrecognized crosstalk between known pathways, and pointing to previously unknown ‘hubs’ of signal integration. We exploited these predictions to show that Cdc14 phosphatase is a central hub in the network and that modification of RNA polymerase II coordinates induction of stress-defense genes with reduction of growth-related transcripts. We find that the orthologous human network is enriched for cancer-causing genes, underscoring the importance of the subnetwork's predictions in understanding stress biology. PMID:25411400
Cannabidiol Affects MK-801-Induced Changes in the PPI Learned Response of Capuchin Monkeys (Sapajus spp.).

PubMed

Saletti, Patricia G; Maior, Rafael S; Barros, Marilia; Nishijo, Hisao; Tomaz, Carlos

2017-01-01

There are several lines of evidence indicating a possible therapeutic action of cannabidiol (CBD) in schizophrenia treatment. Studies with rodents have demonstrated that CBD reverses MK-801 effects in prepulse inhibition (PPI) disruption, which may indicate that CBD acts by improving sensorimotor gating deficits. In the present study, we investigated the effects of CBD on a PPI learned response of capuchin monkeys ( Sapajus spp.). A total of seven monkeys were employed in this study. In Experiment 1, we evaluated the CBD (doses of 15, 30, 60 mg/kg, i.p.) effects on PPI. In Experiment 2, the effects of sub-chronic MK-801 (0.02 mg/kg, i.m.) on PPI were challenged by a CBD pre-treatment. No changes in PPI response were observed after CBD-alone administration. However, MK-801 increased the PPI response of our animals. CBD pre-treatment blocked the PPI increase induced by MK-801. Our findings suggest that CBD's reversal of the MK-801 effects on PPI is unlikely to stem from a direct involvement on sensorimotor mechanisms, but may possibly reflect its anxiolytic properties.
Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks

PubMed Central

Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-01-01

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD. PMID:29262568
Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks.

PubMed

Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-11-28

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD.
Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast.

PubMed

Wang, Zhuo; Danziger, Samuel A; Heavner, Benjamin D; Ma, Shuyi; Smith, Jennifer J; Li, Song; Herricks, Thurston; Simeonidis, Evangelos; Baliga, Nitin S; Aitchison, John D; Price, Nathan D

2017-05-01

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.
In Silico Enhancing M. tuberculosis Protein Interaction Networks in STRING To Predict Drug-Resistance Pathways and Pharmacological Risks.

PubMed

Mei, Suyu

2018-05-04

Bacterial protein-protein interaction (PPI) networks are significant to reveal the machinery of signal transduction and drug resistance within bacterial cells. The database STRING has collected a large number of bacterial pathogen PPI networks, but most of the data are of low quality without being experimentally or computationally validated, thus restricting its further biomedical applications. We exploit the experimental data via four solutions to enhance the quality of M. tuberculosis H37Rv (MTB) PPI networks in STRING. Computational results show that the experimental data derived jointly by two-hybrid and copurification approaches are the most reliable to train an L 2 -regularized logistic regression model for MTB PPI network validation. On the basis of the validated MTB PPI networks, we further study the three problems via breadth-first graph search algorithm: (1) discovery of MTB drug-resistance pathways through searching for the paths between known drug-target genes and drug-resistance genes, (2) choosing potential cotarget genes via searching for the critical genes located on multiple pathways, and (3) choosing essential drug-target genes via analysis of network degree distribution. In addition, we further combine the validated MTB PPI networks with human PPI networks to analyze the potential pharmacological risks of known and candidate drug-target genes from the point of view of system pharmacology. The evidence from protein structure alignment demonstrates that the drugs that act on MTB target genes could also adversely act on human signaling pathways.
Contractor Past Performance Information (PPI) in Source Selection: A Comparison Study of Public and Private Sector

DTIC Science & Technology

2005-03-17

private sector . However, along the way, Government and private sector industry have begun to disagree about how PPI is collected and how PPI is used. Industry prefers a passive system of collecting delivery and quality data during contract performance, while the Federal Government uses both a passive system (similar to industry) as well as an active system of pulling PPI during contract performance. Industry uses PPI to establish and maintain a preferred vendor list from which to solicit bids, quotes, or proposals, while government uses PPI to assess
Identification of infection- and defense-related genes via a dynamic host-pathogen interaction network using a Candida albicans-zebrafish infection model.

PubMed

Kuo, Zong-Yu; Chuang, Yung-Jen; Chao, Chun-Cheih; Liu, Fu-Chen; Lan, Chung-Yu; Chen, Bor-Sen

2013-01-01

Candida albicans infections and candidiasis are difficult to treat and create very serious therapeutic challenges. In this study, based on interactive time profile microarray data of C. albicans and zebrafish during infection, the infection-related protein-protein interaction (PPI) networks of the two species and the intercellular PPI network between host and pathogen were simultaneously constructed by a dynamic interaction model, modeled as an integrated network consisting of intercellular invasion and cellular defense processes during infection. The signal transduction pathways in regulating morphogenesis and hyphal growth of C. albicans were further investigated based on significant interactions found in the intercellular PPI network. Two cellular networks were also developed corresponding to the different infection stages (adhesion and invasion), and then compared with each other to identify proteins from which we can gain more insight into the pathogenic role of hyphal development in the C. albicans infection process. Important defense-related proteins in zebrafish were predicted using the same approach. The hyphal growth PPI network, zebrafish PPI network and host-pathogen intercellular PPI network were combined to form an integrated infectious PPI network that helps us understand the systematic mechanisms underlying the pathogenicity of C. albicans and the immune response of the host, and may help improve medical therapies and facilitate the development of new antifungal drugs. Copyright © 2013 S. Karger AG, Basel.
Easily fabricated and lightweight PPy/PDA/AgNW composites for excellent electromagnetic interference shielding.

PubMed

Wang, Yan; Gu, Fu-Qiang; Ni, Li-Juan; Liang, Kun; Marcus, Kyle; Liu, Shu-Li; Yang, Fan; Chen, Jin-Ju; Feng, Zhe-Sheng

2017-11-30

Conductive polymer composites (CPCs) containing nanoscale conductive fillers have been widely studied for their potential use in various applications. In this paper, polypyrrole (PPy)/polydopamine (PDA)/silver nanowire (AgNW) composites with high electromagnetic interference (EMI) shielding performance, good adhesion ability and light weight are successfully fabricated via a simple in situ polymerization method followed by a mixture process. Benefiting from the intrinsic adhesion properties of PDA, the adhesion ability and mechanical properties of the PPy/PDA/AgNW composites are significantly improved. The incorporation of AgNWs endows the functionalized PPy with tunable electrical conductivity and enhanced EMI shielding effectiveness (SE). By adjusting the AgNW loading degree in the PPy/PDA/AgNW composites from 0 to 50 wt%, the electrical conductivity of the composites greatly increases from 0.01 to 1206.72 S cm -1 , and the EMI SE of the composites changes from 6.5 to 48.4 dB accordingly (8.0-12.0 GHz, X-band). Moreover, due to the extremely low density of PPy, the PPy/PDA/AgNW (20 wt%) composites show a superior light weight of 0.28 g cm -3 . In general, it can be concluded that the PPy/PDA/AgNW composites with tunable electrical conductivity, good adhesion properties and light weight can be used as excellent EMI shielding materials.
Discrete dynamical system modelling for gene regulatory networks of 5-hydroxymethylfurfural tolerance for ethanologenic yeast.

PubMed

Song, M; Ouyang, Z; Liu, Z L

2009-05-01

Composed of linear difference equations, a discrete dynamical system (DDS) model was designed to reconstruct transcriptional regulations in gene regulatory networks (GRNs) for ethanologenic yeast Saccharomyces cerevisiae in response to 5-hydroxymethylfurfural (HMF), a bioethanol conversion inhibitor. The modelling aims at identification of a system of linear difference equations to represent temporal interactions among significantly expressed genes. Power stability is imposed on a system model under the normal condition in the absence of the inhibitor. Non-uniform sampling, typical in a time-course experimental design, is addressed by a log-time domain interpolation. A statistically significant DDS model of the yeast GRN derived from time-course gene expression measurements by exposure to HMF, revealed several verified transcriptional regulation events. These events implicate Yap1 and Pdr3, transcription factors consistently known for their regulatory roles by other studies or postulated by independent sequence motif analysis, suggesting their involvement in yeast tolerance and detoxification of the inhibitor.
Protein-Protein Interaction Network and Gene Ontology

NASA Astrophysics Data System (ADS)

Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.
Three-Dimensional Networked Metal-Organic Frameworks with Conductive Polypyrrole Tubes for Flexible Supercapacitors.

PubMed

Xu, Xingtao; Tang, Jing; Qian, Huayu; Hou, Shujin; Bando, Yoshio; Hossain, Md Shahriar A; Pan, Likun; Yamauchi, Yusuke

2017-11-08

Metal-organic frameworks (MOFs) with high porosity and a regular porous structure have emerged as a promising electrode material for supercapacitors, but their poor electrical conductivity limits their utilization efficiency and capacitive performance. To increase the overall electrical conductivity as well as the efficiency of MOF particles, three-dimensional networked MOFs are developed via using preprepared conductive polypyrrole (PPy) tubes as the support for in situ growth of MOF particles. As a result, the highly conductive PPy tubes that run through the MOF particles not only increase the electron transfer between MOF particles and maintain the high effective porosity of the MOFs but also endow the MOFs with flexibility. Promoted by such elaborately designed MOF-PPy networks, the specific capacitance of MOF particles has been increased from 99.2 F g -1 for pristine zeolitic imidazolate framework (ZIF)-67 to 597.6 F g -1 for ZIF-PPy networks, indicating the importance of the design of the ZIF-PPy continuous microstructure. Furthermore, a flexible supercapacitor device based on ZIF-PPy networks shows an outstanding areal capacitance of 225.8 mF cm -2 , which is far above other MOFs-based supercapacitors reported up to date, confirming the significance of in situ synthetic chemistry as well as the importance of hybrid materials on the nanoscale.
Using a genetic algorithm to abbreviate the Psychopathic Personality Inventory-Revised (PPI-R).

PubMed

Eisenbarth, Hedwig; Lilienfeld, Scott O; Yarkoni, Tal

2015-03-01

Some self-report measures of personality and personality disorders, including the widely used Psychopathic Personality Inventory-Revised (PPI-R), are lengthy and time-intensive. In recent work, we introduced an automated genetic algorithm (GA)-based method for abbreviating psychometric measures. In Study 1, we used this approach to generate a short (40-item) version of the PPI-R using 3 large-N German student samples (total N = 1,590). The abbreviated measure displayed high convergent correlations with the original PPI-R, and outperformed an alternative measure constructed using a conventional approach. Study 2 tested the convergent and discriminant validity of this short version in a fourth student sample (N = 206) using sensation-seeking and sensitivity to reward and punishment scales, again demonstrating similar convergent and discriminant validity for the PPI-R-40 compared with the full version. In a fifth community sample of North American participants acquired using Amazon Mechanical Turk, the PPI-R-40 showed similarly high convergent correlations, demonstrating stability across language, culture, and data-collection method. Taken together, these studies suggest that the GA approach is a viable method for abbreviating measures of psychopathy, and perhaps personality measures in general. 2015 APA, all rights reserved
Evidence for dynamically organized modularity in the yeast protein-protein interaction network

NASA Astrophysics Data System (ADS)

Han, Jing-Dong J.; Bertin, Nicolas; Hao, Tong; Goldberg, Debra S.; Berriz, Gabriel F.; Zhang, Lan V.; Dupuy, Denis; Walhout, Albertha J. M.; Cusick, Michael E.; Roth, Frederick P.; Vidal, Marc

2004-07-01

In apparently scale-free protein-protein interaction networks, or `interactome' networks, most proteins interact with few partners, whereas a small but significant proportion of proteins, the `hubs', interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs. A link between the potential scale-free topology of interactome networks and genetic robustness seems to exist, because knockouts of yeast genes encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs. Here we investigate how hubs might contribute to robustness and other cellular properties for protein-protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: `party' hubs, which interact with most of their partners simultaneously, and `date' hubs, which bind their different partners at different times or locations. Both in silico studies of network connectivity and genetic interactions described in vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes-or modules -to each other, whereas party hubs function inside modules.
HubAlign: an accurate and efficient method for global alignment of protein-protein interaction networks.

PubMed

Hashemifar, Somaye; Xu, Jinbo

2014-09-01

High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data. The study of PPI networks, such as comparative analysis, shall benefit the understanding of life process and diseases at the molecular level. One way of comparative analysis is to align PPI networks to identify conserved or species-specific subnetwork motifs. A few methods have been developed for global PPI network alignment, but it still remains challenging in terms of both accuracy and efficiency. This paper presents a novel global network alignment algorithm, denoted as HubAlign, that makes use of both network topology and sequence homology information, based upon the observation that topologically important proteins in a PPI network usually are much more conserved and thus, more likely to be aligned. HubAlign uses a minimum-degree heuristic algorithm to estimate the topological and functional importance of a protein from the global network topology information. Then HubAlign aligns topologically important proteins first and gradually extends the alignment to the whole network. Extensive tests indicate that HubAlign greatly outperforms several popular methods in terms of both accuracy and efficiency, especially in detecting functionally similar proteins. HubAlign is available freely for non-commercial purposes at http://ttic.uchicago.edu/∼hashemifar/software/HubAlign.zip. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.
Evolution versus "intelligent design": comparing the topology of protein-protein interaction networks to the Internet.

PubMed

Yang, Q; Siganos, G; Faloutsos, M; Lonardi, S

2006-01-01

Recent research efforts have made available genome-wide, high-throughput protein-protein interaction (PPI) maps for several model organisms. This has enabled the systematic analysis of PPI networks, which has become one of the primary challenges for the system biology community. In this study, we attempt to understand better the topological structure of PPI networks by comparing them against man-made communication networks, and more specifically, the Internet. Our comparative study is based on a comprehensive set of graph metrics. Our results exhibit an interesting dichotomy. On the one hand, both networks share several macroscopic properties such as scale-free and small-world properties. On the other hand, the two networks exhibit significant topological differences, such as the cliqueishness of the highest degree nodes. We attribute these differences to the distinct design principles and constraints that both networks are assumed to satisfy. We speculate that the evolutionary constraints that favor the survivability and diversification are behind the building process of PPI networks, whereas the leading force in shaping the Internet topology is a decentralized optimization process geared towards efficient node communication.
FACETS: multi-faceted functional decomposition of protein interaction networks.

PubMed

Seah, Boon-Siew; Bhowmick, Sourav S; Dewey, C Forbes

2012-10-15

The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein-protein interaction (PPI) network using graph theoretic analysis. Despite the recent progress, systems level analysis of high-throughput PPIs remains a daunting task because of the amount of data they present. In this article, we propose a novel PPI network decomposition algorithm called FACETS in order to make sense of the deluge of interaction data using Gene Ontology (GO) annotations. FACETS finds not just a single functional decomposition of the PPI network, but a multi-faceted atlas of functional decompositions that portray alternative perspectives of the functional landscape of the underlying PPI network. Each facet in the atlas represents a distinct interpretation of how the network can be functionally decomposed and organized. Our algorithm maximizes interpretative value of the atlas by optimizing inter-facet orthogonality and intra-facet cluster modularity. We tested our algorithm on the global networks from IntAct, and compared it with gold standard datasets from MIPS and KEGG. We demonstrated the performance of FACETS. We also performed a case study that illustrates the utility of our approach. Supplementary data are available at the Bioinformatics online. Our software is available freely for non-commercial purposes from: http://www.cais.ntu.edu.sg/~assourav/Facets/
Highly biological active antibiofilm, anticancer and osteoblast adhesion efficacy from MWCNT/PPy/Pd nanocomposite

NASA Astrophysics Data System (ADS)

Murugesan, Balaji; Sonamuthu, Jegatheeswaran; Samayanan, Selvam; Arumugam, Sangili; Mahalingam, Sundrarajan

2018-03-01

Multifunctional biologically active materials have approached for antibiofilm, anticancer and osteoblast adhesion activities with significant biomedical applications, owing to this MWCNT modified with polypyrrole (PPy) matrix with the incorporation of palladium nanoparticles (NPs). The synthesized composite displays a tube-shaped morphology with highly dispersed crystalline Pd NPs, which are established through XRD, SEM, TEM and SAED studies. The pyridinic-N(∼402.7), pyrrolic sbnd N (∼400.8) peak in XPS spectra evidenced the interaction of PPy with Pd and MWCNT. Polymer stretching frequencies in FTIR and Raman spectroscopy proves successful formation of PPy and the Pd-N (1609 cm-1) interaction. In the stability aspect, it is up to 58.73% mass withstood at 800 °C in TGA analysis. The composite exhibits an efficient Anti-biofilm against a set of bacterial stain with planktonic cell growth. In vitro cytotoxicity of Vero and HeLa cell line assess the composites toxicity and anticancer activity up to 100 μg. The outcome of cell adhesions showed that human osteosarcoma cells (HOS) can adhere and to develop on the MWCNT/PPy/Pd composites. Furthermore, the proliferation of cells on MWCNT/PPy/Pd composites was also proved the biocompatibility of the composites against HOS cells. These results suggest that Pd-doped MWCNT/PPy composites are promising materials for biomedical applications.
Delineating functional principles of the bow tie structure of a kinase-phosphatase network in the budding yeast.

PubMed

Abd-Rabbo, Diala; Michnick, Stephen W

2017-03-16

Kinases and phosphatases (KP) form complex self-regulating networks essential for cellular signal processing. In spite of having a wealth of data about interactions among KPs and their substrates, we have very limited models of the structures of the directed networks they form and consequently our ability to formulate hypotheses about how their structure determines the flow of information in these networks is restricted. We assembled and studied the largest bona fide kinase-phosphatase network (KP-Net) known to date for the yeast Saccharomyces cerevisiae. Application of the vertex sort (VS) algorithm on the KP-Net allowed us to elucidate its hierarchical structure in which nodes are sorted into top, core and bottom layers, forming a bow tie structure with a strongly connected core layer. Surprisingly, phosphatases tend to sort into the top layer, implying they are less regulated by phosphorylation than kinases. Superposition of the widest range of KP biological properties over the KP-Net hierarchy shows that core layer KPs: (i), receive the largest number of inputs; (ii), form bottlenecks implicated in multiple pathways and in decision-making; (iii), and are among the most regulated KPs both temporally and spatially. Moreover, top layer KPs are more abundant and less noisy than those in the bottom layer. Finally, we showed that the VS algorithm depends on node degrees without biasing the biological results of the sorted network. The VS algorithm is available as an R package ( https://cran.r-project.org/web/packages/VertexSort/index.html ). The KP-Net model we propose possesses a bow tie hierarchical structure in which the top layer appears to ensure highest fidelity and the core layer appears to mediate signal integration and cell state-dependent signal interpretation. Our model of the yeast KP-Net provides both functional insight into its organization as we understand today and a framework for future investigation of information processing in yeast and eukaryotes

Majority of symptoms in esophageal reflux PPI non-responders are not related to reflux

PubMed Central

Roman, Sabine; Keefer, Laurie; Imam, Hala; Korrapati, Praneet; Mogni, Benjamin; Eident, Kate; Friesen, Laurel; Kahrilas, Peter J; Martinovich, Zoran; Pandolfino, John

2015-01-01

Background Genesis of persistent gastro-esophageal reflux symptoms despite proton pump inhibitor (PPI) therapy is not fully understood. We aimed at determining reflux patterns on 24-h pH-impedance monitoring performed on PPI and correlating impedance patterns and symptom occurrence in PPI non-responders. Methods 78 PPI non-responder patients underwent 24-h pH-impedance monitoring on PPI. Reflux impedance characterization included gastric and supragastric belches and proximal extent of reflux. Symptoms were considered associated with reflux if occurring within 5 min after a reflux event. Patients were classified into 3 groups: persistent acid reflux (acid esophageal exposure (AET) >5% of time), reflux sensitivity (AET<5%, symptom index (SI) ≥50%), and functional symptoms (AET<5%, SI<50%). Dominant impedance pattern was determined for each patient. Key results 7 patients (9%) had persistent acid reflux, 28 (36%) reflux sensitivity and 43 (55%) functional symptoms. A total of 4,296 reflux events were identified (median per patient 45 (range 4–221)). Although liquid reflux was the most common pattern in all groups, patients with reflux sensitivity and functional symptoms had much more variability in their pattern profile with a large proportion being associated with gastric and supra-gastric belching. Only 417 reflux events (9.7%) were associated with symptoms. Reflux with a supragastric component and proximal extent were more likely to be associated with symptoms. Conclusions & Inferences The impedance reflux profile in PPI non-responders was heterogeneous and the majority of reflux events were not associated with symptoms. Thus, the treatment of PPI non-responders should focus on mechanisms beyond reflux, such as visceral hypersensitivity and hypervigilance. PMID:26337396
A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks.

PubMed

Laomettachit, Teeraphan; Chen, Katherine C; Baumann, William T; Tyson, John J

2016-01-01

To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a "standard component" modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with "standard components" can capture in quantitative detail many essential properties of cell cycle control in budding yeast.
A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks

PubMed Central

Laomettachit, Teeraphan; Chen, Katherine C.; Baumann, William T.

2016-01-01

To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a “standard component” modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with “standard components” can capture in quantitative detail many essential properties of cell cycle control in budding yeast. PMID:27187804
Examining the necessity for and utility of the Psychopathic Personality Inventory-Revised (PPI-R) validity scales.

PubMed

Anderson, Jaime L; Sellbom, Martin; Wygant, Dustin B; Edens, John F

2013-10-01

The present study aimed to investigate the need for and utility of the Psychopathic Personality Inventory-Revised (PPI-R) Deviant Responding (DR) and Virtuous Responding (VR) validity scales in identifying overreporting and underreporting, respectively. Since the PPI-R was published, there has not been an independent peer-reviewed examination of these scales. Participants were 384 undergraduate individuals asked to respond to the PPI-R under standard, underreporting, or overreporting instructions. A comparison group consisting of 200 forensic psychiatric patients was also used for the overreporting analyses. Effects of response bias on mean elevations on the PPI-R substantive scales were examined along with the effects on the PPI-R total, factor, and content scales' correlations with other relevant extratest measures of psychopathy. Mean elevations differed significantly, and correlations with extratest measures of psychopathy were significantly lower. Substantial decrement in psychometric validity of PPI-R scores was observed in the simulation conditions. In addition, the utility of the PPI-R validity scales in differentiating between groups was also determined. Both the VR and DR scales showed utility in differentiating between their respective dissimulation condition and the comparison groups, with acceptable rates of sensitivity and specificity. PsycINFO Database Record (c) 2013 APA, all rights reserved
A patient and public involvement (PPI) toolkit for meaningful and flexible involvement in clinical trials - a work in progress.

PubMed

Bagley, Heather J; Short, Hannah; Harman, Nicola L; Hickey, Helen R; Gamble, Carrol L; Woolfall, Kerry; Young, Bridget; Williamson, Paula R

2016-01-01

Funders of research are increasingly requiring researchers to involve patients and the public in their research. Patient and public involvement (PPI) in research can potentially help researchers make sure that the design of their research is relevant, that it is participant friendly and ethically sound. Using and sharing PPI resources can benefit those involved in undertaking PPI, but existing PPI resources are not used consistently and this can lead to duplication of effort. This paper describes how we are developing a toolkit to support clinical trials teams in a clinical trials unit. The toolkit will provide a key 'off the shelf' resource to support trial teams with limited resources, in undertaking PPI. Key activities in further developing and maintaining the toolkit are to: ● listen to the views and experience of both research teams and patient and public contributors who use the tools; ● modify the tools based on our experience of using them; ● identify the need for future tools; ● update the toolkit based on any newly identified resources that come to light; ● raise awareness of the toolkit and ● work in collaboration with others to either develop or test out PPI resources in order to reduce duplication of work in PPI. Background Patient and public involvement (PPI) in research is increasingly a funder requirement due to the potential benefits in the design of relevant, participant friendly, ethically sound research. The use and sharing of resources can benefit PPI, but available resources are not consistently used leading to duplication of effort. This paper describes a developing toolkit to support clinical trials teams to undertake effective and meaningful PPI. Methods The first phase in developing the toolkit was to describe which PPI activities should be considered in the pathway of a clinical trial and at what stage these activities should take place. This pathway was informed through review of the type and timing of PPI activities within
Linear motif-mediated interactions have contributed to the evolution of modularity in complex protein interaction networks.

PubMed

Kim, Inhae; Lee, Heetak; Han, Seong Kyu; Kim, Sanguk

2014-10-01

The modular architecture of protein-protein interaction (PPI) networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs) are more likely to connect different biological modules than strong domain-domain interactions (DDIs). This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution.
Yeast killer systems.

PubMed Central

Magliani, W; Conti, S; Gerloni, M; Bertolotti, D; Polonelli, L

1997-01-01

The killer phenomenon in yeasts has been revealed to be a multicentric model for molecular biologists, virologists, phytopathologists, epidemiologists, industrial and medical microbiologists, mycologists, and pharmacologists. The surprisingly widespread occurrence of the killer phenomenon among taxonomically unrelated microorganisms, including prokaryotic and eukaryotic pathogens, has engendered a new interest in its biological significance as well as its theoretical and practical applications. The search for therapeutic opportunities by using yeast killer systems has conceptually opened new avenues for the prevention and control of life-threatening fungal diseases through the idiotypic network that is apparently exploited by the immune system in the course of natural infections. In this review, the biology, ecology, epidemiology, therapeutics, serology, and idiotypy of yeast killer systems are discussed. PMID:9227858
Context-based retrieval of functional modules in protein-protein interaction networks.

PubMed

Dobay, Maria Pamela; Stertz, Silke; Delorenzi, Mauro

2017-03-27

Various techniques have been developed for identifying the most probable interactants of a protein under a given biological context. In this article, we dissect the effects of the choice of the protein-protein interaction network (PPI) and the manipulation of PPI settings on the network neighborhood of the influenza A virus (IAV) network, as well as hits in genome-wide small interfering RNA screen results for IAV host factors. We investigate the potential of context filtering, which uses text mining evidence linked to PPI edges, as a complement to the edge confidence scores typically provided in PPIs for filtering, for obtaining more biologically relevant network neighborhoods. Here, we estimate the maximum performance of context filtering to isolate a Kyoto Encyclopedia of Genes and Genomes (KEGG) network Ki from a union of KEGG networks and its network neighborhood. The work gives insights on the use of human PPIs in network neighborhood approaches for functional inference. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Characterization of recombinant PPi-dependent 6-phosphofructokinases from Methylosinus trichosporium OB3b and Methylobacterium nodulans ORS 2060.

PubMed

Rozova, O N; Khmelenina, V N; Trotsenko, Y A

2012-03-01

The properties of the purified recombinant PPi-dependent 6-phosphofructokinases (PPi-PFKs) from the methanotroph Methylosinus trichosporium OB3b and rhizospheric phytosymbiont Methylobacterium nodulans ORS 2060 were determined. The dependence of activities of PPi-PFK-His(6)-tag from Ms. trichosporium OB3b (6 × 45 kDa) and PPi-PFK from Mb. nodulans ORS 2060 (4 × 43 kDa) on the concentrations of substrates of forward and reverse reactions conformed to Michaelis-Menten kinetics. Besides fructose-6-phosphate, the enzymes also phosphorylated sedoheptulose-7-phosphate. ADP or AMP (1 mM each) inhibited activity of the Ms. trichosporium PPi-PFK but did not affect the activity of the Mb. nodulans enzyme. Preference of PPi-PFKs to fructose-1,6-bisphosphate implied a predominant function of the enzymes in hexose phosphate synthesis in these bacteria. PPi-PFKs from the methylotrophs have low similarity of translated amino acid sequences (17% identity) and belong to different phylogenetic subgroups of type II 6-phosphofructokinases. The relationship of PPi-PFKs with microaerophilic character of Ms. trichosporium OB3b and adaptation of Mb. nodulans ORS 2060 to anaerobic phase of phytosymbiosis are discussed.
FACETS: multi-faceted functional decomposition of protein interaction networks

PubMed Central

Seah, Boon-Siew; Bhowmick, Sourav S.; Forbes Dewey, C.

2012-01-01

Motivation: The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein–protein interaction (PPI) network using graph theoretic analysis. Despite the recent progress, systems level analysis of high-throughput PPIs remains a daunting task because of the amount of data they present. In this article, we propose a novel PPI network decomposition algorithm called FACETS in order to make sense of the deluge of interaction data using Gene Ontology (GO) annotations. FACETS finds not just a single functional decomposition of the PPI network, but a multi-faceted atlas of functional decompositions that portray alternative perspectives of the functional landscape of the underlying PPI network. Each facet in the atlas represents a distinct interpretation of how the network can be functionally decomposed and organized. Our algorithm maximizes interpretative value of the atlas by optimizing inter-facet orthogonality and intra-facet cluster modularity. Results: We tested our algorithm on the global networks from IntAct, and compared it with gold standard datasets from MIPS and KEGG. We demonstrated the performance of FACETS. We also performed a case study that illustrates the utility of our approach. Contact: seah0097@ntu.edu.sg or assourav@ntu.edu.sg Supplementary information: Supplementary data are available at the Bioinformatics online. Availability: Our software is available freely for non-commercial purposes from: http://www.cais.ntu.edu.sg/∼assourav/Facets/ PMID:22908217
Development and characterization of surface engineered PPI dendrimers for targeted drug delivery.

PubMed

Kaur, Avleen; Jain, Keerti; Mehra, Neelesh Kumar; Jain, N K

2017-05-01

In this study, we reported folate-conjugated polypropylene imine dendrimers (FA-PPI) as efficient carrier for model anticancer drug, methotrexate (MTX), for pH-sensitive drug release, selective targeting to cancer cells, and anticancer activity. In the in vitro drug release studies this nanoconjugate of MTX showed initial rapid release followed by gradual slow release, and the drug release was found to be pH sensitive with greater release at acidic pH. The ex vivo investigations with human breast cancer cell lines, MCF-7, showed enhanced cytotoxicity of MTX-FA-PPI with significantly enhanced intracellular uptake. The biofate of nanoconjugate was determined in Wistar rat where MTX-FA-PPI showed 37.79-fold increase in the concentration of MTX in liver after 24 h in comparison with free MTX formulation.
Functional wiring of the yeast kinome revealed by global analysis of genetic network motifs

PubMed Central

Sharifpoor, Sara; van Dyk, Dewald; Costanzo, Michael; Baryshnikova, Anastasia; Friesen, Helena; Douglas, Alison C.; Youn, Ji-Young; VanderSluis, Benjamin; Myers, Chad L.; Papp, Balázs; Boone, Charles; Andrews, Brenda J.

2012-01-01

A combinatorial genetic perturbation strategy was applied to interrogate the yeast kinome on a genome-wide scale. We assessed the global effects of gene overexpression or gene deletion to map an integrated genetic interaction network of synthetic dosage lethal (SDL) and loss-of-function genetic interactions (GIs) for 92 kinases, producing a meta-network of 8700 GIs enriched for pathways known to be regulated by cognate kinases. Kinases most sensitive to dosage perturbations had constitutive cell cycle or cell polarity functions under standard growth conditions. Condition-specific screens confirmed that the spectrum of kinase dosage interactions can be expanded substantially in activating conditions. An integrated network composed of systematic SDL, negative and positive loss-of-function GIs, and literature-curated kinase–substrate interactions revealed kinase-dependent regulatory motifs predictive of novel gene-specific phenotypes. Our study provides a valuable resource to unravel novel functional relationships and pathways regulated by kinases and outlines a general strategy for deciphering mutant phenotypes from large-scale GI networks. PMID:22282571
Feasibility of MR Imaging/MR Spectroscopy-Planned Focal Partial Salvage Permanent Prostate Implant (PPI) for Localized Recurrence After Initial PPI for Prostate Cancer

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

Hsu, Charles C., E-mail: hsucc@radonc.ucsf.edu; Hsu, Howard; Pickett, Barby

Purpose: To assess the feasibility of magnetic resonance imaging (MRI)-planned partial salvage permanent prostate implant (psPPI) among patients with biopsy-proven local recurrence after initial PPI without evidence of distant disease. Methods and Materials: From 2003-2009, 15 patients underwent MRI/magnetic resonance spectroscopy (MRS) planning for salvage brachytherapy (psPPI, I-125 [n=14; 144 Gy]; Pd-103 [n=1; 125 Gy]) without hormone therapy. Full dose was prescribed to areas of recurrence and underdosage, without entire prostate implantation. Limiting urethral and rectal toxicity was prioritized. Follow-up was from salvage date to prostate-specific antigen (PSA) concentration failure (Phoenix criteria = nadir + 2.0; ASTRO = 3 consecutivemore » rises), recurrence, distant metastases, or last follow-up PSA level. Progression-free survival (PFS) was defined as no PSA failure or biopsy-proven recurrence without all-cause mortality. Toxicity was scored using Common Terminology Criteria for Adverse Events version 4.0. Results: At salvage, median age was 68 years, and PSA concentration was 3.5 ng/mL (range, 0.9-5.6 ng/mL). Abnormal MRI/MRS findings were evident in 40% of patients. Biopsy-proven recurrences consisted of a single focus (80%) or 2 foci (20%). At recurrence, Gleason score was 6 (67%) or {>=}7 (27%). Median interval between initial and salvage implantation was 69 months (range, 28-132 months). psPPI planning characteristics limited doses to the rectum (mean V100 = 0.5% [0.07 cc]) and urethra (V100 = 12% [0.3 cc]). At median follow-up (23.3 months; range, 8-88 months), treatment failure (n=2) resulted only in localized recurrence; both patients underwent second psPPI with follow-up PSA tests at 12 and 26 months, resulting in 0.6 and 0.7 ng/mL, respectively. American Society for Radiation Oncology PFS rates at 1, 2, and 3 years were 86.7%, 78.4%, and 62.7%, respectively, with 5 patients for whom treatment failed (n=3 with negative transrectal ultrasound
Factor Structure of the Psychopathic Personality Inventory (PPI): Findings from a Large Incarcerated Sample

PubMed Central

Neumann, Craig S.; Malterer, Melanie B.; Newman, Joseph P.

2010-01-01

Recent exploratory factor analysis (EFA) of the Psychopathic Personality Inventory (PPI; Lilienfeld, 1990) with a community sample suggested that the PPI subscales may be comprised of two higher-order factors (Benning et al., 2003). However, little research has examined the PPI structure in offenders. The current study attempted to replicate the Benning et al. two-factor solution using a large (N=1224) incarcerated male sample. Confirmatory factor analysis (CFA) of this model with the full sample resulted in poor model fit. Next, to identify a factor solution that would summarize the offender data, EFA was conducted using a split-half of the total sample, followed by an attempt to replicate the EFA solution via CFA with the other split-half sample. Using the recommendations of Prooijen and van der Kloot (2001) for recovering EFA solutions, model fit results provided some evidence that the EFA solution could be recovered via CFA. However, this model involved extensive cross-loadings of the subscales across three factors, suggesting item overlap across PPI subscales. In sum, the two-factor solution reported by Benning et al. (2003) was not a viable model for the current sample of offenders, and additional research is needed to elucidate the latent structure of the PPI. PMID:18557694
A Novel Hybrid Iron Regulation Network Combines Features from Pathogenic and Nonpathogenic Yeasts.

PubMed

Gerwien, Franziska; Safyan, Abu; Wisgott, Stephanie; Hille, Fabrice; Kaemmer, Philipp; Linde, Jörg; Brunke, Sascha; Kasper, Lydia; Hube, Bernhard

2016-10-18

Iron is an essential micronutrient for both pathogens and their hosts, which restrict iron availability during infections in an effort to prevent microbial growth. Successful human pathogens like the yeast Candida glabrata have thus developed effective iron acquisition strategies. Their regulation has been investigated well for some pathogenic fungi and in the model organism Saccharomyces cerevisiae, which employs an evolutionarily derived system. Here, we show that C. glabrata uses a regulation network largely consisting of components of the S. cerevisiae regulon but also of elements of other pathogenic fungi. Specifically, similarly to baker's yeast, Aft1 is the main positive regulator under iron starvation conditions, while Cth2 degrades mRNAs encoding iron-requiring enzymes. However, unlike the case with S. cerevisiae, a Sef1 ortholog is required for full growth under iron limitation conditions, making C. glabrata an evolutionary intermediate to SEF1-dependent fungal pathogens. Therefore, C. glabrata has evolved an iron homeostasis system which seems to be unique within the pathogenic fungi. The fungus Candida glabrata represents an evolutionarily close relative of the well-studied and benign baker's yeast and model organism Saccharomyces cerevisiae On the other hand, C. glabrata is an important opportunistic human pathogen causing both superficial and systemic infections. The ability to acquire trace metals, in particular, iron, and to tightly regulate this process during infection is considered an important virulence attribute of a variety of pathogens. Importantly, S. cerevisiae uses a highly derivative regulatory system distinct from those of other fungi. Until now, the regulatory mechanism of iron homeostasis in C. glabrata has been mostly unknown. Our study revealed a hybrid iron regulation network that is unique to C. glabrata and is placed at an evolutionary midpoint between those of S. cerevisiae and related fungal pathogens. We thereby
Significant enhancement in volumetric and gravimetric capacitance of Cu-TiO2/PPY composite for supercapacitor application

NASA Astrophysics Data System (ADS)

Purty, B.; Choudhary, R. B.

2018-04-01

Copper doped titanium dioxide-polypyrrole (Cu-TiO2/PPY) composite was successfully synthesized via chemical oxidative in-situ polymerization process. The structural and morphological properties of Cu-TiO2/PPY composite were investigated using X-ray diffractometer (XRD), field emission electron microscopy (FESEM) and transmission electron microscopy(TEM) techniques. The electrochemical properties of as-synthesized composite were studied using cyclic voltammetry (CV), galvanostatic charge discharge (GCD) and electrochemical impedance spectroscopic (EIS) techniques. The novel Cu-TiO2/PPY composite showed enhanced volumetric capacitance ˜714 F cm-1 and gravimetric capacitance ˜674 F g-1 at 1 A g-1. In addition an excellent coulombic efficiency and comparabley low charge transfer resistance than pure PPY suggests improved supercapacitive performance of Cu-TiO2/PPY composite as an electrode material.
Omics Data Complementarity Underlines Functional Cross-Communication in Yeast.

PubMed

Malod-Dognin, Noël; Pržulj, Nataša

2017-06-10

Mapping the complete functional layout of a cell and understanding the cross-talk between different processes are fundamental challenges. They elude us because of the incompleteness and noisiness of molecular data and because of the computational intractability of finding the exact answer. We perform a simple integration of three types of baker's yeast omics data to elucidate the functional organization and lines of cross-functional communication. We examine protein-protein interaction (PPI), co-expression (COEX) and genetic interaction (GI) data, and explore their relationship with the gold standard of functional organization, the Gene Ontology (GO). We utilize a simple framework that identifies functional cross-communication lines in each of the three data types, in GO, and collectively in the integrated model of the three omics data types; we present each of them in our new Functional Organization Map (FOM) model. We compare the FOMs of the three omics datasets with the FOM of GO and find that GI is in best agreement with GO, followed COEX and PPI. We integrate the three FOMs into a unified FOM and find that it is in better agreement with the FOM of GO than those of any omics dataset alone, demonstrating functional complementarity of different omics data.
Discovering disease-associated genes in weighted protein-protein interaction networks

NASA Astrophysics Data System (ADS)

Cui, Ying; Cai, Meng; Stanley, H. Eugene

2018-04-01

Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.
Identifying protein complexes based on brainstorming strategy.

PubMed

Shen, Xianjun; Zhou, Jin; Yi, Li; Hu, Xiaohua; He, Tingting; Yang, Jincai

2016-11-01

Protein complexes comprising of interacting proteins in protein-protein interaction network (PPI network) play a central role in driving biological processes within cells. Recently, more and more swarm intelligence based algorithms to detect protein complexes have been emerging, which have become the research hotspot in proteomics field. In this paper, we propose a novel algorithm for identifying protein complexes based on brainstorming strategy (IPC-BSS), which is integrated into the main idea of swarm intelligence optimization and the improved K-means algorithm. Distance between the nodes in PPI network is defined by combining the network topology and gene ontology (GO) information. Inspired by human brainstorming process, IPC-BSS algorithm firstly selects the clustering center nodes, and then they are separately consolidated with the other nodes with short distance to form initial clusters. Finally, we put forward two ways of updating the initial clusters to search optimal results. Experimental results show that our IPC-BSS algorithm outperforms the other classic algorithms on yeast and human PPI networks, and it obtains many predicted protein complexes with biological significance. Copyright © 2016 Elsevier Inc. All rights reserved.
A Novel Hybrid Iron Regulation Network Combines Features from Pathogenic and Nonpathogenic Yeasts

PubMed Central

Gerwien, Franziska; Safyan, Abu; Wisgott, Stephanie; Hille, Fabrice; Kaemmer, Philipp; Linde, Jörg; Brunke, Sascha; Kasper, Lydia

2016-01-01

ABSTRACT Iron is an essential micronutrient for both pathogens and their hosts, which restrict iron availability during infections in an effort to prevent microbial growth. Successful human pathogens like the yeast Candida glabrata have thus developed effective iron acquisition strategies. Their regulation has been investigated well for some pathogenic fungi and in the model organism Saccharomyces cerevisiae, which employs an evolutionarily derived system. Here, we show that C. glabrata uses a regulation network largely consisting of components of the S. cerevisiae regulon but also of elements of other pathogenic fungi. Specifically, similarly to baker’s yeast, Aft1 is the main positive regulator under iron starvation conditions, while Cth2 degrades mRNAs encoding iron-requiring enzymes. However, unlike the case with S. cerevisiae, a Sef1 ortholog is required for full growth under iron limitation conditions, making C. glabrata an evolutionary intermediate to SEF1-dependent fungal pathogens. Therefore, C. glabrata has evolved an iron homeostasis system which seems to be unique within the pathogenic fungi. PMID:27795405

Novel insights into the architecture and protein interaction network of yeast eIF3.

PubMed

Khoshnevis, Sohail; Hauer, Florian; Milón, Pohl; Stark, Holger; Ficner, Ralf

2012-12-01

Translation initiation in eukaryotes is a multistep process requiring the orchestrated interaction of several eukaryotic initiation factors (eIFs). The largest of these factors, eIF3, forms the scaffold for other initiation factors, promoting their binding to the 40S ribosomal subunit. Biochemical and structural studies on eIF3 need highly pure eIF3. However, natively purified eIF3 comprise complexes containing other proteins such as eIF5. Therefore we have established in vitro reconstitution protocols for Saccharomyces cerevisiae eIF3 using its five recombinantly expressed and purified subunits. This reconstituted eIF3 complex (eIF3(rec)) exhibits the same size and activity as the natively purified eIF3 (eIF3(nat)). The homogeneity and stoichiometry of eIF3(rec) and eIF3(nat) were confirmed by analytical size exclusion chromatography, mass spectrometry, and multi-angle light scattering, demonstrating the presence of one copy of each subunit in the eIF3 complex. The reconstituted and native eIF3 complexes were compared by single-particle electron microscopy showing a high degree of structural conservation. The interaction network between eIF3 proteins was studied by means of limited proteolysis, analytical size exclusion chromatography, in vitro binding assays, and isothermal titration calorimetry, unveiling distinct protein domains and subcomplexes that are critical for the integrity of the protein network in yeast eIF3. Taken together, the data presented here provide a novel procedure to obtain highly pure yeast eIF3, suitable for biochemical and structural analysis, in addition to a detailed picture of the network of protein interactions within this complex.
77 FR 76303 - Notice of Availability of Producer Price Index (PPI) Data Users Survey

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-27

... conducted a survey of PPI data users in late 1976 through early 1977. Since that time, numerous new time series data have been introduced with the goal of fulfilling the needs of data users. This survey will... series, and identify areas for future expansion. DATES: The Producer Price Index (PPI) user survey will...
Factor Structure of the Psychopathic Personality Inventory (PPI): Findings from a Large Incarcerated Sample

ERIC Educational Resources Information Center

Neumann, Craig S.; Malterer, Melanie B.; Newman, Joseph P.

2008-01-01

Exploratory factor analysis (EFA) of the Psychopathic Personality Inventory (PPI; S. O. Lilienfeld, 1990; S. O. Lilienfeld & B. P. Andrews, 1996) with a community sample has suggested that the PPI subscales may comprise 2 higher order factors (S. D. Benning, C. J. Patrick, B. M. Hicks, D. M. Blonigen, & R. F. Krueger, 2003). However,…
Recent Coselection in Human Populations Revealed by Protein–Protein Interaction Network

PubMed Central

Qian, Wei; Zhou, Hang; Tang, Kun

2015-01-01

Genome-wide scans for signals of natural selection in human populations have identified a large number of candidate loci that underlie local adaptations. This is surprising given the relatively short evolutionary time since the divergence of the human population. One hypothesis that has not been formally examined is whether and how the recent human evolution may have been shaped by coselection in the context of complex molecular interactome. In this study, genome-wide signals of selection were scanned in East Asians, Europeans, and Africans using 1000 Genome data, and subsequently mapped onto the protein–protein interaction (PPI) network. We found that the candidate genes of recent positive selection localized significantly closer to each other on the PPI network than expected, revealing substantial clustering of selected genes. Furthermore, gene pairs of shorter PPI network distances showed higher similarities of their recent evolutionary paths than those further apart. Last, subnetworks enriched with recent coselection signals were identified, which are substantially overrepresented in biological pathways related to signal transduction, neurogenesis, and immune function. These results provide the first genome-wide evidence for association of recent selection signals with the PPI network, shedding light on the potential mechanisms of recent coselection in the human genome. PMID:25532814
The yeast actin cytoskeleton.

PubMed

Mishra, Mithilesh; Huang, Junqi; Balasubramanian, Mohan K

2014-03-01

The actin cytoskeleton is a complex network of dynamic polymers, which plays an important role in various fundamental cellular processes, including maintenance of cell shape, polarity, cell division, cell migration, endocytosis, vesicular trafficking, and mechanosensation. Precise spatiotemporal assembly and disassembly of actin structures is regulated by the coordinated activity of about 100 highly conserved accessory proteins, which nucleate, elongate, cross-link, and sever actin filaments. Both in vivo studies in a wide range of organisms from yeast to metazoans and in vitro studies of purified proteins have helped shape the current understanding of actin dynamics and function. Molecular genetics, genome-wide functional analysis, sophisticated real-time imaging, and ultrastructural studies in concert with biochemical analysis have made yeast an attractive model to understand the actin cytoskeleton, its molecular dynamics, and physiological function. Studies of the yeast actin cytoskeleton have contributed substantially in defining the universal mechanism regulating actin assembly and disassembly in eukaryotes. Here, we review some of the important insights generated by the study of actin cytoskeleton in two important yeast models the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.
Identification of Modules in Protein-Protein Interaction Networks

NASA Astrophysics Data System (ADS)

Erten, Sinan; Koyutürk, Mehmet

In biological systems, most processes are carried out through orchestration of multiple interacting molecules. These interactions are often abstracted using network models. A key feature of cellular networks is their modularity, which contributes significantly to the robustness, as well as adaptability of biological systems. Therefore, modularization of cellular networks is likely to be useful in obtaining insights into the working principles of cellular systems, as well as building tractable models of cellular organization and dynamics. A common, high-throughput source of data on molecular interactions is in the form of physical interactions between proteins, which are organized into protein-protein interaction (PPI) networks. This chapter provides an overview on identification and analysis of functional modules in PPI networks, which has been an active area of research in the last decade.
Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

PubMed Central

Vinayagam, Arunachalam; Gibson, Travis E.; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

2016-01-01

The protein–protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as “indispensable,” “neutral,” or “dispensable,” which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network’s control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. PMID:27091990
[Yeast urinary tract infections. Multicentre study in 14 hospitals belonging to the Buenos Aires City Mycology Network].

PubMed

Maldonado, Ivana; Arechavala, Alicia; Guelfand, Liliana; Relloso, Silvia; Garbasz, Claudia

2016-01-01

Urinary tract infections are a frequent ailment in patients in intensive care units. Candida and other yeasts cause 5-12% of these infections. The value of the finding of any yeast is controversial, and there is no consensus about which parameters are adequate for differentiating urinary infections from colonization or contamination. To analyse the epidemiological characteristics of patients with funguria, to determine potential cut-off points in cultures (to distinguish an infection from other conditions), to identify the prevalent yeast species, and to determine the value of a second urine sample. A multicentre study was conducted in intensive care units of 14 hospitals in the Buenos Aires City Mycology Network. The first and second samples of urine from every patient were cultured. The presence of white cells and yeasts in direct examination, colony counts, and the identification of the isolated species, were evaluated. Yeasts grew in 12.2% of the samples. There was no statistical correlation between the number of white cells and the fungal colony-forming units. Eighty five percent of the patients had indwelling catheters. Funguria was not prevalent in women or in patients over the age of 65. Candida albicans, followed by Candida tropicalis, were the most frequently isolated yeasts. Candida parapsilosis and Candida glabrata appeared less frequently. The same species were isolated in 70% of second samples, and in 23% of the cases the second culture was negative. It was not possible to determine a useful cut-off point for colony counts to help in the diagnosis of urinary infections. As in other publications, C. albicans, followed by C. tropicalis, were the most prevalent species. Copyright © 2015 Asociación Española de Micología. Published by Elsevier Espana. All rights reserved.
Frequency of reporting on patient and public involvement (PPI) in research studies published in a general medical journal: a descriptive study.

PubMed

Price, Amy; Schroter, Sara; Snow, Rosamund; Hicks, Melissa; Harmston, Rebecca; Staniszewska, Sophie; Parker, Sam; Richards, Tessa

2018-03-23

While documented plans for patient and public involvement (PPI) in research are required in many grant applications, little is known about how frequently PPI occurs in practice. Low levels of reported PPI may mask actual activity due to limited PPI reporting requirements. This research analysed the frequency and types of reported PPI in the presence and absence of a journal requirement to include this information. A before and after comparison of PPI reported in research papers published in The BMJ before and 1 year after the introduction of a journal policy requiring authors to report if and how they involved patients and the public within their papers. Between 1 June 2013 and 31 May 2014, The BMJ published 189 research papers and 1 (0.5%) reported PPI activity. From 1 June 2015 to 31 May 2016, following the introduction of the policy, The BMJ published 152 research papers of which 16 (11%) reported PPI activity. Patients contributed to grant applications in addition to designing studies through to coauthorship and participation in study dissemination. Patient contributors were often not fully acknowledged; 6 of 17 (35%) papers acknowledged their contributions and 2 (12%) included them as coauthors. Infrequent reporting of PPI activity does not appear to be purely due to a failure of documentation. Reporting of PPI activity increased after the introduction of The BMJ 's policy, but activity both before and after was low and reporting was inconsistent in quality. Journals, funders and research institutions should collaborate to move us from the current situation where PPI is an optional extra to one where PPI is fully embedded in practice throughout the research process. © 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.
Esophageal motor dysfunction plays a key role in GERD with globus sensation--analysis of factors promoting resistance to PPI therapy.

PubMed

Tsutsui, Hideaki; Manabe, Noriaki; Uno, Masako; Imamura, Hiroshi; Kamada, Tomoari; Kusunoki, Hiroaki; Shiotani, Akiko; Hata, Jiro; Harada, Tamotsu; Haruma, Ken

2012-09-01

Patients with gastroesophageal reflux disease (GERD) also have various extra-esophageal symptoms. Laryngopharyngeal reflux disease (LPRD) is a subtype of GERD associated with globus sensation, but proton pump inhibitor (PPI) therapy achieves disappointing results. This study investigated esophageal motility in GERD patients with globus sensation who were resistant to PPI therapy. The subjects were 350 patients with globus sensation. All patients underwent both laryngoscopy and upper gastrointestinal endoscopy to exclude organic disease. After 4 weeks of treatment with rabeprazole sodium (20 mg daily), the patients were divided into PPI-responsive and PPI-resistant groups. Then we investigated esophageal motility in the PPI-resistant group by a multichannel intraluminal impedance and manometry study. A total of 119 patients (55.6%) were resistant to PPI therapy, among whom 57 patients (47.9%) had abnormal esophageal motility. They included 36 patients (66.4%) with ineffective esophageal motility, 9 patients (14.4%) with achalasia, 6 patients (9.6%) with diffuse esophageal spasm, 5 patients (8%) with nutcracker esophagus, and 1 patient (1.6%) with hypertensive lower esophageal sphincter. There were significant differences of upper esophageal sphincter pressure and esophageal body peristalsis between the patients with PPI-resistant LPRD and healthy controls matched for age and sex. Among patients with PPI-resistant LPRD, 47.9% had abnormal esophageal motility.
Ionically Cross-Linked Polymer Networks for the Multiple-Month Release of Small Molecules

PubMed Central

2016-01-01

Long-term (multiple-week or -month) release of small, water-soluble molecules from hydrogels remains a significant pharmaceutical challenge, which is typically overcome at the expense of more-complicated drug carrier designs. Such approaches are payload-specific and include covalent conjugation of drugs to base materials or incorporation of micro- and nanoparticles. As a simpler alternative, here we report a mild and simple method for achieving multiple-month release of small molecules from gel-like polymer networks. Densely cross-linked matrices were prepared through ionotropic gelation of poly(allylamine hydrochloride) (PAH) with either pyrophosphate (PPi) or tripolyphosphate (TPP), all of which are commonly available commercial molecules. The loading of model small molecules (Fast Green FCF and Rhodamine B dyes) within these polymer networks increases with the payload/network binding strength and with the PAH and payload concentrations used during encapsulation. Once loaded into the PAH/PPi and PAH/TPP ionic networks, only a few percent of the payload is released over multiple months. This extended release is achieved regardless of the payload/network binding strength and likely reflects the small hydrodynamic mesh size within the gel-like matrices. Furthermore, the PAH/TPP networks show promising in vitro cytocompatibility with model cells (human dermal fibroblasts), though slight cytotoxic effects were exhibited by the PAH/PPi networks. Taken together, the above findings suggest that PAH/PPi and (especially) PAH/TPP networks might be attractive materials for the multiple-month delivery of drugs and other active molecules (e.g., fragrances or disinfectants). PMID:26811936
E-DNA sensor of Mycobacterium tuberculosis based on electrochemical assembly of nanomaterials (MWCNTs/PPy/PAMAM).

PubMed

Miodek, Anna; Mejri, Nawel; Gomgnimbou, Michel; Sola, Christophe; Korri-Youssoufi, Hafsa

2015-09-15

Two-step electrochemical patterning methods have been employed to elaborate composite nanomaterials formed with multiwalled carbon nanotubes (MWCNTs) coated with polypyrrole (PPy) and redox PAMAM dendrimers. The nanomaterial has been demonstrated as a molecular transducer for electrochemical DNA detection. The nanocomposite MWCNTs-PPy has been formed by wrapping the PPy film on MWCNTs during electrochemical polymerization of pyrrole on the gold electrode. The MWCNTs-PPy layer was modified with PAMAM dendrimers of fourth generation (PAMAM G4) with covalent bonding by electro-oxidation method. Ferrocenyl groups were then attached to the surface as a redox marker. The electrochemical properties of the nanomaterial (MWCNTs-PPy-PAMAM-Fc) were studied using both square wave voltammetry and cyclic voltammetry to demonstrate efficient electron transfer. The nanomaterial shows high performance in the electrochemical detection of DNA hybridization leading to a variation in the electrochemical signal of ferrocene with a detection limit of 0.3 fM. Furthermore, the biosensor demonstrates ability for sensing DNA of rpoB gene of Mycobacterium tuberculosis in real PCR samples. Developed biosensor was suitable for detection of sequences with a single nucleotide polymorphism (SNP) T (TCG/TTG), responsible for resistance of M. tuberculosis to rifampicin drug, and discriminating them from wild-type samples without such mutation. This shows potential of such systems for further application in pathogens diagnostic and therapeutic purpose.
A validity assessment of the Progress out of Poverty Index (PPI)™.

PubMed

Desiere, Sam; Vellema, Wytse; D'Haese, Marijke

2015-04-01

Development organisations need easy-to-use and quick-to-implement indicators to quantify poverty when requested to measure program impact. In this paper we assess the validity of the Progress out of Poverty Index (PPI)™, a country-specific indicator based on ten closed questions on directly observable household characteristics, by its compliance to the SMART criteria. Each response receives a pre-determined score, such that the sum of these scores can be converted into the likelihood the household is living below the poverty line. We focus on the PPI scorecard for Rwanda, which was validated using two national household surveys conducted in 2005/06 and 2010/11. The PPI is Specific, Measurable, Available cost effectively, and Timely available. Yet, its Relevance depends on the way it is used. Although it accurately distinguishes poor from non-poor households, making it a useful reporting tool, its limited sensitivity to changes in poverty status restricts its usefulness for evaluating the impact of development projects. Copyright © 2014 Elsevier Ltd. All rights reserved.
Recent coselection in human populations revealed by protein-protein interaction network.

PubMed

Qian, Wei; Zhou, Hang; Tang, Kun

2014-12-21

Genome-wide scans for signals of natural selection in human populations have identified a large number of candidate loci that underlie local adaptations. This is surprising given the relatively short evolutionary time since the divergence of the human population. One hypothesis that has not been formally examined is whether and how the recent human evolution may have been shaped by coselection in the context of complex molecular interactome. In this study, genome-wide signals of selection were scanned in East Asians, Europeans, and Africans using 1000 Genome data, and subsequently mapped onto the protein-protein interaction (PPI) network. We found that the candidate genes of recent positive selection localized significantly closer to each other on the PPI network than expected, revealing substantial clustering of selected genes. Furthermore, gene pairs of shorter PPI network distances showed higher similarities of their recent evolutionary paths than those further apart. Last, subnetworks enriched with recent coselection signals were identified, which are substantially overrepresented in biological pathways related to signal transduction, neurogenesis, and immune function. These results provide the first genome-wide evidence for association of recent selection signals with the PPI network, shedding light on the potential mechanisms of recent coselection in the human genome. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Oesophageal narrowing on barium oesophagram is more common in adult patients with eosinophilic oesophagitis than PPI-responsive oesophageal eosinophilia.

PubMed

Podboy, A; Katzka, D A; Enders, F; Larson, J J; Geno, D; Kryzer, L; Alexander, J

2016-06-01

To date there have been no clear features that aid in differentiating patients with eosinophilic oesophagitis (EoE) from PPI-responsive oesophageal eosinophilia (PPI-REE). However, barium swallow roentgenography is a more sensitive and specific measure to detect subtle fibrostenotic remodeling changes present in EoE. We aim to characterise any clinical, endoscopic, histiological or barium roentgenographic differences between EoE and PPI-REE. To characterise any clinical, endoscopic, histiological or barium roentgenographic differences between EoE and PPI-REE. We performed a retrospective cohort analysis on data collected from a tertiary referral centre population from 2010 to 2015. Data from 66 patients with EoE and 28 patients with PPI-REE were analysed. Cases were adults who met consensus guidelines for EOE, and had a barium swallow study within 6 months of the index endoscopy. Clinical, endoscopic, histiological and barium swallow findings were collected. Patients with EoE reported similar characteristics as PPI-REE patients, except EoE patients were younger (35.6 vs. 46.6 years; P = 0.011), had earlier symptom onset (29.0 vs. 38.0 years; P = 0.026), and smaller oesophageal diameters on barium swallow (19.5 mm vs. 20; P = 0.042). Patients with EoE were more likely to have distal strictures (EoE 77% vs. 25%; P = 0.02) and, importantly, a greater likelihood of small calibre oesophagus (51.5% vs. 17.9%; P = 0.002). Moreover, EoE patients had a higher probability of developing small calibre oesophagus after 20 years of symptoms (72.3% vs. 30.2%; P = 0.074) compared to PPI-REE patients. When compared with eosinophilic oesophagitis, PPI-REE patients demonstrate findings that suggest PPI-responsive oesophageal eosinophilia to be a later onset, less aggressive form of oesophageal stricturing disease than eosinophilic oesophagitis. © 2016 John Wiley & Sons Ltd.
HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

PubMed

Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

2015-04-01

The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.
PPI/HASI Pressure Measurements in the Atmosphere of Titan

NASA Astrophysics Data System (ADS)

M'akinen, J. T. T.; Harri, A.-M.; Siili, T.; Lehto, A.; Kahanp'a'a, H.; Genzer, M.; Leppelmeier, G. W.; Leinonen, J.

2005-08-01

The Huygens probe descended through the atmosphere of Titan on January 14, 2005, providing an excellent set of observations. As a part of the Huygens Atmospheric Structure Instrument (HASI) measuring several variables, including acceleration, pressure, temperature and atmospheric electricity, the Pressure Profile Instrument (PPI) provided by FMI commenced operations after the deployment of the main parachute and jettisoning of the heat shield at an altitude of about 160 km. Based on aerodynamic considerations, PPI measured the total pressure with a Kiel probe at the end of a boom, connected to the sensor electronics inside the probe through an inlet tube. The instrument performed flawlessly during the 2.5 hour descent and the 0.5 hour surface phase before the termination of radio link between Huygens and the Cassini orbiter. We present an analysis of the pressure data including recreation of the pressure, temperature, altitude, velocity and acceleration profiles as well as an estimate for the level of atmospheric activity on the surface of Titan.
The OncoPPi Portal: an integrative resource to explore and prioritize protein-protein interactions for cancer target discovery. | Office of Cancer Genomics

Cancer.gov

Motivation: As cancer genomics initiatives move toward comprehensive identification of genetic alterations in cancer, attention is now turning to understanding how interactions among these genes lead to the acquisition of tumor hallmarks. Emerging pharmacological and clinical data suggest a highly promising role of cancer-specific protein-protein interactions (PPIs) as druggable cancer targets. However, large-scale experimental identification of cancer-related PPIs remains challenging, and currently available resources to explore oncogenic PPI networks are limited.
Lager Yeast Comes of Age

PubMed Central

2014-01-01

Alcoholic fermentations have accompanied human civilizations throughout our history. Lager yeasts have a several-century-long tradition of providing fresh beer with clean taste. The yeast strains used for lager beer fermentation have long been recognized as hybrids between two Saccharomyces species. We summarize the initial findings on this hybrid nature, the genomics/transcriptomics of lager yeasts, and established targets of strain improvements. Next-generation sequencing has provided fast access to yeast genomes. Its use in population genomics has uncovered many more hybridization events within Saccharomyces species, so that lager yeast hybrids are no longer the exception from the rule. These findings have led us to propose network evolution within Saccharomyces species. This “web of life” recognizes the ability of closely related species to exchange DNA and thus drain from a combined gene pool rather than be limited to a gene pool restricted by speciation. Within the domesticated lager yeasts, two groups, the Saaz and Frohberg groups, can be distinguished based on fermentation characteristics. Recent evidence suggests that these groups share an evolutionary history. We thus propose to refer to the Saaz group as Saccharomyces carlsbergensis and to the Frohberg group as Saccharomyces pastorianus based on their distinct genomes. New insight into the hybrid nature of lager yeast will provide novel directions for future strain improvement. PMID:25084862
Preparation of stable magnetic nanofluids containing Fe3O4@PPy nanoparticles by a novel one-pot route

PubMed Central

2011-01-01

Stable magnetic nanofluids containing Fe3O4@Polypyrrole (PPy) nanoparticles (NPs) were prepared by using a facile and novel method, in which one-pot route was used. FeCl3·6H2O was applied as the iron source, and the oxidizing agent to produce PPy. Trisodium citrate (Na3cit) was used as the reducing reagent to form Fe3O4 NPs. The as-prepared nanofluid can keep long-term stability. The Fe3O4@PPy NPs can still keep dispersing well after the nanofluid has been standing for 1 month and no sedimentation is found. The polymerization reaction of the pyrrole monomers took place with Fe3+ ions as the initiator, in which these Fe3+ ions remained in the solution adsorbed on the surface of the Fe3O4 NPs. Thus, the core-shell NPs of Fe3O4@PPy were obtained. The particle size of the as-prepared Fe3O4@PPy can be easily controlled from 7 to 30 nm by the polymerization reaction of the pyrrole monomers. The steric stabilization and weight of the NPs affect the stability of the nanofluids. The as-prepared Fe3O4@PPy NPs exhibit superparamagnetic behavior. PMID:21711771

Yeast diversity and native vigor for flavor phenotypes.

PubMed

Carrau, Francisco; Gaggero, Carina; Aguilar, Pablo S

2015-03-01

Saccharomyces cerevisiae, the yeast used widely for beer, bread, cider, and wine production, is the most resourceful eukaryotic model used for genetic engineering. A typical concern about using engineered yeasts for food production might be negative consumer perception of genetically modified organisms. However, we believe the true pitfall of using genetically modified yeasts is their limited capacity to either refine or improve the sensory properties of fermented foods under real production conditions. Alternatively, yeast diversity screening to improve the aroma and flavors could offer groundbreaking opportunities in food biotechnology. We propose a 'Yeast Flavor Diversity Screening' strategy which integrates knowledge from sensory analysis and natural whole-genome evolution with information about flavor metabolic networks and their regulation. Copyright © 2015 Elsevier Ltd. All rights reserved.
Reporting and appraising the context, process and impact of PPI on contributors, researchers and the trial during a randomised controlled trial - the 3D study.

PubMed

Mann, Cindy; Chilcott, Simon; Plumb, Katrina; Brooks, Edmund; Man, Mei-See

2018-01-01

Including patient and public involvement (PPI) in health research is thought to improve research but it is hard to be clear exactly how it helps. This is because PPI takes many forms, is sometimes only token and is not always reported clearly. This makes it difficult to combine the evidence so that clear conclusions can be reached about the ingredients of successful PPI and what PPI achieves. Previous research that has tried to combine the evidence has led to several guidelines for researchers to use in setting up and reporting PPI.This paper was written jointly by researchers and PPI contributors as a reflection on our experiences. The aim was to add to the evidence, by giving detail about the use of PPI in a large randomised controlled trial and the effect it had. We were guided by published PPI reporting guidelines. The effects on the trial are shown in a table of changes made because of suggestions from the PPI group. A survey was used to ask PPI contributors and researchers about their experience and effects they had noticed. Three themes were noted: impact on the trial, the effect of involvement on individual researchers and group members, and group environment. The PPI work affected the trial in many ways, including changes to documents used in the trial and advice on qualitative data collection methods and analysis. Individuals reported positive effects, including enjoying being in the group, gaining confidence, and learning how to share views. Patient and public involvement (PPI) is believed to enhance health care delivery research, and is widely required in research proposals. Detailed, standardised reporting of PPI is needed so that strategies to implement more than token PPI that achieves impact can be identified, properly evaluated and reproduced. Impact includes effects on the research, PPI contributors and researchers. Using contributor and researcher perspectives and drawing on published guidelines for reporting PPI, we aimed to reflect on our
Gene regulatory network identification from the yeast cell cycle based on a neuro-fuzzy system.

PubMed

Wang, B H; Lim, J W; Lim, J S

2016-08-30

Many studies exist for reconstructing gene regulatory networks (GRNs). In this paper, we propose a method based on an advanced neuro-fuzzy system, for gene regulatory network reconstruction from microarray time-series data. This approach uses a neural network with a weighted fuzzy function to model the relationships between genes. Fuzzy rules, which determine the regulators of genes, are very simplified through this method. Additionally, a regulator selection procedure is proposed, which extracts the exact dynamic relationship between genes, using the information obtained from the weighted fuzzy function. Time-series related features are extracted from the original data to employ the characteristics of temporal data that are useful for accurate GRN reconstruction. The microarray dataset of the yeast cell cycle was used for our study. We measured the mean squared prediction error for the efficiency of the proposed approach and evaluated the accuracy in terms of precision, sensitivity, and F-score. The proposed method outperformed the other existing approaches.
Mechanical performance of PPy helix tube microactuator

NASA Astrophysics Data System (ADS)

Bahrami Samani, Mehrdad; Spinks, Geoffrey M.; Cook, Christopher

2004-02-01

Conducting polymer actuators with favourable properties such as linearity, high power density and compliance are of increasing demand in micro applications. These materials generate forces over two times larger than produced by mammalian skeletal muscles. They operate to convert electro chemical energy to mechanical stress and strain. On the other hand, the application of conducting polymers is limited by the lack of a full description of the relation between four essential parameters: stress, strain, voltage and current. In this paper, polypyrrole helix tube micro actuator mechanical characteristics are investigated. The electrolyte is propylene carbonate and the dopant is TBA. PF6. The experiments are both in isotonic and isometric conditions and the input parameters are both electrical and mechanical. A dual mode force and length control and potentiostat / galvanostat are utilized for this purpose. Ultimately, the viscoelastic behaviour of the actuator is presented in this paper by a standard stress relaxation test. The effect of electrical stimulus on mechanical parameters is also explored by cyclic voltametry at different scan rates to obtain the best understanding of the actuation mechanism. The results demonstrate that the linear viscoelastic model, which performed well on conducting polymer film actuators, has to be modified to explain the mechanical behaviour of PPy helix tube fibre micro actuators. Secondly, the changes in mechanical properties of PPy need to be considered when modelling electromechanical behaviour.
atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.
Quantum Chemical Design Guidelines for Absorption and Emission Color Tuning of fac-Ir(ppy)₃ Complexes.

PubMed

Natori, Yoshiki; Kitagawa, Yasutaka; Aoki, Shogo; Teramoto, Rena; Tada, Hayato; Era, Iori; Nakano, Masayoshi

2018-03-05

The fac -Ir(ppy)₃ complex, where ppy denotes 2-phenylpyridine, is one of the well-known luminescent metal complexes having a high quantum yield. However, there have been no specific molecular design guidelines for color tuning. For example, it is still unclear how its optical properties are changed when changing substitution groups of ligands. Therefore, in this study, differences in the electronic structures and optical properties among several substituted fac -Ir(ppy)₃ derivatives are examined in detail by density functional theory (DFT) and time-dependent DFT (TD-DFT) calculations. On the basis of those results, we present rational design guidelines for absorption and emission color tuning by modifying the species of substituents and their substitution positions.
Effects of long-term PPI treatment on producing bowel symptoms and SIBO.

PubMed

Compare, Debora; Pica, Loredana; Rocco, Alba; De Giorgi, Francesco; Cuomo, Rosario; Sarnelli, Giovanni; Romano, Marco; Nardone, Gerardo

2011-04-01

Gastroesophageal reflux disease (GERD), including erosive reflux disease and non-erosive reflux disease (NERD), is a chronic disease with a significant negative effect on quality of life. State-of-the-art treatment involves proton pump inhibitors (PPIs). However, relapse of symptoms occurs in the majority of the patients who require recurrent or continuous therapy. Although PPIs are well tolerated, little information is available about gastrointestinal side effects. To evaluate the effects of long-term PPI treatment on development of bowel symptoms and/or small intestinal bacterial overgrowth (SIBO). Patients with NERD not complaining of bowel symptoms were selected by upper endoscopy, 24-h pH-metry and a structured questionnaire concerning severity and frequency of bloating, flatulence, abdominal pain, diarrhoea and constipation. Patients were treated with esomeprazole 20 mg bid for 6 months. Prior to and after 8 weeks and 6 months of therapy, patients received the structured questionnaire and underwent evaluation of SIBO by glucose hydrogen breath test (GHBT). Forty-two patients with NERD were selected out of 554 eligible patients. After 8 weeks of PPI treatment, patients complained of bloating, flatulence, abdominal pain and diarrhoea in 43%, 17%, 7% and 2%, respectively. After 6 months, the incidence of bowel symptoms further increased and GHBT was found positive in 11/42 (26%) patients. By a post hoc analysis, a significant (P < 0·05) percentage of patients (8/42) met Rome III criteria for irritable bowel syndrome. Prolonged PPI treatment may produce bowel symptoms and SIBO; therefore, the strategy of step-down or on-demand PPI therapy should be encouraged in GERD. © 2010 The Authors. European Journal of Clinical Investigation © 2010 Stichting European Society for Clinical Investigation Journal Foundation.
Corrosion Protection Properties of PPy-ND Composite Coating: Sonoelectrochemical Synthesis and Design of Experiment

NASA Astrophysics Data System (ADS)

Ashassi-Sorkhabi, H.; Bagheri, R.; Rezaei-Moghadam, B.

2016-02-01

In this research, the nanocomposite coatings comprising the polypyrrole-nanodiamond, PPy-ND, on St-12 steel electrodes were electro-synthesized using in situ polymerization process under ultrasonic irradiation. The corrosion protection performance and morphology characterization of prepared coatings were investigated by electrochemical methods and scanning electron microscopy, SEM, respectively. Also, the experimental design was employed to determine the best values considering the effective parameters such as the concentration of nanoparticles, the applied current density and synthesis time to achieve the most protective films. A response surface methodology, RSM, involving a central composite design, CCD, was applied to the modeling and optimization of the PPy-ND nanocomposite deposition. Pareto graphic analysis of the parameters indicated that the applied current density and some of the interactions were effective on the response. The electrochemical results proved that the embedment of diamond nanoparticle, DNP, improves the corrosion resistance of PPy coatings significantly. Therefore, desirable correlation exists between predicted data and experimental results.
IntNetDB v1.0: an integrated protein-protein interaction network database generated by a probabilistic model

PubMed Central

Xia, Kai; Dong, Dong; Han, Jing-Dong J

2006-01-01

Background Although protein-protein interaction (PPI) networks have been explored by various experimental methods, the maps so built are still limited in coverage and accuracy. To further expand the PPI network and to extract more accurate information from existing maps, studies have been carried out to integrate various types of functional relationship data. A frequently updated database of computationally analyzed potential PPIs to provide biological researchers with rapid and easy access to analyze original data as a biological network is still lacking. Results By applying a probabilistic model, we integrated 27 heterogeneous genomic, proteomic and functional annotation datasets to predict PPI networks in human. In addition to previously studied data types, we show that phenotypic distances and genetic interactions can also be integrated to predict PPIs. We further built an easy-to-use, updatable integrated PPI database, the Integrated Network Database (IntNetDB) online, to provide automatic prediction and visualization of PPI network among genes of interest. The networks can be visualized in SVG (Scalable Vector Graphics) format for zooming in or out. IntNetDB also provides a tool to extract topologically highly connected network neighborhoods from a specific network for further exploration and research. Using the MCODE (Molecular Complex Detections) algorithm, 190 such neighborhoods were detected among all the predicted interactions. The predicted PPIs can also be mapped to worm, fly and mouse interologs. Conclusion IntNetDB includes 180,010 predicted protein-protein interactions among 9,901 human proteins and represents a useful resource for the research community. Our study has increased prediction coverage by five-fold. IntNetDB also provides easy-to-use network visualization and analysis tools that allow biological researchers unfamiliar with computational biology to access and analyze data over the internet. The web interface of IntNetDB is freely
Synthesis and characterization of a novel tube-in-tube nanostructured PPy/MnO{sub 2}/CNTs composite for supercapacitor

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

Li, Juan, E-mail: lj-panpan@163.com; Beijing National Laboratory for Molecular Sciences; Que, Tingli

2013-02-15

Graphical abstract: A novel tube-in-tube nanostructured PPy/MnO{sub 2}/CNTs composite have been successfully fabricated. Its inner tubules are CNTs and the outer tubules are template-synthesized PPy. Most MnO{sub 2} nanoparticles are sandwiched between the inner and outer wall, some relatively large particles are also latched onto the outside wall of the PPy tube. The composite yields a good electrochemical reversibility through 1000 cycles’ cyclic voltammogram (CV) test and galvanostatic charge–discharge experiments at different current densities. Display Omitted Highlights: ► We fabricate a ternary organic–inorganic complex of PPy/MnO{sub 2}/CNTs composite. ► We characterize its morphological structures and properties by several techniques. ►more » The composite possesses the typical tube-in-tube nanostructures. ► Most MnO{sub 2} nanoparticles are sandwiched between the inner CNTs and outer PPy wall. ► The composite has good electrochemical reversibility for supercapacitor. -- Abstract: Ternary organic–inorganic complex of polypyrrole/manganese dioxide/carbon nanotubes (PPy/MnO{sub 2}/CNTs) composite was prepared by in situ chemical oxidation polymerization of pyrrole in the host of inorganic matrix of MnO{sub 2} and CNTs, using complex of methyl orange (MO)/FeCl{sub 3} was used as a reactive self-degraded soft-template. The morphological structures of the composite were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), high-resolution transmission electron microscopic (HRTEM), Fourier transform infrared spectroscopy (FT-IR) and X-ray diffraction (XRD), respectively. All the results indicate that the PPy/MnO{sub 2}/CNTs composite possesses the typical tube-in-tube nanostructures: the inner tubules are CNTs and the outer tubules are template-synthesized PPy. MnO{sub 2} nanoparticles may either sandwich the space between the inner and outer tubules or directly latch onto the wall of the PPy tubes. The
Constructing Hierarchical Tectorum-like α-Fe2 O3 /PPy Nanoarrays on Carbon Cloth for Solid-State Asymmetric Supercapacitors.

PubMed

Wang, Libin; Yang, Huiling; Liu, Xiaoxiao; Zeng, Rui; Li, Ming; Huang, Yunhui; Hu, Xianluo

2017-01-19

The design of complex heterostructured electrode materials that deliver superior electrochemical performances to their individual counterparts has stimulated intensive research on configuring supercapacitors with high energy and power densities. Herein we fabricate hierarchical tectorum-like α-Fe 2 O 3 /polypyrrole (PPy) nanoarrays (T-Fe 2 O 3 /PPy NAs). The 3D, and interconnected T-Fe 2 O 3 /PPy NAs are successfully grown on conductive carbon cloth through an easy self-sacrificing template and in situ vapor-phase polymerization route under mild conditions. The electrode made of the T-Fe 2 O 3 /PPy NAs exhibits a high areal capacitance of 382.4 mF cm -2 at a current density of 0.5 mA cm -2 and excellent reversibility. The solid-state asymmetric supercapacitor consisting of T-Fe 2 O 3 /PPy NAs and MnO 2 electrodes achieves a high energy density of 0.22 mWh cm -3 at a power density of 165.6 mW cm -3 . © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Decorating MOF-Derived Nanoporous Co/C in Chain-Like Polypyrrole (PPy) Aerogel: A Lightweight Material with Excellent Electromagnetic Absorption.

PubMed

Sun, Xiaodong; Lv, Xuliang; Sui, Mingxu; Weng, Xiaodi; Li, Xiaopeng; Wang, Jijun

2018-05-11

To clear away the harmful effects of the increment of electromagnetic pollution, high performance absorbers with appropriate impedance matching and strong attenuation capacity are strongly desired. In this study, a chain-like PPy aerogel decorated with MOF-derived nanoporous Co/C (Co/C@PPy) has been successfully prepared by a self-assembled polymerization method. With a filler loading ratio of 10 wt %, the composite of Co/C@PPy could achieve a promising electromagnetic absorption performance both in intensity and bandwidth. An optimal reflection loss value of −44.76 dB is achieved, and the effective bandwidth (reflection loss lower than −10 dB) is as large as 6.56 GHz. Furthermore, a composite only loaded with 5 wt % Co/C@PPy also achieves an effective bandwidth of 5.20 GHz, which is even better than numerous reported electromagnetic absorption (EA) materials. The result reveals that the as-fabricated Co/C@PPy—with high absorption intensity, broad bandwidth, and light weight properties—can be utilized as a competitive absorber.
"Omics" of Selenium Biology: A Prospective Study of Plasma Proteome Network Before and After Selenized-Yeast Supplementation in Healthy Men.

PubMed

Sinha, Indu; Karagoz, Kubra; Fogle, Rachel L; Hollenbeak, Christopher S; Zea, Arnold H; Arga, Kazim Y; Stanley, Anne E; Hawkes, Wayne C; Sinha, Raghu

2016-04-01

Low selenium levels have been linked to a higher incidence of cancer and other diseases, including Keshan, Chagas, and Kashin-Beck, and insulin resistance. Additionally, muscle and cardiovascular disorders, immune dysfunction, cancer, neurological disorders, and endocrine function have been associated with mutations in genes encoding for selenoproteins. Selenium biology is complex, and a systems biology approach to study global metabolomics, genomics, and/or proteomics may provide important clues to examining selenium-responsive markers in circulation. In the current investigation, we applied a global proteomics approach on plasma samples collected from a previously conducted, double-blinded placebo controlled clinical study, where men were supplemented with selenized-yeast (Se-Yeast; 300 μg/day, 3.8 μmol/day) or placebo-yeast for 48 weeks. Proteomic analysis was performed by iTRAQ on 8 plasma samples from each arm at baseline and 48 weeks. A total of 161 plasma proteins were identified in both arms. Twenty-two proteins were significantly altered following Se-Yeast supplementation and thirteen proteins were significantly changed after placebo-yeast supplementation in healthy men. The differentially expressed proteins were involved in complement and coagulation pathways, immune functions, lipid metabolism, and insulin resistance. Reconstruction and analysis of protein-protein interaction network around selected proteins revealed several hub proteins. One of the interactions suggested by our analysis, PHLD-APOA4, which is involved in insulin resistance, was subsequently validated by Western blot analysis. Our systems approach illustrates a viable platform for investigating responsive proteomic profile in 'before and after' condition following Se-Yeast supplementation. The nature of proteins identified suggests that selenium may play an important role in complement and coagulation pathways, and insulin resistance.
Influence of Protein Abundance on High-Throughput Protein-Protein Interaction Detection

DTIC Science & Technology

2009-06-05

the interaction data sets we determined, via comparisons with strict randomized simulations , the propensity for essential proteins to selectively...and analysis of high- quality PPI data sets. Materials and Methods We analyzed protein interaction networks for yeast and E. coli determined from Y2H...we reinvestigated the centrality-lethality rule, which implies that proteins having more interactions are more likely to be essential. From analysis
Neonatal hippocampal Tat injections: developmental effects on prepulse inhibition (PPI) of the auditory startle response

PubMed Central

Fitting, Sylvia; Booze, Rosemarie M.; Mactutus, Charles F.

2013-01-01

The current estimate of children (<15 years) living with HIV and AIDS is 2.2 million [UNAIDS/WHO, 2005. AIDS Epidemic Update. UNAIDS, Geneva]. The major source of infection occurs through vertical transmission of the virus from mother to child during delivery [UNAIDS/ WHO, 2005. AIDS Epidemic Update. UNAIDS, Geneva]. Recent studies have shown that timing of HIV-1 infection might be related to the onset and rate of progression of CNS disease [Blanche, S., Mayaux, M.-J., Rouziox, C., Teglas, J.-P., Firtion, G., Monpoux, F., Cicaru-Vigneron, N., Meier, F., Tricoire, J., Courpotin, C., Vilmer, E., Griscelli, C., Delfraissy, J.-F., 1994. Relation of the course of HIV infection in children to the severity of the disease in their mothers at delivery. N. Engl. J. Med. 330 (5), 308–312]. The effects of HIV on the brain are thought to be mediated indirectly through the viral toxins Tat and gp120. This study characterized developmental effects on PPI following intrahippocampal administration of Tat. On postnatal day (P)1, one male and one female pup from each of eight Sprague–Dawley litters were bilaterally injected with 50 µg Tat or saline (1 µl volume). Animals were tested for PPI of the auditory startle response (ASR) (ISIs of 0, 8,40, 80, 120, and 4000 ms, six trial blocks, Latin-square design) on days 30, 60 and 90. Tat altered PPI and the pattern of alterations was different for males and females. For males, a leftward shift was evident in the ISI for maximal inhibition of the response on day 30 and on day 60 (χ2(1) = 4.7,p ≤ .03, and χ2(1) = 5.3, p ≤ .02, respectively), but not on day 90. For females, Tat altered peak ASR latency across PPI trials (8–120 ms) at all days of testing (30, 60, and 90 days of age), as indexed by orthogonal component analyses, indicating less modulation of PPI by ISI. Data collected from a second group that were tested only once at 90 days of age, suggested that the observed adverse Tat effects for males and females early in
Reflux parameters as modified by laparoscopic fundoplication in 40 patients with heartburn/regurgitation persisting despite PPI therapy: a study using impedance-pH monitoring.

PubMed

Frazzoni, Marzio; Conigliaro, Rita; Melotti, Gianluigi

2011-04-01

Patients with typical reflux symptoms (heartburn/regurgitation) persisting despite proton pump inhibitor (PPI) therapy are not uncommon. Impedance-pH monitoring detects gastroesophageal reflux at all pH levels and may establish if ongoing symptoms on PPI therapy are associated with acid/nonacid reflux. Laparoscopic fundoplication is a therapeutic option in such patients but reflux parameters on PPI therapy and after intervention and their relationship with symptom persistence/remission have been scarcely studied. The aim of this study was to assess reflux parameters and their relationship with symptoms before and after laparoscopic fundoplication, on and off PPI therapy, respectively, in patients with PPI-unresponsive heartburn/regurgitation and with a positive symptom-reflux association and/or abnormal reflux parameters detected on PPI therapy. Impedance-pH monitoring was performed on high-dose PPI therapy and 3 months after laparoscopic fundoplication, off PPI therapy, in 40 patients with PPI-unresponsive heartburn/regurgitation. Symptoms were scored by a validated questionnaire. Esophageal acid exposure time as well as the number of total and proximal reflux events and of acid and weakly acidic refluxes decreased significantly after surgery: normal values were found in 100, 77, 95, 92 and 65% of cases, respectively. Weakly alkaline refluxes increased significantly postoperatively but neither before nor after intervention were associated with symptoms. All patients reported total/subtotal remission of heartburn/regurgitation 3 months after surgery. Laparoscopic fundoplication improves acid and weakly acidic reflux parameters when compared with PPI therapy. This improvement justifies the very high post-surgical symptom remission rate that we observed. Prolonged follow-up is warranted but our findings strongly support the surgical option in PPI failures.
Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

PubMed

Holland, David O; Johnson, Margaret E

2018-03-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module
In-vivo detection of binary PKA network interactions upon activation of endogenous GPCRs

PubMed Central

Röck, Ruth; Bachmann, Verena; Bhang, Hyo-eun C; Malleshaiah, Mohan; Raffeiner, Philipp; Mayrhofer, Johanna E; Tschaikner, Philipp M; Bister, Klaus; Aanstad, Pia; Pomper, Martin G; Michnick, Stephen W; Stefan, Eduard

2015-01-01

Membrane receptor-sensed input signals affect and modulate intracellular protein-protein interactions (PPIs). Consequent changes occur to the compositions of protein complexes, protein localization and intermolecular binding affinities. Alterations of compartmentalized PPIs emanating from certain deregulated kinases are implicated in the manifestation of diseases such as cancer. Here we describe the application of a genetically encoded Protein-fragment Complementation Assay (PCA) based on the Renilla Luciferase (Rluc) enzyme to compare binary PPIs of the spatially and temporally controlled protein kinase A (PKA) network in diverse eukaryotic model systems. The simplicity and sensitivity of this cell-based reporter allows for real-time recordings of mutually exclusive PPIs of PKA upon activation of selected endogenous G protein-coupled receptors (GPCRs) in cancer cells, xenografts of mice, budding yeast, and zebrafish embryos. This extends the application spectrum of Rluc PCA for the quantification of PPI-based receptor-effector relationships in physiological and pathological model systems. PMID:26099953
Selective Phosphonylation of 5'-Adenosine Monophosphate (5'-AMP) via Pyrophosphite [PPi(III)].

PubMed

Kaye, Karl; Bryant, David E; Marriott, Katie E R; Ohara, Shohei; Fishwick, Colin W G; Kee, Terence P

2016-11-01

We describe here experiments which demonstrate the selective phospho-transfer from a plausibly prebiotic condensed phosphorus (P) salt, pyrophosphite [H 2 P 2 O 5 2- ; PPi(III)], to the phosphate group of 5'-adenosine mono phosphate (5'-AMP). We show further that this P-transfer process is accelerated both by divalent metal ions (M 2+ ) and by organic co-factors such as acetate (AcO - ). In this specific case of P-transfer from PPi(III) to 5'-AMP, we show a synergistic enhancement of transfer in the combined presence of M 2+ & AcO - . Isotopic labelling studies demonstrate that hydrolysis of the phosphonylated 5'-AMP, [P(III)P(V)-5'-AMP], proceeds via nuceophilic attack of water at the Pi(III) terminus.
Physiological and environmental control of yeast prions

PubMed Central

Chernova, Tatiana A.; Wilkinson, Keith D.; Chernoff, Yury O.

2014-01-01

Prions are self-perpetuating protein isoforms that cause fatal and incurable neurodegenerative disease in mammals. Recent evidence indicates that a majority of human proteins involved in amyloid and neural inclusion disorders possess at least some prion properties. In lower eukaryotes, such as yeast, prions act as epigenetic elements, which increase phenotypic diversity by altering a range of cellular processes. While some yeast prions are clearly pathogenic, it is also postulated that prion formation could be beneficial in variable environmental conditions. Yeast and mammalian prions have similar molecular properties. Crucial cellular factors and conditions influencing prion formation and propagation were uncovered in the yeast models. Stress-related chaperones, protein quality control deposits, degradation pathways and cytoskeletal networks control prion formation and propagation in yeast. Environmental stresses trigger prion formation and loss, supposedly acting via influencing intracellular concentrations of the prion-inducing proteins, and/or by localizing prionogenic proteins to the prion induction sites via heterologous ancillary helpers. Physiological and environmental modulation of yeast prions points to new opportunities for pharmacological intervention and/or prophylactic measures targeting general cellular systems rather than the properties of individual amyloids and prions. PMID:24236638

Preparation of PPy-Coated MnO2 Hybrid Micromaterials and Their Improved Cyclic Performance as Anode for Lithium-Ion Batteries

NASA Astrophysics Data System (ADS)

Feng, Lili; Zhang, Yinyin; Wang, Rui; Zhang, Yanli; Bai, Wei; Ji, Siping; Xuan, Zhewen; Yang, Jianhua; Zheng, Ziguang; Guan, Hongjin

2017-09-01

MnO2@PPy core-shell micromaterials are prepared by chemical polymerization of pyrrole on the MnO2 surface. The polypyrrole (PPy) is formed as a homogeneous organic shell on the MnO2 surface. The thickness of PPy shell can be adjusted by the usage of pyrrole. The analysis of SEM, FT-IR, X-ray photoelectron spectroscopy (XPS), thermo-gravimetric analysis (TGA), and XRD are used to confirm the formation of PPy shell. Galvanostatic cell cycling and electrochemical impedance spectroscopy (EIS) are used to evaluate the electrochemical performance as anode for lithium-ion batteries. The results show that after formation of MnO2@PPy core-shell micromaterials, the cyclic performance as anode for lithium-ion batteries is improved. Fifty microliters of PPy-coated caddice-clew-like MnO2 has the best cyclic performances as has 620 mAh g-1 discharge specific capacities after 300 cycles. As a comparison, the discharge specific capacity of bare MnO2 materials falls to below 200 mAh g-1 after 10 cycles. The improved lithium-storage cyclic stability of the MnO2@PPy samples attributes to the core-shell hybrid structure which can buffer the structural expansion and contraction of MnO2 caused by the repeated embedding and disengagement of Li ions and can prevent the pulverization of MnO2. This experiment provides an effective way to mitigate the problem of capacity fading of the transition metal oxide materials as anode materials for (lithium-ion batteries) LIBs.
Preparation of PPy-Coated MnO2 Hybrid Micromaterials and Their Improved Cyclic Performance as Anode for Lithium-Ion Batteries.

PubMed

Feng, Lili; Zhang, Yinyin; Wang, Rui; Zhang, Yanli; Bai, Wei; Ji, Siping; Xuan, Zhewen; Yang, Jianhua; Zheng, Ziguang; Guan, Hongjin

2017-09-02

MnO 2 @PPy core-shell micromaterials are prepared by chemical polymerization of pyrrole on the MnO 2 surface. The polypyrrole (PPy) is formed as a homogeneous organic shell on the MnO 2 surface. The thickness of PPy shell can be adjusted by the usage of pyrrole. The analysis of SEM, FT-IR, X-ray photoelectron spectroscopy (XPS), thermo-gravimetric analysis (TGA), and XRD are used to confirm the formation of PPy shell. Galvanostatic cell cycling and electrochemical impedance spectroscopy (EIS) are used to evaluate the electrochemical performance as anode for lithium-ion batteries. The results show that after formation of MnO 2 @PPy core-shell micromaterials, the cyclic performance as anode for lithium-ion batteries is improved. Fifty microliters of PPy-coated caddice-clew-like MnO 2 has the best cyclic performances as has 620 mAh g -1 discharge specific capacities after 300 cycles. As a comparison, the discharge specific capacity of bare MnO 2 materials falls to below 200 mAh g -1 after 10 cycles. The improved lithium-storage cyclic stability of the MnO 2 @PPy samples attributes to the core-shell hybrid structure which can buffer the structural expansion and contraction of MnO 2 caused by the repeated embedding and disengagement of Li ions and can prevent the pulverization of MnO 2 . This experiment provides an effective way to mitigate the problem of capacity fading of the transition metal oxide materials as anode materials for (lithium-ion batteries) LIBs.
Electromagnetic interference attenuation and shielding effect of quaternary Epoxy-PPy/Fe3O4-ZnO nanocomposite as a broad band microwave-absorber

NASA Astrophysics Data System (ADS)

Olad, Ali; Shakoori, Sahar

2018-07-01

An increase in the electromagnetic wave pollution generated from wireless telecommunication devices has devoted to a great request for exploiting microwave absorbing materials for themselves. The combination of inherently conducting polymers such as polypyrrole (PPy) with metal oxides has led to design ideal microwave absorbing materials which benefit both advantage effects of ICPs and metal oxide nanoparticles. Herein, the quaternary nanocomposite of Epoxy-PPy/Fe3O4-ZnO was prepared and tested for the absorption of X-band microwaves. Simultaneous application of metal oxides and conducting polypyrrole in the epoxy matrix was evaluated in order to increase the absorption intensity and broadness of microwaves in X-band region. The morphology, microstructure, and phase structure of Fe3O4, ZnO, and PPy, as well as quaternary nanocomposite were characterized and studied using FTIR, XRD, FESEM and TEM techniques. The presence of nanoparticles in the quaternary nanocomposite was confirmed by EDS. The magnetization of iron oxide was studied by VSM. The synergetic effect of iron oxide and zinc oxide nanoparticles in different weight ratios (Fe3O4/ZnO) on the electromagnetic wave absorption was evaluated. The electromagnetic parameters have been evaluated by the vector network analyzer in the frequency range of 8.2-12.4 GHz which is named as X-band region and is adequate for radar applications. The electromagnetic wave absorbing outcomes indicated that Epoxy-PPy/Fe3O4-ZnO quaternary nanocomposite has wide absorption area and high attenuation, which is believed to be due to dielectric loss properties related to the polypyrrole, magnetic loss factor of Fe3O4, and synergetic effects of components. The maximum reflection loss reached to -32.53 dB at 9.96 GHz with a nanocomposite thickness of 2 mm which is dedicated to the Epoxy-PPy/Fe3O4-ZnO with iron oxide to zinc oxide ratio of 2:1. The absorption bandwidth with the reflection loss lower than -10 dB (90% attenuation) was up to
The Arabidopsis ppi1 Mutant Is Specifically Defective in the Expression, Chloroplast Import, and Accumulation of Photosynthetic ProteinsW⃞

PubMed Central

Kubis, Sybille; Baldwin, Amy; Patel, Ramesh; Razzaq, Azam; Dupree, Paul; Lilley, Kathryn; Kurth, Joachim; Leister, Dario; Jarvis, Paul

2003-01-01

The import of nucleus-encoded proteins into chloroplasts is mediated by translocon complexes in the envelope membranes. A component of the translocon in the outer envelope membrane, Toc34, is encoded in Arabidopsis by two homologous genes, atTOC33 and atTOC34. Whereas atTOC34 displays relatively uniform expression throughout development, atTOC33 is strongly upregulated in rapidly growing, photosynthetic tissues. To understand the reason for the existence of these two related genes, we characterized the atTOC33 knockout mutant ppi1. Immunoblotting and proteomics revealed that components of the photosynthetic apparatus are deficient in ppi1 chloroplasts and that nonphotosynthetic chloroplast proteins are unchanged or enriched slightly. Furthermore, DNA array analysis of 3292 transcripts revealed that photosynthetic genes are moderately, but specifically, downregulated in ppi1. Proteome differences in ppi1 could be correlated with protein import rates: ppi1 chloroplasts imported the ribulose-1,5-bisphosphate carboxylase/oxygenase small subunit and 33-kD oxygen-evolving complex precursors at significantly reduced rates, but the import of a 50S ribosomal subunit precursor was largely unaffected. The ppi1 import defect occurred at the level of preprotein binding, which is consistent with a role for atToc33 during preprotein recognition. The data suggest that atToc33 is involved preferentially in the import of photosynthetic proteins and, by extension, that atToc34 is involved in the import of nonphotosynthetic chloroplast proteins. PMID:12897258
Same-session dorsal vein ligation and testing by intracavernous injection prior to penile prosthesis implantation (DVL-ICI-PPI).

PubMed

Shaeer, Osama; Shaeer, Kamal

2014-09-01

Complications of penile prosthesis implantation (PPI) are rare, nevertheless can be grave. In cases with veno-occlusive dysfunction (VOD), alternative surgical techniques such as dorsal vein ligation (DVL) are controversial. Some patients may opt for trial at DVL to avoid the possible complications of PPI. However, this may be associated with disappointment if DVL fails and another procedure is required. The aim if this study is to evaluate the results of a combined approach involving DVL, same-session testing by intracavernous injection (ICI) of prostaglandin E1 (PGE1), and immediate implantation of a penile prosthesis (PPI) in case of poor response to DVL. Long-term erectile function in cases with favorable intraoperative response to DVL. Twenty-six patients with refractory VOD were operated upon. Through a peno-pubic incision, DVL was performed, followed by ICI of 20 µg PGE1 in two divided doses, 10 µg each, 15 minutes apart. Group 1 exhibited full rigidity in response to the first dose. Group 2 exhibited full rigidity in response to the second dose. PPI was not performed for either. Group 3 exhibited suboptimal response to both doses, and PPI was performed through the same incision. Patients were followed up from 24 to 48 months using International Index of Erectile Function-5 scoring. For Group 1 (n = 8), six patients experienced normal erectile function following DVL throughout the whole follow-up period of 48 months (23.1% of all patients), and two patients relapsed. Group 2 (n = 6) (23.1%) reported normal erectile function for an average of 6 months, then relapsed. Group 3 (n = 12) had a penile prosthesis implanted in the same setting. Combined DVL-ICI-PPI can spare around 23.1% of young patients with VOD from PPI, at no additional risk. Full response to 10 µg PGE1 at intraoperative testing carries good prognosis to DVL on the long run. Investigation of a larger number of patients is necessary before reaching a final conclusion. © 2014
A hybrid network-based method for the detection of disease-related genes

NASA Astrophysics Data System (ADS)

Cui, Ying; Cai, Meng; Dai, Yang; Stanley, H. Eugene

2018-02-01

Detecting disease-related genes is crucial in disease diagnosis and drug design. The accepted view is that neighbors of a disease-causing gene in a molecular network tend to cause the same or similar diseases, and network-based methods have been recently developed to identify novel hereditary disease-genes in available biomedical networks. Despite the steady increase in the discovery of disease-associated genes, there is still a large fraction of disease genes that remains under the tip of the iceberg. In this paper we exploit the topological properties of the protein-protein interaction (PPI) network to detect disease-related genes. We compute, analyze, and compare the topological properties of disease genes with non-disease genes in PPI networks. We also design an improved random forest classifier based on these network topological features, and a cross-validation test confirms that our method performs better than previous similar studies.
ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.

PubMed

Li, Guipeng; Li, Ming; Zhang, Yiwei; Wang, Dong; Li, Rong; Guimerà, Roger; Gao, Juntao Tony; Zhang, Michael Q

2014-01-01

Rapidly increasing amounts of (physical and genetic) protein-protein interaction (PPI) data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network and defines the roles for every node, and produces files for visualization in Cytoscape and Pajek. For given proteins, it analyzes the PPI network from BioGRID database, finds and visualizes the modules these proteins form, and then defines the role every node plays in this network, based on two topological parameters Participation Coefficient and Z-score. This is the first program which provides interactive and very friendly interface for biologists to find and visualize modules and roles of proteins in PPI network. It can be tested online at the website http://www.bioinfo.org/modulerole/index.php, which is free and open to all users and there is no login requirement, with demo data provided by "User Guide" in the menu Help. Non-server application of this program is considered for high-throughput data with more than 200 nodes or user's own interaction datasets. Users are able to bookmark the web link to the result page and access at a later time. As an interactive and highly customizable application, ModuleRole requires no expert knowledge in graph theory on the user side and can be used in both Linux and Windows system, thus a very useful tool for biologist to analyze and visualize PPI networks from databases such as BioGRID. ModuleRole is implemented in Java and C, and is freely available at http://www.bioinfo.org/modulerole/index.php. Supplementary information (user guide, demo data) is also available at this website. API for ModuleRole used for this program can be
Alzheimer Europe's position on involving people with dementia in research through PPI (patient and public involvement).

PubMed

Gove, Dianne; Diaz-Ponce, Ana; Georges, Jean; Moniz-Cook, Esme; Mountain, Gail; Chattat, Rabih; Øksnebjerg, Laila

2018-06-01

This paper reflects Alzheimer Europe's position on PPI (patient and public involvement) in the context of dementia research and highlights some of the challenges and potential risks and benefits associated with such meaningful involvement. The paper was drafted by Alzheimer Europe in collaboration with members of INTERDEM and the European Working Group of People with Dementia. It has been formally adopted by the Board of Alzheimer Europe and endorsed by the Board of INTERDEM and by the JPND working group 'Dementia Outcome Measures - Charting New Territory'. Alzheimer Europe is keen to promote the involvement of people with dementia in research, not only as participants but also in the context of PPI, by generating ideas for research, advising researchers, being involved in consultations and being directly involved in research activities. This position paper is in keeping with this objective. Topics covered include, amongst others, planning involvement, establishing roles and responsibilities, training and support, managing information and input from PPI, recognising the contribution of people with dementia involved in research in this way, promoting and protecting the rights and well-being of people with dementia, training and support, and promoting an inclusive approach and the necessary infrastructure for PPI in dementia research.
Yeast Genetics and Biotechnological Applications

NASA Astrophysics Data System (ADS)

Mishra, Saroj; Baranwal, Richa

Yeast can be recognized as one of the very important groups of microorganisms on account of its extensive use in the fermentation industry and as a basic eukaryotic model cellular system. The yeast Saccharomyces cerevisiae has been extensively used to elucidate the genetics and regulation of several key functions in the cell such as cell mating, electron transport chain, protein trafficking, cell cycle events and others. Even before the genome sequence of the yeast was out, the structural organization and function of several of its genes was known. With the availability of the origin of replication from the 2 μm plasmid and the development of transformation system, it became the host of choice for expression of a number of important proteins. A large number of episomal and integrative shuttle vectors are available for expression of mammalian proteins. The latest developments in genomics and micro-array technology have allowed investigations of individual gene function by site-specific deletion method. The application of metabolic profiling has also assisted in understanding the cellular network operating in this yeast. This chapter is aimed at reviewing the use of this system as an experimental tool for conducting classical genetics. Various vector systems available, foreign genes expressed and the limitations as a host will be discussed. Finally, the use of various yeast enzymes in biotechnology sector will be reviewed.
Novel electrochemical immune sensor based on Hep-PGA-PPy nanoparticles for detection of α-Fetoprotein in whole blood.

PubMed

Xu, Tingting; Chi, Bo; Gao, Jian; Chu, Meilin; Fan, Wenlu; Yi, Meihui; Xu, Hong; Mao, Chun

2017-07-18

A simple and accurate immune sensor for quantitative detection of α-Fetoprotein (AFP) was developed based on the immobilization of antigen on the surface of Hep-PGA-PPy nanoparticles modified glassy carbon electrodes (GCE). The obtained Hep-PGA-PPy nanoparticles were characterized by fourier transform infrared (FT-IR) spectra and transmission electron microscopy (TEM). And the blood compatibility of Hep-PGA-PPy nanoparticles was investigated by in vitro coagulation tests, hemolysis assay and whole blood adhesion tests. Combining the conductive property of polypyrrole (PPy) and the biocompatibility of heparin (Hep), the Hep-PGA-PPy nanoparticles could improve not only the anti-biofouling effect the electrode, but also improved the electrochemical properties of the immune sensor. Under optimal conditions, the proposed immune sensor could detect AFP in a linear range from 0.1 to 100 ng mL -1 with a detection limit of 0.099 ng mL -1 at the signal-to-noise ratio of 3, and it also possessed good reproducibility and storage stability. Furthermore, the detection of AFP in five human blood samples also showed satisfactory accuracy with low relative errors. Thus, the developed immune sensor which showed acceptable reproducibility, selectivity, stability and accuracy could be potentially used for the detection of whole blood samples directly. Copyright © 2017. Published by Elsevier B.V.
Commensurate distances and similar motifs in genetic congruence and protein interaction networks in yeast

PubMed Central

Ye, Ping; Peyser, Brian D; Spencer, Forrest A; Bader, Joel S

2005-01-01

Background In a genetic interaction, the phenotype of a double mutant differs from the combined phenotypes of the underlying single mutants. When the single mutants have no growth defect, but the double mutant is lethal or exhibits slow growth, the interaction is termed synthetic lethality or synthetic fitness. These genetic interactions reveal gene redundancy and compensating pathways. Recently available large-scale data sets of genetic interactions and protein interactions in Saccharomyces cerevisiae provide a unique opportunity to elucidate the topological structure of biological pathways and how genes function in these pathways. Results We have defined congruent genes as pairs of genes with similar sets of genetic interaction partners and constructed a genetic congruence network by linking congruent genes. By comparing path lengths in three types of networks (genetic interaction, genetic congruence, and protein interaction), we discovered that high genetic congruence not only exhibits correlation with direct protein interaction linkage but also exhibits commensurate distance with the protein interaction network. However, consistent distances were not observed between genetic and protein interaction networks. We also demonstrated that congruence and protein networks are enriched with motifs that indicate network transitivity, while the genetic network has both transitive (triangle) and intransitive (square) types of motifs. These results suggest that robustness of yeast cells to gene deletions is due in part to two complementary pathways (square motif) or three complementary pathways, any two of which are required for viability (triangle motif). Conclusion Genetic congruence is superior to genetic interaction in prediction of protein interactions and function associations. Genetically interacting pairs usually belong to parallel compensatory pathways, which can generate transitive motifs (any two of three pathways needed) or intransitive motifs (either of two
Network-Based Comparative Analysis of Arabidopsis Immune Responses to Golovinomyces orontii and Botrytis cinerea Infections.

PubMed

Jiang, Zhenhong; Dong, Xiaobao; Zhang, Ziding

2016-01-11

A comprehensive exploration of common and specific plant responses to biotrophs and necrotrophs is necessary for a better understanding of plant immunity. Here, we compared the Arabidopsis defense responses evoked by the biotrophic fungus Golovinomyces orontii and the necrotrophic fungus Botrytis cinerea through integrative network analysis. Two time-course transcriptional datasets were integrated with an Arabidopsis protein-protein interaction (PPI) network to construct a G. orontii conditional PPI sub-network (gCPIN) and a B. cinerea conditional PPI sub-network (bCPIN). We found that hubs in gCPIN and bCPIN played important roles in disease resistance. Hubs in bCPIN evolved faster than hubs in gCPIN, indicating the different selection pressures imposed on plants by different pathogens. By analyzing the common network from gCPIN and bCPIN, we identified two network components in which the genes were heavily involved in defense and development, respectively. The co-expression relationships between interacting proteins connecting the two components were different under G. orontii and B. cinerea infection conditions. Closer inspection revealed that auxin-related genes were overrepresented in the interactions connecting these two components, suggesting a critical role of auxin signaling in regulating the different co-expression relationships. Our work may provide new insights into plant defense responses against pathogens with different lifestyles.
Rhizoma Dioscoreae extract protects against alveolar bone loss by regulating the cell cycle: A predictive study based on the protein‑protein interaction network.

PubMed

Zhang, Zhi-Guo; Song, Chang-Heng; Zhang, Fang-Zhen; Chen, Yan-Jing; Xiang, Li-Hua; Xiao, Gary Guishan; Ju, Da-Hong

2016-06-01

Rhizoma Dioscoreae extract (RDE) exhibits a protective effect on alveolar bone loss in ovariectomized (OVX) rats. The aim of this study was to predict the pathways or targets that are regulated by RDE, by re‑assessing our previously reported data and conducting a protein‑protein interaction (PPI) network analysis. In total, 383 differentially expressed genes (≥3‑fold) between alveolar bone samples from the RDE and OVX group rats were identified, and a PPI network was constructed based on these genes. Furthermore, four molecular clusters (A‑D) in the PPI network with the smallest P‑values were detected by molecular complex detection (MCODE) algorithm. Using Database for Annotation, Visualization and Integrated Discovery (DAVID) and Ingenuity Pathway Analysis (IPA) tools, two molecular clusters (A and B) were enriched for biological process in Gene Ontology (GO). Only cluster A was associated with biological pathways in the IPA database. GO and pathway analysis results showed that cluster A, associated with cell cycle regulation, was the most important molecular cluster in the PPI network. In addition, cyclin‑dependent kinase 1 (CDK1) may be a key molecule achieving the cell‑cycle‑regulatory function of cluster A. From the PPI network analysis, it was predicted that delayed cell cycle progression in excessive alveolar bone remodeling via downregulation of CDK1 may be another mechanism underling the anti‑osteopenic effect of RDE on alveolar bone.
FITC-modified PPy nanotubes embedded in nanoporous AAO membrane can detect trace PCB20 via fluorescence ratiometric measurement.

PubMed

Wang, Meiling; Meng, Guowen; Huang, Qing; Xu, Qiaoling; Chu, Zhaoqin; Zhu, Chuhong

2011-04-07

A highly sensitive and selective fluorescence ratiometric sensor membrane for 2,3,3'-trichlorobiphenyl has been achieved, via depositing polypyrrole nanotubes (PPyNTs, the fluorescence indicator) in nano-porous anodic aluminium oxide (NPAAO) template and subsequently immobilizing fluorescein isothiocyanate (as an internal reference) onto the inner walls of the PPyNTs embedded in the NPAAO.
Inferring the effective TOR-dependent network: a computational study in yeast

PubMed Central

2013-01-01

Background Calorie restriction (CR) is one of the most conserved non-genetic interventions that extends healthspan in evolutionarily distant species, ranging from yeast to mammals. The target of rapamycin (TOR) has been shown to play a key role in mediating healthspan extension in response to CR by integrating different signals that monitor nutrient-availability and orchestrating various components of cellular machinery in response. Both genetic and pharmacological interventions that inhibit the TOR pathway exhibit a similar phenotype, which is not further amplified by CR. Results In this paper, we present the first comprehensive, computationally derived map of TOR downstream effectors, with the objective of discovering key lifespan mediators, their crosstalk, and high-level organization. We adopt a systematic approach for tracing information flow from the TOR complex and use it to identify relevant signaling elements. By constructing a high-level functional map of TOR downstream effectors, we show that our approach is not only capable of recapturing previously known pathways, but also suggests potential targets for future studies. Information flow scores provide an aggregate ranking of relevance of proteins with respect to the TOR signaling pathway. These rankings must be normalized for degree bias, appropriately interpreted, and mapped to associated roles in pathways. We propose a novel statistical framework for integrating information flow scores, the set of differentially expressed genes in response to rapamycin treatment, and the transcriptional regulatory network. We use this framework to identify the most relevant transcription factors in mediating the observed transcriptional response, and to construct the effective response network of the TOR pathway. This network is hypothesized to mediate life-span extension in response to TOR inhibition. Conclusions Our approach, unlike experimental methods, is not limited to specific aspects of cellular response
Protein complex prediction for large protein protein interaction networks with the Core&Peel method.

PubMed

Pellegrini, Marco; Baglioni, Miriam; Geraci, Filippo

2016-11-08

Biological networks play an increasingly important role in the exploration of functional modularity and cellular organization at a systemic level. Quite often the first tools used to analyze these networks are clustering algorithms. We concentrate here on the specific task of predicting protein complexes (PC) in large protein-protein interaction networks (PPIN). Currently, many state-of-the-art algorithms work well for networks of small or moderate size. However, their performance on much larger networks, which are becoming increasingly common in modern proteome-wise studies, needs to be re-assessed. We present a new fast algorithm for clustering large sparse networks: Core&Peel, which runs essentially in time and storage O(a(G)m+n) for a network G of n nodes and m arcs, where a(G) is the arboricity of G (which is roughly proportional to the maximum average degree of any induced subgraph in G). We evaluated Core&Peel on five PPI networks of large size and one of medium size from both yeast and homo sapiens, comparing its performance against those of ten state-of-the-art methods. We demonstrate that Core&Peel consistently outperforms the ten competitors in its ability to identify known protein complexes and in the functional coherence of its predictions. Our method is remarkably robust, being quite insensible to the injection of random interactions. Core&Peel is also empirically efficient attaining the second best running time over large networks among the tested algorithms. Our algorithm Core&Peel pushes forward the state-of the-art in PPIN clustering providing an algorithmic solution with polynomial running time that attains experimentally demonstrable good output quality and speed on challenging large real networks.
Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes.

PubMed

Srihari, Sriganesh; Yong, Chern Han; Patil, Ashwini; Wong, Limsoon

2015-09-14

Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand the functional organisation of cells. In this review, we discuss the key contributions of computational methods developed till date (approximately between 2003 and 2015) for identifying complexes from the network of interacting proteins (PPI network). We evaluate in depth the performance of these methods on PPI datasets from yeast, and highlight their limitations and challenges, in particular at detecting sparse and small or sub-complexes and discerning overlapping complexes. We describe methods for integrating diverse information including expression profiles and 3D structures of proteins with PPI networks to understand the dynamics of complex formation, for instance, of time-based assembly of complex subunits and formation of fuzzy complexes from intrinsically disordered proteins. Finally, we discuss methods for identifying dysfunctional complexes in human diseases, an application that is proving invaluable to understand disease mechanisms and to discover novel therapeutic targets. We hope this review aptly commemorates a decade of research on computational prediction of complexes and constitutes a valuable reference for further advancements in this exciting area. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).
Characterization of biomarkers in stroke based on ego-networks and pathways.

PubMed

Li, Haixia; Guo, Qianqian

2017-12-01

To explore potential biomarkers in stroke based on ego-networks and pathways. EgoNet method was applied to search for the underlying biomarkers in stroke using transcription profiling of E-GEOD-58294 and protein-protein interaction (PPI) data. Eight ego-genes were identified from PPI network according to the degree characteristics at the criteria of top 5% ranked z-sore and degree >1. Eight candidate ego-networks with classification accuracy ≥0.9 were selected. After performed randomization test, seven significant ego-networks with adjusted p value < 0.05 were identified. Pathway enrichment analysis was then conducted with these ego-networks to search for the significant pathways. Finally, two significant pathways were identified, and six of seven ego-networks were enriched to "3'-UTR-mediated translational regulation" pathway, indicating that this pathway performs an important role in the development of stroke. Seven ego-networks were constructed using EgoNet and two significant enriched by pathways were identified. These may provide new insights into the potential biomarkers for the development of stroke.
Reaching consensus on reporting patient and public involvement (PPI) in research: methods and lessons learned from the development of reporting guidelines

PubMed Central

Brett, Jo; Staniszewska, Sophie; Simera, Iveta; Seers, Kate; Mockford, Carole; Goodlad, Susan; Altman, Doug; Moher, David; Barber, Rosemary; Denegri, Simon; Entwistle, Andrew Robert; Littlejohns, Peter; Suleman, Rashida; Thomas, Victoria; Tysall, Colin

2017-01-01

Introduction Patient and public involvement (PPI) is inconsistently reported in health and social care research. Improving the quality of how PPI is reported is critical in developing a higher quality evidence base to gain a better insight into the methods and impact of PPI. This paper describes the methods used to develop and gain consensus on guidelines for reporting PPI in research studies (updated version of the Guidance for Reporting Patient and Public Involvement (GRIPP2)). Methods There were three key stages in the development of GRIPP2: identification of key items for the guideline from systematic review evidence of the impact of PPI on health research and health services, a three-phase online Delphi survey with a diverse sample of experts in PPI to gain consensus on included items and a face-to-face consensus meeting to finalise and reach definitive agreement on GRIPP2. Challenges and lessons learnt during the development of the reporting guidelines are reported. Discussion The process of reaching consensus is vital within the development of guidelines and policy directions, although debate around how best to reach consensus is still needed. This paper discusses the critical stages of consensus development as applied to the development of consensus for GRIPP2 and discusses the benefits and challenges of consensus development. PMID:29061613

Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis

PubMed Central

2018-01-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that ‘leftover’ proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module
Multichannel Convolutional Neural Network for Biological Relation Extraction.

PubMed

Quan, Chanqin; Hua, Lei; Sun, Xiao; Bai, Wenjun

2016-01-01

The plethora of biomedical relations which are embedded in medical logs (records) demands researchers' attention. Previous theoretical and practical focuses were restricted on traditional machine learning techniques. However, these methods are susceptible to the issues of "vocabulary gap" and data sparseness and the unattainable automation process in feature extraction. To address aforementioned issues, in this work, we propose a multichannel convolutional neural network (MCCNN) for automated biomedical relation extraction. The proposed model has the following two contributions: (1) it enables the fusion of multiple (e.g., five) versions in word embeddings; (2) the need for manual feature engineering can be obviated by automated feature learning with convolutional neural network (CNN). We evaluated our model on two biomedical relation extraction tasks: drug-drug interaction (DDI) extraction and protein-protein interaction (PPI) extraction. For DDI task, our system achieved an overall f -score of 70.2% compared to the standard linear SVM based system (e.g., 67.0%) on DDIExtraction 2013 challenge dataset. And for PPI task, we evaluated our system on Aimed and BioInfer PPI corpus; our system exceeded the state-of-art ensemble SVM system by 2.7% and 5.6% on f -scores.
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
Comparative study of therapeutic effects of PPI and H2RA on ulcers during continuous aspirin therapy

PubMed Central

Nema, Hiroaki; Kato, Mototsugu

2010-01-01

AIM: To compare the therapeutic effects of proton pump inhibitors (PPI) and histamine 2 receptor antagonists (H2RA) on gastroduodenal ulcers under continuous use of low-dose aspirin. METHODS: Sixty patients who had a gastroduodenal ulcer on screening endoscopy but required continuous use of low-dose aspirin were randomly assigned to receive PPI (lansoprazole 30 mg, n = 30) or H2RA (famotidine 40 mg or if famotidine had been administered before assignment, ranitidine 300 mg, n = 30). The therapeutic effects were evaluated by endoscopy after 8-wk treatment. The presence or absence of Helicobacter pylori (H. pylori) was determined by urea breath test before treatment. Abdominal symptoms were compared with the gastrointestinal symptom rating scale (GSRS) questionnaire before and after treatment. RESULTS: Twenty-six patients in the PPI group and 26 patients in the H2RA group, excluding dropouts, were analyzed. There were no significant differences in median age, sex, underlying disease, smoking status, H. pylori infection, prevalence of ulcers before treatment, and lesion site between the two groups. The therapeutic effects were endoscopically evaluated as healed in 23 patients (88.5%) and not healed in 3 patients in the PPI group and as healed in 22 patients (84.6%) and not healed in 4 patients in the H2RA group. Abdominal symptoms before treatment were uncommon in both groups; the GSRS scores were not significantly reduced after treatment as compared with before treatment. CONCLUSION: The healing rate of gastroduodenal ulcers during continuous use of low-dose aspirin was greater than 80% in both the PPI group and the H2RA group, with no significant difference between the two groups. PMID:21072898
Identification of potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma.

PubMed

Pan, Yue; Lu, Lingyun; Chen, Junquan; Zhong, Yong; Dai, Zhehao

2018-01-01

This study aimed to identify potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma by comprehensive bioinformatics analysis. Data of gene expression profiles (GSE28424) and miRNA expression profiles (GSE28423) were downloaded from GEO database. The differentially expressed genes (DEGs) and miRNAs (DEMIs) were obtained by R Bioconductor packages. Functional and enrichment analyses of selected genes were performed using DAVID database. Protein-protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape. The relationships among the DEGs and module in PPI network were analyzed by plug-in NetworkAnalyzer and MCODE seperately. Through the TargetScan and comparing target genes with DEGs, the miRNA-mRNA regulation network was established. Totally 346 DEGs and 90 DEMIs were found to be differentially expressed. These DEGs were enriched in biological processes and KEGG pathway of inflammatory immune response. 25 genes in the PPI network were selected as hub genes. Top 10 hub genes were TYROBP, HLA-DRA, VWF, PPBP, SERPING1, HLA-DPA1, SERPINA1, KIF20A, FERMT3, HLA-E. PPI network of DEGs followed a pattern of power law network and met the characteristics of small-world network. MCODE analysis identified 4 clusters and the most significant cluster consisted of 11 nodes and 55 edges. SEPP1, CKS2, TCAP, BPI were identified as the seed genes in their own clusters, respectively. The miRNA-mRNA regulation network which was composed of 89 pairs was established. MiR-210 had the highest connectivity with 12 target genes. Among the predicted target of MiR-96, HLA-DPA1 and TYROBP were the hub genes. Our study indicated possible differentially expressed genes and miRNA, and microRNA-mRNA negative regulatory networks in osteosarcoma by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of osteosarcoma.
TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

PubMed Central

Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L.; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2017-01-01

Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae. In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. PMID:28325812
Quantifying esophagogastric junction contractility with a novel HRM topographic metric, the EGJ-Contractile Integral: normative values and preliminary evaluation in PPI non-responders.

PubMed

Nicodème, F; Pipa-Muniz, M; Khanna, K; Kahrilas, P J; Pandolfino, J E

2014-03-01

Despite its obvious pathophysiological relevance, the clinical utility of measures of esophagogastric junction (EGJ) contractility is unsubstantiated. High-resolution manometry (HRM) may improve upon this with its inherent ability to integrate the magnitude of contractility over time and length of the EGJ. This study aimed to develop a novel HRM metric summarizing EGJ contractility and test its ability distinguish among subgroups of proton pump inhibitor non-responders (PPI-NRs). 75 normal controls and 88 PPI-NRs were studied. All underwent HRM. PPI-NRs underwent pH-impedance monitoring on PPI therapy scored in terms of acid exposure, number of reflux events, and reflux-symptom correlation and grouped as meeting all criteria, some criteria, or no criteria of abnormality. Control HRM studies were used to establish normal values for candidate EGJ contractility metrics, which were then compared in their ability to differentiate among PPI-NR subgroups. The EGJ contractile integral (EGJ-CI), a metric integrating contractility across the EGJ for three respiratory cycles, best distinguished the All Criteria PPI-NR subgroup from controls and other PPI-NR subgroups. Normal values (median, [IQR]) for this measure were 39 mmHg-cm [25-55 mmHg-cm]. The correlation between the EGJ-CI and a previously proposed metric, the lower esophageal sphincter-pressure integral, that used a fixed 10 s time frame and an atmospheric as opposed to gastric pressure reference was weak. Among HRM metrics tested, the EGJ-CI was best in distinguishing PPI-NRs meeting all criteria of abnormality on pH-impedance testing. Future prospective studies are required to explore its utility in management of broader groups of gastroesophageal reflux disease patients. © 2013 John Wiley & Sons Ltd.
Nanomolar colorimetric quantitative detection of Fe3 + and PPi with high selectivity

NASA Astrophysics Data System (ADS)

Li, Zhanxian; Li, Haixia; Shi, Caixia; Yu, Mingming; Wei, Liuhe; Ni, Zhonghai

2016-04-01

A novel rhodamine and 8-hydroxyquinoline-based derivative was synthesized, which is shown to act as a colorimetric chemosensor for Fe3 + in aqueous solution with high selectivity over various environmentally and biologically relevant metal ions and anions with a distinct color change from colorless to pink in very fast response time (< 1 min). Fe3 + can be detected quantitatively in the concentration range from 6.7 to 16 μM and the detection limit (LOD) on UV-vis response of the sensor can be as low as 15 nM. The 'in situ' prepared Fe3 + complex (1 ṡ Fe) showed high selectivity toward PPi against many common anions, and sensitivity (the LOD can be as low as 71 nM). In addition, both the chemosensor and the 'in situ' prepared Fe3 + complex are reusable for the detection of Fe3 + and PPi respectively.
Evidence of Probabilistic Behaviour in Protein Interaction Networks

DTIC Science & Technology

2008-01-31

Evidence of degree-weighted connectivity in nine PPI networks. a, Homo sapiens (human); b, Drosophila melanogaster (fruit fly); c-e, Saccharomyces...illustrates maps for the networks of Homo sapiens and Dro- sophila melanogaster, while maps for the remaining net- works are provided in Additional file 2. As...protein-protein interaction networks. a, Homo sapiens ; b, Drosophila melanogaster. Distances shown as average shortest path lengths L(k1, k2) between
Decorating MOF-Derived Nanoporous Co/C in Chain-Like Polypyrrole (PPy) Aerogel: A Lightweight Material with Excellent Electromagnetic Absorption

PubMed Central

Sun, Xiaodong; Lv, Xuliang; Sui, Mingxu; Weng, Xiaodi; Li, Xiaopeng; Wang, Jijun

2018-01-01

To clear away the harmful effects of the increment of electromagnetic pollution, high performance absorbers with appropriate impedance matching and strong attenuation capacity are strongly desired. In this study, a chain-like PPy aerogel decorated with MOF-derived nanoporous Co/C (Co/C@PPy) has been successfully prepared by a self-assembled polymerization method. With a filler loading ratio of 10 wt %, the composite of Co/C@PPy could achieve a promising electromagnetic absorption performance both in intensity and bandwidth. An optimal reflection loss value of −44.76 dB is achieved, and the effective bandwidth (reflection loss lower than −10 dB) is as large as 6.56 GHz. Furthermore, a composite only loaded with 5 wt % Co/C@PPy also achieves an effective bandwidth of 5.20 GHz, which is even better than numerous reported electromagnetic absorption (EA) materials. The result reveals that the as-fabricated Co/C@PPy—with high absorption intensity, broad bandwidth, and light weight properties—can be utilized as a competitive absorber. PMID:29751650
Constructing an integrated gene similarity network for the identification of disease genes.

PubMed

Tian, Zhen; Guo, Maozu; Wang, Chunyu; Xing, LinLin; Wang, Lei; Zhang, Yin

2017-09-20

Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale. We proposed a novel method, named RWRB, to infer causal genes of interested diseases. First, we construct five individual gene (protein) similarity networks based on multiple genomic data of human genes. Then, an integrated gene similarity network (IGSN) is reconstructed based on similarity network fusion (SNF) method. Finally, we employee the random walk with restart algorithm on the phenotype-gene bilayer network, which combines phenotype similarity network, IGSN as well as phenotype-gene association network, to prioritize candidate disease genes. We investigate the effectiveness of RWRB through leave-one-out cross-validation methods in inferring phenotype-gene relationships. Results show that RWRB is more accurate than state-of-the-art methods on most evaluation metrics. Further analysis shows that the success of RWRB is benefited from IGSN which has a wider coverage and higher reliability comparing with current PPI networks. Moreover, we conduct a comprehensive case study for Alzheimer's disease and predict some novel disease genes that supported by literature. RWRB is an effective and reliable algorithm in prioritizing candidate disease genes on the genomic scale. Software and supplementary information are available at http://nclab.hit.edu.cn/~tianzhen/RWRB/ .
A Novel Hybrid Yeast-Human Network Analysis Reveals an Essential Role for FNBP1L in Antibacterial Autophagy1

PubMed Central

Huett, Alan; Ng, Aylwin; Cao, Zhifang; Kuballa, Petric; Komatsu, Masaaki; Daly, Mark J.; Podolsky, Daniel K.; Xavier, Ramnik J.

2009-01-01

Autophagy is a conserved cellular process required for the removal of defective organelles, protein aggregates, and intracellular pathogens. We used a network analysis strategy to identify novel human autophagy components based upon the yeast interactome centered on the core yeast autophagy proteins. This revealed the potential involvement of 14 novel mammalian genes in autophagy, several of which have known or predicted roles in membrane organization or dynamics. We selected one of these membrane interactors, FNBP1L (formin binding protein 1-like), an F-BAR-containing protein (also termed Toca-1), for further study based upon a predicted interaction with ATG3. We confirmed the FNBP1L/ATG3 interaction biochemically and mapped the FNBP1L domains responsible. Using a functional RNA interference approach, we determined that FNBP1L is essential for autophagy of the intracellular pathogen Salmonella enterica serovar Typhimurium and show that the autophagy process serves to restrict the growth of intracellular bacteria. However, FNBP1L appears dispensable for other forms of autophagy induced by serum starvation or rapamycin. We present a model where FNBP1L is essential for autophagy of intracellular pathogens and identify FNBP1L as a differentially used molecule in specific autophagic contexts. By using network biology to derive functional biological information, we demonstrate the utility of integrated genomics to novel molecule discovery in autophagy. PMID:19342671
Plasticity of genetic interactions in metabolic networks of yeast.

PubMed

Harrison, Richard; Papp, Balázs; Pál, Csaba; Oliver, Stephen G; Delneri, Daniela

2007-02-13

Why are most genes dispensable? The impact of gene deletions may depend on the environment (plasticity), the presence of compensatory mechanisms (mutational robustness), or both. Here, we analyze the interaction between these two forces by exploring the condition-dependence of synthetic genetic interactions that define redundant functions and alternative pathways. We performed systems-level flux balance analysis of the yeast (Saccharomyces cerevisiae) metabolic network to identify genetic interactions and then tested the model's predictions with in vivo gene-deletion studies. We found that the majority of synthetic genetic interactions are restricted to certain environmental conditions, partly because of the lack of compensation under some (but not all) nutrient conditions. Moreover, the phylogenetic cooccurrence of synthetically interacting pairs is not significantly different from random expectation. These findings suggest that these gene pairs have at least partially independent functions, and, hence, compensation is only a byproduct of their evolutionary history. Experimental analyses that used multiple gene deletion strains not only confirmed predictions of the model but also showed that investigation of false predictions may both improve functional annotation within the model and also lead to the discovery of higher-order genetic interactions. Our work supports the view that functional redundancy may be more apparent than real, and it offers a unified framework for the evolution of environmental adaptation and mutational robustness.
A Network Approach to Rare Disease Modeling

NASA Astrophysics Data System (ADS)

Ghiassian, Susan; Rabello, Sabrina; Sharma, Amitabh; Wiest, Olaf; Barabasi, Albert-Laszlo

2011-03-01

Network approaches have been widely used to better understand different areas of natural and social sciences. Network Science had a particularly great impact on the study of biological systems. In this project, using biological networks, candidate drugs as a potential treatment of rare diseases were identified. Developing new drugs for more than 2000 rare diseases (as defined by ORPHANET) is too expensive and beyond expectation. Disease proteins do not function in isolation but in cooperation with other interacting proteins. Research on FDA approved drugs have shown that most of the drugs do not target the disease protein but a protein which is 2 or 3 steps away from the disease protein in the Protein-Protein Interaction (PPI) network. We identified the already known drug targets in the disease gene's PPI subnetwork (up to the 3rd neighborhood) and among them those in the same sub cellular compartment and higher coexpression coefficient with the disease gene are expected to be stronger candidates. Out of 2177 rare diseases, 1092 were found not to have any drug target. Using the above method, we have found the strongest candidates among the rest in order to further experimental validations.
TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network.

PubMed

Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2017-05-05

Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. Copyright © 2017 Usaj et al.
Fabrication of conductive and high-dispersed Ppy@Ag/g-C3N4 composite photocatalysts for removing various pollutants in water

NASA Astrophysics Data System (ADS)

Zhu, Zhi; Tang, Xu; Ma, Changchang; Song, Minshan; Gao, Nailing; Wang, Youshan; Huo, Pengwei; Lu, Ziyang; Yan, Yongsheng

2016-11-01

The ternary conductive Ppy@Ag/g-C3N4 composite photocatalysts was successfully synthesized by polymerization process and surface polymerization technique. And the as-prepared Ppy@Ag/g-C3N4 sample exhibited the higher photocatalytic activity for various pollutant (MO, DM, TC, CIP, GFLX and EH) remove than that of pure g-C3N4 and Ag/g-C3N4 under visible light irradiation. It mainly originated from the Ag nanoparticles anchored between g-C3N4 and Ppy acted as electron transfer mediator that facilitated the charge carrier separation and then expending the lifetime of the carriers. Meanwhile, the obtained Ppy@Ag/g-C3N4 sample also showed a relatively good recycling stability which was the crucial factor for photocatalyst practical application. This work provided a new facile strategy for improving photo-degradation activity of g-C3N4 photocatalyst.
Transcriptional Regulation and the Diversification of Metabolism in Wine Yeast Strains

PubMed Central

Rossouw, Debra; Jacobson, Dan; Bauer, Florian F.

2012-01-01

Transcription factors and their binding sites have been proposed as primary targets of evolutionary adaptation because changes to single transcription factors can lead to far-reaching changes in gene expression patterns. Nevertheless, there is very little concrete evidence for such evolutionary changes. Industrial wine yeast strains, of the species Saccharomyces cerevisiae, are a geno- and phenotypically diverse group of organisms that have adapted to the ecological niches of industrial winemaking environments and have been selected to produce specific styles of wine. Variation in transcriptional regulation among wine yeast strains may be responsible for many of the observed differences and specific adaptations to different fermentative conditions in the context of commercial winemaking. We analyzed gene expression profiles of wine yeast strains to assess the impact of transcription factor expression on metabolic networks. The data provide new insights into the molecular basis of variations in gene expression in industrial strains and their consequent effects on metabolic networks important to wine fermentation. We show that the metabolic phenotype of a strain can be shifted in a relatively predictable manner by changing expression levels of individual transcription factors, opening opportunities to modify transcription networks to achieve desirable outcomes. PMID:22042577
Fabricate BC/Fe3O4@PPy 3D nanofiber film as flexible electrode for supercapacitor application

NASA Astrophysics Data System (ADS)

Lv, Xvdan; Li, Guohui; Pang, Zengyuan; Li, Dawei; Lei, Luo; Lv, Pengfei; Mushtaq, Muhammad; Wei, Qufu

2018-05-01

For flexible film supercapacitor, high areal capacitance is a main evaluating indicator. In this paper, bacterial cellulose (BC) with special three-dimensional structure was used as the natural flexible base material. Fe3O4 nanoparticles with average diameter of 20 nm were synthesized on the surface of BC fibers. The conductive path polypyrrole (PPy) was introduced as shell of BC/Fe3O4 fibers to further improve the pseudo capacitance in 1 mol/L H2SO4 solution. Besides, the BC/Fe3O4@PPy was used for supercapacitor application in acid electrolyte, and delivered higher areal capacitance compared to other Fe3O4 composites in previous reports. The obtained BC/Fe3O4@PPy film showed excellent mechanical strength (tensile strength reached 11 MPa), high areal specific capacitance (5.4 F cm-2 at active mass of 8.4 mg cm-2), and long cycle life (1.95 F cm-2 over 3500 cycles).
FUSE: a profit maximization approach for functional summarization of biological networks.

PubMed

Seah, Boon-Siew; Bhowmick, Sourav S; Dewey, C Forbes; Yu, Hanry

2012-03-21

The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein interaction network (PPI) using graph theoretic analysis. Despite the recent progress, systems level analysis of PPIS remains a daunting task as it is challenging to make sense out of the deluge of high-dimensional interaction data. Specifically, techniques that automatically abstract and summarize PPIS at multiple resolutions to provide high level views of its functional landscape are still lacking. We present a novel data-driven and generic algorithm called FUSE (Functional Summary Generator) that generates functional maps of a PPI at different levels of organization, from broad process-process level interactions to in-depth complex-complex level interactions, through a pro t maximization approach that exploits Minimum Description Length (MDL) principle to maximize information gain of the summary graph while satisfying the level of detail constraint. We evaluate the performance of FUSE on several real-world PPIS. We also compare FUSE to state-of-the-art graph clustering methods with GO term enrichment by constructing the biological process landscape of the PPIS. Using AD network as our case study, we further demonstrate the ability of FUSE to quickly summarize the network and identify many different processes and complexes that regulate it. Finally, we study the higher-order connectivity of the human PPI. By simultaneously evaluating interaction and annotation data, FUSE abstracts higher-order interaction maps by reducing the details of the underlying PPI to form a functional summary graph of interconnected functional clusters. Our results demonstrate its effectiveness and superiority over state-of-the-art graph clustering methods with GO term enrichment.
Delocalization of π electrons and trapping action of ZnO nanoparticles in PPY matrix for hybrid solar cell application

NASA Astrophysics Data System (ADS)

Singh, Rajinder; Choudhary, Ram Bilash; Kandulna, Rohit

2018-03-01

Polypyrrole (PPY)-Zinc Oxide (ZnO) nanocomposites with varying concentration of ZnO (1:1-1:4) were prepared via in-situ polymerization technique by using pyrrole monomer in the presence of ammonium persulphate (APS) as oxidant. Globular morphology of PPY and sheet like structure of ZnO was examined using FESEM and EDAX. FTIR showed the presence of vibration modes in fingerprint region (1500 cm-1-500 cm-1) for metal oxides confirming the presence and interaction of ZnO with the polymer matrix in nanocomposites. Amorphous nature of PPY and hexagonal wurtzite structure of ZnO was confirmed using XRD with average crystallite size within 20 nm-30 nm. PANI-ZnO (1:1) exhibited blue shift in comparison to PPY (neat) and optimized optical band gap ∼ 1.81 eV. The effect of carrier concentration was investigated using electrochemical analyzer and maximum current was recorded for PANI-ZnO (1:1). The highest conductance was calculated for PANI-ZnO (1:1) ∼ 7.3242 × 10-3 S using current -voltage characteristics. Thermal stability was found to be increasing with the increase in ZnO concentration PANI-ZnO nanocomposite.

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

2016-01-01

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462
Visible light photoelectrochemical aptasensor for adenosine detection based on CdS/PPy/g-C3N4 nanocomposites.

PubMed

Liu, Yixin; Ma, Hongmin; Zhang, Yong; Pang, Xuehui; Fan, Dawei; Wu, Dan; Wei, Qin

2016-12-15

In this work, a label-free photoelectrochemical (PEC) aptasensor was developed for adenosine detection based on CdS/PPy/g-C3N4 nanocomposites. The CdS/g-C3N4 heterojunction effectively prevented the photogenerated charges recombination of g-C3N4 and self-photocorrosion processes of CdS, improving photo-to-current conversion efficiency. The introduced polypyrrole (PPy) nanoparticles could lead to a more effective separation of photogenerated charges, thus resulting in a further increasing of photocurrent. The CdS/PPy/g-C3N4 was firstly employed as the photoactive materials for fabrication of aptasensor, and SH-aptamer was then adsorbed on the CdS/PPy/g-C3N4 modified electrodes through S-Cd bond. With increasing of adenosine concentration, the photocurrent decreased as the formation of SH-aptamer-adenosine bioaffinity complexes. Under optimal conditions, the PEC aptasensor had a sensitive response to adenosine in a linear range of 0.3nmolL(-1) to 200nmolL(-1) with a detection limit of 0.1nmolL(-1). Besides, the as-proposed aptasensor has also been applied in human serum samples analysis. The aptasensor exhibits high sensitivity and good stability, thus opening up a new promising PEC platform for some other small molecules analysis. Copyright © 2016 Elsevier B.V. All rights reserved.
Histomorphological differentiation of non-erosive reflux disease and functional heartburn in patients with PPI-refractory heartburn.

PubMed

Kandulski, A; Jechorek, D; Caro, C; Weigt, J; Wex, T; Mönkemüller, K; Malfertheiner, P

2013-09-01

Proton pump inhibitor (PPI)-refractory heartburn may be due to persistent gastro-oesophageal reflux, oesophageal hypersensitivity or functional heartburn (FH). The differentiation between non-erosive reflux disease (NERD) and FH may be very difficult. However, this differentiation is important for appropriate therapeutic management. Dilated intercellular spaces (DIS), papillary elongation (PE) and basal cell hyperplasia (BCH) can be all assessed by light microscopy. Whether these mucosal abnormalities allow the differentiation of NERD from FH in PPI-refractory patients is uncertain. To assess histopathological findings by light microscopy in patients with refractory heartburn to differentiate NERD from FH. Sixty-two patients with PPI-refractory symptoms underwent EGD and MII-pH after pausing PPI medication for 2 weeks before investigation. Twenty-five subjects without upper gastrointestinal symptoms were included as controls. Symptom assessment was based on the reflux disease questionnaire (RDQ). Biopsies were taken 3-5 cm above the gastro-oesophageal junction. DIS, PE, BCH and infiltration of immune cells were evaluated and a sum score was calculated. Based on endoscopy and MII-pH, GERD was diagnosed in 43 patients (NERD: 20; ERD: 23) and FH in 19 patients. There was no difference in symptoms between the groups. Each individual histopathological item was different between the groups (P < 0.0001). Between NERD and FH, the most significant difference was found for DIS and the histopathological sum score (P < 0.001). These findings suggest that oesophageal biopsies are useful to differentiate NERD from FH. Increased DIS and a histological sum score are the most significant histopathological abnormalities in NERD as compared with FH. © 2013 John Wiley & Sons Ltd.
Synthesis of an air-working trilayer artificial muscle using a conductive cassava starch biofilm (manihot esculenta, cranz) and polypyrrole (PPy)

NASA Astrophysics Data System (ADS)

Núñez D, Y. E.; Arrieta A, Á. A.; Segura B, J. A.; Bertel H, S. D.

2016-02-01

In this study, a methodology for obtaining a conductive cassava starch biofilm doped with lithium perchlorate (LiClO4) is shown, as well as the electrochemical technique for the synthesis of polypyrrole films, which are used for developing the trilayer artificial muscle PPy/Biopolymer/PPy designed to operate in air. Furthermore, results from the trilayer movement using chronoamperometric techniques are shown.
Genome-wide expression analyses of the stationary phase model of ageing in yeast.

PubMed

Wanichthanarak, Kwanjeera; Wongtosrad, Nutvadee; Petranovic, Dina

2015-07-01

Ageing processes involved in replicative lifespan (RLS) and chronological lifespan (CLS) have been found to be conserved among many organisms, including in unicellular Eukarya such as yeast Saccharomyces cerevisiae. Here we performed an integrated approach of genome wide expression profiles of yeast at different time points, during growth and starvation. The aim of the study was to identify transcriptional changes in those conditions by using several different computational analyses in order to propose transcription factors, biological networks and metabolic pathways that seem to be relevant during the process of chronological ageing in yeast. Specifically, we performed differential gene expression analysis, gene-set enrichment analysis and network-based analysis, and we identified pathways affected in the stationary phase and specific transcription factors driving transcriptional adaptations. The results indicate signal propagation from G protein-coupled receptors through signaling pathway components and other stress and nutrient-induced transcription factors resulting in adaptation of yeast cells to the lack of nutrients by activating metabolism associated with aerobic metabolism of carbon sources such as ethanol, glycerol and fatty acids. In addition, we found STE12, XBP1 and TOS8 as highly connected nodes in the subnetworks of ageing yeast. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Downsides and benefits of unicellularity in budding yeast

NASA Astrophysics Data System (ADS)

Balazsi, Gabor; Chen, Lin; Kuzdzal-Fick, Jennie

Yeast cells that do not separate after cell division form clumps. Clumping was shown to aid utilization of certain sugars, but its effects in stressful conditions are unknown. Generally speaking, what are the costs and benefits of unicellularity versus clumping multicellularity in normal and stressful conditions? To address this question, we evolved clumping yeast towards unicellularity by continuously propagating only those cells that remain suspended in liquid culture after settling. Whole-genome sequencing indicated that mutations in the AMN1 (antagonist of mitotic exit network) gene underlie the changes from clumping to unicellular phenotypes in these evolved yeast cells. Simple models predict that clumping should hinder growth in normal conditions while being protective in stress. Accordingly, we find experimentally that yeast clumps are more resistant to freeze/thaw, hydrogen peroxide, and ethanol stressors than their unicellular counterparts. On the other hand, unicellularity seems to be advantageous in normal conditions. Overall, these results reveal the downsides and benefits of unicellularity in different environmental conditions and uncover its genetic bases in yeast. This research was supported by the NIH Director's New Innovator Award Program (1DP2 OD006481-01), by NSF/IOS 1021675 and the Laufer Center for Physical & Quantitative Biology.
Construction of a Hierarchical NiCo2S4@PPy Core-Shell Heterostructure Nanotube Array on Ni Foam for a High-Performance Asymmetric Supercapacitor.

PubMed

Yan, Minglei; Yao, Yadong; Wen, Jiqiu; Long, Lu; Kong, Menglai; Zhang, Guanggao; Liao, Xiaoming; Yin, Guangfu; Huang, Zhongbing

2016-09-21

In this paper, a hierarchical NiCo2S4@polypyrrole core-shell heterostructure nanotube array on Ni foam (NiCo2S4@PPy/NF) was successfully developed as a bind-free electrode for supercapacitors. NiCo2S4@PPy-50/NF obtained under 50 s PPy electrodeposition shows a low charge-transfer resistance (0.31 Ω) and a high area specific capacitance of 9.781 F/cm(2) at a current density of 5 mA/cm(2), which is two times higher than that of pristine NiCo2S4/NF (4.255 F/cm(2)). Furthermore, an asymmetric supercapacitor was assembled using NiCo2S4@PPy-50/NF as positive electrode and activated carbon (AC) as negative electrode. The resulting NiCo2S4@PPy-50/NF//AC device exhibits a high energy density of 34.62 Wh/kg at a power density of 120.19 W/kg with good cycling performance (80.64% of the initial capacitance retention at 50 mA/cm(2) over 2500 cycles). The superior electrochemical performance can be attributed to the combined contribution of both component and unique core-shell heterostructure. The results demonstrate that the NiCo2S4@PPy-50 core-shell heterostructure nanotube array is promising as electrode material for supercapacitors in energy storage.
Prediction and functional analysis of the sweet orange protein-protein interaction network.

PubMed

Ding, Yu-Duan; Chang, Ji-Wei; Guo, Jing; Chen, Dijun; Li, Sen; Xu, Qiang; Deng, Xiu-Xin; Cheng, Yun-Jiang; Chen, Ling-Ling

2014-08-05

Sweet orange (Citrus sinensis) is one of the most important fruits world-wide. Because it is a woody plant with a long growth cycle, genetic studies of sweet orange are lagging behind those of other species. In this analysis, we employed ortholog identification and domain combination methods to predict the protein-protein interaction (PPI) network for sweet orange. The K-nearest neighbors (KNN) classification method was used to verify and filter the network. The final predicted PPI network, CitrusNet, contained 8,195 proteins with 124,491 interactions. The quality of CitrusNet was evaluated using gene ontology (GO) and Mapman annotations, which confirmed the reliability of the network. In addition, we calculated the expression difference of interacting genes (EDI) in CitrusNet using RNA-seq data from four sweet orange tissues, and also analyzed the EDI distribution and variation in different sub-networks. Gene expression in CitrusNet has significant modular features. Target of rapamycin (TOR) protein served as the central node of the hormone-signaling sub-network. All evidence supported the idea that TOR can integrate various hormone signals and affect plant growth. CitrusNet provides valuable resources for the study of biological functions in sweet orange.
Fabrication, characterization and gas sensing studies of PPy/MWCNT/SLS nanocomposite

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

Tiwari, D. C., E-mail: dctiwari2001@yahoo.com; Atri, Priyanka, E-mail: dctiwari2001@yahoo.com; Sharma, R.

2014-04-24

Multiwall carbon nanotubes (MWCNT) coated with polypyrrole nanocomposite was prepared by in-situ chemical oxidative polymerization method in the presence of surfactant (SLS). The scanning electron microscope (SEM) pictures indicate the core shell structure of PPy/MWCNT/SLS nanocomposite. Nature of the prepared material was investigated by X-ray diffraction spectroscopy. This nanocomposite shows the excellent gas sensing behaviour for ammonia gas at 150 ppm and 300 ppm levels.
Genomic signatures of adaptation to wine biological ageing conditions in biofilm-forming flor yeasts.

PubMed

Coi, A L; Bigey, F; Mallet, S; Marsit, S; Zara, G; Gladieux, P; Galeote, V; Budroni, M; Dequin, S; Legras, J L

2017-04-01

The molecular and evolutionary processes underlying fungal domestication remain largely unknown despite the importance of fungi to bioindustry and for comparative adaptation genomics in eukaryotes. Wine fermentation and biological ageing are performed by strains of S. cerevisiae with, respectively, pelagic fermentative growth on glucose and biofilm aerobic growth utilizing ethanol. Here, we use environmental samples of wine and flor yeasts to investigate the genomic basis of yeast adaptation to contrasted anthropogenic environments. Phylogenetic inference and population structure analysis based on single nucleotide polymorphisms revealed a group of flor yeasts separated from wine yeasts. A combination of methods revealed several highly differentiated regions between wine and flor yeasts, and analyses using codon-substitution models for detecting molecular adaptation identified sites under positive selection in the high-affinity transporter gene ZRT1. The cross-population composite likelihood ratio revealed selective sweeps at three regions, including in the hexose transporter gene HXT7, the yapsin gene YPS6 and the membrane protein coding gene MTS27. Our analyses also revealed that the biological ageing environment has led to the accumulation of numerous mutations in proteins from several networks, including Flo11 regulation and divalent metal transport. Together, our findings suggest that the tuning of FLO11 expression and zinc transport networks are a distinctive feature of the genetic changes underlying the domestication of flor yeasts. Our study highlights the multiplicity of genomic changes underlying yeast adaptation to man-made habitats and reveals that flor/wine yeast lineage can serve as a useful model for studying the genomics of adaptive divergence. © 2017 John Wiley & Sons Ltd.
Synthetic Genetic Arrays: Automation of Yeast Genetics.

PubMed

Kuzmin, Elena; Costanzo, Michael; Andrews, Brenda; Boone, Charles

2016-04-01

Genome-sequencing efforts have led to great strides in the annotation of protein-coding genes and other genomic elements. The current challenge is to understand the functional role of each gene and how genes work together to modulate cellular processes. Genetic interactions define phenotypic relationships between genes and reveal the functional organization of a cell. Synthetic genetic array (SGA) methodology automates yeast genetics and enables large-scale and systematic mapping of genetic interaction networks in the budding yeast,Saccharomyces cerevisiae SGA facilitates construction of an output array of double mutants from an input array of single mutants through a series of replica pinning steps. Subsequent analysis of genetic interactions from SGA-derived mutants relies on accurate quantification of colony size, which serves as a proxy for fitness. Since its development, SGA has given rise to a variety of other experimental approaches for functional profiling of the yeast genome and has been applied in a multitude of other contexts, such as genome-wide screens for synthetic dosage lethality and integration with high-content screening for systematic assessment of morphology defects. SGA-like strategies can also be implemented similarly in a number of other cell types and organisms, includingSchizosaccharomyces pombe,Escherichia coli, Caenorhabditis elegans, and human cancer cell lines. The genetic networks emerging from these studies not only generate functional wiring diagrams but may also play a key role in our understanding of the complex relationship between genotype and phenotype. © 2016 Cold Spring Harbor Laboratory Press.
Yeast Based Sensors

NASA Astrophysics Data System (ADS)

Shimomura-Shimizu, Mifumi; Karube, Isao

Since the first microbial cell sensor was studied by Karube et al. in 1977, many types of yeast based sensors have been developed as analytical tools. Yeasts are known as facultative anaerobes. Facultative anaerobes can survive in both aerobic and anaerobic conditions. The yeast based sensor consisted of a DO electrode and an immobilized omnivorous yeast. In yeast based sensor development, many kinds of yeast have been employed by applying their characteristics to adapt to the analyte. For example, Trichosporon cutaneum was used to estimate organic pollution in industrial wastewater. Yeast based sensors are suitable for online control of biochemical processes and for environmental monitoring. In this review, principles and applications of yeast based sensors are summarized.
An electrochemical aptasensor based on a TiO2/three-dimensional reduced graphene oxide/PPy nanocomposite for the sensitive detection of lysozyme.

PubMed

Wang, Minghua; Zhai, Shuyong; Ye, Zihan; He, Linghao; Peng, Donglai; Feng, Xiaozhong; Yang, Yanqin; Fang, Shaoming; Zhang, Hongzhong; Zhang, Zhihong

2015-04-14

A sensitive aptasensor based on a nanocomposite of hollow titanium dioxide nanoball, three-dimensional reduced graphene oxide, and polypyrrole (TiO2/3D-rGO/PPy) was developed for lysozyme detection. A lysozyme aptamer was easily immobilized onto the TiO2/3D-rGO/PPy nanocomposite matrix by assembling the aptamer onto graphene through simple π-stacking interactions and electrostatic interactions between PPy molecular chains and aptamer strands. In the presence of lysozyme, the aptamer on the adsorbent layer catches the target on the electrode interface, which generates a barrier for electrons and inhibits electron transfer, subsequently resulting in decreased electrochemically differential pulse voltammetric signals of a gold electrode modified with TiO2/3D-rGO/PPy. Using this strategy, a low limit of detection of 0.085 ng mL(-1) (5.5 pM) for detecting lysozyme was observed within the detection range of 0.1-50 ng mL(-1) (0.007-3.5 nM). The aptasensor also presents high specificity for lysozyme, which is unaffected by the coexistence of other proteins. Such an aptasensor opens a rapid, selective, and sensitive route to lysozyme detection. This finding indicates that the TiO2/3D-rGO/PPy nanocomposite could be used as an electrochemical biosensor for detecting proteins in the biomedical field.
A solid state actuator based on polypyrrole (PPy) and a solid electrolyte NBR working in air

NASA Astrophysics Data System (ADS)

Cho, Misuk; Nam, Jaedo; Choi, Hyouk Ryeol; Koo, Jachoon; Lee, Youngkwan

2005-05-01

The solid polymer electrolyte based conducting polymer actuator was presented. In the preparation of acutuator module, an ionic liquid impregnated a synthetic rubber (NBR) and PPy were used as a solid polymer electrolyte and conducting polymer, respectively. An ionic liquid, 1-butyl-3-methylimidazolium bis (trifluoromethyl sulfonyl)imide (BMITFSI) is gradually dispersed into the NBR film and the conducting polymer, PPy was synthesized on the surface of NBR. The ionic conductivity of new type solid polymer electrolyte as a function of the immersion time was investigated. The cyclic voltammetry responsed and the redox switching dynamics of PEDOT in NBR matrix were studied. The displacement of the actuator was measured by laser beam.
Gradual cessation of proton pump inhibitor (PPI) treatment may prevent rebound acid secretion, measured by the alkaline tide method, in dyspepsia and reflux patients.

PubMed

Niv, Yaron

2011-09-01

Gastro esophageal reflux disease and ulcer related or non-ulcer dyspepsia, attacks 20% of the Western population. These millions of patients are treated continuously with PPI for different periods, many for many years. Recently, rebound acid hypersecretion was recognized as a major clinical event after cessation of PPI therapy. Sustained hypergastrinemia due to daily PPI therapy causes increased acid-secretory capacity that appears when the drug is stopped. The transient increase in blood and urinary pH following gastric secretion has been termed the alkaline tide phenomenon. Carbonic acid, formed in the presence of the enzyme carbonic anhydrase, neutralizes intracellular hydroxyl ions produced as a result of luminal acid secretion. The bicarbonate generated is removed from the cell via the baso-lateral chloride bicarbonate exchanger. We have shown in several studies that this phenomenon parallels acid secretion. Thus, stimulation of acid secretion with test meal increased base excess maximally after 45 min and these changes parallel peak acid output measured in gastric aspirate. We hypothesize that gradual step down cessation of PPI will prevent this clinical relevant event. By measuring alkaline tide after PPI cessation we may prove this hypothesis. Copyright © 2011 Elsevier Ltd. All rights reserved.
The contribution of glutathione to the destabilizing effect of yeast on wheat dough.

PubMed

Verheyen, C; Albrecht, A; Herrmann, J; Strobl, M; Jekle, M; Becker, T

2015-04-15

Any factor which impairs the development of the gluten network affects the gas retention capacity and the overall baking performance. This study aimed to examine why rising yeast concentrations (Saccharomyces cerevisiae) decrease the dough elasticity in an asymptotic manner. Since in 27 commercial fresh and dry yeasts up to 81 mg glutathione (GSH) per 1g dry sample were found. Through the addition of reduced GSH in dough without yeast, the extent of dough weakening was analysed. Indeed rheological measurements confirmed that yeast-equivalent levels of GSH had a softening effect and during 3h fermentation the weakening coefficient increased from 0.3% to 20.4% in a Rheofermentometer. The present results indicate that free -SH compounds, as represented by GSH, considerably contribute to the softening of dough through dead yeast cells. Copyright © 2014 Elsevier Ltd. All rights reserved.
Environmental and Genetic Determinants of Colony Morphology in Yeast

PubMed Central

Granek, Joshua A.; Magwene, Paul M.

2010-01-01

Nutrient stresses trigger a variety of developmental switches in the budding yeast Saccharomyces cerevisiae. One of the least understood of such responses is the development of complex colony morphology, characterized by intricate, organized, and strain-specific patterns of colony growth and architecture. The genetic bases of this phenotype and the key environmental signals involved in its induction have heretofore remained poorly understood. By surveying multiple strain backgrounds and a large number of growth conditions, we show that limitation for fermentable carbon sources coupled with a rich nitrogen source is the primary trigger for the colony morphology response in budding yeast. Using knockout mutants and transposon-mediated mutagenesis, we demonstrate that two key signaling networks regulating this response are the filamentous growth MAP kinase cascade and the Ras-cAMP-PKA pathway. We further show synergistic epistasis between Rim15, a kinase involved in integration of nutrient signals, and other genes in these pathways. Ploidy, mating-type, and genotype-by-environment interactions also appear to play a role in the controlling colony morphology. Our study highlights the high degree of network reuse in this model eukaryote; yeast use the same core signaling pathways in multiple contexts to integrate information about environmental and physiological states and generate diverse developmental outputs. PMID:20107600
Mitochondrial-morphology-targeted breeding of industrial yeast strains for alcohol fermentation.

PubMed

Kitagaki, Hiroshi

2009-05-29

Since mitochondrial genes are repressed under high glucose and low O2, and these conditions correspond to the conditions in which yeast cells are exposed during alcohol fermentation, the existence and structure of yeast mitochondria during alcohol fermentation have not been elucidated. Yeast mitochondria can be observed throughout brewing of sake (Japanese rice wine) and fragment during brewing. Furthermore, it has been revealed that Fis1 [fission 1 (mitochondrial outer membrane) homologue (Saccharomyces cerevisiae)], which is a transmembrane protein with its C-terminal anchor embedded in the outer membrane of mitochondria, is required for fragmentation of yeast mitochondria during sake brewing. By utilizing this knowledge, a fis1 disruptant of a sake yeast strain has been generated that has a networked mitochondrial structure throughout sake brewing. It transpired that this strain produces a high content of malate, which imparts a crisp acidic taste, during sake brewing. This strategy is a useful and a completely novel strategy towards developing a new yeast strain which produces a high content of malate in sake, and mitochondrial morphology has now emerged as a promising target for the breeding of practical industrial strains.
Examining the reliability and validity of an abbreviated Psychopathic Personality Inventory-Revised (PPI-R) in four samples.

PubMed

Ruchensky, Jared R; Edens, John F; Donnellan, M Brent; Witt, Edward A

2017-02-01

A recently developed 40-item short-form of the Psychopathic Personality Inventory-Revised (PPI-R; Lilienfeld & Widows, 2005) has shown considerable promise as an alternative to the long-form of the instrument (Eisenbarth, Lilienfeld, & Yarkoni, 2015). Beyond the initial construction of the short-form, however, Eisenbarth et al. only evaluated a small number of external correlates in a German college student sample. In this study, we evaluate the internal consistency of the short-form scales in 4 samples previously administered the full PPI-R (3 U.S. college student samples and 1 U.S. forensic psychiatric inpatient sample) and examine a wide range of external correlates to compare the nomological nets of the short- and long-forms. Across all 4 samples, correlations between each short-form scale and its corresponding long-form scale were uniformly high (all rs > .75). In terms of external correlates, the pattern of associations was exceedingly similar, for the short-form and long-form composites with a largely trivial reduction in effect size. Collectively, our findings offer considerable support for the utility of this new short-form as a substitute for the full PPI-R. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Differential reward network functional connectivity in cannabis dependent and non-dependent users☆

PubMed Central

Filbey, Francesca M.; Dunlop, Joseph

2015-01-01

Background Emergent studies show that similar to other substances of abuse, cue-reactivity to cannabis is also associated with neural response in the brain’s reward pathway (Filbey et al., 2009). However, the inter-relatedness of brain regions during cue-reactivity in cannabis users remains unknown. Methods In this study, we conducted a series of investigations to determine functional connectivity during cue-reactivity in 71 cannabis users. First, we used psychophysiological interaction (PPI) analysis to examine coherent neural response to cannabis cues. Second, we evaluated whether these patterns of network functional connectivity differentiated dependent and non-dependent users. Finally, as an exploratory analysis, we determined the directionality of these connections via Granger connectivity analyses. Results PPI analyses showed reward network functional connectivity with the nucleus accumbens (NAc) seed region during cue exposure. Between-group contrasts found differential effects of dependence status. Dependent users (N = 31) had greater functional connectivity with amygdala and anterior cingulate gyrus (ACG) seeds while the non-dependent users (N = 24) had greater functional connectivity with the NAc, orbitofrontal cortex (OFC) and hippocampus seeds. Granger analyses showed that hippocampal and ACG activation preceded neural response in reward areas. Conclusions Both PPI and Granger analyses demonstrated strong functional coherence in reward regions during exposure to cannabis cues in current cannabis users. Functional connectivity (but not regional activation) in the reward network differentiated dependent from non-dependent cannabis users. Our findings suggest that repeated cannabis exposure causes observable changes in functional connectivity in the reward network and should be considered in intervention strategies. PMID:24838032

VANLO - Interactive visual exploration of aligned biological networks

PubMed Central

Brasch, Steffen; Linsen, Lars; Fuellen, Georg

2009-01-01

Background Protein-protein interaction (PPI) is fundamental to many biological processes. In the course of evolution, biological networks such as protein-protein interaction networks have developed. Biological networks of different species can be aligned by finding instances (e.g. proteins) with the same common ancestor in the evolutionary process, so-called orthologs. For a better understanding of the evolution of biological networks, such aligned networks have to be explored. Visualization can play a key role in making the various relationships transparent. Results We present a novel visualization system for aligned biological networks in 3D space that naturally embeds existing 2D layouts. In addition to displaying the intra-network connectivities, we also provide insight into how the individual networks relate to each other by placing aligned entities on top of each other in separate layers. We optimize the layout of the entire alignment graph in a global fashion that takes into account inter- as well as intra-network relationships. The layout algorithm includes a step of merging aligned networks into one graph, laying out the graph with respect to application-specific requirements, splitting the merged graph again into individual networks, and displaying the network alignment in layers. In addition to representing the data in a static way, we also provide different interaction techniques to explore the data with respect to application-specific tasks. Conclusion Our system provides an intuitive global understanding of aligned PPI networks and it allows the investigation of key biological questions. We evaluate our system by applying it to real-world examples documenting how our system can be used to investigate the data with respect to these key questions. Our tool VANLO (Visualization of Aligned Networks with Layout Optimization) can be accessed at . PMID:19821976
Facile Synthesis of SrCO3-Sr(OH)2/PPy Nanocomposite with Enhanced Photocatalytic Activity under Visible Light

PubMed Central

Márquez-Herrera, Alfredo; Ovando-Medina, Victor Manuel; Castillo-Reyes, Blanca Estela; Zapata-Torres, Martin; Meléndez-Lira, Miguel; González-Castañeda, Jaquelina

2016-01-01

Pyrrole monomer was chemically polymerized onto SrCO3-Sr(OH)2 powders to obtain SrCO3-Sr(OH)2/polypyrrole nanocomposite to be used as a candidate for photocatalytic degradation of methylene blue dye (MB). The material was characterized by Fourier transform infrared (FTIR) spectroscopy, UV/Vis spectroscopy, and X-ray diffraction (XRD). It was observed from transmission electronic microscopy (TEM) analysis that the reported synthesis route allows the production of SrCO3-Sr(OH)2 nanoparticles with particle size below 100 nm which were embedded within a semiconducting polypyrrole matrix (PPy). The SrCO3-Sr(OH)2 and SrCO3-Sr(OH)2/PPy nanocomposites were tested in the photodegradation of MB dye under visible light irradiation. Also, the effects of MB dye initial concentration and the catalyst load on photodegradation efficiency were studied and discussed. Under the same conditions, the efficiency of photodegradation of MB employing the SrCO3-Sr(OH)2/PPy nanocomposite increases as compared with that obtained employing the SrCO3-Sr(OH)2 nanocomposite. PMID:28787830
Extracellular Polysaccharides Produced by Yeasts and Yeast-Like Fungi

NASA Astrophysics Data System (ADS)

van Bogaert, Inge N. A.; de Maeseneire, Sofie L.; Vandamme, Erick J.

Several yeasts and yeast-like fungi are known to produce extracellular polysaccharides. Most of these contain D-mannose, either alone or in combination with other sugars or phosphate. A large chemical and structural variability is found between yeast species and even among different strains. The types of polymers that are synthesized can be chemically characterized as mannans, glucans, phosphoman-nans, galactomannans, glucomannans and glucuronoxylomannans. Despite these differences, almost all of the yeast exopolysaccharides display some sort of biological activity. Some of them have already applications in chemistry, pharmacy, cosmetics or as probiotic. Furthermore, some yeast exopolysaccharides, such as pullulan, exhibit specific physico-chemical and rheological properties, making them useful in a wide range of technical applications. A survey is given here of the production, the characteristics and the application potential of currently well studied yeast extracellular polysaccharides.
Yeast Infection (Vaginal)

MedlinePlus

Yeast infection (vaginal) Overview A vaginal yeast infection is a fungal infection that causes irritation, discharge and intense itchiness ... symptoms Causes The fungus candida causes a vaginal yeast infection. Your vagina naturally contains a balanced mix of yeast, including ...
The Topology of the Growing Human Interactome Data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-01

We have long moved past the one-gene-one-function concept originally proposed by Beadle and Tatum back in 1941; but the full understanding of genotype-phenotype relations still largely relies on the analysis of static, snapshot-like, interaction data sets. Here, we look at what global patterns can be uncovered if we simply trace back the human interactome network over the last decade of protein-protein interaction (PPI) screening. We take a purely topological approach and find that as the human interactome is getting denser, it is not only gaining in structure (in terms of now being better fit by structured network models than before), but also there are patterns in the way in which it is growing: (a) newly added proteins tend to get linked to existing proteins in the interactome that are not know to interact; and (b) new proteins tend to link to already well connected proteins. Moreover, the alignment between human and yeast interactomes spanning over 40% of yeast's proteins - that are involved in regulation of transcription, RNA splicing and other cellcycle- related processes-suggests the existence of a part of the interactome which remains topologically and functionally unaffected through evolution. Furthermore, we find a small sub-network, specific to the "core" of the human interactome and involved in regulation of transcription and cancer development, whose wiring has not changed within the human interactome over the last 10 years of interacome data acquisition. Finally, we introduce a generalisation of the clustering coefficient of a network as a new measure called the cycle coefficient, and use it to show that PPI networks of human and model organisms are wired in a tight way which forbids the occurrence large cycles.
The topology of the growing human interactome data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-23

We have long moved past the one-gene–one-function concept originally proposed by Beadle and Tatum back in 1941; but the full understanding of genotype–phenotype relations still largely relies on the analysis of static, snapshot-like, interaction data sets. Here, we look at what global patterns can be uncovered if we simply trace back the human interactome network over the last decade of protein- protein interaction (PPI) screening. We take a purely topological approach and find that as the human interactome is getting denser, it is not only gaining in structure (in terms of now being better fit by structured network models than before), but also there are patterns in the way in which it is growing: (a) newly added proteins tend to get linked to existing proteins in the interactome that are not know to interact; and (b) new proteins tend to link to already well connected proteins. Moreover, the alignment between human and yeast interactomes spanning over 40% of yeast’s proteins — that are involved in regulation of transcription, RNA splicing and other cellcycle-related processes—suggests the existence of a part of the interactome which remains topologically and functionally unaffected through evolution. Furthermore, we find a small sub-network, specific to the “core” of the human interactome and involved in regulation of transcription and cancer development, whose wiring has not changed within the human interactome over the last 10 years of interacome data acquisition. Finally, we introduce a generalisation of the clustering coefficient of a network as a new measure called the cycle coefficient, and use it to show that PPI networks of human and model organisms are wired in a tight way which forbids the occurrence large cycles.
Transport and cytotoxicity of the anticancer drug 3-bromopyruvate in the yeast Saccharomyces cerevisiae.

PubMed

Lis, Paweł; Zarzycki, Marek; Ko, Young H; Casal, Margarida; Pedersen, Peter L; Goffeau, Andre; Ułaszewski, Stanisław

2012-02-01

We have investigated the cytotoxicity in Saccharomyces cerevisiae of the novel antitumor agent 3-bromopyruvate (3-BP). 3-BP enters the yeast cells through the lactate/pyruvate H(+) symporter Jen1p and inhibits cell growth at minimal inhibitory concentration of 1.8 mM when grown on non-glucose conditions. It is not submitted to the efflux pumps conferring Pleiotropic Drug Resistance in yeast. Yeast growth is more sensitive to 3-BP than Gleevec (Imatinib methanesulfonate) which in contrast to 3-BP is submitted to the PDR network of efflux pumps. The sensitivity of yeast to 3-BP is increased considerably by mutations or chemical treatment by buthionine sulfoximine that decrease the intracellular concentration of glutathione.
Global investigation of protein-protein interactions in yeast Saccharomyces cerevisiae using re-occurring short polypeptide sequences.

PubMed

Pitre, S; North, C; Alamgir, M; Jessulat, M; Chan, A; Luo, X; Green, J R; Dumontier, M; Dehne, F; Golshani, A

2008-08-01

Protein-protein interaction (PPI) maps provide insight into cellular biology and have received considerable attention in the post-genomic era. While large-scale experimental approaches have generated large collections of experimentally determined PPIs, technical limitations preclude certain PPIs from detection. Recently, we demonstrated that yeast PPIs can be computationally predicted using re-occurring short polypeptide sequences between known interacting protein pairs. However, the computational requirements and low specificity made this method unsuitable for large-scale investigations. Here, we report an improved approach, which exhibits a specificity of approximately 99.95% and executes 16,000 times faster. Importantly, we report the first all-to-all sequence-based computational screen of PPIs in yeast, Saccharomyces cerevisiae in which we identify 29,589 high confidence interactions of approximately 2 x 10(7) possible pairs. Of these, 14,438 PPIs have not been previously reported and may represent novel interactions. In particular, these results reveal a richer set of membrane protein interactions, not readily amenable to experimental investigations. From the novel PPIs, a novel putative protein complex comprised largely of membrane proteins was revealed. In addition, two novel gene functions were predicted and experimentally confirmed to affect the efficiency of non-homologous end-joining, providing further support for the usefulness of the identified PPIs in biological investigations.
Triangle network motifs predict complexes by complementing high-error interactomes with structural information.

PubMed

Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-06-27

A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient
Ligand functionalization as a deactivation pathway in a fac-Ir(ppy)3-mediated radical addition.

PubMed

Devery Iii, James J; Douglas, James J; Nguyen, John D; Cole, Kevin P; Flowers Ii, Robert A; Stephenson, Corey R J

2015-01-01

Knowledge of the kinetic behavior of catalysts under synthetically relevant conditions is vital for the efficient use of compounds that mediate important transformations regardless of their composition or driving force. In particular, these data are of great importance to add perspective to the growing number of applications of photoactive transition metal complexes. Here we present kinetic, synthetic, and spectroscopic evidence of the mechanistic behavior of fac -Ir(ppy) 3 in a visible light-mediated radical addition to 3-methylindole, demonstrating the instability of fac -Ir(ppy) 3 under these conditions. During the reaction, rapid in situ functionalization of the photocatalyst occurs, eventually leading to deactivation. These findings demonstrate a conceivable deactivation process for catalytic single electron reactions in the presence of radicophilic ligands. Attempts to inhibit photocatalyst deactivation through structural modification provide further insight into catalyst selection for a given system of interest.
Querying graphs in protein-protein interactions networks using feedback vertex set.

PubMed

Blin, Guillaume; Sikora, Florian; Vialette, Stéphane

2010-01-01

Recent techniques increase rapidly the amount of our knowledge on interactions between proteins. The interpretation of these new information depends on our ability to retrieve known substructures in the data, the Protein-Protein Interactions (PPIs) networks. In an algorithmic point of view, it is an hard task since it often leads to NP-hard problems. To overcome this difficulty, many authors have provided tools for querying patterns with a restricted topology, i.e., paths or trees in PPI networks. Such restriction leads to the development of fixed parameter tractable (FPT) algorithms, which can be practicable for restricted sizes of queries. Unfortunately, Graph Homomorphism is a W[1]-hard problem, and hence, no FPT algorithm can be found when patterns are in the shape of general graphs. However, Dost et al. gave an algorithm (which is not implemented) to query graphs with a bounded treewidth in PPI networks (the treewidth of the query being involved in the time complexity). In this paper, we propose another algorithm for querying pattern in the shape of graphs, also based on dynamic programming and the color-coding technique. To transform graphs queries into trees without loss of informations, we use feedback vertex set coupled to a node duplication mechanism. Hence, our algorithm is FPT for querying graphs with a bounded size of their feedback vertex set. It gives an alternative to the treewidth parameter, which can be better or worst for a given query. We provide a python implementation which allows us to validate our implementation on real data. Especially, we retrieve some human queries in the shape of graphs into the fly PPI network.
Gateway Vectors for Efficient Artificial Gene Assembly In Vitro and Expression in Yeast Saccharomyces cerevisiae

PubMed Central

Giuraniuc, Claudiu V.; MacPherson, Murray; Saka, Yasushi

2013-01-01

Construction of synthetic genetic networks requires the assembly of DNA fragments encoding functional biological parts in a defined order. Yet this may become a time-consuming procedure. To address this technical bottleneck, we have created a series of Gateway shuttle vectors and an integration vector, which facilitate the assembly of artificial genes and their expression in the budding yeast Saccharomyces cerevisiae. Our method enables the rapid construction of an artificial gene from a promoter and an open reading frame (ORF) cassette by one-step recombination reaction in vitro. Furthermore, the plasmid thus created can readily be introduced into yeast cells to test the assembled gene’s functionality. As flexible regulatory components of a synthetic genetic network, we also created new versions of the tetracycline-regulated transactivators tTA and rtTA by fusing them to the auxin-inducible degron (AID). Using our gene assembly approach, we made yeast expression vectors of these engineered transactivators, AIDtTA and AIDrtTA and then tested their functions in yeast. We showed that these factors can be regulated by doxycycline and degraded rapidly after addition of auxin to the medium. Taken together, the method for combinatorial gene assembly described here is versatile and would be a valuable tool for yeast synthetic biology. PMID:23675537
Distinct Domestication Trajectories in Top-Fermenting Beer Yeasts and Wine Yeasts.

PubMed

Gonçalves, Margarida; Pontes, Ana; Almeida, Pedro; Barbosa, Raquel; Serra, Marta; Libkind, Diego; Hutzler, Mathias; Gonçalves, Paula; Sampaio, José Paulo

2016-10-24

Beer is one of the oldest alcoholic beverages and is produced by the fermentation of sugars derived from starches present in cereal grains. Contrary to lager beers, made by bottom-fermenting strains of Saccharomyces pastorianus, a hybrid yeast, ale beers are closer to the ancient beer type and are fermented by S. cerevisiae, a top-fermenting yeast. Here, we use population genomics to investigate (1) the closest relatives of top-fermenting beer yeasts; (2) whether top-fermenting yeasts represent an independent domestication event separate from those already described; (3) whether single or multiple beer yeast domestication events can be inferred; and (4) whether top-fermenting yeasts represent non-recombinant or recombinant lineages. Our results revealed that top-fermenting beer yeasts are polyphyletic, with a main clade composed of at least three subgroups, dominantly represented by the German, British, and wheat beer strains. Other beer strains were phylogenetically close to sake, wine, or bread yeasts. We detected genetic signatures of beer yeast domestication by investigating genes previously linked to brewing and using genome-wide scans. We propose that the emergence of the main clade of beer yeasts is related with a domestication event distinct from the previously known cases of wine and sake yeast domestication. The nucleotide diversity of the main beer clade more than doubled that of wine yeasts, which might be a consequence of fundamental differences in the modes of beer and wine yeast domestication. The higher diversity of beer strains could be due to the more intense and different selection regimes associated to brewing. Copyright © 2016 Elsevier Ltd. All rights reserved.
The Vineyard Yeast Microbiome, a Mixed Model Microbial Map

PubMed Central

Setati, Mathabatha Evodia; Jacobson, Daniel; Andong, Ursula-Claire; Bauer, Florian

2012-01-01

Vineyards harbour a wide variety of microorganisms that play a pivotal role in pre- and post-harvest grape quality and will contribute significantly to the final aromatic properties of wine. The aim of the current study was to investigate the spatial distribution of microbial communities within and between individual vineyard management units. For the first time in such a study, we applied the Theory of Sampling (TOS) to sample gapes from adjacent and well established commercial vineyards within the same terroir unit and from several sampling points within each individual vineyard. Cultivation-based and molecular data sets were generated to capture the spatial heterogeneity in microbial populations within and between vineyards and analysed with novel mixed-model networks, which combine sample correlations and microbial community distribution probabilities. The data demonstrate that farming systems have a significant impact on fungal diversity but more importantly that there is significant species heterogeneity between samples in the same vineyard. Cultivation-based methods confirmed that while the same oxidative yeast species dominated in all vineyards, the least treated vineyard displayed significantly higher species richness, including many yeasts with biocontrol potential. The cultivatable yeast population was not fully representative of the more complex populations seen with molecular methods, and only the molecular data allowed discrimination amongst farming practices with multivariate and network analysis methods. Importantly, yeast species distribution is subject to significant intra-vineyard spatial fluctuations and the frequently reported heterogeneity of tank samples of grapes harvested from single vineyards at the same stage of ripeness might therefore, at least in part, be due to the differing microbiota in different sections of the vineyard. PMID:23300721
Symptom-specific amygdala hyperactivity modulates motor control network in conversion disorder.

PubMed

Hassa, Thomas; Sebastian, Alexandra; Liepert, Joachim; Weiller, Cornelius; Schmidt, Roger; Tüscher, Oliver

2017-01-01

Initial historical accounts as well as recent data suggest that emotion processing is dysfunctional in conversion disorder patients and that this alteration may be the pathomechanistic neurocognitive basis for symptoms in conversion disorder. However, to date evidence of direct interaction of altered negative emotion processing with motor control networks in conversion disorder is still lacking. To specifically study the neural correlates of emotion processing interacting with motor networks we used a task combining emotional and sensorimotor stimuli both separately as well as simultaneously during functional magnetic resonance imaging in a well characterized group of 13 conversion disorder patients with functional hemiparesis and 19 demographically matched healthy controls. We performed voxelwise statistical parametrical mapping for a priori regions of interest within emotion processing and motor control networks. Psychophysiological interaction (PPI) was used to test altered functional connectivity of emotion and motor control networks. Only during simultaneous emotional stimulation and passive movement of the affected hand patients displayed left amygdala hyperactivity. PPI revealed increased functional connectivity in patients between the left amygdala and the (pre-)supplemental motor area and the subthalamic nucleus, key regions within the motor control network. These findings suggest a novel mechanistic direct link between dysregulated emotion processing and motor control circuitry in conversion disorder.
Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets.

PubMed

Ho, Hsiang; Milenković, Tijana; Memisević, Vesna; Aruri, Jayavani; Przulj, Natasa; Ganesan, Anand K

2010-06-15

RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis. In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes. We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches.
Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets

PubMed Central

2010-01-01

Background RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis. Results In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes. Conclusions We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches. PMID:20550706
A network biology approach to understanding the importance of chameleon proteins in human physiology and pathology.

PubMed

Bahramali, Golnaz; Goliaei, Bahram; Minuchehr, Zarrin; Marashi, Sayed-Amir

2017-02-01

Chameleon proteins are proteins which include sequences that can adopt α-helix-β-strand (HE-chameleon) or α-helix-coil (HC-chameleon) or β-strand-coil (CE-chameleon) structures to operate their crucial biological functions. In this study, using a network-based approach, we examined the chameleon proteins to give a better knowledge on these proteins. We focused on proteins with identical chameleon sequences with more than or equal to seven residues long in different PDB entries, which adopt HE-chameleon, HC-chameleon, and CE-chameleon structures in the same protein. One hundred and ninety-one human chameleon proteins were identified via our in-house program. Then, protein-protein interaction (PPI) networks, Gene ontology (GO) enrichment, disease network, and pathway enrichment analyses were performed for our derived data set. We discovered that there are chameleon sequences which reside in protein-protein interaction regions between two proteins critical for their dual function. Analysis of the PPI networks for chameleon proteins introduced five hub proteins, namely TP53, EGFR, HSP90AA1, PPARA, and HIF1A, which were presented in four PPI clusters. The outcomes demonstrate that the chameleon regions are in critical domains of these proteins and are important in the development and treatment of human cancers. The present report is the first network-based functional study of chameleon proteins using computational approaches and might provide a new perspective for understanding the mechanisms of diseases helping us in developing new medical therapies along with discovering new proteins with chameleon properties which are highly important in cancer.
Differences in toxicity of anionic and cationic PAMAM and PPI dendrimers in zebrafish embryos and cancer cell lines

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

Bodewein, Lambert

Dendrimers are an emerging class of polymeric nanoparticles with beneficial biomedical applications like early diagnostics, in vitro gene transfection or controlled drug delivery. However, the potential toxic impact of exposure on human health or the environment is often inadequately defined. Thus, polyamidoamine (PAMAM) dendrimers of generations G3.0, 3.5, 4.0, 4.5 and 5.0 and polypropylenimine (PPI) dendrimers G3.0, 4.0 and 5.0 were tested in zebrafish embryos for 96 h and human cancer cell lines for 24 h, to assess and compare developmental in vivo toxicity with cytotoxicity. The zebrafish embryo toxicity of cationic PAMAM and PPI dendrimers increased over time, withmore » EC50 values ranging from 0.16 to just below 1.7 μM at 24 and 48 hpf. The predominant effects were mortality, plus reduced heartbeat and blood circulation for PPI dendrimers. Apoptosis in the embryos increased in line with the general toxicity concentration-dependently. Hatch and dechorionation of the embryos increased the toxicity, suggesting a protective role of the chorion. Lower generation dendrimers were more toxic in the embryos whereas the toxicity in the HepG2 and DU145 cell lines increased with increasing generation of cationic PAMAMs and PPI dendrimers. HepG2 were less sensitive than DU145 cells, with IC50 values ≥ 402 μM (PAMAMs) and ≤ 240 μM (PPIs) for HepG2 and ≤ 13.24 μM (PAMAMs) and ≤ 12.84 μM (PPIs) for DU145. Neither in fish embryos nor cells toxicity thresholds were determinable for anionic PAMAM G3.5 and G4.5. The study demonstrated that the cytotoxicity underestimated the in-vivo toxicity of the dendrimers in the fish embryos. - Highlights: • Zebrafish embryo toxicity of cationic PAMAM and PPI dendrimers increased over time. • Zebrafish embryo toxicity of cationic dendrimers did not increase with generation. • Cationic dendrimers induced apoptosis in zebrafish embryos. • Toxicity of cationic dendrimers was lower in HepG2 and DU145 than zebrafish
Ultra-broad polypyrrole (PPy) nano-ribbons seeded by racemic surfactants aggregates and their high-performance electromagnetic radiation elimination.

PubMed

Jiao, Yingzhi; Wu, Fan; Zhang, Kun; Sun, Mengxiao; Xie, Aming; Dong, Wei

2017-08-04

Ribbon-like nano-structures possess high aspect ratios, and thus have great potential in the development of high-performance microwave absorption (MA) materials that can effectively eliminate adverse electromagnetic radiation. However, these nano-structures have been scarcely constructed in the field of MA, because of the lack of efficient synthetic routes. Herein, we developed an efficient method to successfully construct polypyrrole (PPy) nano-ribbons using the self-assembly aggregates of a racemic surfactant as the seeds. The frequency range with a reflection loss value of lower than -10 dB reached 7.68 GHz in the frequency range of 10.32-18.00 GHz, and surpassed all the currently reported PPy nano-structures, as well as most other MA nano-materials. Through changing the amount of surfactant, both the nano-structures and MA performance can be effectively regulated. Furthermore, the reason behind the high-performance MA of PPy nano-ribbons has been deeply explored. It opens up the opportunity for the application of conducting polymer nano-ribbons as a lightweight and tunable high-performance MA material, especially in applications of special aircraft and flexible electronics.

Ultra-broad polypyrrole (PPy) nano-ribbons seeded by racemic surfactants aggregates and their high-performance electromagnetic radiation elimination

NASA Astrophysics Data System (ADS)

Jiao, Yingzhi; Wu, Fan; Zhang, Kun; Sun, Mengxiao; Xie, Aming; Dong, Wei

2017-08-01

Ribbon-like nano-structures possess high aspect ratios, and thus have great potential in the development of high-performance microwave absorption (MA) materials that can effectively eliminate adverse electromagnetic radiation. However, these nano-structures have been scarcely constructed in the field of MA, because of the lack of efficient synthetic routes. Herein, we developed an efficient method to successfully construct polypyrrole (PPy) nano-ribbons using the self-assembly aggregates of a racemic surfactant as the seeds. The frequency range with a reflection loss value of lower than -10 dB reached 7.68 GHz in the frequency range of 10.32-18.00 GHz, and surpassed all the currently reported PPy nano-structures, as well as most other MA nano-materials. Through changing the amount of surfactant, both the nano-structures and MA performance can be effectively regulated. Furthermore, the reason behind the high-performance MA of PPy nano-ribbons has been deeply explored. It opens up the opportunity for the application of conducting polymer nano-ribbons as a lightweight and tunable high-performance MA material, especially in applications of special aircraft and flexible electronics.
Dielectric and electrical study of PPy doped PVA-PVP films

NASA Astrophysics Data System (ADS)

Jha, Sushma; Tripathi, Deepti

2018-05-01

Dielectric parameters of free standing films of pure PVA (PolyvinylAlcohol) and PVA with varying concentrations of PVP(Polyvinylpyrrolidone) and Polypyrrole were prepared and studied in low frequency range (100Hz - 2MHz). The results show that dielectric constant, loss tangent and conductivity increase sharply on increasing the concentration of PVP above 50wt% in polymer matrix. PVA-PVP film with low concentration of PPy showed improvement in the values of complex permittivity, loss tangent and ac conductivity within the experimental frequency range. This eco - friendly polymeric material will be studied for its probable application for RFI/EMI shielding, biosensors, capacitors & insulation purposes.
Cell-autonomous mechanisms of chronological aging in the yeast Saccharomyces cerevisiae.

PubMed

Arlia-Ciommo, Anthony; Leonov, Anna; Piano, Amanda; Svistkova, Veronika; Titorenko, Vladimir I

2014-05-27

A body of evidence supports the view that the signaling pathways governing cellular aging - as well as mechanisms of their modulation by longevity-extending genetic, dietary and pharmacological interventions - are conserved across species. The scope of this review is to critically analyze recent advances in our understanding of cell-autonomous mechanisms of chronological aging in the budding yeast Saccharomyces cerevisiae . Based on our analysis, we propose a concept of a biomolecular network underlying the chronology of cellular aging in yeast. The concept posits that such network progresses through a series of lifespan checkpoints. At each of these checkpoints, the intracellular concentrations of some key intermediates and products of certain metabolic pathways - as well as the rates of coordinated flow of such metabolites within an intricate network of intercompartmental communications - are monitored by some checkpoint-specific "master regulator" proteins. The concept envisions that a synergistic action of these master regulator proteins at certain early-life and late-life checkpoints modulates the rates and efficiencies of progression of such processes as cell metabolism, growth, proliferation, stress resistance, macromolecular homeostasis, survival and death. The concept predicts that, by modulating these vital cellular processes throughout lifespan (i.e., prior to an arrest of cell growth and division, and following such arrest), the checkpoint-specific master regulator proteins orchestrate the development and maintenance of a pro- or anti-aging cellular pattern and, thus, define longevity of chronologically aging yeast.
P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

PubMed

Young-Rae Cho; Yanan Xin; Speegle, Greg

2015-01-01

Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.
Weighted gene co‑expression network analysis in identification of key genes and networks for ischemic‑reperfusion remodeling myocardium.

PubMed

Guo, Nan; Zhang, Nan; Yan, Liqiu; Lian, Zheng; Wang, Jiawang; Lv, Fengfeng; Wang, Yunfei; Cao, Xufen

2018-06-14

Acute myocardial infarction induces ventricular remodeling, which is implicated in dilated heart and heart failure. The pathogenical mechanism of myocardium remodeling remains to be elucidated. The aim of the present study was to identify key genes and networks for myocardium remodeling following ischemia‑reperfusion (IR). First, the mRNA expression data from the National Center for Biotechnology Information database were downloaded to identify differences in mRNA expression of the IR heart at days 2 and 7. Then, weighted gene co‑expression network analysis, hierarchical clustering, protein‑protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to identify key genes and networks for the heart remodeling process following IR. A total of 3,321 differentially expressed genes were identified during the heart remodeling process. A total of 6 modules were identified through gene co‑expression network analysis. GO and KEGG analysis results suggested that each module represented a different biological function and was associated with different pathways. Finally, hub genes of each module were identified by PPI network construction. The present study revealed that heart remodeling following IR is a complicated process, involving extracellular matrix organization, neural development, apoptosis and energy metabolism. The dysregulated genes, including SRC proto‑oncogene, non‑receptor tyrosine kinase, discs large MAGUK scaffold protein 1, ATP citrate lyase, RAN, member RAS oncogene family, tumor protein p53, and polo like kinase 2, may be essential for heart remodeling following IR and may be used as potential targets for the inhibition of heart remodeling following acute myocardial infarction.
A conserved signaling network monitors delivery of sphingolipids to the plasma membrane in budding yeast

PubMed Central

Clarke, Jesse; Dephoure, Noah; Horecka, Ira; Gygi, Steven; Kellogg, Douglas

2017-01-01

In budding yeast, cell cycle progression and ribosome biogenesis are dependent on plasma membrane growth, which ensures that events of cell growth are coordinated with each other and with the cell cycle. However, the signals that link the cell cycle and ribosome biogenesis to membrane growth are poorly understood. Here we used proteome-wide mass spectrometry to systematically discover signals associated with membrane growth. The results suggest that membrane trafficking events required for membrane growth generate sphingolipid-dependent signals. A conserved signaling network appears to play an essential role in signaling by responding to delivery of sphingolipids to the plasma membrane. In addition, sphingolipid-dependent signals control phosphorylation of protein kinase C (Pkc1), which plays an essential role in the pathways that link the cell cycle and ribosome biogenesis to membrane growth. Together these discoveries provide new clues as to how growth-dependent signals control cell growth and the cell cycle. PMID:28794263
Metabolic reconstruction and flux analysis of industrial Pichia yeasts.

PubMed

Chung, Bevan Kai-Sheng; Lakshmanan, Meiyappan; Klement, Maximilian; Ching, Chi Bun; Lee, Dong-Yup

2013-03-01

Pichia yeasts have been recognized as important microbial cell factories in the biotechnological industry. Notably, the Pichia pastoris and Pichia stipitis species have attracted much research interest due to their unique cellular physiology and metabolic capability: P. pastoris has the ability to utilize methanol for cell growth and recombinant protein production, while P. stipitis is capable of assimilating xylose to produce ethanol under oxygen-limited conditions. To harness these characteristics for biotechnological applications, it is highly required to characterize their metabolic behavior. Recently, following the genome sequencing of these two Pichia species, genome-scale metabolic networks have been reconstructed to model the yeasts' metabolism from a systems perspective. To date, there are three genome-scale models available for each of P. pastoris and P. stipitis. In this mini-review, we provide an overview of the models, discuss certain limitations of previous studies, and propose potential future works that can be conducted to better understand and engineer Pichia yeasts for industrial applications.
In-vitro biocompatibility and corrosion resistance of electrochemically assembled PPy/TNTA hybrid material for biomedical applications

NASA Astrophysics Data System (ADS)

Simi, V. S.; Satish, Aishwarya; Korrapati, Purna Sai; Rajendran, N.

2018-07-01

Nanostructured hybrid materials composed of inorganic and organic constituents of different chemistry and functionality have attracted wide range of biomedical applications. The uniform electrodeposition of polypyrrole into titania nanotube arrays was achieved by normal pulse voltammetry technique in lithium perchlorate electrolyte by varying the pulse period. The electrochemically assembled polypyrrole/titania nanotube arrays (PPy/TNTA) surface was characterized by structural characterizations including attenuated total reflectance -fourier transform infrared spectroscopy, Raman and X-ray photoelectron spectroscopy analysis. Morphological study carried out by high resolution scanning electron microscopy demonstrates the influence of varying pulse period in achieving the controlled deposition of polypyrrole into the nanotube frame work. Cyclic voltammetry study reveals the electroactive nature of the hybrid material. The contact angle measurements and In-vitro immersion studies in stimulated body fluid hanks' solution were carried out to evaluate the wettability and apatite forming ability of the developed hybrid material. The deposition of polypyrrole enhanced the corrosion resistance of TNTA as evidenced from the lower icorr value observed for PPy/TNTA. The corrosion protection behavior of the hybrid material revealed from the electrochemical impedance spectroscopic studies was clearly noticed from the increase in impedance and maximum phase angle values. Further In-vitro cell culture studies were carried out using MG63 osteoblast cells to evaluate the biocompatibility of the hybrid material. Noticeable improvement in corrosion protection and biocompatibility performance suggest the possible application of PPy/TNTA hybrid material for biomedical applications.
Potential mechanism of corpus-predominant gastritis after PPI therapy in Helicobacter pylori-positive patients with GERD.

PubMed

Mukaisho, Ken-ichi; Hagiwara, Tadashi; Nakayama, Takahisa; Hattori, Takanori; Sugihara, Hiroyuki

2014-09-14

The long-term use of proton pump inhibitors (PPIs) exacerbates corpus atrophic gastritis in patients with Helicobacter pylori (H. pylori) infection. To identify a potential mechanism for this change, we discuss interactions between pH, bile acids, and H. pylori. Duodenogastric reflux, which includes bile, occurs in healthy individuals, and bile reflux is increased in patients with gastroesophageal reflux disease (GERD). Diluted human plasma and bile acids have been found to be significant chemoattractants and chemorepellents, respectively, for the bacillus H. pylori. Although only taurine conjugates, with a pKa of 1.8-1.9, are soluble in an acidic environment, glycine conjugates, with a pKa of 4.3-5.2, as well as taurine-conjugated bile acids are soluble in the presence of PPI therapy. Thus, the soluble bile acid concentrations in the gastric contents of patients with GERD after continuous PPI therapy are considerably higher than that in those with intact acid production. In the distal stomach, the high concentration of soluble bile acids is likely to act as a bactericide or chemorepellent for H. pylori. In contrast, the mucous layer in the proximal stomach has an optimal bile concentration that forms chemotactic gradients with plasma components required to direct H. pylori to the epithelial surface. H. pylori may then colonize in the stomach body rather than in the pyloric antrum, which may explain the occurrence of corpus-predominant gastritis after PPI therapy in H. pylori-positive patients with GERD.
Drosophila Regulate Yeast Density and Increase Yeast Community Similarity in a Natural Substrate

PubMed Central

Stamps, Judy A.; Yang, Louie H.; Morales, Vanessa M.; Boundy-Mills, Kyria L.

2012-01-01

Drosophila melanogaster adults and larvae, but especially larvae, had profound effects on the densities and community structure of yeasts that developed in banana fruits. Pieces of fruit exposed to adult female flies previously fed fly-conditioned bananas developed higher yeast densities than pieces of the same fruits that were not exposed to flies, supporting previous suggestions that adult Drosophila vector yeasts to new substrates. However, larvae alone had dramatic effects on yeast density and species composition. When yeast densities were compared in pieces of the same fruits assigned to different treatments, fruits that developed low yeast densities in the absence of flies developed significantly higher yeast densities when exposed to larvae. Across all of the fruits, larvae regulated yeast densities within narrow limits, as compared to a much wider range of yeast densities that developed in pieces of the same fruits not exposed to flies. Larvae also affected yeast species composition, dramatically reducing species diversity across fruits, reducing variation in yeast communities from one fruit to the next (beta diversity), and encouraging the consistent development of a yeast community composed of three species of yeast (Candida californica, C. zemplinina, and Pichia kluvyeri), all of which were palatable to larvae. Larvae excreted viable cells of these three yeast species in their fecal pools, and discouraged the growth of filamentous fungi, processes which may have contributed to their effects on the yeast communities in banana fruits. These and other findings suggest that D. melanogaster adults and their larval offspring together engage in ‘niche construction’, facilitating a predictable microbial environment in the fruit substrates in which the larvae live and develop. PMID:22860093
Mild and Low-Pressure fac-Ir(ppy)3 -Mediated Radical Aminocarbonylation of Unactivated Alkyl Iodides through Visible-Light Photoredox Catalysis.

PubMed

Chow, Shiao Y; Stevens, Marc Y; Åkerbladh, Linda; Bergman, Sara; Odell, Luke R

2016-06-27

A novel, mild and facile preparation of alkyl amides from unactivated alkyl iodides employing a fac-Ir(ppy)3 -catalyzed radical aminocarbonylation protocol has been developed. Using a two-chambered system, alkyl iodides, fac-Ir(ppy)3 , amines, reductants, and CO gas (released ex situ from Mo(CO)6 ), were combined and subjected to an initial radical reductive dehalogenation generating alkyl radicals, and a subsequent aminocarbonylation with amines affording a wide range of alkyl amides in moderate to excellent yields. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Differences in toxicity of anionic and cationic PAMAM and PPI dendrimers in zebrafish embryos and cancer cell lines.

PubMed

Bodewein, Lambert; Schmelter, Frank; Di Fiore, Stefano; Hollert, Henner; Fischer, Rainer; Fenske, Martina

2016-08-15

Dendrimers are an emerging class of polymeric nanoparticles with beneficial biomedical applications like early diagnostics, in vitro gene transfection or controlled drug delivery. However, the potential toxic impact of exposure on human health or the environment is often inadequately defined. Thus, polyamidoamine (PAMAM) dendrimers of generations G3.0, 3.5, 4.0, 4.5 and 5.0 and polypropylenimine (PPI) dendrimers G3.0, 4.0 and 5.0 were tested in zebrafish embryos for 96h and human cancer cell lines for 24h, to assess and compare developmental in vivo toxicity with cytotoxicity. The zebrafish embryo toxicity of cationic PAMAM and PPI dendrimers increased over time, with EC50 values ranging from 0.16 to just below 1.7μM at 24 and 48hpf. The predominant effects were mortality, plus reduced heartbeat and blood circulation for PPI dendrimers. Apoptosis in the embryos increased in line with the general toxicity concentration-dependently. Hatch and dechorionation of the embryos increased the toxicity, suggesting a protective role of the chorion. Lower generation dendrimers were more toxic in the embryos whereas the toxicity in the HepG2 and DU145 cell lines increased with increasing generation of cationic PAMAMs and PPI dendrimers. HepG2 were less sensitive than DU145 cells, with IC50 values≥402μM (PAMAMs) and ≤240μM (PPIs) for HepG2 and ≤13.24μM (PAMAMs) and ≤12.84μM (PPIs) for DU145. Neither in fish embryos nor cells toxicity thresholds were determinable for anionic PAMAM G3.5 and G4.5. The study demonstrated that the cytotoxicity underestimated the in-vivo toxicity of the dendrimers in the fish embryos. Copyright © 2016 Elsevier Inc. All rights reserved.
Interplay of Zero-Field Splitting and Excited State Geometry Relaxation in fac-Ir(ppy)3.

PubMed

Gonzalez-Vazquez, José P; Burn, Paul L; Powell, Benjamin J

2015-11-02

The lowest energy triplet state, T1, of organometallic complexes based on iridium(III) is of fundamental interest, as the behavior of molecules in this state determines the suitability of the complex for use in many applications, e.g., organic light-emitting diodes. Previous characterization of T1 in fac-Ir(ppy)3 suggests that the trigonal symmetry of the complex is weakly broken in the excited state. Here we report relativistic time dependent density functional calculations of the zero-field splitting (ZFS) of fac-Ir(ppy)3 in the ground state (S0) and lowest energy triplet (T1) geometries and at intermediate geometries. We show that the energy scale of the geometry relaxation in the T1 state is large compared to the ZFS. Thus, the natural analysis of the ZFS and the radiative decay rates, based on the assumption that the structural distortion is a small perturbation, fails dramatically. In contrast, our calculations of these quantities are in good agreement with experiment.
Characterizing biomarkers in osteosarcoma metastasis based on an ego-network.

PubMed

Liu, Zhen; Song, Yan

2017-06-01

To characterize biomarkers that underlie osteosarcoma (OS) metastasis based on an ego-network. From the microarray data, we obtained 13,326 genes. By combining PPI data and microarray data, 10,520 shared genes were found and constructed into ego-networks. 17 significant ego-networks were identified with p < 0.05. In the pathway enrichment analysis, seven ego-networks were identified with the most significant pathway. These significant ego-modules were potential biomarkers that reveal the potential mechanisms in OS metastasis, which may contribute to understanding cancer prognoses and providing new perspectives in the treatment of cancer.
Visualization and quantification of three-dimensional distribution of yeast in bread dough.

PubMed

Maeda, Tatsuro; DO, Gab-Soo; Sugiyama, Junichi; Araki, Tetsuya; Tsuta, Mizuki; Shiraga, Seizaburo; Ueda, Mitsuyoshi; Yamada, Masaharu; Takeya, Koji; Sagara, Yasuyuki

2009-07-01

A three-dimensional (3-D) bio-imaging technique was developed for visualizing and quantifying the 3-D distribution of yeast in frozen bread dough samples in accordance with the progress of the mixing process of the samples, applying cell-surface engineering to the surfaces of the yeast cells. The fluorescent yeast was recognized as bright spots at the wavelength of 520 nm. Frozen dough samples were sliced at intervals of 1 microm by an micro-slicer image processing system (MSIPS) equipped with a fluorescence microscope for acquiring cross-sectional images of the samples. A set of successive two-dimensional images was reconstructed to analyze the 3-D distribution of the yeast. The average shortest distance between centroids of enhanced green fluorescent protein (EGFP) yeasts was 10.7 microm at the pick-up stage, 9.7 microm at the clean-up stage, 9.0 microm at the final stage, and 10.2 microm at the over-mixing stage. The results indicated that the distribution of the yeast cells was the most uniform in the dough of white bread at the final stage, while the heterogeneous distribution at the over-mixing stage was possibly due to the destruction of the gluten network structure within the samples.
Triangle network motifs predict complexes by complementing high-error interactomes with structural information

PubMed Central

Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-01-01

Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural
P³DB 3.0: From plant phosphorylation sites to protein networks.

PubMed

Yao, Qiuming; Ge, Huangyi; Wu, Shangquan; Zhang, Ning; Chen, Wei; Xu, Chunhui; Gao, Jianjiong; Thelen, Jay J; Xu, Dong

2014-01-01

In the past few years, the Plant Protein Phosphorylation Database (P(3)DB, http://p3db.org) has become one of the most significant in vivo data resources for studying plant phosphoproteomics. We have substantially updated P(3)DB with respect to format, new datasets and analytic tools. In the P(3)DB 3.0, there are altogether 47 923 phosphosites in 16 477 phosphoproteins curated across nine plant organisms from 32 studies, which have met our multiple quality standards for acquisition of in vivo phosphorylation site data. Centralized by these phosphorylation data, multiple related data and annotations are provided, including protein-protein interaction (PPI), gene ontology, protein tertiary structures, orthologous sequences, kinase/phosphatase classification and Kinase Client Assay (KiC Assay) data--all of which provides context for the phosphorylation event. In addition, P(3)DB 3.0 incorporates multiple network viewers for the above features, such as PPI network, kinase-substrate network, phosphatase-substrate network, and domain co-occurrence network to help study phosphorylation from a systems point of view. Furthermore, the new P(3)DB reflects a community-based design through which users can share datasets and automate data depository processes for publication purposes. Each of these new features supports the goal of making P(3)DB a comprehensive, systematic and interactive platform for phosphoproteomics research.
Prions in Yeast

PubMed Central

Liebman, Susan W.; Chernoff, Yury O.

2012-01-01

The concept of a prion as an infectious self-propagating protein isoform was initially proposed to explain certain mammalian diseases. It is now clear that yeast also has heritable elements transmitted via protein. Indeed, the “protein only” model of prion transmission was first proven using a yeast prion. Typically, known prions are ordered cross-β aggregates (amyloids). Recently, there has been an explosion in the number of recognized prions in yeast. Yeast continues to lead the way in understanding cellular control of prion propagation, prion structure, mechanisms of de novo prion formation, specificity of prion transmission, and the biological roles of prions. This review summarizes what has been learned from yeast prions. PMID:22879407
Yeast for virus research

PubMed Central

Zhao, Richard Yuqi

2017-01-01

Budding yeast (Saccharomyces cerevisiae) and fission yeast (Schizosaccharomyces pombe) are two popular model organisms for virus research. They are natural hosts for viruses as they carry their own indigenous viruses. Both yeasts have been used for studies of plant, animal and human viruses. Many positive sense (+) RNA viruses and some DNA viruses replicate with various levels in yeasts, thus allowing study of those viral activities during viral life cycle. Yeasts are single cell eukaryotic organisms. Hence, many of the fundamental cellular functions such as cell cycle regulation or programed cell death are highly conserved from yeasts to higher eukaryotes. Therefore, they are particularly suited to study the impact of those viral activities on related cellular activities during virus-host interactions. Yeasts present many unique advantages in virus research over high eukaryotes. Yeast cells are easy to maintain in the laboratory with relative short doubling time. They are non-biohazardous, genetically amendable with small genomes that permit genome-wide analysis of virologic and cellular functions. In this review, similarities and differences of these two yeasts are described. Studies of virologic activities such as viral translation, viral replication and genome-wide study of virus-cell interactions in yeasts are highlighted. Impacts of viral proteins on basic cellular functions such as cell cycle regulation and programed cell death are discussed. Potential applications of using yeasts as hosts to carry out functional analysis of small viral genome and to develop high throughput drug screening platform for the discovery of antiviral drugs are presented. PMID:29082230
A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks.

PubMed

Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-03-01

This study applied a knowledge-driven data integration framework for the inference of protein-protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the True positive/false positive rate and true positive/positive rate. By incorporating domain knowledge into the construction of the KD-BN, we demonstrate improvement in predictive performance compared with previous studies based upon the Naive Bayesian approach. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Comparative study on the freeze stability of yeast and chemical leavened steamed bread dough.

PubMed

Wang, Pei; Yang, Runqiang; Gu, Zhenxin; Xu, Xueming; Jin, Zhengyu

2017-04-15

The present study comparatively evaluated the evolution of yeast and chemical leavened steamed bread dough (YLD/CLD) quality during freeze/thaw (FT) cycles. The steamed bread quality of CLD was more freeze-stable than that of the YLD after 3 FT cycles. Decreased yeast viability contributed to the loss of gassing power in YLD while no significant differences were observed for CLD during FT cycles. However, faster gas release rate in frozen CLD indicated gas retention loss due to the distortion of gluten network. Glutenin macropolymers (GMP) depolymerization via breakage of inter-chain disulfide (SS) bonds and conversions of α-helix and β-turn to β-sheet structures were the main indicators of gluten deterioration. Gluten network was more vulnerable in frozen YLD, resulting in detectable loss of viscoelasticity. The results suggested that supplement of chemical leavener contributed to a more freeze-tolerant gluten network besides its stable gassing power. Copyright © 2016 Elsevier Ltd. All rights reserved.
L-arabinose fermenting yeast

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

Zhang, Min; Singh, Arjun; Suominen, Pirkko

An L-arabinose utilizing yeast strain is provided for the production of ethanol by introducing and expressing bacterial araA, araB and araD genes. L-arabinose transporters are also introduced into the yeast to enhance the uptake of arabinose. The yeast carries additional genomic mutations enabling it to consume L-arabinose, even as the only carbon source, and to produce ethanol. A yeast strain engineered to metabolize arabinose through a novel pathway is also disclosed. Methods of producing ethanol include utilizing these modified yeast strains.
L-arabinose fermenting yeast

DOEpatents

Zhang, Min; Singh, Arjun; Suominen, Pirkko; Knoshaug, Eric; Franden, Mary Ann; Jarvis, Eric

2014-09-23

An L-arabinose utilizing yeast strain is provided for the production of ethanol by introducing and expressing bacterial araA, araB and araD genes. L-arabinose transporters are also introduced into the yeast to enhance the uptake of arabinose. The yeast carries additional genomic mutations enabling it to consume L-arabinose, even as the only carbon source, and to produce ethanol. A yeast strain engineered to metabolize arabinose through a novel pathway is also disclosed. Methods of producing ethanol include utilizing these modified yeast strains.
Functional and molecular characterization of a glycosomal PPi-dependent enzyme in trypanosomatids: Pyruvate, phosphate dikinase

PubMed Central

Bringaud, Frederic; Baltz, Dominique; Baltz, Theo

1998-01-01

Trypanosomatids are parasitic protists that have an ATP-dependent glycolysis with no indication of PPi-dependent metabolism. Most of the glycolysis takes place in peroxisome-like organelles, the glycosomes. We characterized in Trypanosoma brucei a single-copy gene encoding a PPi-dependent enzyme, pyruvate, phosphate dikinase (PPDK), which was expressed functionally in Escherichia coli. Specific antibodies detected a 100-kDa protein in procyclic forms but not in mammalian forms of T. brucei, indicating a differential expression. Glycosomal localization of PPDK was determined by immunofluorescence analysis and was confirmed by Western blot analysis on glycosomal fractions by using anti-PPDK antibodies. Expression and localization of recombinant PPDKs in procyclic forms of T. brucei showed that the AKL motif at the C-terminal extremity of PPDK is necessary for glycosomal targeting. PPDK was detected in every trypanosomatid tested—Trypanosoma congolense, Trypanosoma vivax, Trypanosoma cruzi, Phytomonas, Crithidia and Leishmania—with a good correlation between amount of protein and enzymatic activity. The precise role of PPDK in trypanosomatid carbohydrate metabolism remains to be clarified. PMID:9653123
Prevention of Yeast Spoilage in Feed and Food by the Yeast Mycocin HMK

PubMed Central

Lowes, K. F.; Shearman, C. A.; Payne, J.; MacKenzie, D.; Archer, D. B.; Merry, R. J.; Gasson, M. J.

2000-01-01

The yeast Williopsis mrakii produces a mycocin or yeast killer toxin designated HMK; this toxin exhibits high thermal stability, high pH stability, and a broad spectrum of activity against other yeasts. We describe construction of a synthetic gene for mycocin HMK and heterologous expression of this toxin in Aspergillus niger. Mycocin HMK was fused to a glucoamylase protein carrier, which resulted in secretion of biologically active mycocin into the culture media. A partial purification protocol was developed, and a comparison with native W. mrakii mycocin showed that the heterologously expressed mycocin had similar physiological properties and an almost identical spectrum of biological activity against a number of yeasts isolated from silage and yoghurt. Two food and feed production systems prone to yeast spoilage were used as models to assess the ability of mycocin HMK to act as a biocontrol agent. The onset of aerobic spoilage in mature maize silage was delayed by application of A. niger mycocin HMK on opening because the toxin inhibited growth of the indigenous spoilage yeasts. This helped maintain both higher lactic acid levels and a lower pH. In yoghurt spiked with dairy spoilage yeasts, A. niger mycocin HMK was active at all of the storage temperatures tested at which yeast growth occurred, and there was no resurgence of resistant yeasts. The higher the yeast growth rate, the more effective the killing action of the mycocin. Thus, mycocin HMK has potential applications in controlling both silage spoilage and yoghurt spoilage caused by yeasts. PMID:10698773
Striking differences in properties of geometric isomers of [Ir(tpy)(ppy)H](+): Experimental and computational studies on their hydricities, interaction with CO 2, and photochemistry

DOE PAGES

Garg, Komal; Fujita, Etsuko; Matsubara, Yasuo; ...

2015-11-16

Here, we prepared two geometric isomers of [Ir(tpy)(ppy)H] +, previously proposed as a key intermediate in the photochemical reduction of CO 2 to CO, and characterized their notably different ground- and excited-state interactions with CO 2 and their hydricities using experimental and computational methods. Only one isomer, C-trans-[Ir(tpy)(ppy)H] +, reacts with CO 2 to generate the formato complex in the ground state, consistent with its calculated hydricity. Under photocatalytic conditions in CH 3CN/TEOA, a common reactive C-trans-[Ir(tpy)(ppy)] 0 species, irrespective of the starting isomer or monodentate ligand (such as hydride or Cl), reacts with CO 2 and produces CO withmore » the same catalytic efficiency.« less
s-core network decomposition: A generalization of k-core analysis to weighted networks

NASA Astrophysics Data System (ADS)

Eidsaa, Marius; Almaas, Eivind

2013-12-01

A broad range of systems spanning biology, technology, and social phenomena may be represented and analyzed as complex networks. Recent studies of such networks using k-core decomposition have uncovered groups of nodes that play important roles. Here, we present s-core analysis, a generalization of k-core (or k-shell) analysis to complex networks where the links have different strengths or weights. We demonstrate the s-core decomposition approach on two random networks (ER and configuration model with scale-free degree distribution) where the link weights are (i) random, (ii) correlated, and (iii) anticorrelated with the node degrees. Finally, we apply the s-core decomposition approach to the protein-interaction network of the yeast Saccharomyces cerevisiae in the context of two gene-expression experiments: oxidative stress in response to cumene hydroperoxide (CHP), and fermentation stress response (FSR). We find that the innermost s-cores are (i) different from innermost k-cores, (ii) different for the two stress conditions CHP and FSR, and (iii) enriched with proteins whose biological functions give insight into how yeast manages these specific stresses.
Investigation of a protein complex network

NASA Astrophysics Data System (ADS)

Mashaghi, A. R.; Ramezanpour, A.; Karimipour, V.

2004-09-01

The budding yeast Saccharomyces cerevisiae is the first eukaryote whose genome has been completely sequenced. It is also the first eukaryotic cell whose proteome (the set of all proteins) and interactome (the network of all mutual interactions between proteins) has been analyzed. In this paper we study the structure of the yeast protein complex network in which weighted edges between complexes represent the number of shared proteins. It is found that the network of protein complexes is a small world network with scale free behavior for many of its distributions. However we find that there are no strong correlations between the weights and degrees of neighboring complexes. To reveal non-random features of the network we also compare it with a null model in which the complexes randomly select their proteins. Finally we propose a simple evolutionary model based on duplication and divergence of proteins.
Contractor Past Performance Information (PPI) in Source Selection: A Comparison Study of Public and Private Sector

DTIC Science & Technology

2005-05-01

efficiencies similar to those in the private sector . However, along the way, Government and private sector industry have begun to disagree about how PPI is...double that of the private sector due to an evaluation process that is cumbersome, time-consuming, and lacking the efficiencies enjoyed by private
Enhanced leavening ability of baker's yeast by overexpression of SNR84 with PGM2 deletion.

PubMed

Lin, Xue; Zhang, Cui-Ying; Bai, Xiao-Wen; Xiao, Dong-Guang

2015-06-01

Dough-leavening ability is one of the main aspects considered when selecting a baker's yeast strain for baking industry. Generally, modification of maltose metabolic pathway and known regulatory networks of maltose metabolism were used to increase maltose metabolism to improve leavening ability in lean dough. In this study, we focus on the effects of PGM2 (encoding for the phosphoglucomutase) and SNR84 (encoding for the H/ACA snoRNA) that are not directly related to both the maltose metabolic pathway and known regulatory networks of maltose metabolism on the leavening ability of baker's yeast in lean dough. The results show that the modifications on PGM2 and/or SNR84 are effective ways in improving leavening ability of baker's yeast in lean dough. Deletion of PGM2 decreased cellular glucose-1-phosphate and overexpression of SNR84 increased the maltose permease activity. These changes resulted in 11, 19 and 21% increases of the leavening ability for PGM2 deletion, SNR84 overexpression and SNR84 overexpression combining deleted PGM2, respectively.
Actions of novel antipsychotic agents on apomorphine-induced PPI disruption: influence of combined serotonin 5-HT1A receptor activation and dopamine D2 receptor blockade.

PubMed

Auclair, Agnès L; Kleven, Mark S; Besnard, Joël; Depoortère, Ronan; Newman-Tancredi, Adrian

2006-09-01

The dopamine D1/D2 agonist apomorphine (0.63 mg/kg) disrupted prepulse inhibition (PPI) of acoustic startle in rats, a model of sensorimotor gating deficits observed in schizophrenia. All current antipsychotics, which antagonize D2 receptors, prevent this apomorphine-induced deficit. A novel class of antipsychotics possesses, in addition to D2 antagonist property, various levels of 5-HT1A agonist activity. Considering that the latter itself produces PPI deficits, it appeared necessary to assess the potential of this novel class of antipsychotics to reverse apomorphine-PPI deficits. Potent D2 antagonists, like haloperidol (0.63-2.5 mg/kg), risperidone (0.63-10 mg/kg), and olanzapine (0.63-40 mg/kg) prevented apomorphine PPI disruption. The atypical antipsychotics, clozapine (40 mg/kg), nemonapride (0.01-2.5 mg/kg), ziprasidone (10 mg/kg), and aripiprazole (0.01 and 10 mg/kg), which all exhibit 5-HT1A agonist properties, reversed PPI deficits at some doses only, whereas the anti-dyskinetic agent sarizotan (0.16-10 mg/kg), an efficacious 5-HT1A agonist, did not. New generation antipsychotics with marked 5-HT1A agonist properties, such as SLV313 and SSR181507 (0.0025-10 mg/kg and 0.16-10 mg/kg, respectively) did not reverse these deficits whereas bifeprunox (0.04-2.5 mg/kg) did. To reveal the contribution of 5-HT1A agonist properties in the lack of effects of SLV313 and SSR181507, we pretreated rats with the 5-HT1A antagonist WAY100635 (0.63 mg/kg). Under these conditions, significant reversal of PPI deficit was observed, indicating that D2 antagonist properties of SLV313 and SSR181507 are now sufficient to overcome the disruptive effects of apomorphine. To summarize, antipsychotics possessing agonist efficacy at 5-HT1A receptors exhibit diverse profiles against apomorphine-induced PPI deficits, depending on the balance between D2 and 5-HT1A activities, suggesting that they may display distinct activity on some aspects of gating deficits in schizophrenic patients.
Identification of the Transcription Factor Znc1p, which Regulates the Yeast-to-Hypha Transition in the Dimorphic Yeast Yarrowia lipolytica

PubMed Central

Martinez-Vazquez, Azul; Gonzalez-Hernandez, Angelica; Domínguez, Ángel; Rachubinski, Richard; Riquelme, Meritxell; Cuellar-Mata, Patricia; Guzman, Juan Carlos Torres

2013-01-01

The dimorphic yeast Yarrowia lipolytica is used as a model to study fungal differentiation because it grows as yeast-like cells or forms hyphal cells in response to changes in environmental conditions. Here, we report the isolation and characterization of a gene, ZNC1, involved in the dimorphic transition in Y. lipolytica. The ZNC1 gene encodes a 782 amino acid protein that contains a Zn(II)2C6 fungal-type zinc finger DNA-binding domain and a leucine zipper domain. ZNC1 transcription is elevated during yeast growth and decreases during the formation of mycelium. Cells in which ZNC1 has been deleted show increased hyphal cell formation. Znc1p-GFP localizes to the nucleus, but mutations within the leucine zipper domain of Znc1p, and to a lesser extent within the Zn(II)2C6 domain, result in a mislocalization of Znc1p to the cytoplasm. Microarrays comparing gene expression between znc1::URA3 and wild-type cells during both exponential growth and the induction of the yeast-to-hypha transition revealed 1,214 genes whose expression was changed by 2-fold or more under at least one of the conditions analyzed. Our results suggest that Znc1p acts as a transcription factor repressing hyphal cell formation and functions as part of a complex network regulating mycelial growth in Y. lipolytica. PMID:23826133
Effect of wine yeast monoculture practice on the biodiversity of non-Saccharomyces yeasts.

PubMed

Ganga, M A; Martínez, C

2004-01-01

The objective of this work was to study the effect of the use of Saccharomyces cerevisiae monocultures over the biodiversity of non-Saccharomyces yeasts in wine-producing areas in Chile. Microvinifications were carried out with grape musts of two areas. In one of them, the fermentation is carried out mainly in a spontaneous manner, whereas in the other the musts are inoculated with commercial yeasts. The isolated yeasts were identified by the internal transcribed (ITS)/restriction fragment length polymorphism technique. In the industrial production area less variability of yeast genera was observed as compared with the traditional area, an observation that is greatest at the end of the fermentation. Furthermore, a study of the production of extracellular enzymes was done. The majority of the yeasts showed at least one of the activities assayed with the exception of beta-glycosidase. The results suggest that in the industrialized area the diversity of yeasts is less in the traditional area. Likewise, the potentiality of the non-Saccharomyces yeasts as enzyme producers with industrial interest has been confirmed. This study shows the negative effect of the use of monocultures over the biodiversity of yeasts in wine-producing regions.
Exploring the Yeast Acetylome Using Functional Genomics

PubMed Central

Duffy, Supipi Kaluarachchi; Friesen, Helena; Baryshnikova, Anastasia; Lambert, Jean-Philippe; Chong, Yolanda T.; Figeys, Daniel; Andrews, Brenda

2014-01-01

SUMMARY Lysine acetylation is a dynamic posttranslational modification with a well-defined role in regulating histones. The impact of acetylation on other cellular functions remains relatively uncharacterized. We explored the budding yeast acetylome with a functional genomics approach, assessing the effects of gene overexpression in the absence of lysine deacetylases (KDACs). We generated a network of 463 synthetic dosage lethal (SDL) interactions involving class I and II KDACs, revealing many cellular pathways regulated by different KDACs. A biochemical survey of genes interacting with the KDAC RPD3 identified 72 proteins acetylated in vivo. In-depth analysis of one of these proteins, Swi4, revealed a role for acetylation in G1-specific gene expression. Acetylation of Swi4 regulates interaction with its partner Swi6, both components of the SBF transcription factor. This study expands our view of the yeast acetylome, demonstrates the utility of functional genomic screens for exploring enzymatic pathways, and provides functional information that can be mined for future studies. PMID:22579291
Yeast cell differentiation: Lessons from pathogenic and non-pathogenic yeasts.

PubMed

Palková, Zdena; Váchová, Libuše

2016-09-01

Yeasts, historically considered to be single-cell organisms, are able to activate different differentiation processes. Individual yeast cells can change their life-styles by processes of phenotypic switching such as the switch from yeast-shaped cells to filamentous cells (pseudohyphae or true hyphae) and the transition among opaque, white and gray cell-types. Yeasts can also create organized multicellular structures such as colonies and biofilms, and the latter are often observed as contaminants on surfaces in industry and medical care and are formed during infections of the human body. Multicellular structures are formed mostly of stationary-phase or slow-growing cells that diversify into specific cell subpopulations that have unique metabolic properties and can fulfill specific tasks. In addition to the development of multiple protective mechanisms, processes of metabolic reprogramming that reflect a changed environment help differentiated individual cells and/or community cell constituents to survive harmful environmental attacks and/or to escape the host immune system. This review aims to provide an overview of differentiation processes so far identified in individual yeast cells as well as in multicellular communities of yeast pathogens of the Candida and Cryptococcus spp. and the Candida albicans close relative, Saccharomyces cerevisiae. Molecular mechanisms and extracellular signals potentially involved in differentiation processes are also briefly mentioned. Copyright © 2016 Elsevier Ltd. All rights reserved.
L-arabinose fermenting yeast

DOEpatents

Zhang, Min; Singh, Arjun; Knoshaug, Eric; Franden, Mary Ann; Jarvis, Eric; Suominen, Pirkko

2010-12-07

An L-arabinose utilizing yeast strain is provided for the production of ethanol by introducing and expressing bacterial araA, araB and araD genes. L-arabinose transporters are also introduced into the yeast to enhance the uptake of arabinose. The yeast carries additional genomic mutations enabling it to consume L-arabinose, even as the only carbon source, and to produce ethanol. Methods of producing ethanol include utilizing these modified yeast strains. ##STR00001##
Nitrile Metabolizing Yeasts

NASA Astrophysics Data System (ADS)

Bhalla, Tek Chand; Sharma, Monica; Sharma, Nitya Nand

Nitriles and amides are widely distributed in the biotic and abiotic components of our ecosystem. Nitrile form an important group of organic compounds which find their applications in the synthesis of a large number of compounds used as/in pharmaceutical, cosmetics, plastics, dyes, etc>. Nitriles are mainly hydro-lyzed to corresponding amide/acid in organic chemistry. Industrial and agricultural activities have also lead to release of nitriles and amides into the environment and some of them pose threat to human health. Biocatalysis and biotransformations are increasingly replacing chemical routes of synthesis in organic chemistry as a part of ‘green chemistry’. Nitrile metabolizing organisms or enzymes thus has assumed greater significance in all these years to convert nitriles to amides/ acids. The nitrile metabolizing enzymes are widely present in bacteria, fungi and yeasts. Yeasts metabolize nitriles through nitrilase and/or nitrile hydratase and amidase enzymes. Only few yeasts have been reported to possess aldoxime dehydratase. More than sixty nitrile metabolizing yeast strains have been hither to isolated from cyanide treatment bioreactor, fermented foods and soil. Most of the yeasts contain nitrile hydratase-amidase system for metabolizing nitriles. Transformations of nitriles to amides/acids have been carried out with free and immobilized yeast cells. The nitrilases of Torulopsis candida>and Exophiala oligosperma>R1 are enantioselec-tive and regiospecific respectively. Geotrichum>sp. JR1 grows in the presence of 2M acetonitrile and may have potential for application in bioremediation of nitrile contaminated soil/water. The nitrilase of E. oligosperma>R1 being active at low pH (3-6) has shown promise for the hydroxy acids. Immobilized yeast cells hydrolyze some additional nitriles in comparison to free cells. It is expected that more focus in future will be on purification, characterization, cloning, expression and immobilization of nitrile metabolizing
The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean.

PubMed

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla ) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein-protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.
Flexible modulation of network connectivity related to cognition in Alzheimer's disease.

PubMed

McLaren, Donald G; Sperling, Reisa A; Atri, Alireza

2014-10-15

Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer's disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54-82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and encoding repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the
Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

NASA Astrophysics Data System (ADS)

Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

2015-03-01

The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

Genome dynamics and evolution in yeasts: A long-term yeast-bacteria competition experiment

PubMed Central

Katz, Michael; Knecht, Wolfgang; Compagno, Concetta; Piškur, Jure

2018-01-01

There is an enormous genetic diversity evident in modern yeasts, but our understanding of the ecological basis of such diversifications in nature remains at best fragmented so far. Here we report a long-term experiment mimicking a primordial competitive environment, in which yeast and bacteria co-exist and compete against each other. Eighteen yeasts covering a wide phylogenetic background spanning approximately 250 million years of evolutionary history were used to establish independent evolution lines for at most 130 passages. Our collection of hundreds of modified strains generated through such a rare two-species cross-kingdom competition experiment re-created the appearance of large-scale genomic rearrangements and altered phenotypes important in the diversification history of yeasts. At the same time, the methodology employed in this evolutionary study would also be a non-gene-technological method of reprogramming yeast genomes and then selecting yeast strains with desired traits. Cross-kingdom competition may therefore be a method of significant value to generate industrially useful yeast strains with new metabolic traits. PMID:29624585
Effect of Yeast Cell Morphology, Cell Wall Physical Structure and Chemical Composition on Patulin Adsorption.

PubMed

Luo, Ying; Wang, Jianguo; Liu, Bin; Wang, Zhouli; Yuan, Yahong; Yue, Tianli

2015-01-01

The capability of yeast to adsorb patulin in fruit juice can aid in substantially reducing the patulin toxic effect on human health. This study aimed to investigate the capability of yeast cell morphology and cell wall internal structure and composition to adsorb patulin. To compare different yeast cell morphologies, cell wall internal structure and composition, scanning electron microscope, transmission electron microscope and ion chromatography were used. The results indicated that patulin adsorption capability of yeast was influenced by cell surface areas, volume, and cell wall thickness, as well as 1,3-β-glucan content. Among these factors, cell wall thickness and 1,3-β-glucan content serve significant functions. The investigation revealed that patulin adsorption capability was mainly affected by the three-dimensional network structure of the cell wall composed of 1,3-β-glucan. Finally, patulin adsorption in commercial kiwi fruit juice was investigated, and the results indicated that yeast cells could adsorb patulin from commercial kiwi fruit juice efficiently. This study can potentially simulate in vitro cell walls to enhance patulin adsorption capability and successfully apply to fruit juice industry.
Time-gated detection of protein-protein interactions with transcriptional readout

PubMed Central

Sanchez, Mateo I; Coukos, Robert; von Zastrow, Mark

2017-01-01

Transcriptional assays, such as yeast two-hybrid and TANGO, that convert transient protein-protein interactions (PPIs) into stable expression of transgenes are powerful tools for PPI discovery, screens, and analysis of cell populations. However, such assays often have high background and lose information about PPI dynamics. We have developed SPARK (Specific Protein Association tool giving transcriptional Readout with rapid Kinetics), in which proteolytic release of a membrane-tethered transcription factor (TF) requires both a PPI to deliver a protease proximal to its cleavage peptide and blue light to uncage the cleavage site. SPARK was used to detect 12 different PPIs in mammalian cells, with 5 min temporal resolution and signal ratios up to 37. By shifting the light window, we could reconstruct PPI time-courses. Combined with FACS, SPARK enabled 51 fold enrichment of PPI-positive over PPI-negative cells. Due to its high specificity and sensitivity, SPARK has the potential to advance PPI analysis and discovery. PMID:29189201
Synthesis and PPy loading for enhanced visible-light photocatalytic activity of new POMOFs containing silver chains

NASA Astrophysics Data System (ADS)

Sha, Jing-Quan; Yang, Xi-Ya; Sheng, Ning; Liu, Guo-Dong; Li, Ji-Sen; Yang, Jian-Bo

2018-07-01

A new polyoxometalate based hybrid compound containing Ag-Ag chain, [Ag29(trz)18][SiWV7WVI5O40] (Ag29SiW12), was synthesized by the simple one-step hydrothermal reaction of silver nitrate, 1, 2, 3- triazole (trz), and [SiW12O40]4- polyanion. Single crystal X-ray diffraction analysis shows that the [SiW12O40]4- polyanions as coordinating guests were successfully encapsulated into the metal-organic framework host matrix. The Keggin [SiW12O40]n- polyanions as templates and trz molecules as the small and delicate ligands play the decisive factors to the formation of silver chain. In addition, to improve the photocatalytic activity of the new compound Ag29SiW12, its polypyrrole (PPy) composite (PPy@Ag29SiW12) has been prepared and exhibits excellent photocatalytic activity (93.1% for MB and 48.8% for RhB) and selectivity adsorption (16.2 mg/g for MB and 1.60 mg/g for RhB) for organic dyes under the visible light radiation.
New yeasts-new brews: modern approaches to brewing yeast design and development.

PubMed

Gibson, B; Geertman, J-M A; Hittinger, C T; Krogerus, K; Libkind, D; Louis, E J; Magalhães, F; Sampaio, J P

2017-06-01

The brewing industry is experiencing a period of change and experimentation largely driven by customer demand for product diversity. This has coincided with a greater appreciation of the role of yeast in determining the character of beer and the widespread availability of powerful tools for yeast research. Genome analysis in particular has helped clarify the processes leading to domestication of brewing yeast and has identified domestication signatures that may be exploited for further yeast development. The functional properties of non-conventional yeast (both Saccharomyces and non-Saccharomyces) are being assessed with a view to creating beers with new flavours as well as producing flavoursome non-alcoholic beers. The discovery of the psychrotolerant S. eubayanus has stimulated research on de novo S. cerevisiae × S. eubayanus hybrids for low-temperature lager brewing and has led to renewed interest in the functional importance of hybrid organisms and the mechanisms that determine hybrid genome function and stability. The greater diversity of yeast that can be applied in brewing, along with an improved understanding of yeasts' evolutionary history and biology, is expected to have a significant and direct impact on the brewing industry, with potential for improved brewing efficiency, product diversity and, above all, customer satisfaction. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Putative antipsychotics with pronounced agonism at serotonin 5-HT1A and partial agonist activity at dopamine D2 receptors disrupt basal PPI of the startle reflex in rats.

PubMed

Auclair, Agnès L; Galinier, Alexandra; Besnard, Joël; Newman-Tancredi, Adrian; Depoortère, Ronan

2007-07-01

Prepulse inhibition (PPI) of the startle reflex has been extensively studied because it is disrupted in several psychiatric diseases, most notably schizophrenia. In rats, and to a lesser extent, in humans, PPI can be diminished by dopamine (DA) D(2)/D(3) and serotonin 5-HT(1A) receptor agonists. A novel class of potential antipsychotics (SSR181507, bifeprunox, and SLV313) possess partial agonist/antagonist properties at D(2) receptors and various levels of 5-HT(1A) activation. It thus appeared warranted to assess, in Sprague-Dawley rats, the effects of these antipsychotics on basal PPI. SSR181507, sarizotan, and bifeprunox decreased PPI, with a near-complete abolition at 2.5-10 mg/kg; SLV313 had a significant effect at 0.16 mg/kg only. Co-treatment with the 5-HT(1A) receptor antagonist WAY100,635 (0.63 mg/kg) showed that the 5-HT(1A) agonist activity of SSR181507 was responsible for its effect. By contrast, antipsychotics with low affinity and/or efficacy at 5-HT(1A) receptors, such as aripiprazole (another DA D(2)/D(3) and 5-HT(1A) ligand), and established typical and atypical antipsychotics (haloperidol, clozapine, risperidone, olanzapine, quetiapine, and ziprasidone) had no effect on basal PPI (0.01-2.5 to 2.5-40 mg/kg). The present data demonstrate that some putative antipsychotics with pronounced 5-HT(1A) agonist activity, coupled with partial agonist activity at DA D(2) receptors, markedly diminish PPI of the startle reflex in rats. These data raise the issue of the influence of such compounds on sensorimotor gating in humans.
Vaginal yeast infection

MedlinePlus

Yeast infection - vagina; Vaginal candidiasis; Monilial vaginitis ... Most women have a vaginal yeast infection at some time. Candida albicans is a common type of fungus. It is often found in small amounts in the ...
Schizosaccharomyces japonicus: the fission yeast is a fusion of yeast and hyphae.

PubMed

Niki, Hironori

2014-03-01

The clade of Schizosaccharomyces includes 4 species: S. pombe, S. octosporus, S. cryophilus, and S. japonicus. Although all 4 species exhibit unicellular growth with a binary fission mode of cell division, S. japonicus alone is dimorphic yeast, which can transit from unicellular yeast to long filamentous hyphae. Recently it was found that the hyphal cells response to light and then synchronously activate cytokinesis of hyphae. In addition to hyphal growth, S. japonicas has many properties that aren't shared with other fission yeast. Mitosis of S. japonicas is referred to as semi-open mitosis because dynamics of nuclear membrane is an intermediate mode between open mitosis and closed mitosis. Novel genetic tools and the whole genomic sequencing of S. japonicas now provide us with an opportunity for revealing unique characters of the dimorphic yeast. © 2013 The Author. Yeast Published by John Wiley & Sons Ltd.
Protein-protein interaction network of gene expression in the hydrocortisone-treated keloid.

PubMed

Chen, Rui; Zhang, Zhiliang; Xue, Zhujia; Wang, Lin; Fu, Mingang; Lu, Yi; Bai, Ling; Zhang, Ping; Fan, Zhihong

2015-01-01

In order to explore the molecular mechanism of hydrocortisone in keloid tissue, the gene expression profiles of keloid samples treated with hydrocortisone were subjected to bioinformatics analysis. Firstly, the gene expression profiles (GSE7890) of five samples of keloid treated with hydrocortisone and five untreated keloid samples were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, data were preprocessed using packages in R language and differentially expressed genes (DEGs) were screened using a significance analysis of microarrays (SAM) protocol. Thirdly, the DEGs were subjected to gene ontology (GO) function and KEGG pathway enrichment analysis. Finally, the interactions of DEGs in samples of keloid treated with hydrocortisone were explored in a human protein-protein interaction (PPI) network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software. Based on the analysis, 572 DEGs in the hydrocortisone-treated samples were screened; most of these were involved in the signal transduction and cell cycle. Furthermore, three critical genes in the module, including COL1A1, NID1, and PRELP, were screened in the PPI network analysis. These findings enhance understanding of the pathogenesis of the keloid and provide references for keloid therapy. © 2015 The International Society of Dermatology.
SEQUOIA: significance enhanced network querying through context-sensitive random walk and minimization of network conductance.

PubMed

Jeong, Hyundoo; Yoon, Byung-Jun

2017-03-14

Network querying algorithms provide computational means to identify conserved network modules in large-scale biological networks that are similar to known functional modules, such as pathways or molecular complexes. Two main challenges for network querying algorithms are the high computational complexity of detecting potential isomorphism between the query and the target graphs and ensuring the biological significance of the query results. In this paper, we propose SEQUOIA, a novel network querying algorithm that effectively addresses these issues by utilizing a context-sensitive random walk (CSRW) model for network comparison and minimizing the network conductance of potential matches in the target network. The CSRW model, inspired by the pair hidden Markov model (pair-HMM) that has been widely used for sequence comparison and alignment, can accurately assess the node-to-node correspondence between different graphs by accounting for node insertions and deletions. The proposed algorithm identifies high-scoring network regions based on the CSRW scores, which are subsequently extended by maximally reducing the network conductance of the identified subnetworks. Performance assessment based on real PPI networks and known molecular complexes show that SEQUOIA outperforms existing methods and clearly enhances the biological significance of the query results. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/SEQUOIA .
Marine yeast isolation and industrial application.

PubMed

Zaky, Abdelrahman Saleh; Tucker, Gregory A; Daw, Zakaria Yehia; Du, Chenyu

2014-09-01

Over the last century, terrestrial yeasts have been widely used in various industries, such as baking, brewing, wine, bioethanol and pharmaceutical protein production. However, only little attention has been given to marine yeasts. Recent research showed that marine yeasts have several unique and promising features over the terrestrial yeasts, for example higher osmosis tolerance, higher special chemical productivity and production of industrial enzymes. These indicate that marine yeasts have great potential to be applied in various industries. This review gathers the most recent techniques used for marine yeast isolation as well as the latest applications of marine yeast in bioethanol, pharmaceutical and enzyme production fields. © 2014 The Authors FEMS Yeast Research published by John Wiley & Sons Ltd on behalf of Federation of European Microbiological Societies.
[Gastro-Oesophageal Reflux Disease - How to Manage if PPI are not Sufficiently Effective, not Tolerated, or not Wished?

PubMed

Labenz, Joachim; Koop, Herbert

2018-03-01

Die Standardtherapie der GERD mit PPI ist weniger wirksam als gedacht: Mindestens 30 % der Patienten haben persistierende Symptome und Läsionen (Therapielücke). Bei persistierender Symptomatik oder Wunsch einer alternativen Behandlung ist eine stratifizierte Diagnostik erforderlich. Alginate und neue Operationsverfahren erweitern die Therapieoptionen.
Synthetic genome engineering forging new frontiers for wine yeast.

PubMed

Pretorius, Isak S

2017-02-01

Over the past 15 years, the seismic shifts caused by the convergence of biomolecular, chemical, physical, mathematical, and computational sciences alongside cutting-edge developments in information technology and engineering have erupted into a new field of scientific endeavor dubbed Synthetic Biology. Recent rapid advances in high-throughput DNA sequencing and DNA synthesis techniques are enabling the design and construction of new biological parts (genes), devices (gene networks) and modules (biosynthetic pathways), and the redesign of biological systems (cells and organisms) for useful purposes. In 2014, the budding yeast Saccharomyces cerevisiae became the first eukaryotic cell to be equipped with a fully functional synthetic chromosome. This was achieved following the synthesis of the first viral (poliovirus in 2002 and bacteriophage Phi-X174 in 2003) and bacterial (Mycoplasma genitalium in 2008 and Mycoplasma mycoides in 2010) genomes, and less than two decades after revealing the full genome sequence of a laboratory (S288c in 1996) and wine (AWRI1631 in 2008) yeast strain. A large international project - the Synthetic Yeast Genome (Sc2.0) Project - is now underway to synthesize all 16 chromosomes (∼12 Mb carrying ∼6000 genes) of the sequenced S288c laboratory strain by 2018. If successful, S. cerevisiae will become the first eukaryote to cross the horizon of in silico design of complex cells through de novo synthesis, reshuffling, and editing of genomes. In the meantime, yeasts are being used as cell factories for the semi-synthetic production of high-value compounds, such as the potent antimalarial artemisinin, and food ingredients, such as resveratrol, vanillin, stevia, nootkatone, and saffron. As a continuum of previously genetically engineered industrially important yeast strains, precision genome engineering is bound to also impact the study and development of wine yeast strains supercharged with synthetic DNA. The first taste of what the future
Edge usage, motifs, and regulatory logic for cell cycling genetic networks

NASA Astrophysics Data System (ADS)

Zagorski, M.; Krzywicki, A.; Martin, O. C.

2013-01-01

The cell cycle is a tightly controlled process, yet it shows marked differences across species. Which of its structural features follow solely from the ability to control gene expression? We tackle this question in silico by examining the ensemble of all regulatory networks which satisfy the constraint of producing a given sequence of gene expressions. We focus on three cell cycle profiles coming from baker's yeast, fission yeast, and mammals. First, we show that the networks in each of the ensembles use just a few interactions that are repeatedly reused as building blocks. Second, we find an enrichment in network motifs that is similar in the two yeast cell cycle systems investigated. These motifs do not have autonomous functions, yet they reveal a regulatory logic for cell cycling based on a feed-forward cascade of activating interactions.
Yeast ecology of Kombucha fermentation.

PubMed

Teoh, Ai Leng; Heard, Gillian; Cox, Julian

2004-09-01

Kombucha is a traditional fermentation of sweetened tea, involving a symbiosis of yeast species and acetic acid bacteria. Despite reports of different yeast species being associated with the fermentation, little is known of the quantitative ecology of yeasts in Kombucha. Using oxytetracycline-supplemented malt extract agar, yeasts were isolated from four commercially available Kombucha products and identified using conventional biochemical and physiological tests. During the fermentation of each of the four products, yeasts were enumerated from both the cellulosic pellicle and liquor of the Kombucha. The number and diversity of species varied between products, but included Brettanomyces bruxellensis, Candida stellata, Schizosaccharomyces pombe, Torulaspora delbrueckii and Zygosaccharomyces bailii. While these yeast species are known to occur in Kombucha, the enumeration of each species present throughout fermentation of each of the four Kombucha cultures demonstrated for the first time the dynamic nature of the yeast ecology. Kombucha fermentation is, in general, initiated by osmotolerant species, succeeded and ultimately dominated by acid-tolerant species.
PPI4DOCK: large scale assessment of the use of homology models in free docking over more than 1000 realistic targets.

PubMed

Yu, Jinchao; Guerois, Raphaël

2016-12-15

Protein-protein docking methods are of great importance for understanding interactomes at the structural level. It has become increasingly appealing to use not only experimental structures but also homology models of unbound subunits as input for docking simulations. So far we are missing a large scale assessment of the success of rigid-body free docking methods on homology models. We explored how we could benefit from comparative modelling of unbound subunits to expand docking benchmark datasets. Starting from a collection of 3157 non-redundant, high X-ray resolution heterodimers, we developed the PPI4DOCK benchmark containing 1417 docking targets based on unbound homology models. Rigid-body docking by Zdock showed that for 1208 cases (85.2%), at least one correct decoy was generated, emphasizing the efficiency of rigid-body docking in generating correct assemblies. Overall, the PPI4DOCK benchmark contains a large set of realistic cases and provides new ground for assessing docking and scoring methodologies. Benchmark sets can be downloaded from http://biodev.cea.fr/interevol/ppi4dock/ CONTACT: guerois@cea.frSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Yeast ribonuclease III uses a network of multiple hydrogen bonds for RNA binding and cleavage.

PubMed

Lavoie, Mathieu; Abou Elela, Sherif

2008-08-19

Members of the bacterial RNase III family recognize a variety of short structured RNAs with few common features. It is not clear how this group of enzymes supports high cleavage fidelity while maintaining a broad base of substrates. Here we show that the yeast orthologue of RNase III (Rnt1p) uses a network of 2'-OH-dependent interactions to recognize substrates with different structures. We designed a series of bipartite substrates permitting the distinction between binding and cleavage defects. Each substrate was engineered to carry a single or multiple 2'- O-methyl or 2'-fluoro ribonucleotide substitutions to prevent the formation of hydrogen bonds with a specific nucleotide or group of nucleotides. Interestingly, introduction of 2'- O-methyl ribonucleotides near the cleavage site increased the rate of catalysis, indicating that 2'-OH are not required for cleavage. Substitution of nucleotides in known Rnt1p binding site with 2'- O-methyl ribonucleotides inhibited cleavage while single 2'-fluoro ribonucleotide substitutions did not. This indicates that while no single 2'-OH is essential for Rnt1p cleavage, small changes in the substrate structure are not tolerated. Strikingly, several nucleotide substitutions greatly increased the substrate dissociation constant with little or no effect on the Michaelis-Menten constant or rate of catalysis. Together, the results indicate that Rnt1p uses a network of nucleotide interactions to identify its substrate and support two distinct modes of binding. One mode is primarily mediated by the dsRNA binding domain and leads to the formation of stable RNA/protein complex, while the other requires the presence of the nuclease and N-terminal domains and leads to RNA cleavage.
Marine yeast isolation and industrial application

PubMed Central

Zaky, Abdelrahman Saleh; Tucker, Gregory A; Daw, Zakaria Yehia; Du, Chenyu

2014-01-01

Over the last century, terrestrial yeasts have been widely used in various industries, such as baking, brewing, wine, bioethanol and pharmaceutical protein production. However, only little attention has been given to marine yeasts. Recent research showed that marine yeasts have several unique and promising features over the terrestrial yeasts, for example higher osmosis tolerance, higher special chemical productivity and production of industrial enzymes. These indicate that marine yeasts have great potential to be applied in various industries. This review gathers the most recent techniques used for marine yeast isolation as well as the latest applications of marine yeast in bioethanol, pharmaceutical and enzyme production fields. PMID:24738708
The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean

PubMed Central

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms. PMID:29666630
Microarray and network-based identification of functional modules and pathways of active tuberculosis.

PubMed

Bian, Zhong-Rui; Yin, Juan; Sun, Wen; Lin, Dian-Jie

2017-04-01

Diagnose of active tuberculosis (TB) is challenging and treatment response is also difficult to efficiently monitor. The aim of this study was to use an integrated analysis of microarray and network-based method to the samples from publically available datasets to obtain a diagnostic module set and pathways in active TB. Towards this goal, background protein-protein interactions (PPI) network was generated based on global PPI information and gene expression data, following by identification of differential expression network (DEN) from the background PPI network. Then, ego genes were extracted according to the degree features in DEN. Next, module collection was conducted by ego gene expansion based on EgoNet algorithm. After that, differential expression of modules between active TB and controls was evaluated using random permutation test. Finally, biological significance of differential modules was detected by pathways enrichment analysis based on Reactome database, and Fisher's exact test was implemented to extract differential pathways for active TB. Totally, 47 ego genes and 47 candidate modules were identified from the DEN. By setting the cutoff-criteria of gene size >5 and classification accuracy ≥0.9, 7 ego modules (Module 4, Module 7, Module 9, Module 19, Module 25, Module 38 and Module 43) were extracted, and all of them had the statistical significance between active TB and controls. Then, Fisher's exact test was conducted to capture differential pathways for active TB. Interestingly, genes in Module 4, Module 25, Module 38, and Module 43 were enriched in the same pathway, formation of a pool of free 40S subunits. Significant pathway for Module 7 and Module 9 was eukaryotic translation termination, and for Module 19 was nonsense mediated decay enhanced by the exon junction complex (EJC). Accordingly, differential modules and pathways might be potential biomarkers for treating active TB, and provide valuable clues for better understanding of molecular

Effect of Yeast Cell Morphology, Cell Wall Physical Structure and Chemical Composition on Patulin Adsorption

PubMed Central

Luo, Ying; Wang, Jianguo; Liu, Bin; Wang, Zhouli; Yuan, Yahong; Yue, Tianli

2015-01-01

The capability of yeast to adsorb patulin in fruit juice can aid in substantially reducing the patulin toxic effect on human health. This study aimed to investigate the capability of yeast cell morphology and cell wall internal structure and composition to adsorb patulin. To compare different yeast cell morphologies, cell wall internal structure and composition, scanning electron microscope, transmission electron microscope and ion chromatography were used. The results indicated that patulin adsorption capability of yeast was influenced by cell surface areas, volume, and cell wall thickness, as well as 1,3-β-glucan content. Among these factors, cell wall thickness and 1,3-β-glucan content serve significant functions. The investigation revealed that patulin adsorption capability was mainly affected by the three-dimensional network structure of the cell wall composed of 1,3-β-glucan. Finally, patulin adsorption in commercial kiwi fruit juice was investigated, and the results indicated that yeast cells could adsorb patulin from commercial kiwi fruit juice efficiently. This study can potentially simulate in vitro cell walls to enhance patulin adsorption capability and successfully apply to fruit juice industry. PMID:26295574
Morphological, electrical & antibacterial properties of trilayered Cs/PAA/PPy bionanocomposites hydrogel based on Fe3O4-NPs.

PubMed

Youssef, A M; Abdel-Aziz, M E; El-Sayed, E S A; Abdel-Aziz, M S; Abd El-Hakim, A A; Kamel, S; Turky, G

2018-09-15

Bionanocomposites hydrogel based on conducting polymers were successfully fabricated from chitosan/polyacrylic acid/polypyrrole (CS/PAA/PPy) as well as the magnetite nanoparticle (Fe 3 O 4 -NPs) was prepared via co-precipitation method. In addition, different ratios of Fe 3 O 4 -NPs were added to the prepared bionanocomposites to enhance the antimicrobial and the electrical conductivity of the prepared conductive hydrogel. Furthermore, the morphology, the swelling percent, antimicrobial activity and the dielectric properties of the prepared conducting bionanocomposites hydrogel were investigated. The antibacterial activities of the experienced microbes were improved with the increasing the loading of Fe 3 O 4 -NPs in conducting Bio-nanocomposites hydrogel. Moreover, the DC-conductivity was examined and our resulted indicated that the DC-conductivity was enhanced by increasing the loadings of Fe 3 O 4 -NPs compared to that of the pure CS/PAA as well as CS/PAA/PPy. Copyright © 2018 Elsevier Ltd. All rights reserved.
Reconstructing the regulatory circuit of cell fate determination in yeast mating response.

PubMed

Shao, Bin; Yuan, Haiyu; Zhang, Rongfei; Wang, Xuan; Zhang, Shuwen; Ouyang, Qi; Hao, Nan; Luo, Chunxiong

2017-07-01

Massive technological advances enabled high-throughput measurements of proteomic changes in biological processes. However, retrieving biological insights from large-scale protein dynamics data remains a challenging task. Here we used the mating differentiation in yeast Saccharomyces cerevisiae as a model and developed integrated experimental and computational approaches to analyze the proteomic dynamics during the process of cell fate determination. When exposed to a high dose of mating pheromone, the yeast cell undergoes growth arrest and forms a shmoo-like morphology; however, at intermediate doses, chemotropic elongated growth is initialized. To understand the gene regulatory networks that control this differentiation switch, we employed a high-throughput microfluidic imaging system that allows real-time and simultaneous measurements of cell growth and protein expression. Using kinetic modeling of protein dynamics, we classified the stimulus-dependent changes in protein abundance into two sources: global changes due to physiological alterations and gene-specific changes. A quantitative framework was proposed to decouple gene-specific regulatory modes from the growth-dependent global modulation of protein abundance. Based on the temporal patterns of gene-specific regulation, we established the network architectures underlying distinct cell fates using a reverse engineering method and uncovered the dose-dependent rewiring of gene regulatory network during mating differentiation. Furthermore, our results suggested a potential crosstalk between the pheromone response pathway and the target of rapamycin (TOR)-regulated ribosomal biogenesis pathway, which might underlie a cell differentiation switch in yeast mating response. In summary, our modeling approach addresses the distinct impacts of the global and gene-specific regulation on the control of protein dynamics and provides new insights into the mechanisms of cell fate determination. We anticipate that our
Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Motivation: Most functions within the cell emerge thanks to protein–protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable. Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions. Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction. Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules
Pharmacological interventions for stress ulcer prophylaxis in critically ill patients: a mixed treatment comparison network meta-analysis and a recursive cumulative meta-analysis.

PubMed

Sridharan, Kannan; Sivaramakrishnan, Gowri; Gnanaraj, Jerome

2018-02-01

Proton pump inhibitors (PPI), histamine-2 receptor antagonists (H2RA), sucralfate and antacids are the commonly administered agents for stress ulcer prophylaxis (SUP) in critically ill patients. The authors of this paper have conducted a network meta-analysis to compare the efficacy of these agents in SUP. Electronic databases were searched for randomized controlled trials, cohort studies and conference abstracts for studies comparing a SUP agent in critically ill patients to another active SUP agent or placebo. Overt, occult and clinically significant upper gastro-intestinal (UGI) bleeding, all-cause mortality, pneumonia, gastric colonization and ICU length of stay were considered as the outcome measures. A random effects model was used to generate pooled estimates. A total of 53 studies (4258 participants) were included. The pooled estimates were in favor of PPI and sucralfate for the overt UGI bleeding. PPI and H2RA bolus were associated with increased risk of gastric colonization and pneumonia. SUP in critically ill patients was not associated with any benefit with regard to clinically significant bleeding episodes. However, PPI and sucralfate significantly reduces overt UGI bleeding. On the contrary, PPI and H2RA bolus are associated with an increased risk of gastric colonization and pneumonia.
Wine yeasts for the future.

PubMed

Fleet, Graham H

2008-11-01

International competition within the wine market, consumer demands for newer styles of wines and increasing concerns about the environmental sustainability of wine production are providing new challenges for innovation in wine fermentation. Within the total production chain, the alcoholic fermentation of grape juice by yeasts is a key process where winemakers can creatively engineer wine character and value through better yeast management and, thereby, strategically tailor wines to a changing market. This review considers the importance of yeast ecology and yeast metabolic reactions in determining wine quality, and then discusses new directions for exploiting yeasts in wine fermentation. It covers criteria for selecting and developing new commercial strains, the possibilities of using yeasts other than those in the genus of Saccharomyces, the prospects for mixed culture fermentations and explores the possibilities for high cell density, continuous fermentations.
Resinless section electron microscopy reveals the yeast cytoskeleton.

PubMed

Penman, J; Penman, S

1997-04-15

The cytoskeleton of Saccharomyces cerevisiae is essentially invisible using conventional microscopy techniques. A similar problem was solved for the mammalian cell cytoskeleton using resinless section electron microscopy, a technique applied here to yeast. In the resinless image, soluble proteins are no longer cloaked by embedding medium and must be removed by selective detergent extraction. In yeast, this requires breaching the cell wall by digesting with Zymolyase sufficiently to allow detergent extraction of the plasma membrane lipids. Gel electropherograms show that the extracted or "soluble" proteins are distinct from the retained or "structural" proteins that presumably comprise the cytoskeleton. These putative cytoskeleton proteins include the major portions of a 43-kDa protein, which is presumably actin, and of proteins in a band appearing at 55 kDa, as well as numerous less abundant, nonactin proteins. Resinless section electron micrographs show a dense, three-dimensional web of anastomosing, polymorphic filaments bounded by the remnant cell wall. Although the filament network is very heterogenous, there appear to be two principal classes of filament diameters-5 nm and 15-20 nm-which may correspond to actin and intermediate filaments, respectively. A large oval region of lower filament density probably corresponds to the vacuole, and an electron dense spheroidal body, 300-500 nm in diameter, is likely the nucleus. The techniques detailed in this report afford new approaches to the study of yeast cytoarchitecture.
A systems-level approach for metabolic engineering of yeast cell factories.

PubMed

Kim, Il-Kwon; Roldão, António; Siewers, Verena; Nielsen, Jens

2012-03-01

The generation of novel yeast cell factories for production of high-value industrial biotechnological products relies on three metabolic engineering principles: design, construction, and analysis. In the last two decades, strong efforts have been put on developing faster and more efficient strategies and/or technologies for each one of these principles. For design and construction, three major strategies are described in this review: (1) rational metabolic engineering; (2) inverse metabolic engineering; and (3) evolutionary strategies. Independent of the selected strategy, the process of designing yeast strains involves five decision points: (1) choice of product, (2) choice of chassis, (3) identification of target genes, (4) regulating the expression level of target genes, and (5) network balancing of the target genes. At the construction level, several molecular biology tools have been developed through the concept of synthetic biology and applied for the generation of novel, engineered yeast strains. For comprehensive and quantitative analysis of constructed strains, systems biology tools are commonly used and using a multi-omics approach. Key information about the biological system can be revealed, for example, identification of genetic regulatory mechanisms and competitive pathways, thereby assisting the in silico design of metabolic engineering strategies for improving strain performance. Examples on how systems and synthetic biology brought yeast metabolic engineering closer to industrial biotechnology are described in this review, and these examples should demonstrate the potential of a systems-level approach for fast and efficient generation of yeast cell factories. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.
Expression profiling reveals an unexpected growth-stimulating effect of surplus iron on the yeast Saccharomyces cerevisiae.

PubMed

Du, Yang; Cheng, Wang; Li, Wei-Fang

2012-08-01

Iron homeostasis plays a crucial role in growth and division of cells in all kingdoms of life. Although yeast iron metabolism has been extensively studied, little is known about the molecular mechanism of response to surplus iron. In this study, expression profiling of Saccharomyces cerevisiae in the presence of surplus iron revealed a dual effect at 1 and 4 h. A cluster of stress-responsive genes was upregulated via activation of the stress-resistance transcription factor Msn4, which indicated the stress effect of surplus iron on yeast metabolism. Genes involved in aerobic metabolism and several anabolic pathways are also upregulated in iron-surplus conditions, which could significantly accelerate yeast growth. This dual effect suggested that surplus iron might participate in a more complex metabolic network, in addition to serving as a stress inducer. These findings contribute to our understanding of the global response of yeast to the fluctuating availability of iron in the environment.
Discussion of teleomorphic and anamorphic Ascomycetous yeasts and yeast-like taxa

USDA-ARS?s Scientific Manuscript database

The relationship of ascomycetous yeasts with other members of the ascomycete fungi (Ascomycota) has been controversial for over 100 years. Because yeasts are morphologically simple, it was proposed that they represent primitive forms of ascomycetes (e.g., Guilliermond 1912). Alternatively, the ide...
Yeasts and yeast-like organisms associated with fruits and blossoms of different fruit trees.

PubMed

Vadkertiová, Renáta; Molnárová, Jana; Vránová, Dana; Sláviková, Elena

2012-12-01

Yeasts are common inhabitants of the phyllosphere, but our knowledge of their diversity in various plant organs is still limited. This study focused on the diversity of yeasts and yeast-like organisms associated with matured fruits and fully open blossoms of apple, plum, and pear trees, during 2 consecutive years at 3 localities in southwest Slovakia. The occurrence of yeasts and yeast-like organisms in fruit samples was 2½ times higher and the yeast community more diverse than that in blossom samples. Only 2 species (Aureobasidium pullulans and Metschnikowia pulcherrima) occurred regularly in the blossom samples, whereas Galactomyces candidus, Hanseniaspora guilliermondii, Hanseniaspora uvarum, M. pulcherrima, Pichia kluyveri, Pichia kudriavzevii, and Saccharomyces cerevisiae were the most frequently isolated species from the fruit samples. The ratio of the number of samples where only individual species were present to the number of samples where 2 or more species were found (consortium) was counted. The occurrence of individual species in comparison with consortia was much higher in blossom samples than in fruit samples. In the latter, consortia predominated. Aureobasidium pullulans, M. pulcherrima, and S. cerevisiae, isolated from both the fruits and blossoms, can be considered as resident yeast species of various fruit tree species cultivated in southwest Slovakia localities.
Forces in yeast flocculation

NASA Astrophysics Data System (ADS)

El-Kirat-Chatel, Sofiane; Beaussart, Audrey; Vincent, Stéphane P.; Abellán Flos, Marta; Hols, Pascal; Lipke, Peter N.; Dufrêne, Yves F.

2015-01-01

In the baker's yeast Saccharomyces cerevisiae, cell-cell adhesion (``flocculation'') is conferred by a family of lectin-like proteins known as the flocculin (Flo) proteins. Knowledge of the adhesive and mechanical properties of flocculins is important for understanding the mechanisms of yeast adhesion, and may help controlling yeast behaviour in biotechnology. We use single-molecule and single-cell atomic force microscopy (AFM) to explore the nanoscale forces engaged in yeast flocculation, focusing on the role of Flo1 as a prototype of flocculins. Using AFM tips labelled with mannose, we detect single flocculins on Flo1-expressing cells, showing they are widely exposed on the cell surface. When subjected to force, individual Flo1 proteins display two distinct force responses, i.e. weak lectin binding forces and strong unfolding forces reflecting the force-induced extension of hydrophobic tandem repeats. We demonstrate that cell-cell adhesion bonds also involve multiple weak lectin interactions together with strong unfolding forces, both associated with Flo1 molecules. Single-molecule and single-cell data correlate with microscale cell adhesion behaviour, suggesting strongly that Flo1 mechanics is critical for yeast flocculation. These results favour a model in which not only weak lectin-sugar interactions are involved in yeast flocculation but also strong hydrophobic interactions resulting from protein unfolding.
[Thermoresistance in Saccharomyces cerevisiae yeasts].

PubMed

Kaliuzhin, V A

2011-01-01

Under natural conditions, yeast Saccharomyces cerevisiae reproduce, as a rule, on the surface of solid or liquid medium. Thus, life cycle of yeast populations is substantially influenced by diurnal changes in ambient temperature. The pattern in the response of unrestricted yeast S. cerevisiae culture to changes in the temperature of cultivation is revealed experimentally. Yeast population, in the absence of environmental constraints on the functioning of cell chemosmotic bioenergetic system, demonstrates the ability of thermoresistance when the temperature of cultivation switches from the range of 12-36 degrees C to 37.5-40 degrees C. During the transient period that is associated with the temperature switching and lasts from 1 to 4 turnover cycles, yeast reproduction rate remains 1.5-2 times higher than under stationary conditions. This is due to evolutionary acquired adaptive activity of cell chemosmotic system. After the adaptive resources exhausting, yeast thermoresistance fully recovers at the temperature range of 12-36 degrees C within one generation time under conditions of both restricted and unrestricted nourishment. Adaptive significance of such thermoresistance seems obvious enough--it allows maintaining high reproduction rate in yeast when ambient temperature is reaching a brief maximum shortly after noon.
Interaction Between Yeasts and Zinc

NASA Astrophysics Data System (ADS)

Nicola, Raffaele De; Walker, Graeme

Zinc is an essential trace element in biological systems. For example, it acts as a cellular membrane stabiliser, plays a critical role in gene expression and genome modification and activates nearly 300 enzymes, including alcohol dehydrogenase. The present chapter will be focused on the influence of zinc on cell physiology of industrial yeast strains of Saccharomyces cerevisiae, with special regard to the uptake and subsequent utilisation of this metal. Zinc uptake by yeast is metabolism-dependent, with most of the available zinc translocated very quickly into the vacuole. At cell division, zinc is distributed from mother to daughter cells and this effectively lowers the individual cellular zinc concentration, which may become zinc depleted at the onset of the fermentation. Zinc influences yeast fermentative performance and examples will be provided relating to brewing and wine fermentations. Industrial yeasts are subjected to several stresses that may impair fermentation performance. Such stresses may also impact on yeast cell zinc homeostasis. This chapter will discuss the practical implications for the correct management of zinc bioavailability for yeast-based biotechnologies aimed at improving yeast growth, viability, fermentation performance and resistance to environmental stresses
21 CFR 172.896 - Dried yeasts.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Dried yeasts. 172.896 Section 172.896 Food and... PERMITTED FOR DIRECT ADDITION TO FOOD FOR HUMAN CONSUMPTION Multipurpose Additives § 172.896 Dried yeasts. Dried yeast (Saccharomyces cerevisiae and Saccharomyces fragilis) and dried torula yeast (Candida utilis...
Meta-analyses: does long-term PPI use increase the risk of gastric premalignant lesions?

PubMed

Eslami, Layli; Nasseri-Moghaddam, Siavosh

2013-08-01

Proton pump inhibitors (PPIs) are the most effective agents available for reducing acid secretion. They are used for medical treatment of various acid-related disorders. PPIs are used extensively and for extended periods of time in gastroesophageal reflux disease (GERD). A troublesome issue regarding maintenance therapy has been the propensity of PPI-treated patients to develop chronic atrophic gastritis while on therapy that could theoretically lead to an increased incidence of gastric cancer. In addition, animal studies have raised concern for development of enterochromaffin-like cell hyperplasia and carcinoid tumors in the stomachs of mice receiving high dose PPIs. Current literature does not provide a clear-cut conclusion on the subject and the reports are sometimes contradictory. Therefore, this study is a systematic review of the available literature to address the safety of long-term PPI use and its relation to the development of malignant/premalignant gastric lesions. A literature search of biomedical databases was performed. The reference lists of retrieved articles were reviewed to further identify relevant trials. We hand-searched the abstracts of the American Digestive Disease Week (DDW) and the United European Gastroenterology Week (UEGW) from 1995 to 2013. Only randomized clinical trials (RCTs) that used PPIs as the primary treatment for at least six month versus no treatment, placebo, antacid or anti-reflux surgery (ARS) were included. Two reviewers independently extracted the data. Discrepancies in the interpretation were resolved by consensus. All analyses of outcomes were based on the intention-to-treat principle. We performed statistical analysis using Review Manager software. The effect measure of choice was relative risk (RR) for dichotomous data. Six RCTs with a total of 785 patients met the inclusion criteria. Two multicenter RCTs compared Esomeprazole with placebo. One RCT compared omeprazole with ARS. Two RCTs compared omeprazole with
In vivo dynamical behavior of yeast chromatin modeled as an entangled polymer network with constraint release

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Kilfoil, Maria L.

2013-03-01

The high fidelity segregation of chromatin is the central problem in cell mitosis. The role of mechanics underlying this, however, is undetermined. Work in this area has largely focused on cytoskeletal elements of the process. Preliminary work in our lab suggests the mechanical properties of chromatin are fundamental in this process. Nevertheless, the mechanical properties of chromatin in the cellular context are not well-characterized. For better understanding of the role of mechanics in this cellular process, and of the chromatin mechanics in vivo generally, a systematic dynamical description of chromatin in vivo is required. Accordingly, we label specific sites on chromatin with fluorescent proteins of different wave lengths, enabling us to detect multiple spots separately in 3D and track their displacements in time inside living yeast cells. We analyze the pairwise cross-correlated motion between spots as a function of relative distance along the DNA contour. Comparison between the reptation model and our data serves to test our conjecture that chromatin in the cell is basically an entangled polymer network under constraints to thermal motion, and removal of constraints by non-thermal cellular processes is expected to affect its dynamic behavior.
A conserved signaling network monitors delivery of sphingolipids to the plasma membrane in budding yeast.

PubMed

Clarke, Jesse; Dephoure, Noah; Horecka, Ira; Gygi, Steven; Kellogg, Douglas

2017-10-01

In budding yeast, cell cycle progression and ribosome biogenesis are dependent on plasma membrane growth, which ensures that events of cell growth are coordinated with each other and with the cell cycle. However, the signals that link the cell cycle and ribosome biogenesis to membrane growth are poorly understood. Here we used proteome-wide mass spectrometry to systematically discover signals associated with membrane growth. The results suggest that membrane trafficking events required for membrane growth generate sphingolipid-dependent signals. A conserved signaling network appears to play an essential role in signaling by responding to delivery of sphingolipids to the plasma membrane. In addition, sphingolipid-dependent signals control phosphorylation of protein kinase C (Pkc1), which plays an essential role in the pathways that link the cell cycle and ribosome biogenesis to membrane growth. Together these discoveries provide new clues as to how growth--dependent signals control cell growth and the cell cycle. © 2017 Clarke et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
21 CFR 172.896 - Dried yeasts.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 3 2011-04-01 2011-04-01 false Dried yeasts. 172.896 Section 172.896 Food and... Multipurpose Additives § 172.896 Dried yeasts. Dried yeast (Saccharomyces cerevisiae and Saccharomyces fragilis) and dried torula yeast (Candida utilis) may be safely used in food provided the total folic acid...
21 CFR 172.896 - Dried yeasts.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 3 2013-04-01 2013-04-01 false Dried yeasts. 172.896 Section 172.896 Food and... Multipurpose Additives § 172.896 Dried yeasts. Dried yeast (Saccharomyces cerevisiae and Saccharomyces fragilis) and dried torula yeast (Candida utilis) may be safely used in food provided the total folic acid...

21 CFR 172.896 - Dried yeasts.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Dried yeasts. 172.896 Section 172.896 Food and... Multipurpose Additives § 172.896 Dried yeasts. Dried yeast (Saccharomyces cerevisiae and Saccharomyces fragilis) and dried torula yeast (Candida utilis) may be safely used in food provided the total folic acid...
21 CFR 172.896 - Dried yeasts.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 3 2012-04-01 2012-04-01 false Dried yeasts. 172.896 Section 172.896 Food and... Multipurpose Additives § 172.896 Dried yeasts. Dried yeast (Saccharomyces cerevisiae and Saccharomyces fragilis) and dried torula yeast (Candida utilis) may be safely used in food provided the total folic acid...
Big data mining powers fungal research: recent advances in fission yeast systems biology approaches.

PubMed

Wang, Zhe

2017-06-01

Biology research has entered into big data era. Systems biology approaches therefore become the powerful tools to obtain the whole landscape of how cell separate, grow, and resist the stresses. Fission yeast Schizosaccharomyces pombe is wonderful unicellular eukaryote model, especially studying its division and metabolism can facilitate to understanding the molecular mechanism of cancer and discovering anticancer agents. In this perspective, we discuss the recent advanced fission yeast systems biology tools, mainly focus on metabolomics profiling and metabolic modeling, protein-protein interactome and genetic interaction network, DNA sequencing and applications, and high-throughput phenotypic screening. We therefore hope this review can be useful for interested fungal researchers as well as bioformaticians.
Yeast flocculation: New story in fuel ethanol production.

PubMed

Zhao, X Q; Bai, F W

2009-01-01

Yeast flocculation has been used in the brewing industry to facilitate biomass recovery for a long time, and thus its mechanism of yeast flocculation has been intensively studied. However, the application of flocculating yeast in ethanol production garnered attention mainly in the 1980s and 1990s. In this article, updated research progress in the molecular mechanism of yeast flocculation and the impact of environmental conditions on yeast flocculation are reviewed. Construction of flocculating yeast strains by genetic approach and utilization of yeast flocculation for ethanol production from various feedstocks were presented. The concept of self-immobilized yeast cells through their flocculation is revisited through a case study of continuous ethanol fermentation with the flocculating yeast SPSC01, and their technical and economic advantages are highlighted by comparing with yeast cells immobilized with supporting materials and regular free yeast cells as well. Taking the flocculating yeast SPSC01 as an example, the ethanol tolerance of the flocculating yeast was also discussed.
Contractile-Ring Assembly in Fission Yeast Cytokinesis: Recent Advances and New Perspectives

PubMed Central

Lee, I-Ju; Coffman, Valerie C.; Wu, Jian-Qiu

2017-01-01

The fission yeast Schizosaccharomyces pombe is an excellent model organism to study cytokinesis. Here, we review recent advances on contractile-ring assembly in fission yeast. First, we summarize the assembly of cytokinesis nodes, the precursors of a normal contractile ring. IQGAP Rng2 and myosin essential light chain Cdc4 are recruited by the anillin-like protein Mid1, followed by the addition of other cytokinesis node proteins. Mid1 localization on the plasma membrane is stabilized by interphase node proteins. Second, we discuss proteins and processes that contribute to the search, capture, pull, and release mechanism of contractile-ring assembly. Actin filaments nucleated by formin Cdc12, the motor activity of myosin-II, the stiffness of the actin network, and severing of actin filaments by cofilin all play essential roles in contractile-ring assembly. Finally, we discuss the Mid1-independent pathway for ring assembly, and the possible mechanisms underlying the ring maturation and constriction. Collectively, we provide an overview of the current understanding of contractile-ring assembly and uncover future directions in studying cytokinesis in fission yeast. PMID:22887981
Brewing characteristics of piezosensitive sake yeasts

NASA Astrophysics Data System (ADS)

Nomura, Kazuki; Hoshino, Hirofumi; Igoshi, Kazuaki; Onozuka, Haruka; Tanaka, Erika; Hayashi, Mayumi; Yamazaki, Harutake; Takaku, Hiroaki; Iguchi, Akinori; Shigematsu, Toru

2018-04-01

Application of high hydrostatic pressure (HHP) treatment to food processing is expected as a non-thermal fermentation regulation technology that supresses over fermentation. However, the yeast Saccharomyces cerevisiae used for Japanese rice wine (sake) brewing shows high tolerance to HHP. Therefore, we aimed to generate pressure-sensitive (piezosensitive) sake yeast strains by mating sake with piezosensitive yeast strains to establish an HHP fermentation regulation technology and extend the shelf life of fermented foods. The results of phenotypic analyses showed that the generated yeast strains were piezosensitive and exhibited similar fermentation ability compared with the original sake yeast strain. In addition, primary properties of sake brewed using these strains, such as ethanol concentration, sake meter value and sake flavor compounds, were almost equivalent to those obtained using the sake yeast strain. These results suggest that the piezosensitive strains exhibit brewing characteristics essentially equivalent to those of the sake yeast strain.
21 CFR 172.898 - Bakers yeast glycan.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Bakers yeast glycan. 172.898 Section 172.898 Food... Bakers yeast glycan. Bakers yeast glycan may be safely used in food in accordance with the following conditions: (a) Bakers yeast glycan is the comminuted, washed, pasteurized, and dried cell walls of the yeast...
Convergent roles of de novo mutations and common variants in schizophrenia in tissue-specific and spatiotemporal co-expression network.

PubMed

Jia, Peilin; Chen, Xiangning; Fanous, Ayman H; Zhao, Zhongming

2018-05-24

Genetic components susceptible to complex disease such as schizophrenia include a wide spectrum of variants, including common variants (CVs) and de novo mutations (DNMs). Although CVs and DNMs differ by origin, it remains elusive whether and how they interact at the gene, pathway, and network levels that leads to the disease. In this work, we characterized the genes harboring schizophrenia-associated CVs (CVgenes) and the genes harboring DNMs (DNMgenes) using measures from network, tissue-specific expression profile, and spatiotemporal brain expression profile. We developed an algorithm to link the DNMgenes and CVgenes in spatiotemporal brain co-expression networks. DNMgenes tended to have central roles in the human protein-protein interaction (PPI) network, evidenced in their high degree and high betweenness values. DNMgenes and CVgenes connected with each other significantly more often than with other genes in the networks. However, only CVgenes remained significantly connected after adjusting for their degree. In our gene co-expression PPI network, we found DNMgenes and CVgenes connected in a tissue-specific fashion, and such a pattern was similar to that in GTEx brain but not in other GTEx tissues. Importantly, DNMgene-CVgene subnetworks were enriched with pathways of chromatin remodeling, MHC protein complex binding, and neurotransmitter activities. In summary, our results unveiled that both DNMgenes and CVgenes contributed to a core set of biologically important pathways and networks, and their interactions may attribute to the risk for schizophrenia. Our results also suggested a stronger biological effect of DNMgenes than CVgenes in schizophrenia.
The control of translational accuracy is a determinant of healthy ageing in yeast.

PubMed

von der Haar, Tobias; Leadsham, Jane E; Sauvadet, Aimie; Tarrant, Daniel; Adam, Ilectra S; Saromi, Kofo; Laun, Peter; Rinnerthaler, Mark; Breitenbach-Koller, Hannelore; Breitenbach, Michael; Tuite, Mick F; Gourlay, Campbell W

2017-01-01

Life requires the maintenance of molecular function in the face of stochastic processes that tend to adversely affect macromolecular integrity. This is particularly relevant during ageing, as many cellular functions decline with age, including growth, mitochondrial function and energy metabolism. Protein synthesis must deliver functional proteins at all times, implying that the effects of protein synthesis errors like amino acid misincorporation and stop-codon read-through must be minimized during ageing. Here we show that loss of translational accuracy accelerates the loss of viability in stationary phase yeast. Since reduced translational accuracy also reduces the folding competence of at least some proteins, we hypothesize that negative interactions between translational errors and age-related protein damage together overwhelm the cellular chaperone network. We further show that multiple cellular signalling networks control basal error rates in yeast cells, including a ROS signal controlled by mitochondrial activity, and the Ras pathway. Together, our findings indicate that signalling pathways regulating growth, protein homeostasis and energy metabolism may jointly safeguard accurate protein synthesis during healthy ageing. © 2017 The Authors.
The control of translational accuracy is a determinant of healthy ageing in yeast

PubMed Central

Leadsham, Jane E.; Sauvadet, Aimie; Tarrant, Daniel; Adam, Ilectra S.; Saromi, Kofo; Laun, Peter; Rinnerthaler, Mark; Breitenbach-Koller, Hannelore; Breitenbach, Michael; Tuite, Mick F.; Gourlay, Campbell W.

2017-01-01

Life requires the maintenance of molecular function in the face of stochastic processes that tend to adversely affect macromolecular integrity. This is particularly relevant during ageing, as many cellular functions decline with age, including growth, mitochondrial function and energy metabolism. Protein synthesis must deliver functional proteins at all times, implying that the effects of protein synthesis errors like amino acid misincorporation and stop-codon read-through must be minimized during ageing. Here we show that loss of translational accuracy accelerates the loss of viability in stationary phase yeast. Since reduced translational accuracy also reduces the folding competence of at least some proteins, we hypothesize that negative interactions between translational errors and age-related protein damage together overwhelm the cellular chaperone network. We further show that multiple cellular signalling networks control basal error rates in yeast cells, including a ROS signal controlled by mitochondrial activity, and the Ras pathway. Together, our findings indicate that signalling pathways regulating growth, protein homeostasis and energy metabolism may jointly safeguard accurate protein synthesis during healthy ageing. PMID:28100667
Flavivirus NS3 and NS5 proteins interaction network: a high-throughput yeast two-hybrid screen

PubMed Central

2011-01-01

Background The genus Flavivirus encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4). Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle. Results We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation. Conclusions We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy. PMID:22014111
Flavivirus NS3 and NS5 proteins interaction network: a high-throughput yeast two-hybrid screen.

PubMed

Le Breton, Marc; Meyniel-Schicklin, Laurène; Deloire, Alexandre; Coutard, Bruno; Canard, Bruno; de Lamballerie, Xavier; Andre, Patrice; Rabourdin-Combe, Chantal; Lotteau, Vincent; Davoust, Nathalie

2011-10-20

The genus Flavivirus encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4). Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle. We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation. We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy.
Development of petri net-based dynamic model for improved production of farnesyl pyrophosphate by integrating mevalonate and methylerythritol phosphate pathways in yeast.

PubMed

Baadhe, Rama Raju; Mekala, Naveen Kumar; Palagiri, Satwik Reddy; Parcha, Sreenivasa Rao

2012-07-01

In this case study, we designed a farnesyl pyrophosphate (FPP) biosynthetic network using hybrid functional Petri net with extension (HFPNe) which is derived from traditional Petri net theory and allows easy modeling with graphical approach of various types of entities in the networks together. Our main objective is to improve the production of FPP in yeast, which is further converted to amorphadiene (AD), a precursor of artemisinin (antimalarial drug). Natively, mevalonate (MEV) pathway is present in yeast. Methyl erythritol phosphate pathways (MEP) are present only in higher plant plastids and eubacteria, but not present in yeast. IPP and DAMP are common isomeric intermediate in these two pathways, which immediately yields FPP. By integrating these two pathways in yeast, we augmented the FPP synthesis approximately two folds higher (431.16 U/pt) than in MEV pathway alone (259.91 U/pt) by using HFPNe technique. Further enhanced FPP levels converted to AD by amorphadiene synthase gene yielding 436.5 U/pt of AD which approximately two folds higher compared to the AD (258.5 U/pt) synthesized by MEV pathway exclusively. Simulation and validation processes performed using these models are reliable with identified biological information and data.
Opportunistic Pathogenic Yeasts

NASA Astrophysics Data System (ADS)

Banerjee, Uma

Advances in medical research, made during the last few decades, have improved the prophylactic, diagnostic and therapeutic capabilities for variety of infections/diseases. However, many of the prophylactic and therapeutic procedures have been seen in many instances to exact a price of host-vulnerability to an expanding group of opportunistic pathogens and yeasts are one of the important members in it. Fortunately amongst the vast majority of yeasts present in nature only few are considered to have the capability to cause infections when certain opportunities predisposes and these are termed as ‘opportunistic pathogenic yeasts.’ However, the term ‘pathogenic’ is quite tricky, as it depends of various factors of the host, the ‘bug’ and the environment to manifest the clinical infection. The borderline is expanding. In the present century with unprecedented increase in number of immune-compromised host in various disciplines of health care settings, where any yeast, which has the capability to grow at 37 ° C (normal body temperature of human), can be pathogenic and cause infection in particular situation
Dielectric and electric modulus study of PPy/TiO2/CNT/SLS composite with temperature

NASA Astrophysics Data System (ADS)

Tiwari, D. C.; Atri, Priyanka; Sharma, Rishi

2013-02-01

Here we report the preparation and electrical characterization of nanocomposite of PPy/TiO2/CNT/SLS synthesized by in situ oxidative polymerization of pyrrole in the presence of TiO2 nanofibers, CNT and surfactant sodium lauryl sulfate. The surface morphology and elemental analysis is studied by SEM and EDAX. Dielectric and modulas studies were carried out in frequency range of 1 KHz to 2 MHz which provides quantitative description of grain and grain boundary effect in nanocomposite material.
Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer

PubMed Central

CHEN, CHEN; SHEN, HONG; ZHANG, LI-GUO; LIU, JIAN; CAO, XIAO-GE; YAO, AN-LIANG; KANG, SHAO-SAN; GAO, WEI-XING; HAN, HUI; CAO, FENG-HONG; LI, ZHI-GUO

2016-01-01

Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa. PMID:27121963
Yeast Droplets

NASA Astrophysics Data System (ADS)

Nguyen, Baochi; Upadhyaya, Arpita; van Oudenaarden, Alexander; Brenner, Michael

2002-11-01

It is well known that the Young's law and surface tension govern the shape of liquid droplets on solid surfaces. Here we address through experiments and theory the shape of growing aggregates of yeast on agar substrates, and assess whether these ideas still hold. Experiments are carried out on Baker's yeast, with different levels of expressions of an adhesive protein governing cell-cell and cell-substrate adhesion. Changing either the agar concentration or the expression of this protein modifies the local contact angle of a yeast droplet. When the colony is small, the shape is a spherical cap with the contact angle obeying Young's law. However, above a critical volume this structure is unstable, and the droplet becomes nonspherical. We present a theoretical model where this instability is caused by bulk elastic effects. The model predicts that the transition depends on both volume and contact angle, in a manner quantitatively consistent with our experiments.
Not your ordinary yeast: non-Saccharomyces yeasts in wine production uncovered.

PubMed

Jolly, Neil P; Varela, Cristian; Pretorius, Isak S

2014-03-01

Saccharomyces cerevisiae and grape juice are 'natural companions' and make a happy wine marriage. However, this relationship can be enriched by allowing 'wild' non-Saccharomyces yeast to participate in a sequential manner in the early phases of grape must fermentation. However, such a triangular relationship is complex and can only be taken to 'the next level' if there are no spoilage yeast present and if the 'wine yeast' - S. cerevisiae - is able to exert its dominance in time to successfully complete the alcoholic fermentation. Winemakers apply various 'matchmaking' strategies (e.g. cellar hygiene, pH, SO2 , temperature and nutrient management) to keep 'spoilers' (e.g. Dekkera bruxellensis) at bay, and allow 'compatible' wild yeast (e.g. Torulaspora delbrueckii, Pichia kluyveri, Lachancea thermotolerans and Candida/Metschnikowia pulcherrima) to harmonize with potent S. cerevisiae wine yeast and bring the best out in wine. Mismatching can lead to a 'two is company, three is a crowd' scenario. More than 40 of the 1500 known yeast species have been isolated from grape must. In this article, we review the specific flavour-active characteristics of those non-Saccharomyces species that might play a positive role in both spontaneous and inoculated wine ferments. We seek to present 'single-species' and 'multi-species' ferments in a new light and a new context, and we raise important questions about the direction of mixed-fermentation research to address market trends regarding so-called 'natural' wines. This review also highlights that, despite the fact that most frontier research and technological developments are often focussed primarily on S. cerevisiae, non-Saccharomyces research can benefit from the techniques and knowledge developed by research on the former. © 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.
A novel feature extraction scheme with ensemble coding for protein-protein interaction prediction.

PubMed

Du, Xiuquan; Cheng, Jiaxing; Zheng, Tingting; Duan, Zheng; Qian, Fulan

2014-07-18

Protein-protein interactions (PPIs) play key roles in most cellular processes, such as cell metabolism, immune response, endocrine function, DNA replication, and transcription regulation. PPI prediction is one of the most challenging problems in functional genomics. Although PPI data have been increasing because of the development of high-throughput technologies and computational methods, many problems are still far from being solved. In this study, a novel predictor was designed by using the Random Forest (RF) algorithm with the ensemble coding (EC) method. To reduce computational time, a feature selection method (DX) was adopted to rank the features and search the optimal feature combination. The DXEC method integrates many features and physicochemical/biochemical properties to predict PPIs. On the Gold Yeast dataset, the DXEC method achieves 67.2% overall precision, 80.74% recall, and 70.67% accuracy. On the Silver Yeast dataset, the DXEC method achieves 76.93% precision, 77.98% recall, and 77.27% accuracy. On the human dataset, the prediction accuracy reaches 80% for the DXEC-RF method. We extended the experiment to a bigger and more realistic dataset that maintains 50% recall on the Yeast All dataset and 80% recall on the Human All dataset. These results show that the DXEC method is suitable for performing PPI prediction. The prediction service of the DXEC-RF classifier is available at http://ailab.ahu.edu.cn:8087/ DXECPPI/index.jsp.
Prediction of cassava protein interactome based on interolog method.

PubMed

Thanasomboon, Ratana; Kalapanulak, Saowalak; Netrphan, Supatcharee; Saithong, Treenut

2017-12-08

Cassava is a starchy root crop whose role in food security becomes more significant nowadays. Together with the industrial uses for versatile purposes, demand for cassava starch is continuously growing. However, in-depth study to uncover the mystery of cellular regulation, especially the interaction between proteins, is lacking. To reduce the knowledge gap in protein-protein interaction (PPI), genome-scale PPI network of cassava was constructed using interolog-based method (MePPI-In, available at http://bml.sbi.kmutt.ac.th/ppi ). The network was constructed from the information of seven template plants. The MePPI-In included 90,173 interactions from 7,209 proteins. At least, 39 percent of the total predictions were found with supports from gene/protein expression data, while further co-expression analysis yielded 16 highly promising PPIs. In addition, domain-domain interaction information was employed to increase reliability of the network and guide the search for more groups of promising PPIs. Moreover, the topology and functional content of MePPI-In was similar to the networks of Arabidopsis and rice. The potential contribution of MePPI-In for various applications, such as protein-complex formation and prediction of protein function, was discussed and exemplified. The insights provided by our MePPI-In would hopefully enable us to pursue precise trait improvement in cassava.

Centralities in simplicial complexes. Applications to protein interaction networks.

PubMed

Estrada, Ernesto; Ross, Grant J

2018-02-07

Complex networks can be used to represent complex systems which originate in the real world. Here we study a transformation of these complex networks into simplicial complexes, where cliques represent the simplices of the complex. We extend the concept of node centrality to that of simplicial centrality and study several mathematical properties of degree, closeness, betweenness, eigenvector, Katz, and subgraph centrality for simplicial complexes. We study the degree distributions of these centralities at the different levels. We also compare and describe the differences between the centralities at the different levels. Using these centralities we study a method for detecting essential proteins in PPI networks of cells and explain the varying abilities of the centrality measures at the different levels in identifying these essential proteins. Copyright © 2017 Elsevier Ltd. All rights reserved.
Yeasts as distinct life forms of fungi

USDA-ARS?s Scientific Manuscript database

This review describes all presently recognized genera of the Ascomycete yeasts (Saccharomycotina, budding yeasts, and the Taphrinomycotina, fission yeasts and related) as well as all currently recognized genera of the Basidiomycete yeasts. This update will be the lead chapter for a book entitled “Ye...
Study of amyloids using yeast

PubMed Central

Wickner, Reed B.; Kryndushkin, Dmitry; Shewmaker, Frank; McGlinchey, Ryan; Edskes, Herman K.

2012-01-01

Summary Saccharomyces cerevisiae has been a useful model organism in such fields as the cell cycle, regulation of transcription, protein trafficking and cell biology, primarily because of its ease of genetic manipulation. This is no less so in the area of amyloid studies. The endogenous yeast amyloids described to date include prions, infectious proteins (Table 1), and some cell wall proteins (1). and amyloids of humans and a fungal prion have also been studied using the yeast system. Accordingly, the emphasis of this chapter will be on genetic, biochemical, cell biological and physical methods particularly useful in the study of yeast prions and other amyloids studied in yeast. We limit our description of these methods to those aspects which have been most useful in studying yeast prions, citing more detailed expositions in the literature. Volumes on yeast genetics methods (2–4), and on amyloids and prions (5, 6) are useful, and Masison has edited a volume of Methods on “Identification, analysis and characterization of fungal prions” which covers some of this territory (7). We also outline some useful physical methods, pointing the reader to more extensive and authoratative descriptions. PMID:22528100
Evolutionary History of Ascomyceteous Yeasts

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

Haridas, Sajeet; Riley, Robert; Salamov, Asaf

2014-06-06

Yeasts are important for many industrial and biotechnological processes and show remarkable diversity despite morphological similarities. We have sequenced the genomes of 16 ascomycete yeasts of taxonomic and industrial importance including members of Saccharomycotina and Taphrinomycotina. A comparison of these with several other previously published yeast genomes have added increased confidence to the phylogenetic positions of previously poorly placed species including Saitoella complicata, Babjeviella inositovora and Metschnikowia bicuspidata. Phylogenetic analysis also showed that yeasts with alternative nuclear codon usage where CUG encodes serine instead of leucine are monophyletic within the Saccharomycotina. Most of the yeasts have compact genomes with amore » large fraction of single exon genes with Lipomyces starkeyi and the previously published Pneumocystis jirovecii being notable exceptions. Intron analysis suggests that early diverging species have more introns. We also observed a large number of unclassified lineage specific non-simple repeats in these genomes.« less
Eighteen new oleaginous yeast species.

PubMed

Garay, Luis A; Sitepu, Irnayuli R; Cajka, Tomas; Chandra, Idelia; Shi, Sandy; Lin, Ting; German, J Bruce; Fiehn, Oliver; Boundy-Mills, Kyria L

2016-07-01

Of 1600 known species of yeasts, about 70 are known to be oleaginous, defined as being able to accumulate over 20 % intracellular lipids. These yeasts have value for fundamental and applied research. A survey of yeasts from the Phaff Yeast Culture Collection, University of California Davis was performed to identify additional oleaginous species within the Basidiomycota phylum. Fifty-nine strains belonging to 34 species were grown in lipid inducing media, and total cell mass, lipid yield and triacylglycerol profiles were determined. Thirty-two species accumulated at least 20 % lipid and 25 species accumulated over 40 % lipid by dry weight. Eighteen of these species were not previously reported to be oleaginous. Triacylglycerol profiles were suitable for biodiesel production. These results greatly expand the number of known oleaginous yeast species, and reveal the wealth of natural diversity of triacylglycerol profiles within wild-type oleaginous Basidiomycetes.
Default Mode Network (DMN) Deactivation during Odor-Visual Association

PubMed Central

Karunanayaka, Prasanna R.; Wilson, Donald A.; Tobia, Michael J.; Martinez, Brittany; Meadowcroft, Mark; Eslinger, Paul J.; Yang, Qing X.

2017-01-01

Default mode network (DMN) deactivation has been shown to be functionally relevant for goal-directed cognition. In this study, we investigated the DMN’s role during olfactory processing using two complementary functional magnetic resonance imaging (fMRI) paradigms with identical timing, visual-cue stimulation and response monitoring protocols. Twenty-nine healthy, non-smoking, right-handed adults (mean age = 26±4 yrs., 16 females) completed an odor-visual association fMRI paradigm that had two alternating odor+visual and visual-only trial conditions. During odor+visual trials, a visual cue was presented simultaneously with an odor, while during visual-only trial conditions the same visual cue was presented alone. Eighteen of the 29 participants (mean age = 27.0 ± 6.0 yrs.,11 females) also took part in a control no-odor fMRI paradigm that consisted of visual-only trial conditions which were identical to the visual-only trials in the odor-visual association paradigm. We used Independent Component Analysis (ICA), extended unified structural equation modeling (euSEM), and psychophysiological interaction (PPI) to investigate the interplay between the DMN and olfactory network. In the odor-visual association paradigm, DMN deactivation was evoked by both the odor+visual and visual-only trial conditions. In contrast, the visual-only trials in the no-odor paradigm did not evoke consistent DMN deactivation. In the odor-visual association paradigm, the euSEM and PPI analyses identified a directed connectivity between the DMN and olfactory network which was significantly different between odor+visual and visual-only trial conditions. The results support a strong interaction between the DMN and olfactory network and highlights DMN’s role in task-evoked brain activity and behavioral responses during olfactory processing. PMID:27785847
Oral yeast colonization throughout pregnancy

PubMed Central

Rio, Rute; Simões-Silva, Liliana; Garro, Sofia; Silva, Mário-Jorge; Azevedo, Álvaro

2017-01-01

Background Recent studies suggest that placenta may harbour a unique microbiome that may have origin in maternal oral microbiome. Although the major physiological and hormonal adjustments observed in pregnant women lead to biochemical and microbiological modifications of the oral environment, very few studies evaluated the changes suffered by the oral microbiota throughout pregnancy. So, the aim of our study was to evaluate oral yeast colonization throughout pregnancy and to compare it with non-pregnant women. Material and Methods The oral yeast colonization was assessed in saliva of 30 pregnant and non-pregnant women longitudinally over a 6-months period. Demographic information was collected, a non-invasive intra-oral examination was performed and saliva flow and pH were determined. Results Pregnant and non-pregnant groups were similar regarding age and level of education. Saliva flow rate did not differ, but saliva pH was lower in pregnant than in non-pregnant women. Oral yeast prevalence was higher in pregnant than in non-pregnant women, either in the first or in the third trimester, but did not attain statistical significance. In individuals colonized with yeast, the total yeast quantification (Log10CFU/mL) increase from the 1st to the 3rd trimester in pregnant women, but not in non-pregnant women. Conclusions Pregnancy may favour oral yeast growth that may be associated with an acidic oral environment. Key words:Oral yeast, fungi, pregnancy, saliva pH. PMID:28160578
Biomedical applications of yeast- a patent view, part one: yeasts as workhorses for the production of therapeutics and vaccines.

PubMed

Roohvand, Farzin; Shokri, Mehdi; Abdollahpour-Alitappeh, Meghdad; Ehsani, Parastoo

2017-08-01

Yeasts, as Eukaryotes, offer unique features for ease of growth and genetic manipulation possibilities, making it an exceptional microbial host. Areas covered: This review provides general and patent-oriented insights into production of biopharmaceuticals by yeasts. Patents, wherever possible, were correlated to the original or review articles. The review describes applications of major GRAS (generally regarded as safe) yeasts for the production of therapeutic proteins and subunit vaccines; additionally, immunomodulatory properties of yeast cell wall components were reviewed for use of whole yeast cells as a new vaccine platform. The second part of the review will discuss yeast- humanization strategies and innovative applications. Expert opinion: Biomedical applications of yeasts were initiated by utilization of Saccharomyces cerevisiae, for production of leavened (fermented) products, and advanced to serve to produce biopharmaceuticals. Higher biomass production and expression/secretion yields, more similarity of glycosylation patterns to mammals and possibility of host-improvement strategies through application of synthetic biology might enhance selection of Pichia pastoris (instead of S. cerevisiae) as a host for production of biopharmaceutical in future. Immunomodulatory properties of yeast cell wall β-glucans and possibility of intracellular expression of heterologous pathogen/tumor antigens in yeast cells have expanded their application as a new platform, 'Whole Yeast Vaccines'.
Nutrient supplements boost yeast transformation efficiency

PubMed Central

Yu, Sheng-Chun; Dawson, Alexander; Henderson, Alyssa C.; Lockyer, Eloise J.; Read, Emily; Sritharan, Gayathri; Ryan, Marjah; Sgroi, Mara; Ngou, Pok M.; Woodruff, Rosie; Zhang, Ruifeng; Ren Teen Chia, Travis; Liu, Yu; Xiang, Yiyu; Spanu, Pietro D.

2016-01-01

Efficiency of yeast transformation is determined by the rate of yeast endocytosis. The aim of this study was to investigate the effect of introducing amino acids and other nutrients (inositol, adenine, or p-aminobenzoic acid) in the transformation medium to develop a highly efficient yeast transformation protocol. The target of rapamycin complex 1 (TORC1) kinase signalling complex influences the rate of yeast endocytosis. TORC signaling is induced by amino acids in the media. Here, we found that increasing the concentration of amino acids and other nutrients in the growth media lead to an increase yeast transformation efficiency up to 107 CFU per μg plasmid DNA and per 108 cells with a 13.8 kb plasmid DNA. This is over 130 times that of current published methods. This improvement may facilitate more efficient experimentation in which transformation efficiency is critical, such as yeast two-hybrid screening. PMID:27760994
Development of an amperometric sulfite biosensor based on SO(x)/PBNPs/PPY modified ITO electrode.

PubMed

Rawal, Rachna; Pundir, C S

2012-11-01

A sulfite oxidase (SO(x)) (EC 1.8.3.1) purified from Syzygium cumini leaves was immobilized onto prussian blue nanoparticles/polypyrrole composite (PBNPs/PPY) electrodeposited onto the surface of indium tin oxide (ITO) electrode. An amperometric sulfite biosensor was fabricated using SO(x)/PBNPs/PPY/ITO electrode as working electrode, Ag/AgCl as standard and Pt wire as auxiliary electrode connected through a potentiostat. The working electrode was characterized by Fourier transform infrared (FTIR) spectroscopy, cyclic voltammetry (CV), scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS) before and after immobilization of SO(x). The biosensor showed optimum response within 2s, when operated at 20 mV s⁻¹ in 0.1M Tris-HCl buffer, pH 8.5 and at 35 °C. Linear range and minimum detection limit were 0.5-1000 μM and 0.12 μM (S/N=3) respectively. There was good correlation (r=0.99) between red wine samples sulfite value by standard DTNB method and the present method. The sensor was evaluated with 97% recovery of added sulfite in red wine samples and 2.2% and 4.3% within and between batch coefficients of variation respectively. The sensor was employed for determination of sulfite level in red and white wine samples. The enzyme electrode was used 200 times over a period of 3 months when stored at 4 °C. Copyright © 2012 Elsevier B.V. All rights reserved.
Combined zebrafish-yeast chemical-genetic screens reveal gene-copper-nutrition interactions that modulate melanocyte pigmentation.

PubMed

Ishizaki, Hironori; Spitzer, Michaela; Wildenhain, Jan; Anastasaki, Corina; Zeng, Zhiqiang; Dolma, Sonam; Shaw, Michael; Madsen, Erik; Gitlin, Jonathan; Marais, Richard; Tyers, Mike; Patton, E Elizabeth

2010-01-01

Hypopigmentation is a feature of copper deficiency in humans, as caused by mutation of the copper (Cu(2+)) transporter ATP7A in Menkes disease, or an inability to absorb copper after gastric surgery. However, many causes of copper deficiency are unknown, and genetic polymorphisms might underlie sensitivity to suboptimal environmental copper conditions. Here, we combined phenotypic screens in zebrafish for compounds that affect copper metabolism with yeast chemical-genetic profiles to identify pathways that are sensitive to copper depletion. Yeast chemical-genetic interactions revealed that defects in intracellular trafficking pathways cause sensitivity to low-copper conditions; partial knockdown of the analogous Ap3s1 and Ap1s1 trafficking components in zebrafish sensitized developing melanocytes to hypopigmentation in low-copper environmental conditions. Because trafficking pathways are essential for copper loading into cuproproteins, our results suggest that hypomorphic alleles of trafficking components might underlie sensitivity to reduced-copper nutrient conditions. In addition, we used zebrafish-yeast screening to identify a novel target pathway in copper metabolism for the small-molecule MEK kinase inhibitor U0126. The zebrafish-yeast screening method combines the power of zebrafish as a disease model with facile genome-scale identification of chemical-genetic interactions in yeast to enable the discovery and dissection of complex multigenic interactions in disease-gene networks.
Directed network modules

NASA Astrophysics Data System (ADS)

Palla, Gergely; Farkas, Illés J.; Pollner, Péter; Derényi, Imre; Vicsek, Tamás

2007-06-01

A search technique locating network modules, i.e. internally densely connected groups of nodes in directed networks is introduced by extending the clique percolation method originally proposed for undirected networks. After giving a suitable definition for directed modules we investigate their percolation transition in the Erdos-Rényi graph both analytically and numerically. We also analyse four real-world directed networks, including Google's own web-pages, an email network, a word association graph and the transcriptional regulatory network of the yeast Saccharomyces cerevisiae. The obtained directed modules are validated by additional information available for the nodes. We find that directed modules of real-world graphs inherently overlap and the investigated networks can be classified into two major groups in terms of the overlaps between the modules. Accordingly, in the word-association network and Google's web-pages, overlaps are likely to contain in-hubs, whereas the modules in the email and transcriptional regulatory network tend to overlap via out-hubs.
Construction and analysis of protein-protein interaction network correlated with ankylosing spondylitis.

PubMed

Kanwal, Attiya; Fazal, Sahar

2018-01-05

Ankylosing spondylitis, a systemic illness is a foundation of progressing joint swelling that for the most part influences the spine. However, it frequently causes aggravation in different joints far from the spine, and in addition organs, for example, the eyes, heart, lungs, and kidneys. It's an immune system ailment that may be activated by specific sorts of bacterial or viral diseases that initiate an invulnerable reaction that don't close off after the contamination is recuperated. The particular reason for ankylosing spondylitis is obscure, yet hereditary qualities assume a huge part in this condition. The rising apparatuses of network medicine offer a stage to investigate an unpredictable illness at framework level. In this study, we meant to recognize the key proteins and the biological regulator pathways including in AS and further investigating the molecular connectivity between these pathways by the topological examination of the Protein-protein communication (PPI) system. The extended network including of 93 nodes and have 199 interactions respectively scanned from STRING database and some separated small networks. 24 proteins with high BC at the threshold of 0.01 and 55 proteins with large degree at the threshold of 1 have been identified. CD4 with highest BC and Closeness centrality located in the centre of the network. The backbone network derived from high BC proteins presents a clear and visual overview which shows all important regulatory pathways for AS and the crosstalk between them. The finding of this research suggests that AS variation is orchestrated by an integrated PPI network centered on CD4 out of 93 nodes. Ankylosing spondylitis, a systemic disease is an establishment of advancing joint swelling that generally impacts the spine. Be that as it may, it as often as possible causes disturbance in various joints a long way from the spine, and what's more organs. It's a resistant framework affliction that might be actuated by particular sorts
Virgin olive oil yeasts: A review.

PubMed

Ciafardini, Gino; Zullo, Biagi Angelo

2018-04-01

This review summarizes current knowledge on virgin olive oil yeasts. Newly produced olive oil contains solid particles and micro drops of vegetation water in which yeasts reproduce to become the typical microbiota of olive oil. To date, about seventeen yeast species have been isolated from different types of olive oils and their by-products, of which six species have been identified as new species. Certain yeast species contribute greatly to improving the sensorial characteristics of the newly produced olive oil, whereas other species are considered harmful as they can damage the oil quality through the production of unpleasant flavors and triacylglycerol hydrolysis. Studies carried out in certain yeast strains have demonstrated the presence of defects in olive oil treated with Candida adriatica, Nakazawaea wickerhamii and Candida diddensiae specific strains, while other olive oil samples treated with other Candida diddensiae strains were defect-free after four months of storage and categorized as extra virgin. A new acetic acid producing yeast species, namely, Brettanomyces acidodurans sp. nov., which was recently isolated from olive oil, could be implicated in the wine-vinegary defect of the product. Other aspects related to the activity of the lipase-producing yeasts and the survival of the yeast species in the flavored olive oils are also discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Construction of phosphorylation interaction networks by text mining of full-length articles using the eFIP system.

PubMed

Tudor, Catalina O; Ross, Karen E; Li, Gang; Vijay-Shanker, K; Wu, Cathy H; Arighi, Cecilia N

2015-01-01

Protein phosphorylation is a reversible post-translational modification where a protein kinase adds a phosphate group to a protein, potentially regulating its function, localization and/or activity. Phosphorylation can affect protein-protein interactions (PPIs), abolishing interaction with previous binding partners or enabling new interactions. Extracting phosphorylation information coupled with PPI information from the scientific literature will facilitate the creation of phosphorylation interaction networks of kinases, substrates and interacting partners, toward knowledge discovery of functional outcomes of protein phosphorylation. Increasingly, PPI databases are interested in capturing the phosphorylation state of interacting partners. We have previously developed the eFIP (Extracting Functional Impact of Phosphorylation) text mining system, which identifies phosphorylated proteins and phosphorylation-dependent PPIs. In this work, we present several enhancements for the eFIP system: (i) text mining for full-length articles from the PubMed Central open-access collection; (ii) the integration of the RLIMS-P 2.0 system for the extraction of phosphorylation events with kinase, substrate and site information; (iii) the extension of the PPI module with new trigger words/phrases describing interactions and (iv) the addition of the iSimp tool for sentence simplification to aid in the matching of syntactic patterns. We enhance the website functionality to: (i) support searches based on protein roles (kinases, substrates, interacting partners) or using keywords; (ii) link protein entities to their corresponding UniProt identifiers if mapped and (iii) support visual exploration of phosphorylation interaction networks using Cytoscape. The evaluation of eFIP on full-length articles achieved 92.4% precision, 76.5% recall and 83.7% F-measure on 100 article sections. To demonstrate eFIP for knowledge extraction and discovery, we constructed phosphorylation-dependent interaction
Disease-aging network reveals significant roles of aging genes in connecting genetic diseases.

PubMed

Wang, Jiguang; Zhang, Shihua; Wang, Yong; Chen, Luonan; Zhang, Xiang-Sun

2009-09-01

One of the challenging problems in biology and medicine is exploring the underlying mechanisms of genetic diseases. Recent studies suggest that the relationship between genetic diseases and the aging process is important in understanding the molecular mechanisms of complex diseases. Although some intricate associations have been investigated for a long time, the studies are still in their early stages. In this paper, we construct a human disease-aging network to study the relationship among aging genes and genetic disease genes. Specifically, we integrate human protein-protein interactions (PPIs), disease-gene associations, aging-gene associations, and physiological system-based genetic disease classification information in a single graph-theoretic framework and find that (1) human disease genes are much closer to aging genes than expected by chance; and (2) diseases can be categorized into two types according to their relationships with aging. Type I diseases have their genes significantly close to aging genes, while type II diseases do not. Furthermore, we examine the topological characters of the disease-aging network from a systems perspective. Theoretical results reveal that the genes of type I diseases are in a central position of a PPI network while type II are not; (3) more importantly, we define an asymmetric closeness based on the PPI network to describe relationships between diseases, and find that aging genes make a significant contribution to associations among diseases, especially among type I diseases. In conclusion, the network-based study provides not only evidence for the intricate relationship between the aging process and genetic diseases, but also biological implications for prying into the nature of human diseases.
21 CFR 184.1983 - Bakers yeast extract.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Bakers yeast extract. 184.1983 Section 184.1983... GRAS § 184.1983 Bakers yeast extract. (a) Bakers yeast extract is the food ingredient resulting from concentration of the solubles of mechanically ruptured cells of a selected strain of yeast, Saccharomyces...
21 CFR 184.1983 - Bakers yeast extract.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 3 2013-04-01 2013-04-01 false Bakers yeast extract. 184.1983 Section 184.1983... Listing of Specific Substances Affirmed as GRAS § 184.1983 Bakers yeast extract. (a) Bakers yeast extract... a selected strain of yeast, Saccharomyces cerevisiae. It may be concentrated or dried. (b) The...
21 CFR 184.1983 - Bakers yeast extract.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 3 2012-04-01 2012-04-01 false Bakers yeast extract. 184.1983 Section 184.1983... Listing of Specific Substances Affirmed as GRAS § 184.1983 Bakers yeast extract. (a) Bakers yeast extract... a selected strain of yeast, Saccharomyces cerevisiae. It may be concentrated or dried. (b) The...
History of genome editing in yeast.

PubMed

Fraczek, Marcin G; Naseeb, Samina; Delneri, Daniela

2018-05-01

For thousands of years humans have used the budding yeast Saccharomyces cerevisiae for the production of bread and alcohol; however, in the last 30-40 years our understanding of the yeast biology has dramatically increased, enabling us to modify its genome. Although S. cerevisiae has been the main focus of many research groups, other non-conventional yeasts have also been studied and exploited for biotechnological purposes. Our experiments and knowledge have evolved from recombination to high-throughput PCR-based transformations to highly accurate CRISPR methods in order to alter yeast traits for either research or industrial purposes. Since the release of the genome sequence of S. cerevisiae in 1996, the precise and targeted genome editing has increased significantly. In this 'Budding topic' we discuss the significant developments of genome editing in yeast, mainly focusing on Cre-loxP mediated recombination, delitto perfetto and CRISPR/Cas. © 2018 The Authors. Yeast published by John Wiley & Sons, Ltd.

Inventions on baker's yeast strains and specialty ingredients.

PubMed

Gélinas, Pierre

2009-06-01

Baker's yeast is one of the oldest food microbial starters. Between 1927 and 2008, 165 inventions on more than 337 baker's yeast strains were patented. The first generation of patented yeast strains claimed improved biomass yield at the yeast plant, higher gassing power in dough or better survival to drying to prepare active dry baker's yeast. Especially between 1980 and 1995, a major interest was given to strains for multiple bakery applications such as dough with variable sugar content and stored at refrigeration (cold) or freezing temperatures. During the same period, genetically engineered yeast strains became very popular but did not find applications in the baking industry. Since year 2000, patented baker's yeast strains claimed aroma, anti-moulding or nutritive properties to better meet the needs of the baking industry. In addition to patents on yeast strains, 47 patents were issued on baker's yeast specialty ingredients for niche markets. This review shows that patents on baker's yeast with improved characteristics such as aromatic or nutritive properties have regularly been issued since the 1920's. Overall, it also confirms recent interest for a very wide range of tailored-made yeast-based ingredients for bakery applications.
Contractile-ring assembly in fission yeast cytokinesis: Recent advances and new perspectives.

PubMed

Lee, I-Ju; Coffman, Valerie C; Wu, Jian-Qiu

2012-10-01

The fission yeast Schizosaccharomyces pombe is an excellent model organism to study cytokinesis. Here, we review recent advances on contractile-ring assembly in fission yeast. First, we summarize the assembly of cytokinesis nodes, the precursors of a normal contractile ring. IQGAP Rng2 and myosin essential light chain Cdc4 are recruited by the anillin-like protein Mid1, followed by the addition of other cytokinesis node proteins. Mid1 localization on the plasma membrane is stabilized by interphase node proteins. Second, we discuss proteins and processes that contribute to the search, capture, pull, and release mechanism of contractile-ring assembly. Actin filaments nucleated by formin Cdc12, the motor activity of myosin-II, the stiffness of the actin network, and severing of actin filaments by cofilin all play essential roles in contractile-ring assembly. Finally, we discuss the Mid1-independent pathway for ring assembly, and the possible mechanisms underlying the ring maturation and constriction. Collectively, we provide an overview of the current understanding of contractile-ring assembly and uncover future directions in studying cytokinesis in fission yeast. Copyright © 2012 Wiley Periodicals, Inc.
21 CFR 172.898 - Bakers yeast glycan.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 3 2012-04-01 2012-04-01 false Bakers yeast glycan. 172.898 Section 172.898 Food... Multipurpose Additives § 172.898 Bakers yeast glycan. Bakers yeast glycan may be safely used in food in accordance with the following conditions: (a) Bakers yeast glycan is the comminuted, washed, pasteurized, and...
21 CFR 172.898 - Bakers yeast glycan.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 3 2013-04-01 2013-04-01 false Bakers yeast glycan. 172.898 Section 172.898 Food... Multipurpose Additives § 172.898 Bakers yeast glycan. Bakers yeast glycan may be safely used in food in accordance with the following conditions: (a) Bakers yeast glycan is the comminuted, washed, pasteurized, and...
The wine and beer yeast Dekkera bruxellensis

PubMed Central

Schifferdecker, Anna Judith; Dashko, Sofia; Ishchuk, Olena P; Piškur, Jure

2014-01-01

Recently, the non-conventional yeast Dekkera bruxellensis has been gaining more and more attention in the food industry and academic research. This yeast species is a distant relative of Saccharomyces cerevisiae and is especially known for two important characteristics: on the one hand, it is considered to be one of the main spoilage organisms in the wine and bioethanol industry; on the other hand, it is 'indispensable' as a contributor to the flavour profile of Belgium lambic and gueuze beers. Additionally, it adds to the characteristic aromatic properties of some red wines. Recently this yeast has also become a model for the study of yeast evolution. In this review we focus on the recently developed molecular and genetic tools, such as complete genome sequencing and transformation, to study and manipulate this yeast. We also focus on the areas that are particularly well explored in this yeast, such as the synthesis of off-flavours, yeast detection methods, carbon metabolism and evolutionary history. © 2014 The Authors. Yeast published by John Wiley & Sons, Ltd. PMID:24932634
The wine and beer yeast Dekkera bruxellensis.

PubMed

Schifferdecker, Anna Judith; Dashko, Sofia; Ishchuk, Olena P; Piškur, Jure

2014-09-01

Recently, the non-conventional yeast Dekkera bruxellensis has been gaining more and more attention in the food industry and academic research. This yeast species is a distant relative of Saccharomyces cerevisiae and is especially known for two important characteristics: on the one hand, it is considered to be one of the main spoilage organisms in the wine and bioethanol industry; on the other hand, it is 'indispensable' as a contributor to the flavour profile of Belgium lambic and gueuze beers. Additionally, it adds to the characteristic aromatic properties of some red wines. Recently this yeast has also become a model for the study of yeast evolution. In this review we focus on the recently developed molecular and genetic tools, such as complete genome sequencing and transformation, to study and manipulate this yeast. We also focus on the areas that are particularly well explored in this yeast, such as the synthesis of off-flavours, yeast detection methods, carbon metabolism and evolutionary history. © 2014 The Authors. Yeast published by John Wiley & Sons, Ltd.
Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells.

PubMed

Recouvreux, Pierre; Sokolowski, Thomas R; Grammoustianou, Aristea; ten Wolde, Pieter Rein; Dogterom, Marileen

2016-02-16

Cell polarity refers to a functional spatial organization of proteins that is crucial for the control of essential cellular processes such as growth and division. To establish polarity, cells rely on elaborate regulation networks that control the distribution of proteins at the cell membrane. In fission yeast cells, a microtubule-dependent network has been identified that polarizes the distribution of signaling proteins that restricts growth to cell ends and targets the cytokinetic machinery to the middle of the cell. Although many molecular components have been shown to play a role in this network, it remains unknown which molecular functionalities are minimally required to establish a polarized protein distribution in this system. Here we show that a membrane-binding protein fragment, which distributes homogeneously in wild-type fission yeast cells, can be made to concentrate at cell ends by attaching it to a cytoplasmic microtubule end-binding protein. This concentration results in a polarized pattern of chimera proteins with a spatial extension that is very reminiscent of natural polarity patterns in fission yeast. However, chimera levels fluctuate in response to microtubule dynamics, and disruption of microtubules leads to disappearance of the pattern. Numerical simulations confirm that the combined functionality of membrane anchoring and microtubule tip affinity is in principle sufficient to create polarized patterns. Our chimera protein may thus represent a simple molecular functionality that is able to polarize the membrane, onto which additional layers of molecular complexity may be built to provide the temporal robustness that is typical of natural polarity patterns.
Biotechnology of non-Saccharomyces yeasts-the basidiomycetes.

PubMed

Johnson, Eric A

2013-09-01

Yeasts are the major producer of biotechnology products worldwide, exceeding production in capacity and economic revenues of other groups of industrial microorganisms. Yeasts have wide-ranging fundamental and industrial importance in scientific, food, medical, and agricultural disciplines (Fig. 1). Saccharomyces is the most important genus of yeast from fundamental and applied perspectives and has been expansively studied. Non-Saccharomyces yeasts (non-conventional yeasts) including members of the Ascomycetes and Basidiomycetes also have substantial current utility and potential applicability in biotechnology. In an earlier mini-review, "Biotechnology of non-Saccharomyces yeasts-the ascomycetes" (Johnson Appl Microb Biotechnol 97: 503-517, 2013), the extensive biotechnological utility and potential of ascomycetous yeasts are described. Ascomycetous yeasts are particularly important in food and ethanol formation, production of single-cell protein, feeds and fodder, heterologous production of proteins and enzymes, and as model and fundamental organisms for the delineation of genes and their function in mammalian and human metabolism and disease processes. In contrast, the roles of basidiomycetous yeasts in biotechnology have mainly been evaluated only in the past few decades and compared to the ascomycetous yeasts and currently have limited industrial utility. From a biotechnology perspective, the basidiomycetous yeasts are known mainly for the production of enzymes used in pharmaceutical and chemical synthesis, for production of certain classes of primary and secondary metabolites such as terpenoids and carotenoids, for aerobic catabolism of complex carbon sources, and for bioremediation of environmental pollutants and xenotoxicants. Notwithstanding, the basidiomycetous yeasts appear to have considerable potential in biotechnology owing to their catabolic utilities, formation of enzymes acting on recalcitrant substrates, and through the production of unique primary
Bioinspired Design of Strong, Tough, and Highly Conductive Polyol-Polypyrrole Composites for Flexible Electronics.

PubMed

Gao, Fengxian; Zhang, Ning; Fang, Xiaodong; Ma, Mingming

2017-02-22

Inspired by the dynamic network structure of animal dermis, we have designed and synthesized a series of polyol-polypyrrole (polyol-PPy) composites. Polyols and polypyrrole are cross-linked by hydrogen bonding and electrostatic interactions to form a dynamic network, which helps to dissipate destructive energy. We have found a clear correlation between the mechanical properties of polyol-PPy composites and the polyols structure. Particularly, the PEE-PPy film shows both high strength and flexibility, leading to a remarkable tensile toughness comparable to cocoon silk. The combination of outstanding strength, ductility, and conductivity enables polyol-PPy composites (especially PEE-PPy) as potential electronic materials for making flexible electronics.
Between science and industry-applied yeast research.

PubMed

Korhola, Matti

2018-03-01

I was fortunate to enter yeast research at the Alko Research Laboratories with a strong tradition in yeast biochemistry and physiology studies. At the same time in the 1980s there was a fundamental or paradigm change in molecular biology research with discoveries in DNA sequencing and other analytical and physical techniques for studying macromolecules and cells. Since that time biotechnological research has expanded the traditional fermentation industries to efficient production of industrial and other enzymes and specialty chemicals. Our efforts were directed towards improving the industrial production organisms: minerals enriched yeasts (Se, Cr, Zn) and high glutathione content yeast, baker´s, distiller´s, sour dough and wine yeasts, and the fungal Trichoderma reesei platform for enzyme production. I am grateful for the trust of my colleagues in several leadership positions at the Alko Research Laboratories, Yeast Industry Platform and at the international yeast community.
Synchronization of glycolytic oscillations in a yeast cell population.

PubMed

Danø, S; Hynne, F; De Monte, S; d'Ovidio, F; Sørensen, P G; Westerhoff, H

2001-01-01

The mechanism of active phase synchronization in a suspension of oscillatory yeast cells has remained a puzzle for almost half a century. The difficulty of the problem stems from the fact that the synchronization phenomenon involves the entire metabolic network of glycolysis and fermentation, and consequently it cannot be addressed at the level of a single enzyme or a single chemical species. In this paper it is shown how this system in a CSTR (continuous flow stirred tank reactor) can be modelled quantitatively as a population of Stuart-Landau oscillators interacting by exchange of metabolites through the extracellular medium, thus reducing the complexity of the problem without sacrificing the biochemical realism. The parameters of the model can be derived by a systematic expansion from any full-scale model of the yeast cell kinetics with a supercritical Hopf bifurcation. Some parameter values can also be obtained directly from analysis of perturbation experiments. In the mean-field limit, equations for the study of populations having a distribution of frequencies are used to simulate the effect of the inherent variations between cells.
Selective inhibition of yeast regulons by daunorubicin: A transcriptome-wide analysis

PubMed Central

Rojas, Marta; Casado, Marta; Portugal, José; Piña, Benjamin

2008-01-01

Background The antitumor drug daunorubicin exerts some of its cytotoxic effects by binding to DNA and inhibiting the transcription of different genes. We analysed this effect in vivo at the transcriptome level using the budding yeast Saccharomyces cerevisiae as a model and sublethal (IC40) concentrations of the drug to minimise general toxic effects. Results Daunorubicin affected a minor proportion (14%) of the yeast transcriptome, increasing the expression of 195 genes and reducing expression of 280 genes. Daunorubicin down-regulated genes included essentially all genes involved in the glycolytic pathway, the tricarboxylic acid cycle and alcohol metabolism, whereas transcription of ribosomal protein genes was not affected or even slightly increased. This pattern is consistent with a specific inhibition of glucose usage in treated cells, with only minor effects on proliferation or other basic cell functions. Analysis of promoters of down-regulated genes showed that they belong to a limited number of transcriptional regulatory units (regulons). Consistently, data mining showed that daunorubicin-induced changes in expression patterns were similar to those observed in yeast strains deleted for some transcription factors functionally related to the glycolysis and/or the cAMP regulatory pathway, which appeared to be particularly sensitive to daunorubicin. Conclusion The effects of daunorubicin treatment on the yeast transcriptome are consistent with a model in which this drug impairs binding of different transcription factors by competing for their DNA binding sequences, therefore limiting their effectiveness and affecting the corresponding regulatory networks. This proposed mechanism might have broad therapeutic implications against cancer cells growing under hypoxic conditions. PMID:18667070
Gene essentiality and the topology of protein interaction networks

PubMed Central

Coulomb, Stéphane; Bauer, Michel; Bernard, Denis; Marsolier-Kergoat, Marie-Claude

2005-01-01

The mechanistic bases for gene essentiality and for cell mutational resistance have long been disputed. The recent availability of large protein interaction databases has fuelled the analysis of protein interaction networks and several authors have proposed that gene dispensability could be strongly related to some topological parameters of these networks. However, many results were based on protein interaction data whose biases were not taken into account. In this article, we show that the essentiality of a gene in yeast is poorly related to the number of interactants (or degree) of the corresponding protein and that the physiological consequences of gene deletions are unrelated to several other properties of proteins in the interaction networks, such as the average degrees of their nearest neighbours, their clustering coefficients or their relative distances. We also found that yeast protein interaction networks lack degree correlation, i.e. a propensity for their vertices to associate according to their degrees. Gene essentiality and more generally cell resistance against mutations thus seem largely unrelated to many parameters of protein network topology. PMID:16087428
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
Coactivation of cognitive control networks during task switching.

PubMed

Yin, Shouhang; Deák, Gedeon; Chen, Antao

2018-01-01

The ability to flexibly switch between tasks is considered an important component of cognitive control that involves frontal and parietal cortical areas. The present study was designed to characterize network dynamics across multiple brain regions during task switching. Functional magnetic resonance images (fMRI) were captured during a standard rule-switching task to identify switching-related brain regions. Multiregional psychophysiological interaction (PPI) analysis was used to examine effective connectivity between these regions. During switching trials, behavioral performance declined and activation of a generic cognitive control network increased. Concurrently, task-related connectivity increased within and between cingulo-opercular and fronto-parietal cognitive control networks. Notably, the left inferior frontal junction (IFJ) was most consistently coactivated with the 2 cognitive control networks. Furthermore, switching-dependent effective connectivity was negatively correlated with behavioral switch costs. The strength of effective connectivity between left IFJ and other regions in the networks predicted individual differences in switch costs. Task switching was supported by coactivated connections within cognitive control networks, with left IFJ potentially acting as a key hub between the fronto-parietal and cingulo-opercular networks. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Yeast-based biosensors: design and applications.

PubMed

Adeniran, Adebola; Sherer, Michael; Tyo, Keith E J

2015-02-01

Yeast-based biosensing (YBB) is an exciting research area, as many studies have demonstrated the use of yeasts to accurately detect specific molecules. Biosensors incorporating various yeasts have been reported to detect an incredibly large range of molecules including but not limited to odorants, metals, intracellular metabolites, carcinogens, lactate, alcohols, and sugars. We review the detection strategies available for different types of analytes, as well as the wide range of output methods that have been incorporated with yeast biosensors. We group biosensors into two categories: those that are dependent upon transcription of a gene to report the detection of a desired molecule and those that are independent of this reporting mechanism. Transcription-dependent biosensors frequently depend on heterologous expression of sensing elements from non-yeast organisms, a strategy that has greatly expanded the range of molecules available for detection by YBBs. Transcription-independent biosensors circumvent the problem of sensing difficult-to-detect analytes by instead relying on yeast metabolism to generate easily detected molecules when the analyte is present. The use of yeast as the sensing element in biosensors has proven to be successful and continues to hold great promise for a variety of applications. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.
Novelty seeking and reward dependence-related large-scale brain networks functional connectivity variation during salience expectancy.

PubMed

Li, Shijia; Demenescu, Liliana Ramona; Sweeney-Reed, Catherine M; Krause, Anna Linda; Metzger, Coraline D; Walter, Martin

2017-08-01

A salience network (SN) anchored in the anterior insula (AI) and dorsal anterior cingulate cortex (dACC) plays a key role in switching between brain networks during salience detection and attention regulation. Previous fMRI studies have associated expectancy behaviors and SN activation with novelty seeking (NS) and reward dependence (RD) personality traits. To address the question of how functional connectivity (FC) in the SN is modulated by internal (expectancy-related) salience assignment and different personality traits, 68 healthy participants performed a salience expectancy task using functional magnetic resonance imaging, and psychophysiological interaction analysis (PPI) was conducted to determine salience-related connectivity changes during these anticipation periods. Correlation was then evaluated between PPI and personality traits, assessed using the temperament and character inventory of 32 male participants. During high salience expectancy, SN-seed regions showed reduced FC to visual areas and parts of the default mode network, but increased FC to the central executive network. With increasing NS, participants showed significantly increasing disconnection between right AI and middle cingulate cortex when expecting high-salience pictures as compared to low-salience pictures, while increased RD also predicted decreased right dACC and caudate FC for high salience expectancy. Our findings suggest a direct link between personality traits and internal salience processing mediated by differential network integration of the SN. SN activity and coordination may therefore be moderated by novelty seeking and reward dependency personality traits, which are associated with risk of addiction. Hum Brain Mapp 38:4064-4077, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

PubMed

Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.
Oral yeast colonization throughout pregnancy.

PubMed

Rio, R; Simões-Silva, L; Garro, S; Silva, M-J; Azevedo, Á; Sampaio-Maia, B

2017-03-01

Recent studies suggest that placenta may harbour a unique microbiome that may have origin in maternal oral microbiome. Although the major physiological and hormonal adjustments observed in pregnant women lead to biochemical and microbiological modifications of the oral environment, very few studies evaluated the changes suffered by the oral microbiota throughout pregnancy. So, the aim of our study was to evaluate oral yeast colonization throughout pregnancy and to compare it with non-pregnant women. The oral yeast colonization was assessed in saliva of 30 pregnant and non-pregnant women longitudinally over a 6-months period. Demographic information was collected, a non-invasive intra-oral examination was performed and saliva flow and pH were determined. Pregnant and non-pregnant groups were similar regarding age and level of education. Saliva flow rate did not differ, but saliva pH was lower in pregnant than in non-pregnant women. Oral yeast prevalence was higher in pregnant than in non-pregnant women, either in the first or in the third trimester, but did not attain statistical significance. In individuals colonized with yeast, the total yeast quantification (Log10CFU/mL) increase from the 1st to the 3rd trimester in pregnant women, but not in non-pregnant women. Pregnancy may favour oral yeast growth that may be associated with an acidic oral environment.

Biotechnological Applications of Dimorphic Yeasts

NASA Astrophysics Data System (ADS)

Doiphode, N.; Joshi, C.; Ghormade, V.; Deshpande, M. V.

The dimorphic yeasts have the equilibrium between spherical growth (budding) and polarized (hyphal or pseudohyphal tip elongation) which can be triggered by change in the environmental conditions. The reversible growth phenomenon has made dimorphic yeasts as an useful model to understand fungal evolution and fungal differentiation, in general. In nature dimorphism is clearly evident in plant and animal fungal pathogens, which survive and most importantly proliferate in the respective hosts. However, number of organisms with no known pathogenic behaviour also show such a transition, which can be exploited for the technological applications due to their different biochemical make up under different morphologies. For instance, chitin and chitosan production using dimorphic Saccharomyces, Mucor, Rhizopus and Benjaminiella, oil degradation and biotransformation with yeast-form of Yarrowia species, bioremediation of organic pollutants, exopolysac-charide production by yeast-phase of Aureobasidium pullulans, to name a few. Myrothecium verrucaria can be used for seed dressing in its yeast form and it produces a mycolytic enzyme complex in its hyphal-form for the biocontrol of fungal pathogens, while Beauveria bassiana and other entomopathogens kill the insect pest by producing yeast- like cells in the insect body. The form-specific expression of protease, chitinase, lipase, ornithine decarboxylase, glutamate dehydrogenases, etc. make Benjaminiella poitrasii, Basidiobolus sp., and Mucor rouxii strains important in bioremediation, nanobiotechnology, fungal evolution and other areas.
Yeasts of the soil – obscure but precious

PubMed Central

2018-01-01

Abstract Pioneering studies performed in the nineteenth century demonstrated that yeasts are present in below‐ground sources. Soils were regarded more as a reservoir for yeasts that reside in habitats above it. Later studies showed that yeast communities in soils are taxonomically diverse and different from those above‐ground. Soil yeasts possess extraordinary adaptations that allow them to survive in a wide range of environmental conditions. A few species are promising sources of yeast oils and have been used in agriculture as potential antagonists of soil‐borne plant pathogens or as plant growth promoters. Yeasts have been studied mainly in managed soils such as vineyards, orchards and agricultural fields, and to a lesser extent under forests and grasslands. Our knowledge of soil yeasts is further biased towards temperate and boreal forests, whereas data from Africa, the Americas and Asia are scarce. Although soil yeast communities are often species‐poor in a single sample, they are more diverse on the biotope level. Soil yeasts display pronounced endemism along with a surprisingly high proportion of currently unidentified species. However, like other soil inhabitants, yeasts are threatened by habitat alterations owing to anthropogenic activities such as agriculture, deforestation and urbanization. In view of the rapid decline of many natural habitats, the study of soil yeasts in undisturbed or low‐managed biotopes is extremely valuable. The purpose of this review is to encourage researchers, both biologists and soil scientists, to include soil yeasts in future studies. PMID:29365211
Electron transport chain in a thermotolerant yeast.

PubMed

Mejía-Barajas, Jorge A; Martínez-Mora, José A; Salgado-Garciglia, Rafael; Noriega-Cisneros, Ruth; Ortiz-Avila, Omar; Cortés-Rojo, Christian; Saavedra-Molina, Alfredo

2017-04-01

Yeasts capable of growing and surviving at high temperatures are regarded as thermotolerant. For appropriate functioning of cellular processes and cell survival, the maintenance of an optimal redox state is critical of reducing and oxidizing species. We studied mitochondrial functions of the thermotolerant Kluyveromyces marxianus SLP1 and the mesophilic OFF1 yeasts, through the evaluation of its mitochondrial membrane potential (ΔΨ m ), ATPase activity, electron transport chain (ETC) activities, alternative oxidase activity, lipid peroxidation. Mitochondrial membrane potential and the cytoplasmic free Ca 2+ ions (Ca 2+ cyt) increased in the SLP1 yeast when exposed to high temperature, compared with the mesophilic yeast OFF1. ATPase activity in the mesophilic yeast diminished 80% when exposed to 40° while the thermotolerant SLP1 showed no change, despite an increase in the mitochondrial lipid peroxidation. The SLP1 thermotolerant yeast exposed to high temperature showed a diminution of 33% of the oxygen consumption in state 4. The uncoupled state 3 of oxygen consumption did not change in the mesophilic yeast when it had an increase of temperature, whereas in the thermotolerant SLP1 yeast resulted in an increase of 2.5 times when yeast were grown at 30 o , while a decrease of 51% was observed when it was exposed to high temperature. The activities of the ETC complexes were diminished in the SLP1 when exposed to high temperature, but also it was distinguished an alternative oxidase activity. Our results suggest that the mitochondria state, particularly ETC state, is an important characteristic of the thermotolerance of the SLP1 yeast strain.
Regulatory networks and connected components of the neutral space. A look at functional islands

NASA Astrophysics Data System (ADS)

Boldhaus, G.; Klemm, K.

2010-09-01

The functioning of a living cell is largely determined by the structure of its regulatory network, comprising non-linear interactions between regulatory genes. An important factor for the stability and evolvability of such regulatory systems is neutrality - typically a large number of alternative network structures give rise to the necessary dynamics. Here we study the discretized regulatory dynamics of the yeast cell cycle [Li et al., PNAS, 2004] and the set of networks capable of reproducing it, which we call functional. Among these, the empirical yeast wildtype network is close to optimal with respect to sparse wiring. Under point mutations, which establish or delete single interactions, the neutral space of functional networks is fragmented into ≈ 4.7 × 108 components. One of the smaller ones contains the wildtype network. On average, functional networks reachable from the wildtype by mutations are sparser, have higher noise resilience and fewer fixed point attractors as compared with networks outside of this wildtype component.
The Semantic Network at Work and Rest: Differential Connectivity of Anterior Temporal Lobe Subregions.

PubMed

Jackson, Rebecca L; Hoffman, Paul; Pobric, Gorana; Lambon Ralph, Matthew A

2016-02-03

The anterior temporal lobe (ATL) makes a critical contribution to semantic cognition. However, the functional connectivity of the ATL and the functional network underlying semantic cognition has not been elucidated. In addition, subregions of the ATL have distinct functional properties and thus the potential differential connectivity between these subregions requires investigation. We explored these aims using both resting-state and active semantic task data in humans in combination with a dual-echo gradient echo planar imaging (EPI) paradigm designed to ensure signal throughout the ATL. In the resting-state analysis, the ventral ATL (vATL) and anterior middle temporal gyrus (MTG) were shown to connect to areas responsible for multimodal semantic cognition, including bilateral ATL, inferior frontal gyrus, medial prefrontal cortex, angular gyrus, posterior MTG, and medial temporal lobes. In contrast, the anterior superior temporal gyrus (STG)/superior temporal sulcus was connected to a distinct set of auditory and language-related areas, including bilateral STG, precentral and postcentral gyri, supplementary motor area, supramarginal gyrus, posterior temporal cortex, and inferior and middle frontal gyri. Complementary analyses of functional connectivity during an active semantic task were performed using a psychophysiological interaction (PPI) analysis. The PPI analysis highlighted the same semantic regions suggesting a core semantic network active during rest and task states. This supports the necessity for semantic cognition in internal processes occurring during rest. The PPI analysis showed additional connectivity of the vATL to regions of occipital and frontal cortex. These areas strongly overlap with regions found to be sensitive to executively demanding, controlled semantic processing. Previous studies have shown that semantic cognition depends on subregions of the anterior temporal lobe (ATL). However, the network of regions functionally connected to these
The Semantic Network at Work and Rest: Differential Connectivity of Anterior Temporal Lobe Subregions

PubMed Central

Jackson, Rebecca L.; Hoffman, Paul; Pobric, Gorana

2016-01-01

The anterior temporal lobe (ATL) makes a critical contribution to semantic cognition. However, the functional connectivity of the ATL and the functional network underlying semantic cognition has not been elucidated. In addition, subregions of the ATL have distinct functional properties and thus the potential differential connectivity between these subregions requires investigation. We explored these aims using both resting-state and active semantic task data in humans in combination with a dual-echo gradient echo planar imaging (EPI) paradigm designed to ensure signal throughout the ATL. In the resting-state analysis, the ventral ATL (vATL) and anterior middle temporal gyrus (MTG) were shown to connect to areas responsible for multimodal semantic cognition, including bilateral ATL, inferior frontal gyrus, medial prefrontal cortex, angular gyrus, posterior MTG, and medial temporal lobes. In contrast, the anterior superior temporal gyrus (STG)/superior temporal sulcus was connected to a distinct set of auditory and language-related areas, including bilateral STG, precentral and postcentral gyri, supplementary motor area, supramarginal gyrus, posterior temporal cortex, and inferior and middle frontal gyri. Complementary analyses of functional connectivity during an active semantic task were performed using a psychophysiological interaction (PPI) analysis. The PPI analysis highlighted the same semantic regions suggesting a core semantic network active during rest and task states. This supports the necessity for semantic cognition in internal processes occurring during rest. The PPI analysis showed additional connectivity of the vATL to regions of occipital and frontal cortex. These areas strongly overlap with regions found to be sensitive to executively demanding, controlled semantic processing. SIGNIFICANCE STATEMENT Previous studies have shown that semantic cognition depends on subregions of the anterior temporal lobe (ATL). However, the network of regions
Exploring Wound-Healing Genomic Machinery with a Network-Based Approach

PubMed Central

Vitali, Francesca; Marini, Simone; Balli, Martina; Grosemans, Hanne; Sampaolesi, Maurilio; Lussier, Yves A.; Cusella De Angelis, Maria Gabriella; Bellazzi, Riccardo

2017-01-01

The molecular mechanisms underlying tissue regeneration and wound healing are still poorly understood despite their importance. In this paper we develop a bioinformatics approach, combining biology and network theory to drive experiments for better understanding the genetic underpinnings of wound healing mechanisms and for selecting potential drug targets. We start by selecting literature-relevant genes in murine wound healing, and inferring from them a Protein-Protein Interaction (PPI) network. Then, we analyze the network to rank wound healing-related genes according to their topological properties. Lastly, we perform a procedure for in-silico simulation of a treatment action in a biological pathway. The findings obtained by applying the developed pipeline, including gene expression analysis, confirms how a network-based bioinformatics method is able to prioritize candidate genes for in vitro analysis, thus speeding up the understanding of molecular mechanisms and supporting the discovery of potential drug targets. PMID:28635674
In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein-protein interaction networks.

PubMed

Folador, Edson Luiz; de Carvalho, Paulo Vinícius Sanches Daltro; Silva, Wanderson Marques; Ferreira, Rafaela Salgado; Silva, Artur; Gromiha, Michael; Ghosh, Preetam; Barh, Debmalya; Azevedo, Vasco; Röttger, Richard

2016-11-04

Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis. Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous. The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing according wet-lab studies. The non-host homologous essential proteins are attractive targets for therapeutic and diagnostic proposes. They allow for searching of small molecule inhibitors of binding interactions enabling modern drug discovery. Overall, the predicted Cp PPI networks form a valuable and versatile tool for researchers interested in Corynebacterium pseudotuberculosis.
Yeasts in floral nectar: a quantitative survey

PubMed Central

Herrera, Carlos M.; de Vega, Clara; Canto, Azucena; Pozo, María I.

2009-01-01

Background and Aims One peculiarity of floral nectar that remains relatively unexplored from an ecological perspective is its role as a natural habitat for micro-organisms. This study assesses the frequency of occurrence and abundance of yeast cells in floral nectar of insect-pollinated plants from three contrasting plant communities on two continents. Possible correlations between interspecific differences in yeast incidence and pollinator composition are also explored. Methods The study was conducted at three widely separated areas, two in the Iberian Peninsula (Spain) and one in the Yucatán Peninsula (Mexico). Floral nectar samples from 130 species (37–63 species per region) in 44 families were examined microscopically for the presence of yeast cells. For one of the Spanish sites, the relationship across species between incidence of yeasts in nectar and the proportion of flowers visited by each of five major pollinator categories was also investigated. Key Results Yeasts occurred regularly in the floral nectar of many species, where they sometimes reached extraordinary densities (up to 4 × 105 cells mm−3). Depending on the region, between 32 and 44 % of all nectar samples contained yeasts. Yeast cell densities in the order of 104 cells mm−3 were commonplace, and densities >105 cells mm−3 were not rare. About one-fifth of species at each site had mean yeast cell densities >104 cells mm−3. Across species, yeast frequency and abundance were directly correlated with the proportion of floral visits by bumble-bees, and inversely with the proportion of visits by solitary bees. Conclusions Incorporating nectar yeasts into the scenario of plant–pollinator interactions opens up a number of intriguing avenues for research. In addition, with yeasts being as ubiquitous and abundant in floral nectars as revealed by this study, and given their astounding metabolic versatility, studies focusing on nectar chemical features should carefully control for the presence
Integrating high-throughput genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis

PubMed Central

Vizeacoumar, Franco J.; van Dyk, Nydia; S.Vizeacoumar, Frederick; Cheung, Vincent; Li, Jingjing; Sydorskyy, Yaroslav; Case, Nicolle; Li, Zhijian; Datti, Alessandro; Nislow, Corey; Raught, Brian; Zhang, Zhaolei; Frey, Brendan; Bloom, Kerry

2010-01-01

We describe the application of a novel screening approach that combines automated yeast genetics, synthetic genetic array (SGA) analysis, and a high-content screening (HCS) system to examine mitotic spindle morphogenesis. We measured numerous spindle and cellular morphological parameters in thousands of single mutants and corresponding sensitized double mutants lacking genes known to be involved in spindle function. We focused on a subset of genes that appear to define a highly conserved mitotic spindle disassembly pathway, which is known to involve Ipl1p, the yeast aurora B kinase, as well as the cell cycle regulatory networks mitotic exit network (MEN) and fourteen early anaphase release (FEAR). We also dissected the function of the kinetochore protein Mcm21p, showing that sumoylation of Mcm21p regulates the enrichment of Ipl1p and other chromosomal passenger proteins to the spindle midzone to mediate spindle disassembly. Although we focused on spindle disassembly in a proof-of-principle study, our integrated HCS-SGA method can be applied to virtually any pathway, making it a powerful means for identifying specific cellular functions. PMID:20065090
The maternal immune activation (MIA) model of schizophrenia produces pre-pulse inhibition (PPI) deficits in both juvenile and adult rats but these effects are not associated with maternal weight loss.

PubMed

Wolff, Amy R; Bilkey, David K

2010-12-01

The developmental onset of deficits in sensorimotor-gating was examined in the maternal immune activation (MIA) animal model of schizophrenia. Pre-pulse inhibition (PPI) deficits were evident in juvenile MIA rats. This parallels the sensorimotor-gating deficits observed in groups at high-risk of schizophrenia. PPI deficits were independent of maternal weight loss following the MIA manipulation, suggesting that this measure may not be a useful marker of treatment efficacy. Copyright (c) 2010 Elsevier B.V. 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
Interactions between Drosophila and its natural yeast symbionts—Is Saccharomyces cerevisiae a good model for studying the fly-yeast relationship?

PubMed Central

Hoang, Don; Kopp, Artyom

2015-01-01

Yeasts play an important role in the biology of the fruit fly, Drosophila melanogaster. In addition to being a valuable source of nutrition, yeasts affect D. melanogaster behavior and interact with the host immune system. Most experiments investigating the role of yeasts in D. melanogaster biology use the baker’s yeast, Saccharomyces cerevisiae. However, S. cerevisiae is rarely found with natural populations of D. melanogaster or other Drosophila species. Moreover, the strain of S. cerevisiae used most often in D. melanogaster experiments is a commercially and industrially important strain that, to the best of our knowledge, was not isolated from flies. Since disrupting natural host–microbe interactions can have profound effects on host biology, the results from D. melanogaster–S. cerevisiae laboratory experiments may not be fully representative of host–microbe interactions in nature. In this study, we explore the D. melanogaster-yeast relationship using five different strains of yeast that were isolated from wild Drosophila populations. Ingested live yeasts have variable persistence in the D. melanogaster gastrointestinal tract. For example, Hanseniaspora occidentalis persists relative to S. cerevisiae, while Brettanomyces naardenensis is removed. Despite these differences in persistence relative to S. cerevisiae, we find that all yeasts decrease in total abundance over time. Reactive oxygen species (ROS) are an important component of the D. melanogaster anti-microbial response and can inhibit S. cerevisiae growth in the intestine. To determine if sensitivity to ROS explains the differences in yeast persistence, we measured yeast growth in the presence and absence of hydrogen peroxide. We find that B. naardenesis is completely inhibited by hydrogen peroxide, while H. occidentalis is not, which is consistent with yeast sensitivity to ROS affecting persistence within the D. melanogaster gastrointestinal tract. We also compared the feeding preference of D
Interactions between Drosophila and its natural yeast symbionts-Is Saccharomyces cerevisiae a good model for studying the fly-yeast relationship?

PubMed

Hoang, Don; Kopp, Artyom; Chandler, James Angus

2015-01-01

Yeasts play an important role in the biology of the fruit fly, Drosophila melanogaster. In addition to being a valuable source of nutrition, yeasts affect D. melanogaster behavior and interact with the host immune system. Most experiments investigating the role of yeasts in D. melanogaster biology use the baker's yeast, Saccharomyces cerevisiae. However, S. cerevisiae is rarely found with natural populations of D. melanogaster or other Drosophila species. Moreover, the strain of S. cerevisiae used most often in D. melanogaster experiments is a commercially and industrially important strain that, to the best of our knowledge, was not isolated from flies. Since disrupting natural host-microbe interactions can have profound effects on host biology, the results from D. melanogaster-S. cerevisiae laboratory experiments may not be fully representative of host-microbe interactions in nature. In this study, we explore the D. melanogaster-yeast relationship using five different strains of yeast that were isolated from wild Drosophila populations. Ingested live yeasts have variable persistence in the D. melanogaster gastrointestinal tract. For example, Hanseniaspora occidentalis persists relative to S. cerevisiae, while Brettanomyces naardenensis is removed. Despite these differences in persistence relative to S. cerevisiae, we find that all yeasts decrease in total abundance over time. Reactive oxygen species (ROS) are an important component of the D. melanogaster anti-microbial response and can inhibit S. cerevisiae growth in the intestine. To determine if sensitivity to ROS explains the differences in yeast persistence, we measured yeast growth in the presence and absence of hydrogen peroxide. We find that B. naardenesis is completely inhibited by hydrogen peroxide, while H. occidentalis is not, which is consistent with yeast sensitivity to ROS affecting persistence within the D. melanogaster gastrointestinal tract. We also compared the feeding preference of D
Mechanics and morphogenesis of fission yeast cells.

PubMed

Davì, Valeria; Minc, Nicolas

2015-12-01

The integration of biochemical and biomechanical elements is at the heart of morphogenesis. While animal cells are relatively soft objects which shape and mechanics is mostly regulated by cytoskeletal networks, walled cells including those of plants, fungi and bacteria are encased in a rigid cell wall which resist high internal turgor pressure. How these particular mechanical properties may influence basic cellular processes, such as growth, shape and division remains poorly understood. Recent work using the model fungal cell fission yeast, Schizosaccharomyces pombe, highlights important contribution of cell mechanics to various morphogenesis processes. We envision this genetically tractable system to serve as a novel standard for the mechanobiology of walled cell. Copyright © 2015 Elsevier Ltd. All rights reserved.
Evaluation of Automated Yeast Identification System

NASA Technical Reports Server (NTRS)

McGinnis, M. R.

1996-01-01

One hundred and nine teleomorphic and anamorphic yeast isolates representing approximately 30 taxa were used to evaluate the accuracy of the Biolog yeast identification system. Isolates derived from nomenclatural types, environmental, and clinica isolates of known identity were tested in the Biolog system. Of the isolates tested, 81 were in the Biolog database. The system correctly identified 40, incorrectly identified 29, and was unable to identify 12. Of the 28 isolates not in the database, 18 were given names, whereas 10 were not. The Biolog yeast identification system is inadequate for the identification of yeasts originating from the environment during space program activities.
New scaling relation for information transfer in biological networks

PubMed Central

Kim, Hyunju; Davies, Paul; Walker, Sara Imari

2015-01-01

We quantify characteristics of the informational architecture of two representative biological networks: the Boolean network model for the cell-cycle regulatory network of the fission yeast Schizosaccharomyces pombe (Davidich et al. 2008 PLoS ONE 3, e1672 (doi:10.1371/journal.pone.0001672)) and that of the budding yeast Saccharomyces cerevisiae (Li et al. 2004 Proc. Natl Acad. Sci. USA 101, 4781–4786 (doi:10.1073/pnas.0305937101)). We compare our results for these biological networks with the same analysis performed on ensembles of two different types of random networks: Erdös–Rényi and scale-free. We show that both biological networks share features in common that are not shared by either random network ensemble. In particular, the biological networks in our study process more information than the random networks on average. Both biological networks also exhibit a scaling relation in information transferred between nodes that distinguishes them from random, where the biological networks stand out as distinct even when compared with random networks that share important topological properties, such as degree distribution, with the biological network. We show that the most biologically distinct regime of this scaling relation is associated with a subset of control nodes that regulate the dynamics and function of each respective biological network. Information processing in biological networks is therefore interpreted as an emergent property of topology (causal structure) and dynamics (function). Our results demonstrate quantitatively how the informational architecture of biologically evolved networks can distinguish them from other classes of network architecture that do not share the same informational properties. PMID:26701883
Effects of cognitive-behavioural therapy (CBT) and positive psychological intervention (PPI) on female offenders with psychological distress in Hong Kong.

PubMed

Mak, Vivian W M; Chan, Calais K Y

2018-04-01

Despite rapid growth in the female prison population, there is little research on effectiveness of psychological interventions for them. To test the hypotheses that (1) each of two psychological interventions administered separately - cognitive behavioural therapy (CBT) or positive psychology intervention (PPI) - would be more effective than 'treatment-as-usual' alone in reducing psychological distress and enhancing psychological well-being; (2) outcomes would differ according to intervention; and (3) combining the interventions would be more effective than delivering either alone. We recruited 40 women in a special Hong Kong prison unit for female offenders with psychological distress. Half of them received eight sessions of CBT followed by eight sessions of PPI; the other half received the same interventions in the reverse order. We recruited another 35 women who received only 'treatment as usual' (TAU) in the same unit. We used various clinical scales to assess the women's psychological distress or well-being before and after the interventions or at similar time points for the comparison women. All intervention group women showed a significant reduction in psychological distress and enhancement in psychological well-being after each intervention alone compared to the TAU women. There were no significant differences between CBT and PPI in this respect. Receiving both treatments, however, did yield significantly more improvement than either intervention alone in reducing depressive thoughts and enhancing global judgement of life satisfaction, self-perceived strengths and hopeful thinking style. Our findings provide preliminary empirical support for the effectiveness of psychological interventions with psychologically distressed women in prison. It would be important now to conduct a full, randomised trial to determine optimal length and combinations of treatment. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Genomics and the making of yeast biodiversity.

PubMed

Hittinger, Chris Todd; Rokas, Antonis; Bai, Feng-Yan; Boekhout, Teun; Gonçalves, Paula; Jeffries, Thomas W; Kominek, Jacek; Lachance, Marc-André; Libkind, Diego; Rosa, Carlos A; Sampaio, José Paulo; Kurtzman, Cletus P

2015-12-01

Yeasts are unicellular fungi that do not form fruiting bodies. Although the yeast lifestyle has evolved multiple times, most known species belong to the subphylum Saccharomycotina (syn. Hemiascomycota, hereafter yeasts). This diverse group includes the premier eukaryotic model system, Saccharomyces cerevisiae; the common human commensal and opportunistic pathogen, Candida albicans; and over 1000 other known species (with more continuing to be discovered). Yeasts are found in every biome and continent and are more genetically diverse than angiosperms or chordates. Ease of culture, simple life cycles, and small genomes (∼10-20Mbp) have made yeasts exceptional models for molecular genetics, biotechnology, and evolutionary genomics. Here we discuss recent developments in understanding the genomic underpinnings of the making of yeast biodiversity, comparing and contrasting natural and human-associated evolutionary processes. Only a tiny fraction of yeast biodiversity and metabolic capabilities has been tapped by industry and science. Expanding the taxonomic breadth of deep genomic investigations will further illuminate how genome function evolves to encode their diverse metabolisms and ecologies. Copyright © 2015 Elsevier Ltd. All rights reserved.
Accelerating Yeast Prion Biology using Droplet Microfluidics

NASA Astrophysics Data System (ADS)

Ung, Lloyd; Rotem, Assaf; Jarosz, Daniel; Datta, Manoshi; Lindquist, Susan; Weitz, David

2012-02-01

Prions are infectious proteins in a misfolded form, that can induce normal proteins to take the misfolded state. Yeast prions are relevant, as a model of human prion diseases, and interesting from an evolutionary standpoint. Prions may also be a form of epigenetic inheritance, which allow yeast to adapt to stressful conditions at rates exceeding those of random mutations and propagate that adaptation to their offspring. Encapsulation of yeast in droplet microfluidic devices enables high-throughput measurements with single cell resolution, which would not be feasible using bulk methods. Millions of populations of yeast can be screened to obtain reliable measurements of prion induction and loss rates. The population dynamics of clonal yeast, when a fraction of the cells are prion expressing, can be elucidated. Furthermore, the mechanism by which certain strains of bacteria induce yeast to express prions in the wild can be deduced. Integrating the disparate fields of prion biology and droplet microfluidics reveals a more complete picture of how prions may be more than just diseases and play a functional role in yeast.

PICKLE 2.0: A human protein-protein interaction meta-database employing data integration via genetic information ontology

PubMed Central

Gioutlakis, Aris; Klapa, Maria I.

2017-01-01

It has been acknowledged that source databases recording experimentally supported human protein-protein interactions (PPIs) exhibit limited overlap. Thus, the reconstruction of a comprehensive PPI network requires appropriate integration of multiple heterogeneous primary datasets, presenting the PPIs at various genetic reference levels. Existing PPI meta-databases perform integration via normalization; namely, PPIs are merged after converted to a certain target level. Hence, the node set of the integrated network depends each time on the number and type of the combined datasets. Moreover, the irreversible a priori normalization process hinders the identification of normalization artifacts in the integrated network, which originate from the nonlinearity characterizing the genetic information flow. PICKLE (Protein InteraCtion KnowLedgebasE) 2.0 implements a new architecture for this recently introduced human PPI meta-database. Its main novel feature over the existing meta-databases is its approach to primary PPI dataset integration via genetic information ontology. Building upon the PICKLE principles of using the reviewed human complete proteome (RHCP) of UniProtKB/Swiss-Prot as the reference protein interactor set, and filtering out protein interactions with low probability of being direct based on the available evidence, PICKLE 2.0 first assembles the RHCP genetic information ontology network by connecting the corresponding genes, nucleotide sequences (mRNAs) and proteins (UniProt entries) and then integrates PPI datasets by superimposing them on the ontology network without any a priori transformations. Importantly, this process allows the resulting heterogeneous integrated network to be reversibly normalized to any level of genetic reference without loss of the original information, the latter being used for identification of normalization biases, and enables the appraisal of potential false positive interactions through PPI source database cross-checking. The
[Groups and sources of yeasts in house dust].

PubMed

Glushakova, A M; Zheltikova, T M; Chernov, I Iu

2004-01-01

House dust contains bacteria, mycelial fungi, microarthropods, and yeasts. The house dust samples collected in 25 apartments in Moscow and the Moscow region were found to contain yeasts belonging to the genera Candida, Cryptococcus, Debaryomyces, Rhodotorula, Sporobolomyces, and Trichosporon. The most frequently encountered microorganisms were typical epiphytic yeasts, such as Cryptococcus diffluens and Rhodotorula mucilaginosa, which are capable of long-term preservation in an inactive state. The direct source of epiphytic yeasts occurring in the house dust might be the indoor plants, which were contaminated with these yeasts, albeit to a lesser degree than outdoor plants. Along with the typical epiphytic yeasts, the house dust contained the opportunistic yeast pathogens Candida catenulata, C. guillermondii, C. haemulonii, C. rugosa, and C. tropicalis, which are known as the causal agents of candidiasis. We failed to reveal any correlation between the abundance of particular yeast species in the house dust, residential characteristics, and the atopic dermatitis of the inhabitants.
Genome-wide bisulfite sensitivity profiling of yeast suggests bisulfite inhibits transcription.

PubMed

Segovia, Romulo; Mathew, Veena; Tam, Annie S; Stirling, Peter C

2017-09-01

Bisulfite, in the form of sodium bisulfite or metabisulfite, is used commercially as a food preservative. Bisulfite is used in the laboratory as a single-stranded DNA mutagen in epigenomic analyses of DNA methylation. Recently it has also been used on whole yeast cells to induce mutations in exposed single-stranded regions in vivo. To understand the effects of bisulfite on live cells we conducted a genome-wide screen for bisulfite sensitive mutants in yeast. Screening the deletion mutant array, and collections of essential gene mutants we define a genetic network of bisulfite sensitive mutants. Validation of screen hits revealed hyper-sensitivity of transcription and RNA processing mutants, rather than DNA repair pathways and follow-up analyses support a role in perturbation of RNA transactions. We propose a model in which bisulfite-modified nucleotides may interfere with transcription or RNA metabolism when used in vivo. Copyright © 2017 Elsevier B.V. All rights reserved.
Transcriptional Regulatory Networks in Saccharomyces cerevisiae

NASA Astrophysics Data System (ADS)

Lee, Tong Ihn; Rinaldi, Nicola J.; Robert, François; Odom, Duncan T.; Bar-Joseph, Ziv; Gerber, Georg K.; Hannett, Nancy M.; Harbison, Christopher T.; Thompson, Craig M.; Simon, Itamar; Zeitlinger, Julia; Jennings, Ezra G.; Murray, Heather L.; Gordon, D. Benjamin; Ren, Bing; Wyrick, John J.; Tagne, Jean-Bosco; Volkert, Thomas L.; Fraenkel, Ernest; Gifford, David K.; Young, Richard A.

2002-10-01

We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.
Genome-wide protein-protein interactions and protein function exploration in cyanobacteria

PubMed Central

Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

2015-01-01

Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and “interologs” in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033
Genomics and the making of yeast biodiversity

USDA-ARS?s Scientific Manuscript database

Yeasts are unicellular fungi that do not form fruiting bodies. Although the yeast lifestyle has evolved multiple times, most known species belong to the subphylum Saccharomycotina (syn. Hemiascomycota, hereafter yeasts). This diverse group includes the premier eukaryotic model system, Saccharomyces ...
Network methods to support user involvement in qualitative data analyses: an introduction to Participatory Theme Elicitation.

PubMed

Best, Paul; Badham, Jennifer; Corepal, Rekesh; O'Neill, Roisin F; Tully, Mark A; Kee, Frank; Hunter, Ruth F

2017-11-23

While Patient and Public Involvement (PPI) is encouraged throughout the research process, engagement is typically limited to intervention design and post-analysis stages. There are few approaches to participatory data analyses within complex health interventions. Using qualitative data from a feasibility randomised controlled trial (RCT), this proof-of-concept study tests the value of a new approach to participatory data analysis called Participatory Theme Elicitation (PTE). Forty excerpts were given to eight members of a youth advisory PPI panel to sort into piles based on their perception of related thematic content. Using algorithms to detect communities in networks, excerpts were then assigned to a thematic cluster that combined the panel members' perspectives. Network analysis techniques were also used to identify key excerpts in each grouping that were then further explored qualitatively. While PTE analysis was, for the most part, consistent with the researcher-led analysis, young people also identified new emerging thematic content. PTE appears promising for encouraging user led identification of themes arising from qualitative data collected during complex interventions. Further work is required to validate and extend this method. ClinicalTrials.gov, ID: NCT02455986 . Retrospectively Registered on 21 May 2015.
Negative Effect of Proton-pump Inhibitors (PPIs) on Helicobacter pylori Growth, Morphology, and Urease Test and Recovery after PPI Removal--An In vitro Study.

PubMed

Saniee, Parastoo; Shahreza, Somayeh; Siavoshi, Farideh

2016-04-01

Proton-pump inhibitor (PPI) consumption does lead to false-negative results of Helicobacter pylori diagnostic tests such as biopsy culture and rapid urease test (RUT). Helicobacter pylori isolates from 112 dyspeptic patients with (56.5%) or without (43.5%) PPI consumption were recruited for examining the negative effects of omeprazole (OMP), lansoprazole (LPZ), and pantoprazole (PAN) on H. pylori viability, morphology, and urease, in vitro. The effect of a sublethal concentration of OMP on bacterial features and their recovery after removal of OMP was also assessed. Of 112 culture-positive gastric biopsies, 87.5% were RUT positive and 12.5% RUT negative. There was a significant correlation between negative RUT results and PPI consumption (p < .05). OMP (minimum inhibitory concentration, MIC 32 μg/mL) and LPZ (MIC 8 μg/mL) inhibited the growth of 78.6% of H. pylori isolates. OMP and LPZ inhibited urease of 90.3% of isolates between 0 and 40 minutes and 54.4% between 20 and 40 minutes, respectively. PAN did not inhibit H. pylori growth and urease. Three 3-day (9 days) consecutive subcultures of H. pylori on brucella blood agar (BBA) supplemented with OMP resulted in reduced bacterial viability (1+), compared with control (4+), change of spiral morphology to coccoid, and reduction in pink color intensity in urea agar. Bacterial growth (1+), morphology, and urease test did not improve after the first 3-day and second 3-day (6 days) subcultures on BBA. However, relative recovery occurred after the third 3-day (9 days) subculture and complete recovery was observed after the fourth 3-day (12 days) subculture, as confluent growth (4+), 100% spiral cells, and strong urease test. Proton-pump Inhibitors exert transient negative effects on H. pylori viability, morphology, and urease test. Accordingly, cessation of PPI consumption at least 12 days before endoscopy could help avoiding false-negative results of H. pylori diagnostic tests. © 2015 John Wiley & Sons Ltd.
21 CFR 172.590 - Yeast-malt sprout extract.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Yeast-malt sprout extract. 172.590 Section 172.590... Substances § 172.590 Yeast-malt sprout extract. Yeast-malt sprout extract, as described in this section, may... produced by partial hydrolysis of yeast extract (derived from Saccharomyces cereviseae, Saccharomyces...
Yeasts Diversity in Fermented Foods and Beverages

NASA Astrophysics Data System (ADS)

Tamang, Jyoti Prakash; Fleet, Graham H.

People across the world have learnt to culture and use the essential microorganisms for production of fermented foods and alcoholic beverages. A fermented food is produced either spontaneously or by adding mixed/pure starter culture(s). Yeasts are among the essential functional microorganisms encountered in many fermented foods, and are commercially used in production of baker's yeast, breads, wine, beer, cheese, etc. In Asia, moulds are predominant followed by amylolytic and alcohol-producing yeasts in the fermentation processes, whereas in Africa, Europe, Australia and America, fermented products are prepared exclusively using bacteria or bacteria-yeasts mixed cultures. This chapter would focus on the varieties of fermented foods and alcoholic beverages produced by yeasts, their microbiology and role in food fermentation, widely used commercial starters (pilot production, molecular aspects), production technology of some common commercial fermented foods and alcoholic beverages, toxicity and food safety using yeasts cultures and socio-economy
Genetics of Yeasts

NASA Astrophysics Data System (ADS)

Querol, Amparo; Fernández-Espinar, M. Teresa; Belloch, Carmela

The use of yeasts in biotechnology processes dates back to ancient days. Before 7000 BC, beer was produced in Sumeria. Wine was made in Assyria in 3500 BC, and ancient Rome had over 250 bakeries, which were making leavened bread by 100 BC. And milk has been made into Kefyr and Koumiss in Asia for many centuries (Demain, Phaff, & Kurtzman, 1999). However, the importance of yeast in the food and beverage industries was only realized about 1860, when their role in food manufacturing became evident.
21 CFR 172.590 - Yeast-malt sprout extract.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Yeast-malt sprout extract. 172.590 Section 172.590... CONSUMPTION Flavoring Agents and Related Substances § 172.590 Yeast-malt sprout extract. Yeast-malt sprout... prescribed conditions: (a) The additive is produced by partial hydrolysis of yeast extract (derived from...
21 CFR 172.590 - Yeast-malt sprout extract.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 3 2013-04-01 2013-04-01 false Yeast-malt sprout extract. 172.590 Section 172.590... CONSUMPTION Flavoring Agents and Related Substances § 172.590 Yeast-malt sprout extract. Yeast-malt sprout... prescribed conditions: (a) The additive is produced by partial hydrolysis of yeast extract (derived from...
21 CFR 172.590 - Yeast-malt sprout extract.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 3 2012-04-01 2012-04-01 false Yeast-malt sprout extract. 172.590 Section 172.590... CONSUMPTION Flavoring Agents and Related Substances § 172.590 Yeast-malt sprout extract. Yeast-malt sprout... prescribed conditions: (a) The additive is produced by partial hydrolysis of yeast extract (derived from...
21 CFR 172.590 - Yeast-malt sprout extract.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 3 2011-04-01 2011-04-01 false Yeast-malt sprout extract. 172.590 Section 172.590... CONSUMPTION Flavoring Agents and Related Substances § 172.590 Yeast-malt sprout extract. Yeast-malt sprout... prescribed conditions: (a) The additive is produced by partial hydrolysis of yeast extract (derived from...
Yeasts in sustainable bioethanol production: A review.

PubMed

Mohd Azhar, Siti Hajar; Abdulla, Rahmath; Jambo, Siti Azmah; Marbawi, Hartinie; Gansau, Jualang Azlan; Mohd Faik, Ainol Azifa; Rodrigues, Kenneth Francis

2017-07-01

Bioethanol has been identified as the mostly used biofuel worldwide since it significantly contributes to the reduction of crude oil consumption and environmental pollution. It can be produced from various types of feedstocks such as sucrose, starch, lignocellulosic and algal biomass through fermentation process by microorganisms. Compared to other types of microoganisms, yeasts especially Saccharomyces cerevisiae is the common microbes employed in ethanol production due to its high ethanol productivity, high ethanol tolerance and ability of fermenting wide range of sugars. However, there are some challenges in yeast fermentation which inhibit ethanol production such as high temperature, high ethanol concentration and the ability to ferment pentose sugars. Various types of yeast strains have been used in fermentation for ethanol production including hybrid, recombinant and wild-type yeasts. Yeasts can directly ferment simple sugars into ethanol while other type of feedstocks must be converted to fermentable sugars before it can be fermented to ethanol. The common processes involves in ethanol production are pretreatment, hydrolysis and fermentation. Production of bioethanol during fermentation depends on several factors such as temperature, sugar concentration, pH, fermentation time, agitation rate, and inoculum size. The efficiency and productivity of ethanol can be enhanced by immobilizing the yeast cells. This review highlights the different types of yeast strains, fermentation process, factors affecting bioethanol production and immobilization of yeasts for better bioethanol production.
Yeast and Mammalian Metallothioneins Functionally Substitute for Yeast Copper-Zinc Superoxide Dismutase

NASA Astrophysics Data System (ADS)

Tamai, Katherine T.; Gralla, Edith B.; Ellerby, Lisa M.; Valentine, Joan S.; Thiele, Dennis J.

1993-09-01

Copper-zinc superoxide dismutase catalyzes the disproportionation of superoxide anion to hydrogen peroxide and dioxygen and is thought to play an important role in protecting cells from oxygen toxicity. Saccharomyces cerevisiae strains lacking copper-zinc superoxide dismutase, which is encoded by the SOD1 gene, are sensitive to oxidative stress and exhibit a variety of growth defects including hypersensitivity to dioxygen and to superoxide-generating drugs such as paraquat. We have found that in addition to these known phenotypes, SOD1-deletion strains fail to grow on agar containing the respiratory carbon source lactate. We demonstrate here that expression of the yeast or monkey metallothionein proteins in the presence of copper suppresses the lactate growth defect and some other phenotypes associated with SOD1-deletion strains, indicating that copper metallothioneins substitute for copper-zinc superoxide dismutase in vivo to protect cells from oxygen toxicity. Consistent with these results, we show that yeast metallothionein mRNA levels are dramatically elevated under conditions of oxidative stress. Furthermore, in vitro assays demonstrate that yeast metallothionein, purified or from whole-cell extracts, exhibits copper-dependent antioxidant activity. Taken together, these data suggest that both yeast and mammalian metallothioneins may play a direct role in the cellular defense against oxidative stress by functioning as antioxidants.
A Molecular Portrait of De Novo Genes in Yeasts.

PubMed

Vakirlis, Nikolaos; Hebert, Alex S; Opulente, Dana A; Achaz, Guillaume; Hittinger, Chris Todd; Fischer, Gilles; Coon, Joshua J; Lafontaine, Ingrid

2018-03-01

New genes, with novel protein functions, can evolve "from scratch" out of intergenic sequences. These de novo genes can integrate the cell's genetic network and drive important phenotypic innovations. Therefore, identifying de novo genes and understanding how the transition from noncoding to coding occurs are key problems in evolutionary biology. However, identifying de novo genes is a difficult task, hampered by the presence of remote homologs, fast evolving sequences and erroneously annotated protein coding genes. To overcome these limitations, we developed a procedure that handles the usual pitfalls in de novo gene identification and predicted the emergence of 703 de novo gene candidates in 15 yeast species from 2 genera whose phylogeny spans at least 100 million years of evolution. We validated 85 candidates by proteomic data, providing new translation evidence for 25 of them through mass spectrometry experiments. We also unambiguously identified the mutations that enabled the transition from noncoding to coding for 30 Saccharomyces de novo genes. We established that de novo gene origination is a widespread phenomenon in yeasts, only a few being ultimately maintained by selection. We also found that de novo genes preferentially emerge next to divergent promoters in GC-rich intergenic regions where the probability of finding a fortuitous and transcribed ORF is the highest. Finally, we found a more than 3-fold enrichment of de novo genes at recombination hot spots, which are GC-rich and nucleosome-free regions, suggesting that meiotic recombination contributes to de novo gene emergence in yeasts.
The YeastGenome app: the Saccharomyces Genome Database at your fingertips.

PubMed

Wong, Edith D; Karra, Kalpana; Hitz, Benjamin C; Hong, Eurie L; Cherry, J Michael

2013-01-01

The Saccharomyces Genome Database (SGD) is a scientific database that provides researchers with high-quality curated data about the genes and gene products of Saccharomyces cerevisiae. To provide instant and easy access to this information on mobile devices, we have developed YeastGenome, a native application for the Apple iPhone and iPad. YeastGenome can be used to quickly find basic information about S. cerevisiae genes and chromosomal features regardless of internet connectivity. With or without network access, you can view basic information and Gene Ontology annotations about a gene of interest by searching gene names and gene descriptions or by browsing the database within the app to find the gene of interest. With internet access, the app provides more detailed information about the gene, including mutant phenotypes, references and protein and genetic interactions, as well as provides hyperlinks to retrieve detailed information by showing SGD pages and views of the genome browser. SGD provides online help describing basic ways to navigate the mobile version of SGD, highlights key features and answers frequently asked questions related to the app. The app is available from iTunes (http://itunes.com/apps/yeastgenome). The YeastGenome app is provided freely as a service to our community, as part of SGD's mission to provide free and open access to all its data and annotations.
Modular synchronization in complex networks.

PubMed

Oh, E; Rho, K; Hong, H; Kahng, B

2005-10-01

We study the synchronization transition (ST) of a modified Kuramoto model on two different types of modular complex networks. It is found that the ST depends on the type of intermodular connections. For the network with decentralized (centralized) intermodular connections, the ST occurs at finite coupling constant (behaves abnormally). Such distinct features are found in the yeast protein interaction network and the Internet, respectively. Moreover, by applying the finite-size scaling analysis to an artificial network with decentralized intermodular connections, we obtain the exponent associated with the order parameter of the ST to be beta approximately 1 different from beta(MF) approximately 1/2 obtained from the scale-free network with the same degree distribution but the absence of modular structure, corresponding to the mean field value.

Experimental Systems to Study Yeast Pexophagy.

PubMed

Yamashita, Shun-Ichi; Oku, Masahide; Sakai, Yasuyoshi; Fujiki, Yukio

2017-01-01

Peroxisome abundance is tightly regulated according to the physiological contexts, through regulations of both proliferation and degradation of the organelles. Here, we describe detailed methods to analyze processes for autophagic degradation of peroxisomes, termed pexophagy, in yeast organisms. The assay systems include a method for biochemical detection of pexophagy completion, and one for microscopic visualization of specialized membrane structures acting in pexophagy. As a model yeast organism utilized in studies of pexophagy, the methylotrophic yeast Komagataella phaffii (Pichia pastoris) is referred to in this chapter and related information on the studies with baker's yeast (Saccharomyces cerevisiae) is also included. The described techniques facilitate elucidation of molecular machineries for pexophagy and understanding of peroxisome-selective autophagic pathways.
Process-driven inference of biological network structure: feasibility, minimality, and multiplicity

NASA Astrophysics Data System (ADS)

Zeng, Chen

2012-02-01

For a given dynamic process, identifying the putative interaction networks to achieve it is the inference problem. In this talk, we address the computational complexity of inference problem in the context of Boolean networks under dominant inhibition condition. The first is a proof that the feasibility problem (is there a network that explains the dynamics?) can be solved in polynomial-time. Second, while the minimality problem (what is the smallest network that explains the dynamics?) is shown to be NP-hard, a simple polynomial-time heuristic is shown to produce near-minimal solutions, as demonstrated by simulation. Third, the theoretical framework also leads to a fast polynomial-time heuristic to estimate the number of network solutions with reasonable accuracy. We will apply these approaches to two simplified Boolean network models for the cell cycle process of budding yeast (Li 2004) and fission yeast (Davidich 2008). Our results demonstrate that each of these networks contains a giant backbone motif spanning all the network nodes that provides the desired main functionality, while the remaining edges in the network form smaller motifs whose role is to confer stability properties rather than provide function. Moreover, we show that the bioprocesses of these two cell cycle models differ considerably from a typically generated process and are intrinsically cascade-like.
From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.
[Distiller Yeasts Producing Antibacterial Peptides].

PubMed

Klyachko, E V; Morozkina, E V; Zaitchik, B Ts; Benevolensky, S V

2015-01-01

A new method of controlling lactic acid bacteria contamination was developed with the use of recombinant Saccharomyces cerevisiae strains producing antibacterial peptides. Genes encoding the antibacterial peptides pediocin and plantaricin with codons preferable for S. cerevisiae were synthesized, and a system was constructed for their secretory expression. Recombinant S. cerevisiae strains producing antibacterial peptides effectively inhibit the growth of Lactobacillus sakei, Pediacoccus pentasaceus, Pediacoccus acidilactici, etc. The application of distiller yeasts producing antibacterial peptides enhances the ethanol yield in cases of bacterial contamination. Recombinant yeasts producing the antibacterial peptides pediocin and plantaricin can successfully substitute the available industrial yeast strains upon ethanol production.
Differential Adsorption of Ochratoxin A and Anthocyanins by Inactivated Yeasts and Yeast Cell Walls during Simulation of Wine Aging

PubMed Central

Petruzzi, Leonardo; Baiano, Antonietta; De Gianni, Antonio; Sinigaglia, Milena; Corbo, Maria Rosaria; Bevilacqua, Antonio

2015-01-01

The adsorption of ochratoxin A (OTA) by yeasts is a promising approach for the decontamination of musts and wines, but some potential competitive or interactive phenomena between mycotoxin, yeast cells, and anthocyanins might modify the intensity of the phenomenon. The aim of this study was to examine OTA adsorption by two strains of Saccharomyces cerevisiae (the wild strain W13, and the commercial isolate BM45), previously inactivated by heat, and a yeast cell wall preparation. Experiments were conducted using Nero di Troia red wine contaminated with 2 μg/L OTA and supplemented with yeast biomass (20 g/L). The samples were analyzed periodically to assess mycotoxin concentration, chromatic characteristics, and total anthocyanins over 84 days of aging. Yeast cell walls revealed the highest OTA-adsorption in comparison to thermally-inactivated cells (50% vs. 43% toxin reduction), whilst no significant differences were found for the amount of adsorbed anthocyanins in OTA-contaminated and control wines. OTA and anthocyanins adsorption were not competitive phenomena. Unfortunately, the addition of yeast cells to wine could cause color loss; therefore, yeast selection should also focus on this trait to select the best strain. PMID:26516913
Made for Each Other: Ascomycete Yeasts and Insects.

PubMed

Blackwell, Meredith

2017-06-01

Fungi and insects live together in the same habitats, and many species of both groups rely on each other for success. Insects, the most successful animals on Earth, cannot produce sterols, essential vitamins, and many enzymes; fungi, often yeast-like in growth form, make up for these deficits. Fungi, however, require constantly replenished substrates because they consume the previous ones, and insects, sometimes lured by volatile fungal compounds, carry fungi directly to a similar, but fresh, habitat. Yeasts associated with insects include Ascomycota (Saccharomycotina, Pezizomycotina) and a few Basidiomycota. Beetles, homopterans, and flies are important associates of fungi, and in turn the insects carry yeasts in pits, specialized external pouches, and modified gut pockets. Some yeasts undergo sexual reproduction within the insect gut, where the genetic diversity of the population is increased, while others, well suited to their stable environment, may never mate. The range of interactions extends from dispersal of yeasts on the surface of insects (e.g., cactus- Drosophila -yeast and ephemeral flower communities, ambrosia beetles, yeasts with holdfasts) to extremely specialized associations of organisms that can no longer exist independently, as in the case of yeast-like symbionts of planthoppers. In a few cases yeast-like fungus-insect associations threaten butterflies and other species with extinction. Technical advances improve discovery and identification of the fungi but also inform our understanding of the evolution of yeast-insect symbioses, although there is much more to learn.
The growth of solar radiated yeast

NASA Technical Reports Server (NTRS)

Kraft, Tyrone

1995-01-01

This researcher plans to determine if solar radiation affects the growth of yeast. The irradiated yeast was obtained from a sample exposed in space during a Space Shuttle flight of September 9-20, 1994. Further, the control groups were held at: (1) Goddard Space Flight Center (GSFC) in Greenbelt, Maryland; and (2) South Dakota School of Mines and Technology. The procedure used was based on the fact that yeast is most often used in consumable baked goods. Therefore, the yeast was incorporated into a basic Betty Crocker bread recipe. Data was collected by placing measured amounts of dough into sample containers with fifteen minute growth in height measurements collected and recorded. This researcher assumed the viability of yeast to be relative to its ability to produce carbon dioxide gas and cause the dough to rise. As all ingredients and surroundings were equal, this researcher assumed the yeast will produce the only significant difference in data collected. This researcher noted the approximate use date on all sample packages to be prior to arrival and experiment date. All dates equal, it was then assumed each would act in a similar manner of response. This assumption will allow for equally correct data collection.
The growth of solar radiated yeast

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

Kraft, T.

This researcher plans to determine if solar radiation affects the growth of yeast. The irradiated yeast was obtained from a sample exposed in space during a Space Shuttle flight of September 9-20, 1994. Further, the control groups were held at: (1) Goddard Space Flight Center (GSFC) in Greenbelt, Maryland; and (2) South Dakota School of Mines and Technology. The procedure used was based on the fact that yeast is most often used in consumable baked goods. Therefore, the yeast was incorporated into a basic Betty Crocker bread recipe. Data was collected by placing measured amounts of dough into sample containersmore » with fifteen minute growth in height measurements collected and recorded. This researcher assumed the viability of yeast to be relative to its ability to produce carbon dioxide gas and cause the dough to rise. As all ingredients and surroundings were equal, this researcher assumed the yeast will produce the only significant difference in data collected. This researcher noted the approximate use date on all sample packages to be prior to arrival and experiment date. All dates equal, it was then assumed each would act in a similar manner of response. This assumption will allow for equally correct data collection.« less
Freeze-drying of yeast cultures.

PubMed

Bond, Chris

2007-01-01

A method is described that allows yeast species to be stored using a variation on the standard freeze-drying method, which employs evaporative cooling in a two-stage process. Yeast cultures are placed in glass ampoules after having been mixed with a lyoprotectant. Primary drying is carried out using a centrifuge head connected to a standard freeze-dryer. Once the centrifuge head is running, air is removed and evaporated liquid is captured in the freeze-dryer. Centrifugation continues for 15 min and primary drying for a further 3 h. The ampoules are constricted using a glass blowing torch. They are then placed on the freeze-dryer manifold for secondary drying under vacuum overnight, using phosphorus pentoxide as a desiccant. The ampoules are sealed and removed from the manifold by melting the constricted section. Although the process causes an initial large drop in viability, further losses after storage are minimal. Yeast strains have remained viable for more than 30 yr when stored using this method and sufficient cells are recovered to produce new working stocks. Although survival rates are strain specific, nearly all National Collection of Yeast Cultures strains covering most yeast genera, have been successfully stored with little or no detectable change in strain characteristics.
Cellular Ubc2/Rad6 E2 ubiquitin-conjugating enzyme facilitates tombusvirus replication in yeast and plants

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

Imura, Yoshiyuki, E-mail: imura@brs.nihon-u.ac.jp; Molho, Melissa; Chuang, Chingkai

Mono- and multi-ubiquitination alters the functions and subcellular localization of many cellular and viral proteins. Viruses can co-opt or actively manipulate the ubiquitin network to support viral processes or suppress innate immunity. Using yeast (Saccharomyces cerevisiae) model host, we show that the yeast Rad6p (radiation sensitive 6) E2 ubiquitin-conjugating enzyme and its plant ortholog, AtUbc2, interact with two tombusviral replication proteins and these E2 ubiquitin-conjugating enzymes could be co-purified with the tombusvirus replicase. We demonstrate that TBSV RNA replication and the mono- and bi-ubiquitination level of p33 is decreased in rad6Δ yeast. However, plasmid-based expression of AtUbc2p could complement bothmore » defects in rad6Δ yeast. Knockdown of UBC2 expression in plants also decreases tombusvirus accumulation and reduces symptom severity, suggesting that Ubc2p is critical for virus replication in plants. We provide evidence that Rad6p is involved in promoting the subversion of Vps23p and Vps4p ESCRT proteins for viral replicase complex assembly. - Highlights: • Tombusvirus p33 replication protein interacts with cellular RAD6/Ubc2 E2 enzymes. • Deletion of RAD6 reduces tombusvirus replication in yeast. • Silencing of UBC2 in plants inhibits tombusvirus replication. • Mono- and bi-ubiquitination of p33 replication protein in yeast and in vitro. • Rad6p promotes the recruitment of cellular ESCRT proteins into the tombusvirus replicase.« less
UDoNC: An Algorithm for Identifying Essential Proteins Based on Protein Domains and Protein-Protein Interaction Networks.

PubMed

Peng, Wei; Wang, Jianxin; Cheng, Yingjiao; Lu, Yu; Wu, Fangxiang; Pan, Yi

2015-01-01

Prediction of essential proteins which are crucial to an organism's survival is important for disease analysis and drug design, as well as the understanding of cellular life. The majority of prediction methods infer the possibility of proteins to be essential by using the network topology. However, these methods are limited to the completeness of available protein-protein interaction (PPI) data and depend on the network accuracy. To overcome these limitations, some computational methods have been proposed. However, seldom of them solve this problem by taking consideration of protein domains. In this work, we first analyze the correlation between the essentiality of proteins and their domain features based on data of 13 species. We find that the proteins containing more protein domain types which rarely occur in other proteins tend to be essential. Accordingly, we propose a new prediction method, named UDoNC, by combining the domain features of proteins with their topological properties in PPI network. In UDoNC, the essentiality of proteins is decided by the number and the frequency of their protein domain types, as well as the essentiality of their adjacent edges measured by edge clustering coefficient. The experimental results on S. cerevisiae data show that UDoNC outperforms other existing methods in terms of area under the curve (AUC). Additionally, UDoNC can also perform well in predicting essential proteins on data of E. coli.
Network Compression as a Quality Measure for Protein Interaction Networks

PubMed Central

Royer, Loic; Reimann, Matthias; Stewart, A. Francis; Schroeder, Michael

2012-01-01

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients. PMID:22719828
The Calcineurin Signaling Network Evolves Via Conserved Kinase–Phosphatase Modules That Transcend Substrate Identity

PubMed Central

Bodenmiller, Bernd; Wanka, Stefanie; Landry, Christian R.; Aebersold, Ruedi; Cyert, Martha S.

2014-01-01

Summary To define the first functional network for calcineurin, the conserved Ca2+/calmodulin-regulated phosphatase, we systematically identified its substrates in S. cerevisiae using phosphoproteomics and bioinformatics, followed by co-purification and dephosphorylation assays. This study establishes new calcineurin functions and reveals mechanisms that shape calcineurin network evolution. Analyses of closely related yeasts show that many proteins were recently recruited to the network by acquiring a calcineurin-recognition motif. Calcineurin substrates in yeast and mammals are distinct due to network rewiring but surprisingly are phosphorylated by similar kinases. We postulate that co-recognition of conserved substrate features, including phosphorylation and docking motifs, preserves calcineurin-kinase opposition during evolution. One example we document is a composite docking site that confers substrate recognition by both calcineurin and MAPK. We propose that conserved kinase-phosphatase pairs define the architecture of signaling networks and allow other connections between kinases and phosphatases to develop and establish common regulatory motifs in signaling networks. PMID:24930733
Biotechnology of non-Saccharomyces yeasts--the ascomycetes.

PubMed

Johnson, Eric A

2013-01-01

Saccharomyces cerevisiae and several other yeast species are among the most important groups of biotechnological organisms. S. cerevisiae and closely related ascomycetous yeasts are the major producer of biotechnology products worldwide, exceeding other groups of industrial microorganisms in productivity and economic revenues. Traditional industrial attributes of the S. cerevisiae group include their primary roles in food fermentations such as beers, cider, wines, sake, distilled spirits, bakery products, cheese, sausages, and other fermented foods. Other long-standing industrial processes involving S. cerevisae yeasts are production of fuel ethanol, single-cell protein (SCP), feeds and fodder, industrial enzymes, and small molecular weight metabolites. More recently, non-Saccharomyces yeasts (non-conventional yeasts) have been utilized as industrial organisms for a variety of biotechnological roles. Non-Saccharomyces yeasts are increasingly being used as hosts for expression of proteins, biocatalysts and multi-enzyme pathways for the synthesis of fine chemicals and small molecular weight compounds of medicinal and nutritional importance. Non-Saccharomyces yeasts also have important roles in agriculture as agents of biocontrol, bioremediation, and as indicators of environmental quality. Several of these products and processes have reached commercial utility, while others are in advanced development. The objective of this mini-review is to describe processes currently used by industry and those in developmental stages and close to commercialization primarily from non-Saccharomyces yeasts with an emphasis on new opportunities. The utility of S. cerevisiae in heterologous production of selected products is also described.
Yeast proteome map (last update).

PubMed

Perrot, Michel; Moes, Suzette; Massoni, Aurélie; Jenoe, Paul; Boucherie, Hélian

2009-10-01

The identification of proteins separated on 2-D gels is essential to exploit the full potential of 2-D gel electrophoresis for proteomic investigations. For this purpose we have undertaken the systematic identification of Saccharomyces cerevisiae proteins separated on 2-D gels. We report here the identification by mass spectrometry of 100 novel yeast protein spots that have so far not been tackled due to their scarcity on our standard 2-D gels. These identifications extend the number of protein spots identified on our yeast 2-D proteome map to 716. They correspond to 485 unique proteins. Among these, 154 were resolved into several isoforms. The present data set can now be expanded to report for the first time a map of 363 protein isoforms that significantly deepens our knowledge of the yeast proteome. The reference map and a list of all identified proteins can be accessed on the Yeast Protein Map server (www.ibgc.u-bordeaux2.fr/YPM).
High-resolution genome-wide scan of genes, gene-networks and cellular systems impacting the yeast ionome

USDA-ARS?s Scientific Manuscript database

To balance the demand for uptake of essential elements with their potential toxicity living cells have complex regulatory mechanisms. Here, we describe a genome-wide screen to identify genes that impact the elemental composition (‘ionome’) of yeast Saccharomyces cerevisiae. Using inductively coupled...
Septin Organization and Functions in Budding Yeast

PubMed Central

Glomb, Oliver; Gronemeyer, Thomas

2016-01-01

The septins are a conserved family of GTP-binding proteins present in all eukaryotic cells except plants. They were originally discovered in the baker's yeast Saccharomyces cerevisiae that serves until today as an important model organism for septin research. In yeast, the septins assemble into a highly ordered array of filaments at the mother bud neck. The septins are regulators of spatial compartmentalization in yeast and act as key players in cytokinesis. This minireview summarizes the recent findings about structural features and cell biology of the yeast septins. PMID:27857941
Taming wild yeast: potential of conventional and nonconventional yeasts in industrial fermentations.

PubMed

Steensels, Jan; Verstrepen, Kevin J

2014-01-01

Yeasts are the main driving force behind several industrial food fermentation processes, including the production of beer, wine, sake, bread, and chocolate. Historically, these processes developed from uncontrolled, spontaneous fermentation reactions that rely on a complex mixture of microbes present in the environment. Because such spontaneous processes are generally inconsistent and inefficient and often lead to the formation of off-flavors, most of today's industrial production utilizes defined starter cultures, often consisting of a specific domesticated strain of Saccharomyces cerevisiae, S. bayanus, or S. pastorianus. Although this practice greatly improved process consistency, efficiency, and overall quality, it also limited the sensorial complexity of the end product. In this review, we discuss how Saccharomyces yeasts were domesticated to become the main workhorse of food fermentations, and we investigate the potential and selection of nonconventional yeasts that are often found in spontaneous fermentations, such as Brettanomyces, Hanseniaspora, and Pichia spp.
Yeast: A Research Organism for Teaching Genetics.

ERIC Educational Resources Information Center

Manney, Thomas R.; Manney, Monta L.

1992-01-01

Explains why laboratory strains of bakers yeast, Saccharomyces cerevisiae, are particularly suited for classroom science activities. Describes the sexual life cycle of yeast and the genetic system with visible mutations. Presents an overview of activities that can be done with yeast and gives a source for teachers to obtain more information. (PR)
The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

PubMed Central

Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

2010-01-01

The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

Introducing a new breed of wine yeast: interspecific hybridisation between a commercial Saccharomyces cerevisiae wine yeast and Saccharomyces mikatae.

PubMed

Bellon, Jennifer R; Schmid, Frank; Capone, Dimitra L; Dunn, Barbara L; Chambers, Paul J

2013-01-01

Interspecific hybrids are commonplace in agriculture and horticulture; bread wheat and grapefruit are but two examples. The benefits derived from interspecific hybridisation include the potential of generating advantageous transgressive phenotypes. This paper describes the generation of a new breed of wine yeast by interspecific hybridisation between a commercial Saccharomyces cerevisiae wine yeast strain and Saccharomyces mikatae, a species hitherto not associated with industrial fermentation environs. While commercially available wine yeast strains provide consistent and reliable fermentations, wines produced using single inocula are thought to lack the sensory complexity and rounded palate structure obtained from spontaneous fermentations. In contrast, interspecific yeast hybrids have the potential to deliver increased complexity to wine sensory properties and alternative wine styles through the formation of novel, and wider ranging, yeast volatile fermentation metabolite profiles, whilst maintaining the robustness of the wine yeast parent. Screening of newly generated hybrids from a cross between a S. cerevisiae wine yeast and S. mikatae (closely-related but ecologically distant members of the Saccharomyces sensu stricto clade), has identified progeny with robust fermentation properties and winemaking potential. Chemical analysis showed that, relative to the S. cerevisiae wine yeast parent, hybrids produced wines with different concentrations of volatile metabolites that are known to contribute to wine flavour and aroma, including flavour compounds associated with non-Saccharomyces species. The new S. cerevisiae x S. mikatae hybrids have the potential to produce complex wines akin to products of spontaneous fermentation while giving winemakers the safeguard of an inoculated ferment.
Yeast fuel cell: Application for desalination

NASA Astrophysics Data System (ADS)

Mardiana, Ummy; Innocent, Christophe; Cretin, Marc; Buchari, Buchari; Gandasasmita, Suryo

2016-02-01

Yeasts have been implicated in microbial fuel cells as biocatalysts because they are non-pathogenic organisms, easily handled and robust with a good tolerance in different environmental conditions. Here we investigated baker's yeast Saccharomyces cerevisiae through the oxidation of glucose. Yeast was used in the anolyte, to transfer electrons to the anode in the presence of methylene blue as mediator whereas K3Fe(CN)6 was used as an electron acceptor for the reduction reaction in the catholyte. Power production with biofuel cell was coupled with a desalination process. The maximum current density produced by the cell was 88 mA.m-2. In those conditions, it was found that concentration of salt was removed 64% from initial 0.6 M after 1-month operation. This result proves that yeast fuel cells can be used to remove salt through electrically driven membrane processes and demonstrated that could be applied for energy production and desalination. Further developments are in progress to improve power output to make yeast fuel cells applicable for water treatment.
A novel method to identify hub pathways of rheumatoid arthritis based on differential pathway networks.

PubMed

Wei, Shi-Tong; Sun, Yong-Hua; Zong, Shi-Hua

2017-09-01

The aim of the current study was to identify hub pathways of rheumatoid arthritis (RA) using a novel method based on differential pathway network (DPN) analysis. The present study proposed a DPN where protein‑protein interaction (PPI) network was integrated with pathway‑pathway interactions. Pathway data was obtained from background PPI network and the Reactome pathway database. Subsequently, pathway interactions were extracted from the pathway data by building randomized gene‑gene interactions and a weight value was assigned to each pathway interaction using Spearman correlation coefficient (SCC) to identify differential pathway interactions. Differential pathway interactions were visualized using Cytoscape to construct a DPN. Topological analysis was conducted to identify hub pathways that possessed the top 5% degree distribution of DPN. Modules of DPN were mined according to ClusterONE. A total of 855 pathways were selected to build pathway interactions. By filtrating pathway interactions of weight values >0.7, a DPN with 312 nodes and 791 edges was obtained. Topological degree analysis revealed 15 hub pathways, such as heparan sulfate/heparin‑glycosaminoglycan (HS‑GAG) degradation, HS‑GAG metabolism and keratan sulfate degradation for RA based on DPN. Furthermore, hub pathways were also important in modules, which validated the significance of hub pathways. In conclusion, the proposed method is a computationally efficient way to identify hub pathways of RA, which identified 15 hub pathways that may be potential biomarkers and provide insight to future investigation and treatment of RA.
Yeasts for Global Happiness: report of the 14th International Congress on Yeasts (ICY14) held in Awaji Island.

PubMed

Watanabe, Daisuke; Takagi, Hiroshi

2017-02-01

The 14th International Congress on Yeasts (ICY14) was held at Awaji Yumebutai International Conference Center (Awaji, Hyogo) in Japan from 11 to 15 September 2016. The main slogan of ICY14 was 'Yeasts for Global Happiness', which enabled us to acknowledge the high-potential usefulness of yeasts contributing to the global happiness in terms of food/beverage, health/medicine and energy/environment industries, as well as to basic biosciences. In addition, two more concepts were introduced: 'from Japan to the world' and 'from senior to junior'. As it was the first ICY meeting held in Japan or other Asian countries, ICY14 provided a good opportunity to widely spread the great achievements by Japanese and Asian yeast researchers, such as those by the 2016 Nobel Laureate Dr. Yoshinori Ohsumi, and also, to convey the fun and importance of yeasts to the next generation of researchers from Asia and all over the world. As a result, a total of 426 yeast lovers from 42 countries (225 overseas and 201 domestic participants) with different generations attended ICY14 to share the latest knowledge of a wide range of yeast research fields and to join active and constructive scientific discussions. © 2017 Molecular Biology Society of Japan and John Wiley & Sons Australia, Ltd.
Global study of holistic morphological effectors in the budding yeast Saccharomyces cerevisiae.

PubMed

Suzuki, Godai; Wang, Yang; Kubo, Karen; Hirata, Eri; Ohnuki, Shinsuke; Ohya, Yoshikazu

2018-02-20

The size of the phenotypic effect of a gene has been thoroughly investigated in terms of fitness and specific morphological traits in the budding yeast Saccharomyces cerevisiae, but little is known about gross morphological abnormalities. We identified 1126 holistic morphological effectors that cause severe gross morphological abnormality when deleted, and 2241 specific morphological effectors with weak holistic effects but distinctive effects on yeast morphology. Holistic effectors fell into many gene function categories and acted as network hubs, affecting a large number of morphological traits, interacting with a large number of genes, and facilitating high protein expression. Holistic morphological abnormality was useful for estimating the importance of a gene to morphology. The contribution of gene importance to fitness and morphology could be used to efficiently classify genes into functional groups. Holistic morphological abnormality can be used as a reproducible and reliable gene feature for high-dimensional morphological phenotyping. It can be used in many functional genomic applications.
The secretory pathway: exploring yeast diversity.

PubMed

Delic, Marizela; Valli, Minoska; Graf, Alexandra B; Pfeffer, Martin; Mattanovich, Diethard; Gasser, Brigitte

2013-11-01

Protein secretion is an essential process for living organisms. In eukaryotes, this encompasses numerous steps mediated by several hundred cellular proteins. The core functions of translocation through the endoplasmic reticulum membrane, primary glycosylation, folding and quality control, and vesicle-mediated secretion are similar from yeasts to higher eukaryotes. However, recent research has revealed significant functional differences between yeasts and mammalian cells, and even among diverse yeast species. This review provides a current overview of the canonical protein secretion pathway in the model yeast Saccharomyces cerevisiae, highlighting differences to mammalian cells as well as currently unresolved questions, and provides a genomic comparison of the S. cerevisiae pathway to seven other yeast species where secretion has been investigated due to their attraction as protein production platforms, or for their relevance as pathogens. The analysis of Candida albicans, Candida glabrata, Kluyveromyces lactis, Pichia pastoris, Hansenula polymorpha, Yarrowia lipolytica, and Schizosaccharomyces pombe reveals that many - but not all - secretion steps are more redundant in S. cerevisiae due to duplicated genes, while some processes are even absent in this model yeast. Recent research obviates that even where homologous genes are present, small differences in protein sequence and/or differences in the regulation of gene expression may lead to quite different protein secretion phenotypes. © 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.
Modular biological function is most effectively captured by combining molecular interaction data types.

PubMed

Ames, Ryan M; Macpherson, Jamie I; Pinney, John W; Lovell, Simon C; Robertson, David L

2013-01-01

Large-scale molecular interaction data sets have the potential to provide a comprehensive, system-wide understanding of biological function. Although individual molecules can be promiscuous in terms of their contribution to function, molecular functions emerge from the specific interactions of molecules giving rise to modular organisation. As functions often derive from a range of mechanisms, we demonstrate that they are best studied using networks derived from different sources. Implementing a graph partitioning algorithm we identify subnetworks in yeast protein-protein interaction (PPI), genetic interaction and gene co-regulation networks. Among these subnetworks we identify cohesive subgraphs that we expect to represent functional modules in the different data types. We demonstrate significant overlap between the subgraphs generated from the different data types and show these overlaps can represent related functions as represented by the Gene Ontology (GO). Next, we investigate the correspondence between our subgraphs and the Gene Ontology. This revealed varying degrees of coverage of the biological process, molecular function and cellular component ontologies, dependent on the data type. For example, subgraphs from the PPI show enrichment for 84%, 58% and 93% of annotated GO terms, respectively. Integrating the interaction data into a combined network increases the coverage of GO. Furthermore, the different annotation types of GO are not predominantly associated with one of the interaction data types. Collectively our results demonstrate that successful capture of functional relationships by network data depends on both the specific biological function being characterised and the type of network data being used. We identify functions that require integrated information to be accurately represented, demonstrating the limitations of individual data types. Combining interaction subnetworks across data types is therefore essential for fully understanding the
Yeasts are essential for cocoa bean fermentation.

PubMed

Ho, Van Thi Thuy; Zhao, Jian; Fleet, Graham

2014-03-17

Cocoa beans (Theobroma cacao) are the major raw material for chocolate production and fermentation of the beans is essential for the development of chocolate flavor precursors. In this study, a novel approach was used to determine the role of yeasts in cocoa fermentation and their contribution to chocolate quality. Cocoa bean fermentations were conducted with the addition of 200ppm Natamycin to inhibit the growth of yeasts, and the resultant microbial ecology and metabolism, bean chemistry and chocolate quality were compared with those of normal (control) fermentations. The yeasts Hanseniaspora guilliermondii, Pichia kudriavzevii and Kluyveromyces marxianus, the lactic acid bacteria Lactobacillus plantarum and Lactobacillus fermentum and the acetic acid bacteria Acetobacter pasteurianus and Gluconobacter frateurii were the major species found in the control fermentation. In fermentations with the presence of Natamycin, the same bacterial species grew but yeast growth was inhibited. Physical and chemical analyses showed that beans fermented without yeasts had increased shell content, lower production of ethanol, higher alcohols and esters throughout fermentation and lesser presence of pyrazines in the roasted product. Quality tests revealed that beans fermented without yeasts were purplish-violet in color and not fully brown, and chocolate prepared from these beans tasted more acid and lacked characteristic chocolate flavor. Beans fermented with yeast growth were fully brown in color and gave chocolate with typical characters which were clearly preferred by sensory panels. Our findings demonstrate that yeast growth and activity were essential for cocoa bean fermentation and the development of chocolate characteristics. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.
Functional adaptation between yeast actin and its cognate myosin motors.

PubMed

Stark, Benjamin C; Wen, Kuo-Kuang; Allingham, John S; Rubenstein, Peter A; Lord, Matthew

2011-09-02

We employed budding yeast and skeletal muscle actin to examine the contribution of the actin isoform to myosin motor function. While yeast and muscle actin are highly homologous, they exhibit different charge density at their N termini (a proposed myosin-binding interface). Muscle myosin-II actin-activated ATPase activity is significantly higher with muscle versus yeast actin. Whether this reflects inefficiency in the ability of yeast actin to activate myosin is not known. Here we optimized the isolation of two yeast myosins to assess actin function in a homogenous system. Yeast myosin-II (Myo1p) and myosin-V (Myo2p) accommodate the reduced N-terminal charge density of yeast actin, showing greater activity with yeast over muscle actin. Increasing the number of negative charges at the N terminus of yeast actin from two to four (as in muscle) had little effect on yeast myosin activity, while other substitutions of charged residues at the myosin interface of yeast actin reduced activity. Thus, yeast actin functions most effectively with its native myosins, which in part relies on associations mediated by its outer domain. Compared with yeast myosin-II and myosin-V, muscle myosin-II activity was very sensitive to salt. Collectively, our findings suggest differing degrees of reliance on electrostatic interactions during weak actomyosin binding in yeast versus muscle. Our study also highlights the importance of native actin isoforms when considering the function of myosins.
On the integration of protein-protein interaction networks with gene expression and 3D structural data: What can be gained?

NASA Astrophysics Data System (ADS)

Bertolazzi, Paola; Bock, Mary Ellen; Guerra, Concettina; Paci, Paola; Santoni, Daniele

2014-06-01

The biological role of proteins has been analyzed from different perspectives, initially by considering proteins as isolated biological entities, then as cooperating entities that perform their function by interacting with other molecules. There are other dimensions that are important for the complete understanding of the biological processes: time and location. However a protein is rarely annotated with temporal and spatial information. Experimental Protein-Proteins Interaction (PPI) data are static; furthermore they generally do not include transient interactions which are a considerable fraction of the interactome of many organisms. One way to incorporate temporal and condition information is to use other sources of information, such as gene expression data and 3D structural data. Here we review work done to understand the insight that can be gained by enriching PPI data with gene expression and 3D structural data. In particular, we address the following questions: Can the dynamics of a single protein or of an interaction be accurately derived from these data? Can the assembly-disassembly of protein complexes be traced over time? What type of topological changes occur in a PPI network architecture over time?
Genomic Evolution of the Ascomycete Yeasts

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

Riley, Robert; Haridas, Sajeet; Salamov, Asaf

2015-03-16

Yeasts are important for industrial and biotechnological processes and show remarkable metabolic and phylogenetic diversity despite morphological similarities. We have sequenced the genomes of 16 ascomycete yeasts of taxonomic and industrial importance including members of Saccharomycotina and Taphrinomycotina. Phylogenetic analysis of these and previously published yeast genomes helped resolve the placement of species including Saitoella complicata, Babjeviella inositovora, Hyphopichia burtonii, and Metschnikowia bicuspidata. Moreover, we find that alternative nuclear codon usage, where CUG encodes serine instead of leucine, are monophyletic within the Saccharomycotina. Most of the yeasts have compact genomes with a large fraction of single exon genes, and amore » tendency towards more introns in early-diverging species. Analysis of enzyme phylogeny gives insights into the evolution of metabolic capabilities such as methanol utilization and assimilation of alternative carbon sources.« less
Specialist nectar-yeasts decline with urbanization in Berlin

NASA Astrophysics Data System (ADS)

Wehner, Jeannine; Mittelbach, Moritz; Rillig, Matthias C.; Verbruggen, Erik

2017-03-01

Nectar yeasts are common inhabitants of insect-pollinated flowers but factors determining their distribution are not well understood. We studied the influence of host identity, environmental factors related to pollution/urbanization, and the distance to a target beehive on local distribution of nectar yeasts within Robinia pseudoacacia L. and Tilia tomentosa Moench in Berlin, Germany. Nectar samples of six individuals per species were collected at seven sites in a 2 km radius from each target beehive and plated on YM-Agar to visualise the different morphotypes, which were then identified by sequencing a section of the 26S rDNA gene. Multivariate linear models were used to analyze the effects of all investigated factors on yeast occurrence per tree. Yeast distribution was mainly driven by host identity. The influence of the environmental factors (NO2, height of construction, soil sealing) strongly depended on the radius around the tree, similar to the distance of the sampled beehive. Incidence of specialist nectar-borne yeast species decreased with increasing pollution/urbanization index. Given that specialist yeast species gave way to generalist yeasts that have a reduced dependency on pollinators for between-flower dispersal, our results indicate that increased urbanization may restrict the movement of nectar-specialized yeasts, via limitations of pollinator foraging behavior.
Accumulation and metabolism of selenium by yeast cells.

PubMed

Kieliszek, Marek; Błażejak, Stanisław; Gientka, Iwona; Bzducha-Wróbel, Anna

2015-07-01

This paper examines the process of selenium bioaccumulation and selenium metabolism in yeast cells. Yeast cells can bind elements in ionic from the environment and permanently integrate them into their cellular structure. Up to now, Saccharomyces cerevisiae, Candida utilis, and Yarrowia lipolytica yeasts have been used primarily in biotechnological studies to evaluate binding of minerals. Yeast cells are able to bind selenium in the form of both organic and inorganic compounds. The process of bioaccumulation of selenium by microorganisms occurs through two mechanisms: extracellular binding by ligands of membrane assembly and intracellular accumulation associated with the transport of ions across the cytoplasmic membrane into the cell interior. During intracellular metabolism of selenium, oxidation, reduction, methylation, and selenoprotein synthesis processes are involved, as exemplified by detoxification processes that allow yeasts to survive under culture conditions involving the elevated selenium concentrations which were observed. Selenium yeasts represent probably the best absorbed form of this element. In turn, in terms of wide application, the inclusion of yeast with accumulated selenium may aid in lessening selenium deficiency in a diet.
Introducing a New Breed of Wine Yeast: Interspecific Hybridisation between a Commercial Saccharomyces cerevisiae Wine Yeast and Saccharomyces mikatae

PubMed Central

Bellon, Jennifer R.; Schmid, Frank; Capone, Dimitra L.; Dunn, Barbara L.; Chambers, Paul J.

2013-01-01

Interspecific hybrids are commonplace in agriculture and horticulture; bread wheat and grapefruit are but two examples. The benefits derived from interspecific hybridisation include the potential of generating advantageous transgressive phenotypes. This paper describes the generation of a new breed of wine yeast by interspecific hybridisation between a commercial Saccharomyces cerevisiae wine yeast strain and Saccharomyces mikatae, a species hitherto not associated with industrial fermentation environs. While commercially available wine yeast strains provide consistent and reliable fermentations, wines produced using single inocula are thought to lack the sensory complexity and rounded palate structure obtained from spontaneous fermentations. In contrast, interspecific yeast hybrids have the potential to deliver increased complexity to wine sensory properties and alternative wine styles through the formation of novel, and wider ranging, yeast volatile fermentation metabolite profiles, whilst maintaining the robustness of the wine yeast parent. Screening of newly generated hybrids from a cross between a S. cerevisiae wine yeast and S. mikatae (closely-related but ecologically distant members of the Saccharomyces sensu stricto clade), has identified progeny with robust fermentation properties and winemaking potential. Chemical analysis showed that, relative to the S. cerevisiae wine yeast parent, hybrids produced wines with different concentrations of volatile metabolites that are known to contribute to wine flavour and aroma, including flavour compounds associated with non-Saccharomyces species. The new S. cerevisiae x S. mikatae hybrids have the potential to produce complex wines akin to products of spontaneous fermentation while giving winemakers the safeguard of an inoculated ferment. PMID:23614011
Yeast Can Affect Behavior and Learning.

ERIC Educational Resources Information Center

Crook, William G.

1984-01-01

A pediatrician recounts his experiences in diagnosing and treating allergies to common yeast germs that may result in behavior and learning problems. He lists characteristics that may predispose children to yeast-connected health problems. (CL)
Chemical signaling and insect attraction is a conserved trait in yeasts.

PubMed

Becher, Paul G; Hagman, Arne; Verschut, Vasiliki; Chakraborty, Amrita; Rozpędowska, Elżbieta; Lebreton, Sébastien; Bengtsson, Marie; Flick, Gerhard; Witzgall, Peter; Piškur, Jure

2018-03-01

Yeast volatiles attract insects, which apparently is of mutual benefit, for both yeasts and insects. However, it is unknown whether biosynthesis of metabolites that attract insects is a basic and general trait, or if it is specific for yeasts that live in close association with insects. Our goal was to study chemical insect attractants produced by yeasts that span more than 250 million years of evolutionary history and vastly differ in their metabolism and lifestyle. We bioassayed attraction of the vinegar fly Drosophila melanogaster to odors of phylogenetically and ecologically distinct yeasts grown under controlled conditions. Baker's yeast Saccharomyces cerevisiae , the insect-associated species Candida californica , Pichia kluyveri and Metschnikowia andauensis , wine yeast Dekkera bruxellensis , milk yeast Kluyveromyces lactis , the vertebrate pathogens Candida albicans and Candida glabrata , and oleophilic Yarrowia lipolytica were screened for fly attraction in a wind tunnel. Yeast headspace was chemically analyzed, and co-occurrence of insect attractants in yeasts and flowering plants was investigated through a database search. In yeasts with known genomes, we investigated the occurrence of genes involved in the synthesis of key aroma compounds. Flies were attracted to all nine yeasts studied. The behavioral response to baker's yeast was independent of its growth stage. In addition to Drosophila , we tested the basal hexapod Folsomia candida (Collembola) in a Y-tube assay to the most ancient yeast, Y. lipolytica, which proved that early yeast signals also function on clades older than neopteran insects. Behavioral and chemical data and a search for selected genes of volatile metabolites underline that biosynthesis of chemical signals is found throughout the yeast clade and has been conserved during the evolution of yeast lifestyles. Literature and database reviews corroborate that yeast signals mediate mutualistic interactions between insects and yeasts
A network biology-based approach to evaluating the effect of environmental contaminants on human interactome and diseases.

PubMed

Iida, M; Takemoto, K

2018-09-30

Environmental contaminant exposure can pose significant risks to human health. Therefore, evaluating the impact of this exposure is of great importance; however, it is often difficult because both the molecular mechanism of disease and the mode of action of the contaminants are complex. We used network biology techniques to quantitatively assess the impact of environmental contaminants on the human interactome and diseases with a particular focus on seven major contaminant categories: persistent organic pollutants (POPs), dioxins, polycyclic aromatic hydrocarbons (PAHs), pesticides, perfluorochemicals (PFCs), metals, and pharmaceutical and personal care products (PPCPs). We integrated publicly available data on toxicogenomics, the diseasome, protein-protein interactions (PPIs), and gene essentiality and found that a few contaminants were targeted to many genes, and a few genes were targeted by many contaminants. The contaminant targets were hub proteins in the human PPI network, whereas the target proteins in most categories did not contain abundant essential proteins. Generally, contaminant targets and disease-associated proteins were closely associated with the PPI network, and the closeness of the associations depended on the disease type and chemical category. Network biology techniques were used to identify environmental contaminants with broad effects on the human interactome and contaminant-sensitive biomarkers. Moreover, this method enabled us to quantify the relationship between environmental contaminants and human diseases, which was supported by epidemiological and experimental evidence. These methods and findings have facilitated the elucidation of the complex relationship between environmental exposure and adverse health outcomes. Copyright © 2018 Elsevier Inc. All rights reserved.
The PathoYeastract database: an information system for the analysis of gene and genomic transcription regulation in pathogenic yeasts.

PubMed

Monteiro, Pedro Tiago; Pais, Pedro; Costa, Catarina; Manna, Sauvagya; Sá-Correia, Isabel; Teixeira, Miguel Cacho

2017-01-04

We present the PATHOgenic YEAst Search for Transcriptional Regulators And Consensus Tracking (PathoYeastract - http://pathoyeastract.org) database, a tool for the analysis and prediction of transcription regulatory associations at the gene and genomic levels in the pathogenic yeasts Candida albicans and C. glabrata Upon data retrieval from hundreds of publications, followed by curation, the database currently includes 28 000 unique documented regulatory associations between transcription factors (TF) and target genes and 107 DNA binding sites, considering 134 TFs in both species. Following the structure used for the YEASTRACT database, PathoYeastract makes available bioinformatics tools that enable the user to exploit the existing information to predict the TFs involved in the regulation of a gene or genome-wide transcriptional response, while ranking those TFs in order of their relative importance. Each search can be filtered based on the selection of specific environmental conditions, experimental evidence or positive/negative regulatory effect. Promoter analysis tools and interactive visualization tools for the representation of TF regulatory networks are also provided. The PathoYeastract database further provides simple tools for the prediction of gene and genomic regulation based on orthologous regulatory associations described for other yeast species, a comparative genomics setup for the study of cross-species evolution of regulatory networks. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
A reverse engineering approach to optimize experiments for the construction of biological regulatory networks.

PubMed

Zhang, Xiaomeng; Shao, Bin; Wu, Yangle; Qi, Ouyang

2013-01-01

One of the major objectives in systems biology is to understand the relation between the topological structures and the dynamics of biological regulatory networks. In this context, various mathematical tools have been developed to deduct structures of regulatory networks from microarray expression data. In general, from a single data set, one cannot deduct the whole network structure; additional expression data are usually needed. Thus how to design a microarray expression experiment in order to get the most information is a practical problem in systems biology. Here we propose three methods, namely, maximum distance method, trajectory entropy method, and sampling method, to derive the optimal initial conditions for experiments. The performance of these methods is tested and evaluated in three well-known regulatory networks (budding yeast cell cycle, fission yeast cell cycle, and E. coli. SOS network). Based on the evaluation, we propose an efficient strategy for the design of microarray expression experiments.
Yeast as a model for Ras signalling.

PubMed

Tisi, Renata; Belotti, Fiorella; Martegani, Enzo

2014-01-01

For centuries yeast species have been popular hosts for classical biotechnology processes, such as baking, brewing, and wine making, and more recently for recombinant proteins production, thanks to the advantages of unicellular organisms (i.e., ease of genetic manipulation and rapid growth) together with the ability to perform eukaryotic posttranslational modifications. Moreover, yeast cells have been used for few decades as a tool for identifying the genes and pathways involved in basic cellular processes such as the cell cycle, aging, and stress response. In the budding yeast S. cerevisiae the Ras/cAMP/PKA pathway is directly involved in the regulation of metabolism, cell growth, stress resistance, and proliferation in response to the availability of nutrients and in the adaptation to glucose, controlling cytosolic cAMP levels and consequently the cAMP-dependent protein kinase (PKA) activity. Moreover, Ras signalling has been identified in several pathogenic yeasts as a key controller for virulence, due to its involvement in yeast morphogenesis. Nowadays, yeasts are still useful for Ras-like proteins investigation, both as model organisms and as a test tube to study variants of heterologous Ras-like proteins.

Flor Yeast: New Perspectives Beyond Wine Aging

PubMed Central

Legras, Jean-Luc; Moreno-Garcia, Jaime; Zara, Severino; Zara, Giacomo; Garcia-Martinez, Teresa; Mauricio, Juan C.; Mannazzu, Ilaria; Coi, Anna L.; Bou Zeidan, Marc; Dequin, Sylvie; Moreno, Juan; Budroni, Marilena

2016-01-01

The most important dogma in white-wine production is the preservation of the wine aroma and the limitation of the oxidative action of oxygen. In contrast, the aging of Sherry and Sherry-like wines is an aerobic process that depends on the oxidative activity of flor strains of Saccharomyces cerevisiae. Under depletion of nitrogen and fermentable carbon sources, these yeast produce aggregates of floating cells and form an air–liquid biofilm on the wine surface, which is also known as velum or flor. This behavior is due to genetic and metabolic peculiarities that differentiate flor yeast from other wine yeast. This review will focus first on the most updated data obtained through the analysis of flor yeast with -omic tools. Comparative genomics, proteomics, and metabolomics of flor and wine yeast strains are shedding new light on several features of these special yeast, and in particular, they have revealed the extent of proteome remodeling imposed by the biofilm life-style. Finally, new insights in terms of promotion and inhibition of biofilm formation through small molecules, amino acids, and di/tri-peptides, and novel possibilities for the exploitation of biofilm immobilization within a fungal hyphae framework, will be discussed. PMID:27148192
Protein biogenesis machinery is a driver of replicative aging in yeast

PubMed Central

Janssens, Georges E; Meinema, Anne C; González, Javier; Wolters, Justina C; Schmidt, Alexander; Guryev, Victor; Bischoff, Rainer; Wit, Ernst C; Veenhoff, Liesbeth M; Heinemann, Matthias

2015-01-01

An integrated account of the molecular changes occurring during the process of cellular aging is crucial towards understanding the underlying mechanisms. Here, using novel culturing and computational methods as well as latest analytical techniques, we mapped the proteome and transcriptome during the replicative lifespan of budding yeast. With age, we found primarily proteins involved in protein biogenesis to increase relative to their transcript levels. Exploiting the dynamic nature of our data, we reconstructed high-level directional networks, where we found the same protein biogenesis-related genes to have the strongest ability to predict the behavior of other genes in the system. We identified metabolic shifts and the loss of stoichiometry in protein complexes as being consequences of aging. We propose a model whereby the uncoupling of protein levels of biogenesis-related genes from their transcript levels is causal for the changes occurring in aging yeast. Our model explains why targeting protein synthesis, or repairing the downstream consequences, can serve as interventions in aging. DOI: http://dx.doi.org/10.7554/eLife.08527.001 PMID:26422514
Isolation and characterization of ethanol tolerant yeast strains

PubMed Central

Tikka, Chiranjeevi; Osuru, Hari Prasad; Atluri, Navya; Raghavulu, Praveen Chakravarthi Veera; yellapu, Nanda Kumar; Mannur, Ismail Shaik; Prasad, Uppu Venkateswara; Aluru, Sudheer; K, Narasimha Varma; Bhaskar, Matcha

2013-01-01

Yeast strains are commonly associated with sugar rich environments. Various fruit samples were selected as source for isolating yeast cells. The isolated cultures were identified at Genus level by colony morphology, biochemical characteristics and cell morphological characters. An attempt has been made to check the viability of yeast cells under different concentrations of ethanol. Ethanol tolerance of each strain was studied by allowing the yeast to grow in liquid YEPD (Yeast Extract Peptone Dextrose) medium having different concentrations of ethanol. A total of fifteen yeast strains isolated from different samples were used for the study. Seven strains of Saccharomyces cerevisiae obtained from different fruit sources were screened for ethanol tolerance. The results obtained in this study show a range of tolerance levels between 7%-12% in all the stains. Further, the cluster analysis based on 22 RAPD (Random Amplified polymorphic DNA) bands revealed polymorphisms in these seven Saccharomyces strains. PMID:23750092
Phylogenetics of Saccharomycetales, the ascomycete yeasts.

PubMed

Suh, Sung-Oui; Blackwell, Meredith; Kurtzman, Cletus P; Lachance, Marc-André

2006-01-01

Ascomycete yeasts (phylum Ascomycota: subphylum Saccharomycotina: class Saccharomycetes: order Saccharomycetales) comprise a monophyletic lineage with a single order of about 1000 known species. These yeasts live as saprobes, often in association with plants, animals and their interfaces. A few species account for most human mycotic infections, and fewer than 10 species are plant pathogens. Yeasts are responsible for important industrial and biotechnological processes, including baking, brewing and synthesis of recombinant proteins. Species such as Saccharomyces cerevisiae are model organisms in research, some of which led to a Nobel Prize. Yeasts usually reproduce asexually by budding, and their sexual states are not enclosed in a fruiting body. The group also is well defined by synapomorphies visible at the ultrastructural level. Yeast identification and classification changed dramatically with the availability of DNA sequencing. Species identification now benefits from a constantly updated sequence database and no longer relies on ambiguous growth tests. A phylogeny based on single gene analyses has shown the order to be remarkably divergent despite morphological similarities among members. The limits of many previously described genera are not supported by sequence comparisons, and multigene phylogenetic studies are under way to provide a stable circumscription of genera, families and orders. One recent multigene study has resolved species of the Saccharomycetaceae into genera that differ markedly from those defined by analysis of morphology and growth responses, and similar changes are likely to occur in other branches of the yeast tree as additional sequences become available.
Yeast species associated with wine grapes in China.

PubMed

Li, Shuang-Shi; Cheng, Chao; Li, Zheng; Chen, Jing-Yu; Yan, Bin; Han, Bei-Zhong; Reeves, Malcolm

2010-03-31

Having more information on the yeast ecology of grapes is important for wine-makers to produce wine with high quality and typical attributes. China is a significant wine-consuming country and is becoming a serious wine-producer, but little has been reported about the yeast ecology of local ecosystems. This study provides the first step towards the exploitation of the yeast wealth in China's vine-growing regions. The aim of this study was to investigate the yeast population density and diversity on three grape varieties cultivated in four representative vine-growing regions of China. Yeast species diversity was evaluated by using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and sequence analysis of the 5.8S internal transcribed spacer (ITS) ribosomal DNA (rDNA) region of cultivable yeasts. The grapes harbored yeast populations at 10(2)-10(6)CFU/mL, consisting mostly of non-Saccharomyces species. Seventeen different yeast species belonging to eight genera were detected on the grape samples tested, including Hanseniaspora uvarum, Cryptococcus flavescens, Pichia fermentans, Candida zemplinina, Cryptococcus carnescens, Candida inconpicua, Zygosaccharomyces fermentati, Issatchenkia terricola, Candida quercitrusa, Hanseniaspora guilliermondii, Candida bombi, Zygosaccharomyces bailii, Sporidiobolus pararoseus, Cryptococcus magnus, Metschnikowia pulcherrima, Issatchenkia orientalis and Pichia guilliermondii. H. uvarum and C. flavescens were the dominant species present on the grapes. For the first time Sporidiobolus pararoseus was discovered as an inhabitant of the grape ecosystem. The yeast community on grape berries was influenced by the grape chemical composition, vine-variety and vine-growing region. This study is the first to identify the yeast communities associated with grapes in China using molecular methods. The results enrich our knowledge of wine-related microorganisms, and can be used to promote the development of the local wine
Antimicrobial activity of yeasts against some pathogenic bacteria

PubMed Central

Younis, Gamal; Awad, Amal; Dawod, Rehab E.; Yousef, Nehal E.

2017-01-01

Aim: This study was designed to isolate and identify yeast species from milk and meat products, and to test their antimicrobial activity against some bacterial species. Materials and Methods: A total of 160 milk and meat products samples were collected from random sellers and super markets in New Damietta city, Damietta, Egypt. Samples were subjected to yeast isolation procedures and tested for its antimicrobial activity against Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli. In addition, all yeast species isolates were subjected to polymerase chain reaction (PCR) for detection of khs (kievitone hydratase) and pelA (pectate degrading enzyme)genes. Results: The recovery rate of yeasts from sausage was 20% (2/10) followed by kareish cheese, processed cheese, and butter 10% (1/10) each as well as raw milk 9% (9/100), and fruit yoghurt 30% (6/20). Different yeast species were recovered, namely, Candida kefyr (5 isolates), Saccharomyces cerevisiae (4 isolates), Candida intermedia (3 isolates), Candida tropicalis (2 isolates), Candida lusitaniae (2 isolates), and Candida krusei (1 isolate). khs gene was detected in all S. cerevisiae isolates, however, pelA gene was not detected in all identified yeast species. Antimicrobial activity of recovered yeasts against the selected bacterial species showed high activity with C. intermedia against S. aureus and E. coli, C. kefyr against E. coli, and C. lusitaniae against S. aureus. Moderate activities were obtained with C. tropicalis, C. lusitaniae, and S. cerevisiae against E. coli; meanwhile, all the tested yeasts revealed a very low antimicrobial activity against P. aeruginosa. Conclusion: The obtained results confirmed that some kinds of yeasts have the ability to produce antimicrobial compounds that could inhibit some pathogenic and spoilage bacteria and these antimicrobial activity of yeasts enables them to be one of the novel agents in controlling spoilage of food. PMID:28919693
Genomic evolution of the ascomycetous yeasts

USDA-ARS?s Scientific Manuscript database

Yeasts are important for industrial and biotechnological processes and show remarkable metabolic and phylogenetic diversity despite morphological similarities. We have sequenced the genomes of 16 ascomycete yeasts of taxonomic and industrial importance including members of Saccharomycotina and Taphr...
Repeat-Associated Fission Yeast-Like Regional Centromeres in the Ascomycetous Budding Yeast Candida tropicalis

PubMed Central

Chatterjee, Gautam; Sankaranarayanan, Sundar Ram; Guin, Krishnendu; Thattikota, Yogitha; Padmanabhan, Sreedevi; Siddharthan, Rahul; Sanyal, Kaustuv

2016-01-01

The centromere, on which kinetochore proteins assemble, ensures precise chromosome segregation. Centromeres are largely specified by the histone H3 variant CENP-A (also known as Cse4 in yeasts). Structurally, centromere DNA sequences are highly diverse in nature. However, the evolutionary consequence of these structural diversities on de novo CENP-A chromatin formation remains elusive. Here, we report the identification of centromeres, as the binding sites of four evolutionarily conserved kinetochore proteins, in the human pathogenic budding yeast Candida tropicalis. Each of the seven centromeres comprises a 2 to 5 kb non-repetitive mid core flanked by 2 to 5 kb inverted repeats. The repeat-associated centromeres of C. tropicalis all share a high degree of sequence conservation with each other and are strikingly diverged from the unique and mostly non-repetitive centromeres of related Candida species—Candida albicans, Candida dubliniensis, and Candida lusitaniae. Using a plasmid-based assay, we further demonstrate that pericentric inverted repeats and the underlying DNA sequence provide a structural determinant in CENP-A recruitment in C. tropicalis, as opposed to epigenetically regulated CENP-A loading at centromeres in C. albicans. Thus, the centromere structure and its influence on de novo CENP-A recruitment has been significantly rewired in closely related Candida species. Strikingly, the centromere structural properties along with role of pericentric repeats in de novo CENP-A loading in C. tropicalis are more reminiscent to those of the distantly related fission yeast Schizosaccharomyces pombe. Taken together, we demonstrate, for the first time, fission yeast-like repeat-associated centromeres in an ascomycetous budding yeast. PMID:26845548
A hydrazone based probe for selective sensing of Al(iii) and Al(iii)-probe complex mediated secondary sensing of PPi: framing of molecular logic circuit and memory device and computational studies.

PubMed

Mohammad, Hasan; Islam, Abu Saleh Musha; Prodhan, Chandraday; Chaudhuri, Keya; Ali, Mahammad

2018-02-14

A hydrazone-based conjugate Nap-hyz-pyz (H 3 L3) with potential N 2 O 2 donor atoms was found to act as a dual channel (colori- and fluori-metric) sensor towards Al 3+ and PPi in H 2 O-MeOH (6 : 4, v/v) at pH 7.2 (40 mM HEPES buffer) at 25 °C. The formation constants, K f = (3.49 ± 1.77) × 10 4 and (3.78 ± 0.1) × 10 4 M -1 , of the sensor towards Al 3+ were determined by absorption and fluorescence titrations, respectively. The 1 : 1 stoichiometry of the reaction was determined by Job's method and confirmed by ESI-MS + (m/z) studies. The LOD for Al 3+ , as determined by the 3σ method, was found to be 114.54 nM. Most strikingly, the addition of ∼115 μM PPi to the Nap-hyz-pyz-Al 3+ ensemble (20 μM ligand and 74 μM Al 3+ ) leads to complete quenching of fluorescence. The fluorescence response of Nap-hyz-pyz towards Al 3+ was not perturbed by the presence of 5 equivalents or more of other ions and inorganic anions. The structure of the [Al(L 3 )(H 2 O)] complex was delineated by DFT calculations. TD-DFT studies were performed to investigate various spectral transitions. Based on changes in the fluorescence intensities of Nap-hyz-pyz in the presence of Al 3+ and PPi at 487 nm, INHIBIT and molecular logic gates were constructed and interpreted. The probe was found to be bio-compatible and cell permeable with no or negligible cytotoxicity; thus, it provides a good opportunity for in vitro cell imaging studies of these ions. The presence of ATP or Pi did not interfere with the fluorescent detection of PPi. Thus, these evident and excellent sensing capabilities of Nap-hyz-pyz towards Al 3+ and PPi were further scrutinized in HepG2 cell lines.
EgoNet: identification of human disease ego-network modules

PubMed Central

2014-01-01

Background Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks. Results We present EgoNet, a novel method based on egocentric network-analysis techniques, to exhaustively search and prioritize disease subnetworks and gene markers from a large-scale biological network. When applied to a triple-negative breast cancer (TNBC) microarray dataset, the top selected modules contain both known gene markers in TNBC and novel candidates, such as RAD51 and DOK1, which play a central role in their respective ego-networks by connecting many differentially expressed genes. Conclusions Our results suggest that EgoNet, which is based on the ego network concept, allows the identification of novel biomarkers and provides a deeper understanding of their roles in complex diseases. PMID:24773628
An iterative network partition algorithm for accurate identification of dense network modules

PubMed Central

Sun, Siqi; Dong, Xinran; Fu, Yao; Tian, Weidong

2012-01-01

A key step in network analysis is to partition a complex network into dense modules. Currently, modularity is one of the most popular benefit functions used to partition network modules. However, recent studies suggested that it has an inherent limitation in detecting dense network modules. In this study, we observed that despite the limitation, modularity has the advantage of preserving the primary network structure of the undetected modules. Thus, we have developed a simple iterative Network Partition (iNP) algorithm to partition a network. The iNP algorithm provides a general framework in which any modularity-based algorithm can be implemented in the network partition step. Here, we tested iNP with three modularity-based algorithms: multi-step greedy (MSG), spectral clustering and Qcut. Compared with the original three methods, iNP achieved a significant improvement in the quality of network partition in a benchmark study with simulated networks, identified more modules with significantly better enrichment of functionally related genes in both yeast protein complex network and breast cancer gene co-expression network, and discovered more cancer-specific modules in the cancer gene co-expression network. As such, iNP should have a broad application as a general method to assist in the analysis of biological networks. PMID:22121225
Dynamic Changes in Amygdala Psychophysiological Connectivity Reveal Distinct Neural Networks for Facial Expressions of Basic Emotions.

PubMed

Diano, Matteo; Tamietto, Marco; Celeghin, Alessia; Weiskrantz, Lawrence; Tatu, Mona-Karina; Bagnis, Arianna; Duca, Sergio; Geminiani, Giuliano; Cauda, Franco; Costa, Tommaso

2017-03-27

The quest to characterize the neural signature distinctive of different basic emotions has recently come under renewed scrutiny. Here we investigated whether facial expressions of different basic emotions modulate the functional connectivity of the amygdala with the rest of the brain. To this end, we presented seventeen healthy participants (8 females) with facial expressions of anger, disgust, fear, happiness, sadness and emotional neutrality and analyzed amygdala's psychophysiological interaction (PPI). In fact, PPI can reveal how inter-regional amygdala communications change dynamically depending on perception of various emotional expressions to recruit different brain networks, compared to the functional interactions it entertains during perception of neutral expressions. We found that for each emotion the amygdala recruited a distinctive and spatially distributed set of structures to interact with. These changes in amygdala connectional patters characterize the dynamic signature prototypical of individual emotion processing, and seemingly represent a neural mechanism that serves to implement the distinctive influence that each emotion exerts on perceptual, cognitive, and motor responses. Besides these differences, all emotions enhanced amygdala functional integration with premotor cortices compared to neutral faces. The present findings thus concur to reconceptualise the structure-function relation between brain-emotion from the traditional one-to-one mapping toward a network-based and dynamic perspective.
Comparative genomics of biotechnologically important yeasts

USDA-ARS?s Scientific Manuscript database

Ascomycete yeasts are metabolically diverse, with great potential for biotechnology. Here, we report the comparative genome analysis of 29 taxonomically and biotechnologically important yeasts, including 16 newly sequenced. We identify a genetic code change, CUG-Ala, in Pachysolen tannophilus in the...
Counting Yeast.

ERIC Educational Resources Information Center

Bealer, Jonathan; Welton, Briana

1998-01-01

Describes changes to a traditional study of population in yeast colonies. Changes to the procedures include: (1) only one culture per student team; (2) cultures are inoculated only once; and (3) the same tube is sampled daily. (DDR)
Efficient prediction of human protein-protein interactions at a global scale.

PubMed

Schoenrock, Andrew; Samanfar, Bahram; Pitre, Sylvain; Hooshyar, Mohsen; Jin, Ke; Phillips, Charles A; Wang, Hui; Phanse, Sadhna; Omidi, Katayoun; Gui, Yuan; Alamgir, Md; Wong, Alex; Barrenäs, Fredrik; Babu, Mohan; Benson, Mikael; Langston, Michael A; Green, James R; Dehne, Frank; Golshani, Ashkan

2014-12-10

Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods. On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments. The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.
Making Sense of the Yeast Sphingolipid Pathway.

PubMed

Megyeri, Márton; Riezman, Howard; Schuldiner, Maya; Futerman, Anthony H

2016-12-04

Sphingolipids (SL) and their metabolites play key roles both as structural components of membranes and as signaling molecules. Many of the key enzymes and regulators of SL metabolism were discovered using the yeast Saccharomyces cerevisiae, and based on the high degree of conservation, a number of mammalian homologs were identified. Although yeast continues to be an important tool for SL research, the complexity of SL structure and nomenclature often hampers the ability of new researchers to grasp the subtleties of yeast SL biology and discover new modulators of this intricate pathway. Moreover, the emergence of lipidomics by mass spectrometry has enabled the rapid identification of SL species in yeast and rendered the analysis of SL composition under various physiological and pathophysiological conditions readily amenable. However, the complex nomenclature of the identified species renders much of the data inaccessible to non-specialists. In this review, we focus on parsing both the classical SL nomenclature and the nomenclature normally used during mass spectrometry analysis, which should facilitate the understanding of yeast SL data and might shed light on biological processes in which SLs are involved. Finally, we discuss a number of putative roles of various yeast SL species. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Novel brewing yeast hybrids: creation and application.

PubMed

Krogerus, Kristoffer; Magalhães, Frederico; Vidgren, Virve; Gibson, Brian

2017-01-01

The natural interspecies Saccharomyces cerevisiae × Saccharomyces eubayanus hybrid yeast is responsible for global lager beer production and is one of the most important industrial microorganisms. Its success in the lager brewing environment is due to a combination of traits not commonly found in pure yeast species, principally low-temperature tolerance, and maltotriose utilization. Parental transgression is typical of hybrid organisms and has been exploited previously for, e.g., the production of wine yeast with beneficial properties. The parental strain S. eubayanus has only been discovered recently and newly created lager yeast strains have not yet been applied industrially. A number of reports attest to the feasibility of this approach and artificially created hybrids are likely to have a significant impact on the future of lager brewing. De novo S. cerevisiae × S. eubayanus hybrids outperform their parent strains in a number of respects, including, but not restricted to, fermentation rate, sugar utilization, stress tolerance, and aroma formation. Hybrid genome function and stability, as well as different techniques for generating hybrids and their relative merits are discussed. Hybridization not only offers the possibility of generating novel non-GM brewing yeast strains with unique properties, but is expected to aid in unraveling the complex evolutionary history of industrial lager yeast.
Biology of the Heat Shock Response and Protein Chaperones: Budding Yeast (Saccharomyces cerevisiae) as a Model System

PubMed Central

Verghese, Jacob; Abrams, Jennifer; Wang, Yanyu

2012-01-01

Summary: The eukaryotic heat shock response is an ancient and highly conserved transcriptional program that results in the immediate synthesis of a battery of cytoprotective genes in the presence of thermal and other environmental stresses. Many of these genes encode molecular chaperones, powerful protein remodelers with the capacity to shield, fold, or unfold substrates in a context-dependent manner. The budding yeast Saccharomyces cerevisiae continues to be an invaluable model for driving the discovery of regulatory features of this fundamental stress response. In addition, budding yeast has been an outstanding model system to elucidate the cell biology of protein chaperones and their organization into functional networks. In this review, we evaluate our understanding of the multifaceted response to heat shock. In addition, the chaperone complement of the cytosol is compared to those of mitochondria and the endoplasmic reticulum, organelles with their own unique protein homeostasis milieus. Finally, we examine recent advances in the understanding of the roles of protein chaperones and the heat shock response in pathogenic fungi, which is being accelerated by the wealth of information gained for budding yeast. PMID:22688810
Yeast-Leavened Laminated Salty Baked Goods: Flour and Dough Properties and Their Relationship with Product Technological Quality

PubMed Central

de la Horra, Ana E.; Steffolani, María Eugenia; Barrera, Gabriela N.; Ribotta, Pablo D.

2015-01-01

Summary The effect of protein composition and content on the characteristics and properties of laminated baked products has been studied for a long time. However, there are no flour quality parameters related to its suitability to produce yeast-leavened laminated salty baked products. The relationships among flour characteristics, laminated dough pieces and baked products were studied in order to establish flour quality parameters and help predict the quality of the products. Yeast-leavened salty laminated products made with hard wheat flour had better quality properties than the products made with soft wheat flour. Hydrophilic components and a high gluten network quality are responsible for the generation of a rigid structure and viscous dough. Consequently, during baking, the dough rises rather than extends laterally and does not experience any change in the expected shape. Among the analysed flour characteristics, glutenin macropolymer content, lactic acid and sodium carbonate solvent retention capacities together with dough viscosity and resistance to deformation were the variables which influenced the most the quality of yeast-leavened salty laminated products. PMID:27904379
Yeast-Leavened Laminated Salty Baked Goods: Flour and Dough Properties and Their Relationship with Product Technological Quality.

PubMed

de la Horra, Ana E; Steffolani, María Eugenia; Barrera, Gabriela N; Ribotta, Pablo D; León, Alberto E

2015-12-01

The effect of protein composition and content on the characteristics and properties of laminated baked products has been studied for a long time. However, there are no flour quality parameters related to its suitability to produce yeast-leavened laminated salty baked products. The relationships among flour characteristics, laminated dough pieces and baked products were studied in order to establish flour quality parameters and help predict the quality of the products. Yeast-leavened salty laminated products made with hard wheat flour had better quality properties than the products made with soft wheat flour. Hydrophilic components and a high gluten network quality are responsible for the generation of a rigid structure and viscous dough. Consequently, during baking, the dough rises rather than extends laterally and does not experience any change in the expected shape. Among the analysed flour characteristics, glutenin macropolymer content, lactic acid and sodium carbonate solvent retention capacities together with dough viscosity and resistance to deformation were the variables which influenced the most the quality of yeast-leavened salty laminated products.

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