Dilemma solving by the coevolution of networks and strategy in a 2 x 2 game.

PubMed

Tanimoto, Jun

2007-08-01

A 2 x 2 game model implemented by a coevolution mechanism of both networks and strategy, inspired by the work of Zimmermann and Eguiluz [Phys. Rev. E72, 056118 (2005)] is established. Network adaptation is the manner in which an existing link between two agents is destroyed and how a new one is established to replace it. The strategy is defined as whether an agent offers cooperation (C) or defection (D) . Both the networks and strategy are synchronously renovated in a simulation time step. A series of numerical experiments, considering various 2 x 2 game structures, reveals that the proposed coevolution mechanism can solve dilemmas in several game classes. The effect of solving a dilemma means mutual-cooperation reciprocity (R reciprocity), which is brought about by emerging several cooperative hub agents who have plenty of links. This effect can be primarily observed in game classes of the prisoner's dilemma and stag hunt. The coevolution mechanism, however, seems counterproductive for game classes of leader and hero, where the alternating reciprocity (ST reciprocity) is meaningful.

Coevolved Mutations Reveal Distinct Architectures for Two Core Proteins in the Bacterial Flagellar Motor

PubMed Central

Pandini, Alessandro; Kleinjung, Jens; Rasool, Shafqat; Khan, Shahid

2015-01-01

Switching of bacterial flagellar rotation is caused by large domain movements of the FliG protein triggered by binding of the signal protein CheY to FliM. FliG and FliM form adjacent multi-subunit arrays within the basal body C-ring. The movements alter the interaction of the FliG C-terminal (FliGC) “torque” helix with the stator complexes. Atomic models based on the Salmonella entrovar C-ring electron microscopy reconstruction have implications for switching, but lack consensus on the relative locations of the FliG armadillo (ARM) domains (amino-terminal (FliGN), middle (FliGM) and FliGC) as well as changes during chemotaxis. The generality of the Salmonella model is challenged by the variation in motor morphology and response between species. We studied coevolved residue mutations to determine the unifying elements of switch architecture. Residue interactions, measured by their coevolution, were formalized as a network, guided by structural data. Our measurements reveal a common design with dedicated switch and motor modules. The FliM middle domain (FliMM) has extensive connectivity most simply explained by conserved intra and inter-subunit contacts. In contrast, FliG has patchy, complex architecture. Conserved structural motifs form interacting nodes in the coevolution network that wire FliMM to the FliGC C-terminal, four-helix motor module (C3-6). FliG C3-6 coevolution is organized around the torque helix, differently from other ARM domains. The nodes form separated, surface-proximal patches that are targeted by deleterious mutations as in other allosteric systems. The dominant node is formed by the EHPQ motif at the FliMMFliGM contact interface and adjacent helix residues at a central location within FliGM. The node interacts with nodes in the N-terminal FliGc α-helix triad (ARM-C) and FliGN. ARM-C, separated from C3-6 by the MFVF motif, has poor intra-network connectivity consistent with its variable orientation revealed by structural data. ARM-C could be the convertor element that provides mechanistic and species diversity. PMID:26561852

Protein-protein interaction network-based detection of functionally similar proteins within species.

PubMed

Song, Baoxing; Wang, Fen; Guo, Yang; Sang, Qing; Liu, Min; Li, Dengyun; Fang, Wei; Zhang, Deli

2012-07-01

Although functionally similar proteins across species have been widely studied, functionally similar proteins within species showing low sequence similarity have not been examined in detail. Identification of these proteins is of significant importance for understanding biological functions, evolution of protein families, progression of co-evolution, and convergent evolution and others which cannot be obtained by detection of functionally similar proteins across species. Here, we explored a method of detecting functionally similar proteins within species based on graph theory. After denoting protein-protein interaction networks using graphs, we split the graphs into subgraphs using the 1-hop method. Proteins with functional similarities in a species were detected using a method of modified shortest path to compare these subgraphs and to find the eligible optimal results. Using seven protein-protein interaction networks and this method, some functionally similar proteins with low sequence similarity that cannot detected by sequence alignment were identified. By analyzing the results, we found that, sometimes, it is difficult to separate homologous from convergent evolution. Evaluation of the performance of our method by gene ontology term overlap showed that the precision of our method was excellent. Copyright © 2012 Wiley Periodicals, Inc.

Accurate Simulation and Detection of Coevolution Signals in Multiple Sequence Alignments

PubMed Central

Ackerman, Sharon H.; Tillier, Elisabeth R.; Gatti, Domenico L.

2012-01-01

Background While the conserved positions of a multiple sequence alignment (MSA) are clearly of interest, non-conserved positions can also be important because, for example, destabilizing effects at one position can be compensated by stabilizing effects at another position. Different methods have been developed to recognize the evolutionary relationship between amino acid sites, and to disentangle functional/structural dependencies from historical/phylogenetic ones. Methodology/Principal Findings We have used two complementary approaches to test the efficacy of these methods. In the first approach, we have used a new program, MSAvolve, for the in silico evolution of MSAs, which records a detailed history of all covarying positions, and builds a global coevolution matrix as the accumulated sum of individual matrices for the positions forced to co-vary, the recombinant coevolution, and the stochastic coevolution. We have simulated over 1600 MSAs for 8 protein families, which reflect sequences of different sizes and proteins with widely different functions. The calculated coevolution matrices were compared with the coevolution matrices obtained for the same evolved MSAs with different coevolution detection methods. In a second approach we have evaluated the capacity of the different methods to predict close contacts in the representative X-ray structures of an additional 150 protein families using only experimental MSAs. Conclusions/Significance Methods based on the identification of global correlations between pairs were found to be generally superior to methods based only on local correlations in their capacity to identify coevolving residues using either simulated or experimental MSAs. However, the significant variability in the performance of different methods with different proteins suggests that the simulation of MSAs that replicate the statistical properties of the experimental MSA can be a valuable tool to identify the coevolution detection method that is most effective in each case. PMID:23091608

Network analysis reveals the recognition mechanism for complex formation of mannose-binding lectins

NASA Astrophysics Data System (ADS)

Jian, Yiren; Zhao, Yunjie; Zeng, Chen

The specific carbohydrate binding of lectin makes the protein a powerful molecular tool for various applications including cancer cell detection due to its glycoprotein profile on the cell surface. Most biologically active lectins are dimeric. To understand the structure-function relation of lectin complex, it is essential to elucidate the short- and long-range driving forces behind the dimer formation. Here we report our molecular dynamics simulations and associated dynamical network analysis on a particular lectin, i.e., the mannose-binding lectin from garlic. Our results, further supported by sequence coevolution analysis, shed light on how different parts of the complex communicate with each other. We propose a general framework for deciphering the recognition mechanism underlying protein-protein interactions that may have potential applications in signaling pathways.

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.

Coevolution of metabolic networks and membranes: the scenario of progressive sequestration.

PubMed

Szathmáry, Eörs

2007-10-29

Many regard metabolism as one of the central phenomena (or criteria) of life. Yet, the earliest infrabiological systems may have been devoid of metabolism: such systems would have been extreme heterotrophs. We do not know what level of complexity is attainable for chemical systems without enzymatic aid. Lack of template-instructed enzymatic catalysis may put a ceiling on complexity owing to inevitable spontaneous decay and wear and tear of chemodynamical machines. Views on the origin of metabolism critically depend on the assumptions concerning the sites of synthesis and consumption of organic compounds. If these sites are different, non-enzymatic origin of autotrophy is excluded. Whether autotrophy is secondary or not, it seems that protocell boundaries may have become more selective with time, concurrent with the enzymatization of the metabolic network. Primary heterotrophy and autotrophy imply pathway innovation and retention, respectively. The idea of metabolism-membrane coevolution leads to a scenario of progressive sequestration of the emerging living system from its exterior milieu. Comparative data on current protein enzymes may shed some light on such a primeval process by analogy, since two main ideas about enzymatization (the retroevolution and the patchwork scenarios) may not necessarily be mutually exclusive and the earliest enzymatic system may have used ribozymes rather than proteins.

Co-evolution of electric and telecommunications networks

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

Rivkin, S.R.

1998-05-01

There are potentially significant societal benefits in co-evolution between electricity and telecommunications in the areas of common infrastructure, accelerated deployment of distributed energy, tighter integration of information flow for energy management and distribution, and improved customer care. With due regard for natural processes that are more potent than any regulation and more real than any ideology, the gains from co-evolution would far outweigh the attenuated and speculative savings from restructuring of electricity that is too simplistic.

Studying the co-evolution of protein families with the Mirrortree web server.

PubMed

Ochoa, David; Pazos, Florencio

2010-05-15

The Mirrortree server allows to graphically and interactively study the co-evolution of two protein families, and investigate their possible interactions and functional relationships in a taxonomic context. The server includes the possibility of starting from single sequences and hence it can be used by non-expert users. The web server is freely available at http://csbg.cnb.csic.es/mtserver. It was tested in the main web browsers. Adobe Flash Player is required at the client side to perform the interactive assessment of co-evolution. pazos@cnb.csic.es Supplementary data are available at Bioinformatics online.

Mechanical Network in Titin Immunoglobulin from Force Distribution Analysis

PubMed Central

Wilmanns, Matthias; Gräter, Frauke

2009-01-01

The role of mechanical force in cellular processes is increasingly revealed by single molecule experiments and simulations of force-induced transitions in proteins. How the applied force propagates within proteins determines their mechanical behavior yet remains largely unknown. We present a new method based on molecular dynamics simulations to disclose the distribution of strain in protein structures, here for the newly determined high-resolution crystal structure of I27, a titin immunoglobulin (IG) domain. We obtain a sparse, spatially connected, and highly anisotropic mechanical network. This allows us to detect load-bearing motifs composed of interstrand hydrogen bonds and hydrophobic core interactions, including parts distal to the site to which force was applied. The role of the force distribution pattern for mechanical stability is tested by in silico unfolding of I27 mutants. We then compare the observed force pattern to the sparse network of coevolved residues found in this family. We find a remarkable overlap, suggesting the force distribution to reflect constraints for the evolutionary design of mechanical resistance in the IG family. The force distribution analysis provides a molecular interpretation of coevolution and opens the road to the study of the mechanism of signal propagation in proteins in general. PMID:19282960

Structure-based Markov random field model for representing evolutionary constraints on functional sites.

PubMed

Jeong, Chan-Seok; Kim, Dongsup

2016-02-24

Elucidating the cooperative mechanism of interconnected residues is an important component toward understanding the biological function of a protein. Coevolution analysis has been developed to model the coevolutionary information reflecting structural and functional constraints. Recently, several methods have been developed based on a probabilistic graphical model called the Markov random field (MRF), which have led to significant improvements for coevolution analysis; however, thus far, the performance of these models has mainly been assessed by focusing on the aspect of protein structure. In this study, we built an MRF model whose graphical topology is determined by the residue proximity in the protein structure, and derived a novel positional coevolution estimate utilizing the node weight of the MRF model. This structure-based MRF method was evaluated for three data sets, each of which annotates catalytic site, allosteric site, and comprehensively determined functional site information. We demonstrate that the structure-based MRF architecture can encode the evolutionary information associated with biological function. Furthermore, we show that the node weight can more accurately represent positional coevolution information compared to the edge weight. Lastly, we demonstrate that the structure-based MRF model can be reliably built with only a few aligned sequences in linear time. The results show that adoption of a structure-based architecture could be an acceptable approximation for coevolution modeling with efficient computation complexity.

Limited ability driven phase transitions in the coevolution process in Axelrod's model

NASA Astrophysics Data System (ADS)

Wang, Bing; Han, Yuexing; Chen, Luonan; Aihara, Kazuyuki

2009-04-01

We study the coevolution process in Axelrod's model by taking into account of agents' abilities to access information, which is described by a parameter α to control the geographical range of communication. We observe two kinds of phase transitions in both cultural domains and network fragments, which depend on the parameter α. By simulation, we find that not all rewiring processes pervade the dissemination of culture, that is, a very limited ability to access information constrains the cultural dissemination, while an exceptional ability to access information aids the dissemination of culture. Furthermore, by analyzing the network characteristics at the frozen states, we find that there exists a stage at which the network develops to be a small-world network with community structures.

Plastid–Nuclear Interaction and Accelerated Coevolution in Plastid Ribosomal Genes in Geraniaceae

PubMed Central

Weng, Mao-Lun; Ruhlman, Tracey A.; Jansen, Robert K.

2016-01-01

Plastids and mitochondria have many protein complexes that include subunits encoded by organelle and nuclear genomes. In animal cells, compensatory evolution between mitochondrial and nuclear-encoded subunits was identified and the high mitochondrial mutation rates were hypothesized to drive compensatory evolution in nuclear genomes. In plant cells, compensatory evolution between plastid and nucleus has rarely been investigated in a phylogenetic framework. To investigate plastid–nuclear coevolution, we focused on plastid ribosomal protein genes that are encoded by plastid and nuclear genomes from 27 Geraniales species. Substitution rates were compared for five sets of genes representing plastid- and nuclear-encoded ribosomal subunit proteins targeted to the cytosol or the plastid as well as nonribosomal protein controls. We found that nonsynonymous substitution rates (dN) and the ratios of nonsynonymous to synonymous substitution rates (ω) were accelerated in both plastid- (CpRP) and nuclear-encoded subunits (NuCpRP) of the plastid ribosome relative to control sequences. Our analyses revealed strong signals of cytonuclear coevolution between plastid- and nuclear-encoded subunits, in which nonsynonymous substitutions in CpRP and NuCpRP tend to occur along the same branches in the Geraniaceae phylogeny. This coevolution pattern cannot be explained by physical interaction between amino acid residues. The forces driving accelerated coevolution varied with cellular compartment of the sequence. Increased ω in CpRP was mainly due to intensified positive selection whereas increased ω in NuCpRP was caused by relaxed purifying selection. In addition, the many indels identified in plastid rRNA genes in Geraniaceae may have contributed to changes in plastid subunits. PMID:27190001

Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

PubMed Central

Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

2006-01-01

Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097

Sequence, structure and function relationships in flaviviruses as assessed by evolutive aspects of its conserved non-structural protein domains.

PubMed

da Fonseca, Néli José; Lima Afonso, Marcelo Querino; Pedersolli, Natan Gonçalves; de Oliveira, Lucas Carrijo; Andrade, Dhiego Souto; Bleicher, Lucas

2017-10-28

Flaviviruses are responsible for serious diseases such as dengue, yellow fever, and zika fever. Their genomes encode a polyprotein which, after cleavage, results in three structural and seven non-structural proteins. Homologous proteins can be studied by conservation and coevolution analysis as detected in multiple sequence alignments, usually reporting positions which are strictly necessary for the structure and/or function of all members in a protein family or which are involved in a specific sub-class feature requiring the coevolution of residue sets. This study provides a complete conservation and coevolution analysis on all flaviviruses non-structural proteins, with results mapped on all well-annotated available sequences. A literature review on the residues found in the analysis enabled us to compile available information on their roles and distribution among different flaviviruses. Also, we provide the mapping of conserved and coevolved residues for all sequences currently in SwissProt as a supplementary material, so that particularities in different viruses can be easily analyzed. Copyright © 2017 Elsevier Inc. All rights reserved.

Incorporating information on predicted solvent accessibility to the co-evolution-based study of protein interactions.

PubMed

Ochoa, David; García-Gutiérrez, Ponciano; Juan, David; Valencia, Alfonso; Pazos, Florencio

2013-01-27

A widespread family of methods for studying and predicting protein interactions using sequence information is based on co-evolution, quantified as similarity of phylogenetic trees. Part of the co-evolution observed between interacting proteins could be due to co-adaptation caused by inter-protein contacts. In this case, the co-evolution is expected to be more evident when evaluated on the surface of the proteins or the internal layers close to it. In this work we study the effect of incorporating information on predicted solvent accessibility to three methods for predicting protein interactions based on similarity of phylogenetic trees. We evaluate the performance of these methods in predicting different types of protein associations when trees based on positions with different characteristics of predicted accessibility are used as input. We found that predicted accessibility improves the results of two recent versions of the mirrortree methodology in predicting direct binary physical interactions, while it neither improves these methods, nor the original mirrortree method, in predicting other types of interactions. That improvement comes at no cost in terms of applicability since accessibility can be predicted for any sequence. We also found that predictions of protein-protein interactions are improved when multiple sequence alignments with a richer representation of sequences (including paralogs) are incorporated in the accessibility prediction.

Conservation of coevolving protein interfaces bridges prokaryote-eukaryote homologies in the twilight zone.

PubMed

Rodriguez-Rivas, Juan; Marsili, Simone; Juan, David; Valencia, Alfonso

2016-12-27

Protein-protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein-protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein-protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein-protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach.

Plastid-Nuclear Interaction and Accelerated Coevolution in Plastid Ribosomal Genes in Geraniaceae.

PubMed

Weng, Mao-Lun; Ruhlman, Tracey A; Jansen, Robert K

2016-06-27

Plastids and mitochondria have many protein complexes that include subunits encoded by organelle and nuclear genomes. In animal cells, compensatory evolution between mitochondrial and nuclear-encoded subunits was identified and the high mitochondrial mutation rates were hypothesized to drive compensatory evolution in nuclear genomes. In plant cells, compensatory evolution between plastid and nucleus has rarely been investigated in a phylogenetic framework. To investigate plastid-nuclear coevolution, we focused on plastid ribosomal protein genes that are encoded by plastid and nuclear genomes from 27 Geraniales species. Substitution rates were compared for five sets of genes representing plastid- and nuclear-encoded ribosomal subunit proteins targeted to the cytosol or the plastid as well as nonribosomal protein controls. We found that nonsynonymous substitution rates (dN) and the ratios of nonsynonymous to synonymous substitution rates (ω) were accelerated in both plastid- (CpRP) and nuclear-encoded subunits (NuCpRP) of the plastid ribosome relative to control sequences. Our analyses revealed strong signals of cytonuclear coevolution between plastid- and nuclear-encoded subunits, in which nonsynonymous substitutions in CpRP and NuCpRP tend to occur along the same branches in the Geraniaceae phylogeny. This coevolution pattern cannot be explained by physical interaction between amino acid residues. The forces driving accelerated coevolution varied with cellular compartment of the sequence. Increased ω in CpRP was mainly due to intensified positive selection whereas increased ω in NuCpRP was caused by relaxed purifying selection. In addition, the many indels identified in plastid rRNA genes in Geraniaceae may have contributed to changes in plastid subunits. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Sequence co-evolution gives 3D contacts and structures of protein complexes

PubMed Central

Hopf, Thomas A; Schärfe, Charlotta P I; Rodrigues, João P G L M; Green, Anna G; Kohlbacher, Oliver; Sander, Chris; Bonvin, Alexandre M J J; Marks, Debora S

2014-01-01

Protein–protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein–protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein–protein interaction networks and used for interaction predictions at residue resolution. DOI: http://dx.doi.org/10.7554/eLife.03430.001 PMID:25255213

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure

NASA Astrophysics Data System (ADS)

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Engemann, Denis A.; Levermann, Anders

2016-08-01

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalized clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking.

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure.

PubMed

Schleussner, Carl-Friedrich; Donges, Jonathan F; Engemann, Denis A; Levermann, Anders

2016-08-11

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalized clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking.

Interfacing Network Simulations and Empirical Data

DTIC Science & Technology

2009-05-01

contraceptive innovations in the Cameroon. He found that real-world adoption rates did not follow simulation models when the network relationships were...Analysis of the Coevolution of Adolescents ’ Friendship Networks, Taste in Music, and Alcohol Consumption. Methodology, 2: 48-56. Tichy, N.M., Tushman

Detecting Coevolution in Mammalian Sperm–Egg Fusion Proteins

PubMed Central

CLAW, KATRINA G.; GEORGE, RENEE D.; SWANSON, WILLIE J.

2018-01-01

SUMMARY Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm–egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm–egg proteins; interacting sperm–egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm–egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm–egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm–egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm–egg protein pairs. PMID:24644026

Detecting coevolution in mammalian sperm-egg fusion proteins.

PubMed

Claw, Katrina G; George, Renee D; Swanson, Willie J

2014-06-01

Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm-egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm-egg proteins; interacting sperm-egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm-egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm-egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm-egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm-egg protein pairs. © 2014 Wiley Periodicals, Inc.

Conservation of coevolving protein interfaces bridges prokaryote–eukaryote homologies in the twilight zone

PubMed Central

Rodriguez-Rivas, Juan; Marsili, Simone; Juan, David; Valencia, Alfonso

2016-01-01

Protein–protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein–protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein–protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein–protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach. PMID:27965389

Clustered marginalization of minorities during social transitions induced by co-evolution of behaviour and network structure

PubMed Central

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Engemann, Denis A.; Levermann, Anders

2016-01-01

Large-scale transitions in societies are associated with both individual behavioural change and restructuring of the social network. These two factors have often been considered independently, yet recent advances in social network research challenge this view. Here we show that common features of societal marginalization and clustering emerge naturally during transitions in a co-evolutionary adaptive network model. This is achieved by explicitly considering the interplay between individual interaction and a dynamic network structure in behavioural selection. We exemplify this mechanism by simulating how smoking behaviour and the network structure get reconfigured by changing social norms. Our results are consistent with empirical findings: The prevalence of smoking was reduced, remaining smokers were preferentially connected among each other and formed increasingly marginalized clusters. We propose that self-amplifying feedbacks between individual behaviour and dynamic restructuring of the network are main drivers of the transition. This generative mechanism for co-evolution of individual behaviour and social network structure may apply to a wide range of examples beyond smoking. PMID:27510641

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis.

PubMed

Bai, Fang; Morcos, Faruck; Cheng, Ryan R; Jiang, Hualiang; Onuchic, José N

2016-12-13

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

ComplexContact: a web server for inter-protein contact prediction using deep learning.

PubMed

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

High-confidence prediction of global interactomes based on genome-wide coevolutionary networks

PubMed Central

Juan, David; Pazos, Florencio; Valencia, Alfonso

2008-01-01

Interacting or functionally related protein families tend to have similar phylogenetic trees. Based on this observation, techniques have been developed to predict interaction partners. The observed degree of similarity between the phylogenetic trees of two proteins is the result of many different factors besides the actual interaction or functional relationship between them. Such factors influence the performance of interaction predictions. One aspect that can influence this similarity is related to the fact that a given protein interacts with many others, and hence it must adapt to all of them. Accordingly, the interaction or coadaptation signal within its tree is a composite of the influence of all of the interactors. Here, we introduce a new estimator of coevolution to overcome this and other problems. Instead of relying on the individual value of tree similarity between two proteins, we use the whole network of similarities between all of the pairs of proteins within a genome to reassess the similarity of that pair, thereby taking into account its coevolutionary context. We show that this approach offers a substantial improvement in interaction prediction performance, providing a degree of accuracy/coverage comparable with, or in some cases better than, that of experimental techniques. Moreover, important information on the structure, function, and evolution of macromolecular complexes can be inferred with this methodology. PMID:18199838

High-confidence prediction of global interactomes based on genome-wide coevolutionary networks.

PubMed

Juan, David; Pazos, Florencio; Valencia, Alfonso

2008-01-22

Interacting or functionally related protein families tend to have similar phylogenetic trees. Based on this observation, techniques have been developed to predict interaction partners. The observed degree of similarity between the phylogenetic trees of two proteins is the result of many different factors besides the actual interaction or functional relationship between them. Such factors influence the performance of interaction predictions. One aspect that can influence this similarity is related to the fact that a given protein interacts with many others, and hence it must adapt to all of them. Accordingly, the interaction or coadaptation signal within its tree is a composite of the influence of all of the interactors. Here, we introduce a new estimator of coevolution to overcome this and other problems. Instead of relying on the individual value of tree similarity between two proteins, we use the whole network of similarities between all of the pairs of proteins within a genome to reassess the similarity of that pair, thereby taking into account its coevolutionary context. We show that this approach offers a substantial improvement in interaction prediction performance, providing a degree of accuracy/coverage comparable with, or in some cases better than, that of experimental techniques. Moreover, important information on the structure, function, and evolution of macromolecular complexes can be inferred with this methodology.

Coevolutionary modeling of protein sequences: Predicting structure, function, and mutational landscapes

NASA Astrophysics Data System (ADS)

Weigt, Martin

Over the last years, biological research has been revolutionized by experimental high-throughput techniques, in particular by next-generation sequencing technology. Unprecedented amounts of data are accumulating, and there is a growing request for computational methods unveiling the information hidden in raw data, thereby increasing our understanding of complex biological systems. Statistical-physics models based on the maximum-entropy principle have, in the last few years, played an important role in this context. To give a specific example, proteins and many non-coding RNA show a remarkable degree of structural and functional conservation in the course of evolution, despite a large variability in amino acid sequences. We have developed a statistical-mechanics inspired inference approach - called Direct-Coupling Analysis - to link this sequence variability (easy to observe in sequence alignments, which are available in public sequence databases) to bio-molecular structure and function. In my presentation I will show, how this methodology can be used (i) to infer contacts between residues and thus to guide tertiary and quaternary protein structure prediction and RNA structure prediction, (ii) to discriminate interacting from non-interacting protein families, and thus to infer conserved protein-protein interaction networks, and (iii) to reconstruct mutational landscapes and thus to predict the phenotypic effect of mutations. References [1] M. Figliuzzi, H. Jacquier, A. Schug, O. Tenaillon and M. Weigt ''Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1'', Mol. Biol. Evol. (2015), doi: 10.1093/molbev/msv211 [2] E. De Leonardis, B. Lutz, S. Ratz, S. Cocco, R. Monasson, A. Schug, M. Weigt ''Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction'', Nucleic Acids Research (2015), doi: 10.1093/nar/gkv932 [3] F. Morcos, A. Pagnani, B. Lunt, A. Bertolino, D. Marks, C. Sander, R. Zecchina, J.N. Onuchic, T. Hwa, M. Weigt, ''Direct-coupling analysis of residue co-evolution captures native contacts across many protein families'', Proc. Natl. Acad. Sci. 108, E1293-E1301 (2011).

Coevolution of Vertex Weights Resolves Social Dilemma in Spatial Networks.

PubMed

Shen, Chen; Chu, Chen; Guo, Hao; Shi, Lei; Duan, Jiangyan

2017-11-09

In realistic social system, the role or influence of each individual varies and adaptively changes in time in the population. Inspired by this fact, we thus consider a new coevolution setup of game strategy and vertex weight on a square lattice. In detail, we model the structured population on a square lattice, on which the role or influence of each individual is depicted by vertex weight, and the prisoner's dilemma game has been applied to describe the social dilemma of pairwise interactions of players. Through numerical simulation, we conclude that our coevolution setup can promote the evolution of cooperation effectively. Especially, there exists a moderate value of δ for each ε that can warrant an optimal resolution of social dilemma. For a further understanding of these results, we find that intermediate value of δ enables the strongest heterogeneous distribution of vertex weight. We hope our coevolution setup of vertex weight will provide new insight for the future research.

Phylogenetically informed logic relationships improve detection of biological network organization

PubMed Central

2011-01-01

Background A "phylogenetic profile" refers to the presence or absence of a gene across a set of organisms, and it has been proven valuable for understanding gene functional relationships and network organization. Despite this success, few studies have attempted to search beyond just pairwise relationships among genes. Here we search for logic relationships involving three genes, and explore its potential application in gene network analyses. Results Taking advantage of a phylogenetic matrix constructed from the large orthologs database Roundup, we invented a method to create balanced profiles for individual triplets of genes that guarantee equal weight on the different phylogenetic scenarios of coevolution between genes. When we applied this idea to LAPP, the method to search for logic triplets of genes, the balanced profiles resulted in significant performance improvement and the discovery of hundreds of thousands more putative triplets than unadjusted profiles. We found that logic triplets detected biological network organization and identified key proteins and their functions, ranging from neighbouring proteins in local pathways, to well separated proteins in the whole pathway, and to the interactions among different pathways at the system level. Finally, our case study suggested that the directionality in a logic relationship and the profile of a triplet could disclose the connectivity between the triplet and surrounding networks. Conclusion Balanced profiles are superior to the raw profiles employed by traditional methods of phylogenetic profiling in searching for high order gene sets. Gene triplets can provide valuable information in detection of biological network organization and identification of key genes at different levels of cellular interaction. PMID:22172058

Suppressing disease spreading by using information diffusion on multiplex networks.

PubMed

Wang, Wei; Liu, Quan-Hui; Cai, Shi-Min; Tang, Ming; Braunstein, Lidia A; Stanley, H Eugene

2016-07-06

Although there is always an interplay between the dynamics of information diffusion and disease spreading, the empirical research on the systemic coevolution mechanisms connecting these two spreading dynamics is still lacking. Here we investigate the coevolution mechanisms and dynamics between information and disease spreading by utilizing real data and a proposed spreading model on multiplex network. Our empirical analysis finds asymmetrical interactions between the information and disease spreading dynamics. Our results obtained from both the theoretical framework and extensive stochastic numerical simulations suggest that an information outbreak can be triggered in a communication network by its own spreading dynamics or by a disease outbreak on a contact network, but that the disease threshold is not affected by information spreading. Our key finding is that there is an optimal information transmission rate that markedly suppresses the disease spreading. We find that the time evolution of the dynamics in the proposed model qualitatively agrees with the real-world spreading processes at the optimal information transmission rate.

Effects of adaptive degrees of trust on coevolution of quantum strategies on scale-free networks.

PubMed

Li, Qiang; Chen, Minyou; Perc, Matjaž; Iqbal, Azhar; Abbott, Derek

2013-10-15

We study the impact of adaptive degrees of trust on the evolution of cooperation in the quantum prisoner's dilemma game. In addition to the strategies, links between players are also subject to evolution. Starting with a scale-free interaction network, players adjust trust towards their neighbors based on received payoffs. The latter governs the strategy adoption process, while trust governs the rewiring of links. As soon as the degree of trust towards a neighbor drops to zero, the link is rewired to another randomly chosen player within the network. We find that for small temptations to defect cooperators always dominate, while for intermediate and strong temptations a single quantum strategy is able to outperform all other strategies. In general, reciprocal trust remains within close relationships and favors the dominance of a single strategy. Due to coevolution, the power-law degree distributions transform to Poisson distributions.

Effects of adaptive degrees of trust on coevolution of quantum strategies on scale-free networks

NASA Astrophysics Data System (ADS)

Li, Qiang; Chen, Minyou; Perc, Matjaž; Iqbal, Azhar; Abbott, Derek

2013-10-01

We study the impact of adaptive degrees of trust on the evolution of cooperation in the quantum prisoner's dilemma game. In addition to the strategies, links between players are also subject to evolution. Starting with a scale-free interaction network, players adjust trust towards their neighbors based on received payoffs. The latter governs the strategy adoption process, while trust governs the rewiring of links. As soon as the degree of trust towards a neighbor drops to zero, the link is rewired to another randomly chosen player within the network. We find that for small temptations to defect cooperators always dominate, while for intermediate and strong temptations a single quantum strategy is able to outperform all other strategies. In general, reciprocal trust remains within close relationships and favors the dominance of a single strategy. Due to coevolution, the power-law degree distributions transform to Poisson distributions.

Evolution-Based Functional Decomposition of Proteins

PubMed Central

Rivoire, Olivier; Reynolds, Kimberly A.; Ranganathan, Rama

2016-01-01

The essential biological properties of proteins—folding, biochemical activities, and the capacity to adapt—arise from the global pattern of interactions between amino acid residues. The statistical coupling analysis (SCA) is an approach to defining this pattern that involves the study of amino acid coevolution in an ensemble of sequences comprising a protein family. This approach indicates a functional architecture within proteins in which the basic units are coupled networks of amino acids termed sectors. This evolution-based decomposition has potential for new understandings of the structural basis for protein function. To facilitate its usage, we present here the principles and practice of the SCA and introduce new methods for sector analysis in a python-based software package (pySCA). We show that the pattern of amino acid interactions within sectors is linked to the divergence of functional lineages in a multiple sequence alignment—a model for how sector properties might be differentially tuned in members of a protein family. This work provides new tools for studying proteins and for generally testing the concept of sectors as the principal units of function and adaptive variation. PMID:27254668

Dynamic self-guiding analysis of Alzheimer's disease

PubMed Central

Kurakin, Alexei; Bredesen, Dale E.

2015-01-01

We applied a self-guiding evolutionary algorithm to initiate the synthesis of the Alzheimer's disease-related data and literature. A protein interaction network associated with amyloid-beta precursor protein (APP) and a seed model that treats Alzheimer's disease as progressive dysregulation of APP-associated signaling were used as dynamic “guides” and structural “filters” in the recursive search, analysis, and assimilation of data to drive the evolution of the seed model in size, detail, and complexity. Analysis of data and literature across sub-disciplines and system-scale discovery platforms suggests a key role of dynamic cytoskeletal connectivity in the stability, plasticity, and performance of multicellular networks and architectures. Chronic impairment and/or dysregulation of cell adhesions/synapses, cytoskeletal networks, and/or reversible epithelial-to-mesenchymal-like transitions, which enable and mediate the stable and coherent yet dynamic and reconfigurable multicellular architectures, may lead to the emergence and persistence of the disordered, wound-like pockets/microenvironments of chronically disconnected cells. Such wound-like microenvironments support and are supported by pro-inflammatory, pro-secretion, de-differentiated cellular phenotypes with altered metabolism and signaling. The co-evolution of wound-like microenvironments and their inhabitants may lead to the selection and stabilization of degenerated cellular phenotypes, via acquisition of epigenetic modifications and mutations, which eventually result in degenerative disorders such as cancer and Alzheimer's disease. PMID:26041885

Opinion diversity and community formation in adaptive networks

NASA Astrophysics Data System (ADS)

Yu, Y.; Xiao, G.; Li, G.; Tay, W. P.; Teoh, H. F.

2017-10-01

It is interesting and of significant importance to investigate how network structures co-evolve with opinions. In this article, we show that, a simple model integrating consensus formation, link rewiring, and opinion change allows complex system dynamics to emerge, driving the system into a dynamic equilibrium with the co-existence of diversified opinions. Specifically, similar opinion holders may form into communities yet with no strict community consensus; and rather than being separated into disconnected communities, different communities are connected by a non-trivial proportion of inter-community links. More importantly, we show that the complex dynamics may lead to different numbers of communities at the steady state with a given tolerance between different opinion holders. We construct a framework for theoretically analyzing the co-evolution process. Theoretical analysis and extensive simulation results reveal some useful insights into the complex co-evolution process, including the formation of dynamic equilibrium, the transition between different steady states with different numbers of communities, and the dynamics between opinion distribution and network modularity.

Coevolution of cooperation and network structure under natural selection

NASA Astrophysics Data System (ADS)

Yang, D.-P.; Lin, H.; Shuai, J. W.

2011-02-01

A coevolution model by coupling mortality and fertility selection is introduced to investigate the evolution of cooperation and network structure in the prisoner's dilemma game. The cooperation level goes through a continuous phase transition vs. defection temptation b for low mortality selection intensity β and through a discontinuous one for infinite β. The cooperation level is enhanced most at β≈1 for any b. The local and global properties of the network structure, such as cluster and cooperating k-core, are investigated for the understanding of cooperation evolution. Cooperation is promoted by forming a tight cooperating k-core at moderate β, but too large β will destroy the cooperating k-core rapidly resulting in a rapid drop of the cooperation level. Importantly, the infinite β changes the normalized sucker's payoff S from 0 to 1-b and its dynamics of the cooperation level undergoes a very slow power-law decay, which leads the evolution into the regime of neutral evolution.

Analysis of deep learning methods for blind protein contact prediction in CASP12.

PubMed

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2018-03-01

Here we present the results of protein contact prediction achieved in CASP12 by our RaptorX-Contact server, which is an early implementation of our deep learning method for contact prediction. On a set of 38 free-modeling target domains with a median family size of around 58 effective sequences, our server obtained an average top L/5 long- and medium-range contact accuracy of 47% and 44%, respectively (L = length). A complete implementation has an average accuracy of 59% and 57%, respectively. Our deep learning method formulates contact prediction as a pixel-level image labeling problem and simultaneously predicts all residue pairs of a protein using a combination of two deep residual neural networks, taking as input the residue conservation information, predicted secondary structure and solvent accessibility, contact potential, and coevolution information. Our approach differs from existing methods mainly in (1) formulating contact prediction as a pixel-level image labeling problem instead of an image-level classification problem; (2) simultaneously predicting all contacts of an individual protein to make effective use of contact occurrence patterns; and (3) integrating both one-dimensional and two-dimensional deep convolutional neural networks to effectively learn complex sequence-structure relationship including high-order residue correlation. This paper discusses the RaptorX-Contact pipeline, both contact prediction and contact-based folding results, and finally the strength and weakness of our method. © 2017 Wiley Periodicals, Inc.

Coordinated Rates of Evolution between Interacting Plastid and Nuclear Genes in Geraniaceae

PubMed Central

Zhang, Jin; Ruhlman, Tracey A.; Sabir, Jamal; Blazier, J. Chris; Jansen, Robert K.

2015-01-01

Although gene coevolution has been widely observed within individuals and between different organisms, rarely has this phenomenon been investigated within a phylogenetic framework. The Geraniaceae is an attractive system in which to study plastid-nuclear genome coevolution due to the highly elevated evolutionary rates in plastid genomes. In plants, the plastid-encoded RNA polymerase (PEP) is a protein complex composed of subunits encoded by both plastid (rpoA, rpoB, rpoC1, and rpoC2) and nuclear genes (sig1-6). We used transcriptome and genomic data for 27 species of Geraniales in a systematic evaluation of coevolution between genes encoding subunits of the PEP holoenzyme. We detected strong correlations of dN (nonsynonymous substitutions) but not dS (synonymous substitutions) within rpoB/sig1 and rpoC2/sig2, but not for other plastid/nuclear gene pairs, and identified the correlation of dN/dS ratio between rpoB/C1/C2 and sig1/5/6, rpoC1/C2 and sig2, and rpoB/C2 and sig3 genes. Correlated rates between interacting plastid and nuclear sequences across the Geraniales could result from plastid-nuclear genome coevolution. Analyses of coevolved amino acid positions suggest that structurally mediated coevolution is not the major driver of plastid-nuclear coevolution. The detection of strong correlation of evolutionary rates between SIG and RNAP genes suggests a plausible explanation for plastome-genome incompatibility in Geraniaceae. PMID:25724640

Duplicate Abalone Egg Coat Proteins Bind Sperm Lysin Similarly, but Evolve Oppositely, Consistent with Molecular Mimicry at Fertilization

PubMed Central

Aagaard, Jan E.; Springer, Stevan A.; Soelberg, Scott D.; Swanson, Willie J.

2013-01-01

Sperm and egg proteins constitute a remarkable paradigm in evolutionary biology: despite their fundamental role in mediating fertilization (suggesting stasis), some of these molecules are among the most rapidly evolving ones known, and their divergence can lead to reproductive isolation. Because of strong selection to maintain function among interbreeding individuals, interacting fertilization proteins should also exhibit a strong signal of correlated divergence among closely related species. We use evidence of such molecular co-evolution to target biochemical studies of fertilization in North Pacific abalone (Haliotis spp.), a model system of reproductive protein evolution. We test the evolutionary rates (d N/d S) of abalone sperm lysin and two duplicated egg coat proteins (VERL and VEZP14), and find a signal of co-evolution specific to ZP-N, a putative sperm binding motif previously identified by homology modeling. Positively selected residues in VERL and VEZP14 occur on the same face of the structural model, suggesting a common mode of interaction with sperm lysin. We test this computational prediction biochemically, confirming that the ZP-N motif is sufficient to bind lysin and that the affinities of VERL and VEZP14 are comparable. However, we also find that on phylogenetic lineages where lysin and VERL evolve rapidly, VEZP14 evolves slowly, and vice versa. We describe a model of sexual conflict that can recreate this pattern of anti-correlated evolution by assuming that VEZP14 acts as a VERL mimic, reducing the intensity of sexual conflict and slowing the co-evolution of lysin and VERL. PMID:23408913

Assembling the Tat protein translocase

PubMed Central

Alcock, Felicity; Stansfeld, Phillip J; Basit, Hajra; Habersetzer, Johann; Baker, Matthew AB; Palmer, Tracy; Wallace, Mark I; Berks, Ben C

2016-01-01

The twin-arginine protein translocation system (Tat) transports folded proteins across the bacterial cytoplasmic membrane and the thylakoid membranes of plant chloroplasts. The Tat transporter is assembled from multiple copies of the membrane proteins TatA, TatB, and TatC. We combine sequence co-evolution analysis, molecular simulations, and experimentation to define the interactions between the Tat proteins of Escherichia coli at molecular-level resolution. In the TatBC receptor complex the transmembrane helix of each TatB molecule is sandwiched between two TatC molecules, with one of the inter-subunit interfaces incorporating a functionally important cluster of interacting polar residues. Unexpectedly, we find that TatA also associates with TatC at the polar cluster site. Our data provide a structural model for assembly of the active Tat translocase in which substrate binding triggers replacement of TatB by TatA at the polar cluster site. Our work demonstrates the power of co-evolution analysis to predict protein interfaces in multi-subunit complexes. DOI: http://dx.doi.org/10.7554/eLife.20718.001 PMID:27914200

Characterizing the roles of changing population size and selection on the evolution of flux control in metabolic pathways.

PubMed

Orlenko, Alena; Chi, Peter B; Liberles, David A

2017-05-25

Understanding the genotype-phenotype map is fundamental to our understanding of genomes. Genes do not function independently, but rather as part of networks or pathways. In the case of metabolic pathways, flux through the pathway is an important next layer of biological organization up from the individual gene or protein. Flux control in metabolic pathways, reflecting the importance of mutation to individual enzyme genes, may be evolutionarily variable due to the role of mutation-selection-drift balance. The evolutionary stability of rate limiting steps and the patterns of inter-molecular co-evolution were evaluated in a simulated pathway with a system out of equilibrium due to fluctuating selection, population size, or positive directional selection, to contrast with those under stabilizing selection. Depending upon the underlying population genetic regime, fluctuating population size was found to increase the evolutionary stability of rate limiting steps in some scenarios. This result was linked to patterns of local adaptation of the population. Further, during positive directional selection, as with more complex mutational scenarios, an increase in the observation of inter-molecular co-evolution was observed. Differences in patterns of evolution when systems are in and out of equilibrium, including during positive directional selection may lead to predictable differences in observed patterns for divergent evolutionary scenarios. In particular, this result might be harnessed to detect differences between compensatory processes and directional processes at the pathway level based upon evolutionary observations in individual proteins. Detecting functional shifts in pathways reflects an important milestone in predicting when changes in genotypes result in changes in phenotypes.

Practical aspects of protein co-evolution.

PubMed

Ochoa, David; Pazos, Florencio

2014-01-01

Co-evolution is a fundamental aspect of Evolutionary Theory. At the molecular level, co-evolutionary linkages between protein families have been used as indicators of protein interactions and functional relationships from long ago. Due to the complexity of the problem and the amount of genomic data required for these approaches to achieve good performances, it took a relatively long time from the appearance of the first ideas and concepts to the quotidian application of these approaches and their incorporation to the standard toolboxes of bioinformaticians and molecular biologists. Today, these methodologies are mature (both in terms of performance and usability/implementation), and the genomic information that feeds them large enough to allow their general application. This review tries to summarize the current landscape of co-evolution-based methodologies, with a strong emphasis on describing interesting cases where their application to important biological systems, alone or in combination with other computational and experimental approaches, allowed getting new insight into these.

Practical aspects of protein co-evolution

PubMed Central

Ochoa, David; Pazos, Florencio

2014-01-01

Co-evolution is a fundamental aspect of Evolutionary Theory. At the molecular level, co-evolutionary linkages between protein families have been used as indicators of protein interactions and functional relationships from long ago. Due to the complexity of the problem and the amount of genomic data required for these approaches to achieve good performances, it took a relatively long time from the appearance of the first ideas and concepts to the quotidian application of these approaches and their incorporation to the standard toolboxes of bioinformaticians and molecular biologists. Today, these methodologies are mature (both in terms of performance and usability/implementation), and the genomic information that feeds them large enough to allow their general application. This review tries to summarize the current landscape of co-evolution-based methodologies, with a strong emphasis on describing interesting cases where their application to important biological systems, alone or in combination with other computational and experimental approaches, allowed getting new insight into these. PMID:25364721

Telecommunications Options Connect OCLC and Libraries to the Future: The Co-Evolution of OCLC Connectivity Options and the Library Computing Environment.

ERIC Educational Resources Information Center

Breeding, Marshall

1998-01-01

The Online Computer Library Center's (OCLC) access options have kept pace with the evolving trends in telecommunications and the library computing environment. As libraries deploy microcomputers and develop networks, OCLC offers access methods consistent with these environments. OCLC works toward reorienting its network paradigm through TCP/IP…

Analysis on the urban street network of Korea: Connections between topology and meta-information

NASA Astrophysics Data System (ADS)

Lee, Byoung-Hwa; Jung, Woo-Sung

2018-05-01

Cities consist of infrastructure that enables transportation, which can be considered as topology in abstract terms. Once cities are physically organized in terms of infrastructure, people interact with each other to form the values, which can be regarded as the meta-information of the cities. The topology and meta-information coevolve together as the cities are developed. In this study, we investigate the relationship between the topology and meta-information for a street network, which has aspects of both a complex network and planar graph. The degree of organization of a street structure determines the efficiency and productivity of the city in that they act as blood vessels to transport people, goods, and information. We analyze the topological aspect of a street network using centralities including the betweenness, closeness, straightness, and information. We classify the cities into several groups that share common meta-information based on the centrality, indicating that the topological factor of the street structure is closely related to meta-information through coevolution. We also obtain the coevolution in the planned cities using the regularity. Another footprint is the relation between the street segment length and the population, which shows the sublinear scaling.

Coordinated rates of evolution between interacting plastid and nuclear genes in Geraniaceae.

PubMed

Zhang, Jin; Ruhlman, Tracey A; Sabir, Jamal; Blazier, J Chris; Jansen, Robert K

2015-03-01

Although gene coevolution has been widely observed within individuals and between different organisms, rarely has this phenomenon been investigated within a phylogenetic framework. The Geraniaceae is an attractive system in which to study plastid-nuclear genome coevolution due to the highly elevated evolutionary rates in plastid genomes. In plants, the plastid-encoded RNA polymerase (PEP) is a protein complex composed of subunits encoded by both plastid (rpoA, rpoB, rpoC1, and rpoC2) and nuclear genes (sig1-6). We used transcriptome and genomic data for 27 species of Geraniales in a systematic evaluation of coevolution between genes encoding subunits of the PEP holoenzyme. We detected strong correlations of dN (nonsynonymous substitutions) but not dS (synonymous substitutions) within rpoB/sig1 and rpoC2/sig2, but not for other plastid/nuclear gene pairs, and identified the correlation of dN/dS ratio between rpoB/C1/C2 and sig1/5/6, rpoC1/C2 and sig2, and rpoB/C2 and sig3 genes. Correlated rates between interacting plastid and nuclear sequences across the Geraniales could result from plastid-nuclear genome coevolution. Analyses of coevolved amino acid positions suggest that structurally mediated coevolution is not the major driver of plastid-nuclear coevolution. The detection of strong correlation of evolutionary rates between SIG and RNAP genes suggests a plausible explanation for plastome-genome incompatibility in Geraniaceae. © 2015 American Society of Plant Biologists. All rights reserved.

The interplay between social networks and culture: theoretically and among whales and dolphins.

PubMed

Cantor, Mauricio; Whitehead, Hal

2013-05-19

Culture is increasingly being understood as a driver of mammalian phenotypes. Defined as group-specific behaviour transmitted by social learning, culture is shaped by social structure. However, culture can itself affect social structure if individuals preferentially interact with others whose behaviour is similar, or cultural symbols are used to mark groups. Using network formalism, this interplay can be depicted by the coevolution of nodes and edges together with the coevolution of network topology and transmission patterns. We review attempts to model the links between the spread, persistence and diversity of culture and the network topology of non-human societies. We illustrate these processes using cetaceans. The spread of socially learned begging behaviour within a population of bottlenose dolphins followed the topology of the social network, as did the evolution of the song of the humpback whale between breeding areas. In three bottlenose dolphin populations, individuals preferentially associated with animals using the same socially learned foraging behaviour. Homogeneous behaviour within the tight, nearly permanent social structures of the large matrilineal whales seems to result from transmission bias, with cultural symbols marking social structures. We recommend the integration of studies of culture and society in species for which social learning is an important determinant of behaviour.

The interplay between social networks and culture: theoretically and among whales and dolphins

PubMed Central

Cantor, Mauricio; Whitehead, Hal

2013-01-01

Culture is increasingly being understood as a driver of mammalian phenotypes. Defined as group-specific behaviour transmitted by social learning, culture is shaped by social structure. However, culture can itself affect social structure if individuals preferentially interact with others whose behaviour is similar, or cultural symbols are used to mark groups. Using network formalism, this interplay can be depicted by the coevolution of nodes and edges together with the coevolution of network topology and transmission patterns. We review attempts to model the links between the spread, persistence and diversity of culture and the network topology of non-human societies. We illustrate these processes using cetaceans. The spread of socially learned begging behaviour within a population of bottlenose dolphins followed the topology of the social network, as did the evolution of the song of the humpback whale between breeding areas. In three bottlenose dolphin populations, individuals preferentially associated with animals using the same socially learned foraging behaviour. Homogeneous behaviour within the tight, nearly permanent social structures of the large matrilineal whales seems to result from transmission bias, with cultural symbols marking social structures. We recommend the integration of studies of culture and society in species for which social learning is an important determinant of behaviour. PMID:23569288

Gα and regulator of G-protein signaling (RGS) protein pairs maintain functional compatibility and conserved interaction interfaces throughout evolution despite frequent loss of RGS proteins in plants.

PubMed

Hackenberg, Dieter; McKain, Michael R; Lee, Soon Goo; Roy Choudhury, Swarup; McCann, Tyler; Schreier, Spencer; Harkess, Alex; Pires, J Chris; Wong, Gane Ka-Shu; Jez, Joseph M; Kellogg, Elizabeth A; Pandey, Sona

2017-10-01

Signaling pathways regulated by heterotrimeric G-proteins exist in all eukaryotes. The regulator of G-protein signaling (RGS) proteins are key interactors and critical modulators of the Gα protein of the heterotrimer. However, while G-proteins are widespread in plants, RGS proteins have been reported to be missing from the entire monocot lineage, with two exceptions. A single amino acid substitution-based adaptive coevolution of the Gα:RGS proteins was proposed to enable the loss of RGS in monocots. We used a combination of evolutionary and biochemical analyses and homology modeling of the Gα and RGS proteins to address their expansion and its potential effects on the G-protein cycle in plants. Our results show that RGS proteins are widely distributed in the monocot lineage, despite their frequent loss. There is no support for the adaptive coevolution of the Gα:RGS protein pair based on single amino acid substitutions. RGS proteins interact with, and affect the activity of, Gα proteins from species with or without endogenous RGS. This cross-functional compatibility expands between the metazoan and plant kingdoms, illustrating striking conservation of their interaction interface. We propose that additional proteins or alternative mechanisms may exist which compensate for the loss of RGS in certain plant species. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Coevolving agent strategies and network topology for the public goods games

NASA Astrophysics Data System (ADS)

Zhang, C. Y.; Zhang, J. L.; Xie, G. M.; Wang, L.

2011-03-01

Much of human cooperation remains an evolutionary riddle. Coevolutionary public goods games in structured populations are studied where players can change from an unproductive public goods game to a productive one, by evaluating the productivity of the public goods games. In our model, each individual participates in games organized by its neighborhood plus by itself. Coevolution here refers to an evolutionary process entailing both deletion of existing links and addition of new links between agents that accompanies the evolution of their strategies. Furthermore, we investigate the effects of time scale separation of strategy and structure on cooperation level. This study presents the following: Foremost, we observe that high cooperation levels in public goods interactions are attained by the entangled coevolution of strategy and structure. Presented results also confirm that the resulting networks show many features of real systems, such as cooperative behavior and hierarchical clustering. The heterogeneity of the interaction network is held responsible for the observed promotion of cooperation. We hope our work may offer an explanation for the origin of large-scale cooperative behavior among unrelated individuals.

Coevolution at protein complex interfaces can be detected by the complementarity trace with important impact for predictive docking

PubMed Central

Madaoui, Hocine; Guerois, Raphaël

2008-01-01

Protein surfaces are under significant selection pressure to maintain interactions with their partners throughout evolution. Capturing how selection pressure acts at the interfaces of protein–protein complexes is a fundamental issue with high interest for the structural prediction of macromolecular assemblies. We tackled this issue under the assumption that, throughout evolution, mutations should minimally disrupt the physicochemical compatibility between specific clusters of interacting residues. This constraint drove the development of the so-called Surface COmplementarity Trace in Complex History score (SCOTCH), which was found to discriminate with high efficiency the structure of biological complexes. SCOTCH performances were assessed not only with respect to other evolution-based approaches, such as conservation and coevolution analyses, but also with respect to statistically based scoring methods. Validated on a set of 129 complexes of known structure exhibiting both permanent and transient intermolecular interactions, SCOTCH appears as a robust strategy to guide the prediction of protein–protein complex structures. Of particular interest, it also provides a basic framework to efficiently track how protein surfaces could evolve while keeping their partners in contact. PMID:18511568

The Verrucomicrobia LexA-Binding Motif: Insights into the Evolutionary Dynamics of the SOS Response.

PubMed

Erill, Ivan; Campoy, Susana; Kılıç, Sefa; Barbé, Jordi

2016-01-01

The SOS response is the primary bacterial mechanism to address DNA damage, coordinating multiple cellular processes that include DNA repair, cell division, and translesion synthesis. In contrast to other regulatory systems, the composition of the SOS genetic network and the binding motif of its transcriptional repressor, LexA, have been shown to vary greatly across bacterial clades, making it an ideal system to study the co-evolution of transcription factors and their regulons. Leveraging comparative genomics approaches and prior knowledge on the core SOS regulon, here we define the binding motif of the Verrucomicrobia, a recently described phylum of emerging interest due to its association with eukaryotic hosts. Site directed mutagenesis of the Verrucomicrobium spinosum recA promoter confirms that LexA binds a 14 bp palindromic motif with consensus sequence TGTTC-N4-GAACA. Computational analyses suggest that recognition of this novel motif is determined primarily by changes in base-contacting residues of the third alpha helix of the LexA helix-turn-helix DNA binding motif. In conjunction with comparative genomics analysis of the LexA regulon in the Verrucomicrobia phylum, electrophoretic shift assays reveal that LexA binds to operators in the promoter region of DNA repair genes and a mutagenesis cassette in this organism, and identify previously unreported components of the SOS response. The identification of tandem LexA-binding sites generating instances of other LexA-binding motifs in the lexA gene promoter of Verrucomicrobia species leads us to postulate a novel mechanism for LexA-binding motif evolution. This model, based on gene duplication, successfully addresses outstanding questions in the intricate co-evolution of the LexA protein, its binding motif and the regulatory network it controls.

Coevolution Theory of the Genetic Code at Age Forty: Pathway to Translation and Synthetic Life

PubMed Central

Wong, J. Tze-Fei; Ng, Siu-Kin; Mat, Wai-Kin; Hu, Taobo; Xue, Hong

2016-01-01

The origins of the components of genetic coding are examined in the present study. Genetic information arose from replicator induction by metabolite in accordance with the metabolic expansion law. Messenger RNA and transfer RNA stemmed from a template for binding the aminoacyl-RNA synthetase ribozymes employed to synthesize peptide prosthetic groups on RNAs in the Peptidated RNA World. Coevolution of the genetic code with amino acid biosynthesis generated tRNA paralogs that identify a last universal common ancestor (LUCA) of extant life close to Methanopyrus, which in turn points to archaeal tRNA introns as the most primitive introns and the anticodon usage of Methanopyrus as an ancient mode of wobble. The prediction of the coevolution theory of the genetic code that the code should be a mutable code has led to the isolation of optional and mandatory synthetic life forms with altered protein alphabets. PMID:26999216

Autonomous Agent-Based Systems and Their Applications in Fluid Dynamics, Particle Separation, and Co-evolving Networks

NASA Astrophysics Data System (ADS)

Graeser, Oliver

This thesis comprises three parts, reporting research results in Fluid Dynamics (Part I), Particle Separation (Part II) and Co-evolving Networks (Part III). Part I deals with the simulation of fluid dynamics using the lattice-Boltzmann method. Microfluidic devices often feature two-dimensional, repetitive arrays. Flows through such devices are pressure-driven and confined by solid walls. We have defined new adaptive generalised periodic boundary conditions to represent the effects of outer solid walls, and are thus able to exploit the periodicity of the array by simulating the flow through one unit cell in lieu of the entire device. The so-calculated fully developed flow describes the flow through the entire array accurately, but with computational requirements that are reduced according to the dimensions of the array. Part II discusses the problem of separating macromolecules like proteins or DNA coils. The reliable separation of such molecules is a crucial task in molecular biology. The use of Brownian ratchets as mechanisms for the separation of such particles has been proposed and discussed during the last decade. Pressure-driven flows have so far been dismissed as possible driving forces for Brownian ratchets, as they do not generate ratchet asymmetry. We propose a microfluidic design that uses pressure-driven flows to create asymmetry and hence allows particle separation. The dependence of the asymmetry on various factors of the microfluidic geometry is discussed. We further exemplify the feasibility of our approach using Brownian dynamics simulations of particles of different sizes in such a device. The results show that ratchet-based particle separation using flows as the driving force is possible. Simulation results and ratchet theory predictions are in excellent agreement. Part III deals with the co-evolution of networks and dynamic models. A group of agents occupies the nodes of a network, which defines the relationship between these agents. The evolution of the agents is defined by the rules of the dynamic model and depends on the relationship between agents, i.e., the state of the network. In return, the evolution of the network depends on the state of the dynamic model. The concept is introduced through the adaptive SIS model. We show that the previously used criterion determining the critical infected fraction, i.e., the number of infected agents required to sustain the epidemic, is inappropriate for this model. We introduce a different criterion and show that the critical infected fraction so determined is in good agreement with results obtained by numerical simulations. We further discuss the concept of co-evolving dynamics using the Snowdrift Game as a model paradigm. Co-evolution occurs through agents cutting dissatisfied links and rewiring to other agents at random. The effect of co-evolution on the emergence of cooperation is discussed using a mean-field theory and numerical simulations. A transition between a connected and a disconnected, highly cooperative state of the system is observed, and explained using the mean-field model. Quantitative deviations regarding the level of cooperation in the disconnected regime can be fully resolved through an improved mean-field theory that includes the effect of random fluctuations into its model.

MISTIC2: comprehensive server to study coevolution in protein families.

PubMed

Colell, Eloy A; Iserte, Javier A; Simonetti, Franco L; Marino-Buslje, Cristina

2018-06-14

Correlated mutations between residue pairs in evolutionarily related proteins arise from constraints needed to maintain a functional and stable protein. Identifying these inter-related positions narrows down the search for structurally or functionally important sites. MISTIC is a server designed to assist users to calculate covariation in protein families and provide them with an interactive tool to visualize the results. Here, we present MISTIC2, an update to the previous server, that allows to calculate four covariation methods (MIp, mfDCA, plmDCA and gaussianDCA). The results visualization framework has been reworked for improved performance, compatibility and user experience. It includes a circos representation of the information contained in the alignment, an interactive covariation network, a 3D structure viewer and a sequence logo. Others components provide additional information such as residue annotations, a roc curve for assessing contact prediction, data tables and different ways of filtering the data and exporting figures. Comparison of different methods is easily done and scores combination is also possible. A newly implemented web service allows users to access MISTIC2 programmatically using an API to calculate covariation and retrieve results. MISTIC2 is available at: https://mistic2.leloir.org.ar.

Question 6: coevolution theory of the genetic code: a proven theory.

PubMed

Wong, Jeffrey Tze-Fei

2007-10-01

The coevolution theory proposes that primordial proteins consisted only of those amino acids readily obtainable from the prebiotic environment, representing about half the twenty encoded amino acids of today, and the missing amino acids entered the system as the code expanded along with pathways of amino acid biosynthesis. The isolation of genetic code mutants, and the antiquity of pretran synthesis revealed by the comparative genomics of tRNAs and aminoacyl-tRNA synthetases, have combined to provide a rigorous proof of the four fundamental tenets of the theory, thus solving the riddle of the structure of the universal genetic code.

A Complex Network Analysis of Granular Fabric Evolution in Three-Dimensions

DTIC Science & Technology

2011-01-01

organized pattern formation (e.g., strain localization), and co-evolution of emergent in- ternal structures (e.g., force cycles and force chains) [15...these networks, particularly recurring patterns or motifs, and understanding how these co-evolve are crucial to the robust characterization and...the lead up to and during failure. Since failure patterns and boundaries of flow in three-dimensional specimens can be quite complicated and difficult

Long-legged bees make adaptive leaps: linking adaptation to coevolution in a plant-pollinator network.

PubMed

Pauw, Anton; Kahnt, Belinda; Kuhlmann, Michael; Michez, Denis; Montgomery, Graham A; Murray, Elizabeth; Danforth, Bryan N

2017-09-13

Adaptation is evolution in response to natural selection. Hence, an adaptation is expected to originate simultaneously with the acquisition of a particular selective environment. Here we test whether long legs evolve in oil-collecting Rediviva bees when they come under selection by long-spurred, oil-secreting flowers. To quantify the selective environment, we drew a large network of the interactions between Rediviva species and oil-secreting plant species. The selective environment of each bee species was summarized as the average spur length of the interacting plant species weighted by interaction frequency. Using phylogenetically independent contrasts, we calculated divergence in selective environment and evolutionary divergence in leg length between sister species (and sister clades) of Rediviva We found that change in the selective environment explained 80% of evolutionary change in leg length, with change in body size contributing an additional 6% of uniquely explained variance. The result is one of four proposed steps in testing for plant-pollinator coevolution. © 2017 The Author(s).

Co-evolution of Hormone Metabolism and Signaling Networks Expands Plant Adaptive Plasticity.

PubMed

Weng, Jing-Ke; Ye, Mingli; Li, Bin; Noel, Joseph P

2016-08-11

Classically, hormones elicit specific cellular responses by activating dedicated receptors. Nevertheless, the biosynthesis and turnover of many of these hormone molecules also produce chemically related metabolites. These molecules may also possess hormonal activities; therefore, one or more may contribute to the adaptive plasticity of signaling outcomes in host organisms. Here, we show that a catabolite of the plant hormone abscisic acid (ABA), namely phaseic acid (PA), likely emerged in seed plants as a signaling molecule that fine-tunes plant physiology, environmental adaptation, and development. This trait was facilitated by both the emergence-selection of a PA reductase that modulates PA concentrations and by the functional diversification of the ABA receptor family to perceive and respond to PA. Our results suggest that PA serves as a hormone in seed plants through activation of a subset of ABA receptors. This study demonstrates that the co-evolution of hormone metabolism and signaling networks can expand organismal resilience. Copyright © 2016 Elsevier Inc. All rights reserved.

An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework

PubMed Central

Zhang, Xuejun; Lei, Jiaxing

2015-01-01

Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology. PMID:26180840

Coevolution of Information Sharing and Implementation of Evidence-Based Practices Among North American Tobacco Cessation Quitlines

PubMed Central

Saul, Jessie E.; Lemaire, Robin H.; Valente, Thomas W.; Leischow, Scott J.

2015-01-01

Objectives. We examined the coevolution of information sharing and implementation of evidence-based practices among US and Canadian tobacco cessation quitlines within the North American Quitline Consortium (NAQC). Methods. Web-based surveys were used to collect data from key respondents representing each of 74 participating funders of NAQC quitlines during the summer and fall of 2009, 2010, and 2011. We used stochastic actor-based models to estimate changes in information sharing and practice implementation in the NAQC network. Results. Funders were more likely to share information within their own country and with funders that contracted with the same service provider. Funders contracting with larger service providers shared less information but implemented significantly more practices. Funders connected to larger numbers of tobacco control researchers more often received information from other funders. Intensity of ties to the NAQC network administrative organization did not influence funders’ decisions to share information or implement practices. Conclusions. Our findings show the importance of monitoring the NAQC network over time. We recommend increased cross-border information sharing and sharing of information between funders contracting with different and smaller service providers. PMID:26180993

Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks.

PubMed

Lin, Na; Chen, Hanning; Jing, Shikai; Liu, Fang; Liang, Xiaodan

2017-03-01

In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS 2 Os, which extend the single population particle swarm optimization (PSO) algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS 2 O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS 2 O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm's performance. Then PS 2 O is used for solving the radio frequency identification (RFID) network planning (RNP) problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.

Emerging directions in the study of the ecology and evolution of plant-animal mutualistic networks: a review.

PubMed

Gu, Hao; Goodale, Eben; Chen, Jin

2015-03-18

The study of mutualistic plant and animal networks is an emerging field of ecological research. We reviewed progress in this field over the past 30 years. While earlier studies mostly focused on network structure, stability, and biodiversity maintenance, recent studies have investigated the conservation implications of mutualistic networks, specifically the influence of invasive species and how networks respond to habitat loss. Current research has also focused on evolutionary questions including phylogenetic signal in networks, impact of networks on the coevolution of interacting partners, and network influences on the evolution of interacting species. We outline some directions for future research, particularly the evolution of specialization in mutualistic networks, and provide concrete recommendations for environmental managers.

DNCON2: improved protein contact prediction using two-level deep convolutional neural networks.

PubMed

Adhikari, Badri; Hou, Jie; Cheng, Jianlin

2018-05-01

Significant improvements in the prediction of protein residue-residue contacts are observed in the recent years. These contacts, predicted using a variety of coevolution-based and machine learning methods, are the key contributors to the recent progress in ab initio protein structure prediction, as demonstrated in the recent CASP experiments. Continuing the development of new methods to reliably predict contact maps is essential to further improve ab initio structure prediction. In this paper we discuss DNCON2, an improved protein contact map predictor based on two-level deep convolutional neural networks. It consists of six convolutional neural networks-the first five predict contacts at 6, 7.5, 8, 8.5 and 10 Å distance thresholds, and the last one uses these five predictions as additional features to predict final contact maps. On the free-modeling datasets in CASP10, 11 and 12 experiments, DNCON2 achieves mean precisions of 35, 50 and 53.4%, respectively, higher than 30.6% by MetaPSICOV on CASP10 dataset, 34% by MetaPSICOV on CASP11 dataset and 46.3% by Raptor-X on CASP12 dataset, when top L/5 long-range contacts are evaluated. We attribute the improved performance of DNCON2 to the inclusion of short- and medium-range contacts into training, two-level approach to prediction, use of the state-of-the-art optimization and activation functions, and a novel deep learning architecture that allows each filter in a convolutional layer to access all the input features of a protein of arbitrary length. The web server of DNCON2 is at http://sysbio.rnet.missouri.edu/dncon2/ where training and testing datasets as well as the predictions for CASP10, 11 and 12 free-modeling datasets can also be downloaded. Its source code is available at https://github.com/multicom-toolbox/DNCON2/. chengji@missouri.edu. Supplementary data are available at Bioinformatics online.

CMCpy: Genetic Code-Message Coevolution Models in Python

PubMed Central

Becich, Peter J.; Stark, Brian P.; Bhat, Harish S.; Ardell, David H.

2013-01-01

Code-message coevolution (CMC) models represent coevolution of a genetic code and a population of protein-coding genes (“messages”). Formally, CMC models are sets of quasispecies coupled together for fitness through a shared genetic code. Although CMC models display plausible explanations for the origin of multiple genetic code traits by natural selection, useful modern implementations of CMC models are not currently available. To meet this need we present CMCpy, an object-oriented Python API and command-line executable front-end that can reproduce all published results of CMC models. CMCpy implements multiple solvers for leading eigenpairs of quasispecies models. We also present novel analytical results that extend and generalize applications of perturbation theory to quasispecies models and pioneer the application of a homotopy method for quasispecies with non-unique maximally fit genotypes. Our results therefore facilitate the computational and analytical study of a variety of evolutionary systems. CMCpy is free open-source software available from http://pypi.python.org/pypi/CMCpy/. PMID:23532367

Construct - A Multi-Agent Network Model for the Co-Evolution of Agents and Socio-Cultural Environments

DTIC Science & Technology

2004-05-01

grounded in structuration theory (Giddens, 1984), social information processing theory (Salancik and Pfeffer, 1978) and symbolic interactionism (Manis...and B. N. Meltzer. Symbolic interaction: A reader in social psychology. Boston: Allyn & Bacon. 1978 Mcpherson, J. M. and L. Smith-Lovin

Privileged Biofuels, Marginalized Indigenous Peoples: The Coevolution of Biofuels Development in the Tropics

ERIC Educational Resources Information Center

Montefrio, Marvin Joseph F.

2012-01-01

Biofuels development has assumed an important role in integrating Indigenous peoples and other marginalized populations in the production of biofuels for global consumption. By combining the theories of commoditization and the environmental sociology of networks and flows, the author analyzed emerging trends and possible changes in institutions…

Mixed strategy and coevolution dynamics in social networks

NASA Astrophysics Data System (ADS)

Zhong, Weicai; Abbass, Hussein A.; Bender, Axel; Liu, Jing

2011-01-01

We investigate coevolution dynamics of both individual strategies and social ties as they adapt within the snowdrift game with mixed strategies. We propose a partner selection mechanism based on the concept of trust. Here trust is considered an instrument for an individual both selecting the right partners and being selected amongst other potential partners. Based on her local views of the system, the focal individual dismisses the link from the partner with the lowest trust and rewires to the partner’s partner with the highest trust. It is shown that such a trust-based partner switching mechanism favors the emergence of cooperators. Furthermore, when the number of an individual’s partners is restricted (which is a metaphor of limited capacities and capabilities of an individual in real environments), surprising assortative mixing patterns are formed in the emerging network and change the network’s degree distribution from a power-law distribution to an asymmetrically U-shaped distribution. This plays a leading role in preventing global avalanches triggered by perturbations acting on the state of the highly connected individuals.

Host-parasite oscillation dynamics and evolution in a compartmentalized RNA replication system.

PubMed

Bansho, Yohsuke; Furubayashi, Taro; Ichihashi, Norikazu; Yomo, Tetsuya

2016-04-12

To date, various cellular functions have been reconstituted in vitro such as self-replication systems using DNA, RNA, and proteins. The next important challenges include the reconstitution of the interactive networks of self-replicating species and investigating how such interactions generate complex ecological behaviors observed in nature. Here, we synthesized a simple replication system composed of two self-replicating host and parasitic RNA species. We found that the parasitic RNA eradicates the host RNA under bulk conditions; however, when the system is compartmentalized, a continuous oscillation pattern in the population dynamics of the two RNAs emerges. The oscillation pattern changed as replication proceeded mainly owing to the evolution of the host RNA. These results demonstrate that a cell-like compartment plays an important role in host-parasite ecological dynamics and suggest that the origin of the host-parasite coevolution might date back to the very early stages of the evolution of life.

Meta genome-wide network from functional linkages of genes in human gut microbial ecosystems.

PubMed

Ji, Yan; Shi, Yixiang; Wang, Chuan; Dai, Jianliang; Li, Yixue

2013-03-01

The human gut microbial ecosystem (HGME) exerts an important influence on the human health. In recent researches, meta-genomics provided deep insights into the HGME in terms of gene contents, metabolic processes and genome constitutions of meta-genome. Here we present a novel methodology to investigate the HGME on the basis of a set of functionally coupled genes regardless of their genome origins when considering the co-evolution properties of genes. By analyzing these coupled genes, we showed some basic properties of HGME significantly associated with each other, and further constructed a protein interaction map of human gut meta-genome to discover some functional modules that may relate with essential metabolic processes. Compared with other studies, our method provides a new idea to extract basic function elements from meta-genome systems and investigate complex microbial environment by associating its biological traits with co-evolutionary fingerprints encoded in it.

Coevolution of dynamical states and interactions in dynamic networks

NASA Astrophysics Data System (ADS)

Zimmermann, Martín G.; Eguíluz, Víctor M.; San Miguel, Maxi

2004-06-01

We explore the coupled dynamics of the internal states of a set of interacting elements and the network of interactions among them. Interactions are modeled by a spatial game and the network of interaction links evolves adapting to the outcome of the game. As an example, we consider a model of cooperation in which the adaptation is shown to facilitate the formation of a hierarchical interaction network that sustains a highly cooperative stationary state. The resulting network has the characteristics of a small world network when a mechanism of local neighbor selection is introduced in the adaptive network dynamics. The highly connected nodes in the hierarchical structure of the network play a leading role in the stability of the network. Perturbations acting on the state of these special nodes trigger global avalanches leading to complete network reorganization.

An experimental and computational evolution-based method to study a mode of co-evolution of overlapping open reading frames in the AAV2 viral genome.

PubMed

Kawano, Yasuhiro; Neeley, Shane; Adachi, Kei; Nakai, Hiroyuki

2013-01-01

Overlapping open reading frames (ORFs) in viral genomes undergo co-evolution; however, how individual amino acids coded by overlapping ORFs are structurally, functionally, and co-evolutionarily constrained remains difficult to address by conventional homologous sequence alignment approaches. We report here a new experimental and computational evolution-based methodology to address this question and report its preliminary application to elucidating a mode of co-evolution of the frame-shifted overlapping ORFs in the adeno-associated virus (AAV) serotype 2 viral genome. These ORFs encode both capsid VP protein and non-structural assembly-activating protein (AAP). To show proof of principle of the new method, we focused on the evolutionarily conserved QVKEVTQ and KSKRSRR motifs, a pair of overlapping heptapeptides in VP and AAP, respectively. In the new method, we first identified a large number of capsid-forming VP3 mutants and functionally competent AAP mutants of these motifs from mutant libraries by experimental directed evolution under no co-evolutionary constraints. We used Illumina sequencing to obtain a large dataset and then statistically assessed the viability of VP and AAP heptapeptide mutants. The obtained heptapeptide information was then integrated into an evolutionary algorithm, with which VP and AAP were co-evolved from random or native nucleotide sequences in silico. As a result, we demonstrate that these two heptapeptide motifs could exhibit high degeneracy if coded by separate nucleotide sequences, and elucidate how overlap-evoked co-evolutionary constraints play a role in making the VP and AAP heptapeptide sequences into the present shape. Specifically, we demonstrate that two valine (V) residues and β-strand propensity in QVKEVTQ are structurally important, the strongly negative and hydrophilic nature of KSKRSRR is functionally important, and overlap-evoked co-evolution imposes strong constraints on serine (S) residues in KSKRSRR, despite high degeneracy of the motifs in the absence of co-evolutionary constraints.

Lessons from (co-)evolution in the docking of proteins and peptides for CAPRI Rounds 28-35.

PubMed

Yu, Jinchao; Andreani, Jessica; Ochsenbein, Françoise; Guerois, Raphaël

2017-03-01

Computational protein-protein docking is of great importance for understanding protein interactions at the structural level. Critical assessment of prediction of interactions (CAPRI) experiments provide the protein docking community with a unique opportunity to blindly test methods based on real-life cases and help accelerate methodology development. For CAPRI Rounds 28-35, we used an automatic docking pipeline integrating the coarse-grained co-evolution-based potential InterEvScore. This score was developed to exploit the information contained in the multiple sequence alignments of binding partners and selectively recognize co-evolved interfaces. Together with Zdock/Frodock for rigid-body docking, SOAP-PP for atomic potential and Rosetta applications for structural refinement, this pipeline reached high performance on a majority of targets. For protein-peptide docking and interfacial water position predictions, we also explored different means of taking evolutionary information into account. Overall, our group ranked 1 st by correctly predicting 10 targets, composed of 1 High, 7 Medium and 2 Acceptable predictions. Excellent and Outstanding levels of accuracy were reached for each of the two water prediction targets, respectively. Altogether, in 15 out of 18 targets in total, evolutionary information, either through co-evolution or conservation analyses, could provide key constraints to guide modeling towards the most likely assemblies. These results open promising perspectives regarding the way evolutionary information can be valuable to improve docking prediction accuracy. Proteins 2017; 85:378-390. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Co-evolution of SNF spliceosomal proteins with their RNA targets in trans-splicing nematodes.

PubMed

Strange, Rex Meade; Russelburg, L Peyton; Delaney, Kimberly J

2016-08-01

Although the mechanism of pre-mRNA splicing has been well characterized, the evolution of spliceosomal proteins is poorly understood. The U1A/U2B″/SNF family (hereafter referred to as the SNF family) of RNA binding spliceosomal proteins participates in both the U1 and U2 small interacting nuclear ribonucleoproteins (snRNPs). The highly constrained nature of this system has inhibited an analysis of co-evolutionary trends between the proteins and their RNA binding targets. Here we report accelerated sequence evolution in the SNF protein family in Phylum Nematoda, which has allowed an analysis of protein:RNA co-evolution. In a comparison of SNF genes from ecdysozoan species, we found a correlation between trans-splicing species (nematodes) and increased phylogenetic branch lengths of the SNF protein family, with respect to their sister clade Arthropoda. In particular, we found that nematodes (~70-80 % of pre-mRNAs are trans-spliced) have experienced higher rates of SNF sequence evolution than arthropods (predominantly cis-spliced) at both the nucleotide and amino acid levels. Interestingly, this increased evolutionary rate correlates with the reliance on trans-splicing by nematodes, which would alter the role of the SNF family of spliceosomal proteins. We mapped amino acid substitutions to functionally important regions of the SNF protein, specifically to sites that are predicted to disrupt protein:RNA and protein:protein interactions. Finally, we investigated SNF's RNA targets: the U1 and U2 snRNAs. Both are more divergent in nematodes than arthropods, suggesting the RNAs have co-evolved with SNF in order to maintain the necessarily high affinity interaction that has been characterized in other species.

Biological evolution and statistical physics

NASA Astrophysics Data System (ADS)

Drossel, Barbara

2001-03-01

This review is an introduction to theoretical models and mathematical calculations for biological evolution, aimed at physicists. The methods in the field are naturally very similar to those used in statistical physics, although the majority of publications have appeared in biology journals. The review has three parts, which can be read independently. The first part deals with evolution in fitness landscapes and includes Fisher's theorem, adaptive walks, quasispecies models, effects of finite population sizes, and neutral evolution. The second part studies models of coevolution, including evolutionary game theory, kin selection, group selection, sexual selection, speciation, and coevolution of hosts and parasites. The third part discusses models for networks of interacting species and their extinction avalanches. Throughout the review, attention is paid to giving the necessary biological information, and to pointing out the assumptions underlying the models, and their limits of validity.

Controlling Contagion Processes in Activity Driven Networks

NASA Astrophysics Data System (ADS)

Liu, Suyu; Perra, Nicola; Karsai, Márton; Vespignani, Alessandro

2014-03-01

The vast majority of strategies aimed at controlling contagion processes on networks consider the connectivity pattern of the system either quenched or annealed. However, in the real world, many networks are highly dynamical and evolve, in time, concurrently with the contagion process. Here, we derive an analytical framework for the study of control strategies specifically devised for a class of time-varying networks, namely activity-driven networks. We develop a block variable mean-field approach that allows the derivation of the equations describing the coevolution of the contagion process and the network dynamic. We derive the critical immunization threshold and assess the effectiveness of three different control strategies. Finally, we validate the theoretical picture by simulating numerically the spreading process and control strategies in both synthetic networks and a large-scale, real-world, mobile telephone call data set.

Structure, Function, Interaction, Co-evolution of Rice Blast Resistance Genes

USDA-ARS?s Scientific Manuscript database

Rice blast disease caused by the fungal pathogen Magnaporthe oryzae is one of the most destructive rice diseases worldwide. Resistance (R) genes to blast encode proteins that detect pathogen signaling molecules encoded by M. oryzae avirulence (AVR) genes. R genes can be a single or a member of clu...

Investigation of Dynamic Algorithms for Pattern Recognition Identified in Cerebral Cortex

DTIC Science & Technology

1991-12-02

oscillatory and possibly chaotic activity forin the actual cortical substrate of the diverse sensory, motor, and cognitive operations now studied in...September Neural Information Processing Systems - Natural and Synthetic, Denver, Colo., November 1989 U.C. San Diego, Cognitive Science Dept...Baird. Biologically applied neural networks may foster the co-evolution of neurobiology and cognitive psychology. Brain and Behavioral Sciences, 37

Direct protein interaction underlies gene-for-gene specificity and coevolution of the flax resistance genes and flax rust avirulence genes

PubMed Central

Dodds, Peter N.; Lawrence, Gregory J.; Catanzariti, Ann-Maree; Teh, Trazel; Wang, Ching-I. A.; Ayliffe, Michael A.; Kobe, Bostjan; Ellis, Jeffrey G.

2006-01-01

Plant resistance proteins (R proteins) recognize corresponding pathogen avirulence (Avr) proteins either indirectly through detection of changes in their host protein targets or through direct R–Avr protein interaction. Although indirect recognition imposes selection against Avr effector function, pathogen effector molecules recognized through direct interaction may overcome resistance through sequence diversification rather than loss of function. Here we show that the flax rust fungus AvrL567 genes, whose products are recognized by the L5, L6, and L7 R proteins of flax, are highly diverse, with 12 sequence variants identified from six rust strains. Seven AvrL567 variants derived from Avr alleles induce necrotic responses when expressed in flax plants containing corresponding resistance genes (R genes), whereas five variants from avr alleles do not. Differences in recognition specificity between AvrL567 variants and evidence for diversifying selection acting on these genes suggest they have been involved in a gene-specific arms race with the corresponding flax R genes. Yeast two-hybrid assays indicate that recognition is based on direct R–Avr protein interaction and recapitulate the interaction specificity observed in planta. Biochemical analysis of Escherichia coli-produced AvrL567 proteins shows that variants that escape recognition nevertheless maintain a conserved structure and stability, suggesting that the amino acid sequence differences directly affect the R–Avr protein interaction. We suggest that direct recognition associated with high genetic diversity at corresponding R and Avr gene loci represents an alternative outcome of plant–pathogen coevolution to indirect recognition associated with simple balanced polymorphisms for functional and nonfunctional R and Avr genes. PMID:16731621

The evolution of reduced antagonism--A role for host-parasite coevolution.

PubMed

Gibson, A K; Stoy, K S; Gelarden, I A; Penley, M J; Lively, C M; Morran, L T

2015-11-01

Why do some host-parasite interactions become less antagonistic over evolutionary time? Vertical transmission can select for reduced antagonism. Vertical transmission also promotes coevolution between hosts and parasites. Therefore, we hypothesized that coevolution itself may underlie transitions to reduced antagonism. To test the coevolution hypothesis, we selected for reduced antagonism between the host Caenorhabditis elegans and its parasite Serratia marcescens. This parasite is horizontally transmitted, which allowed us to study coevolution independently of vertical transmission. After 20 generations, we observed a response to selection when coevolution was possible: reduced antagonism evolved in the copassaged treatment. Reduced antagonism, however, did not evolve when hosts or parasites were independently selected without coevolution. In addition, we found strong local adaptation for reduced antagonism between replicate host/parasite lines in the copassaged treatment. Taken together, these results strongly suggest that coevolution was critical to the rapid evolution of reduced antagonism. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Older partner selection promotes the prevalence of cooperation in evolutionary games.

PubMed

Yang, Guoli; Huang, Jincai; Zhang, Weiming

2014-10-21

Evolutionary games typically come with the interplays between evolution of individual strategy and adaptation to network structure. How these dynamics in the co-evolution promote (or obstruct) the cooperation is regarded as an important topic in social, economic, and biological fields. Combining spatial selection with partner choice, the focus of this paper is to identify which neighbour should be selected as a role to imitate during the process of co-evolution. Age, an internal attribute and kind of local piece of information regarding the survivability of the agent, is a significant consideration for the selection strategy. The analysis and simulations presented, demonstrate that older partner selection for strategy imitation could foster the evolution of cooperation. The younger partner selection, however, may decrease the level of cooperation. Our model highlights the importance of agent׳s age on the promotion of cooperation in evolutionary games, both efficiently and effectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Co-evolution of proteins and solutions: protein adaptation versus cytoprotective micromolecules and their roles in marine organisms.

PubMed

Yancey, Paul H; Siebenaller, Joseph F

2015-06-01

Organisms experience a wide range of environmental factors such as temperature, salinity and hydrostatic pressure, which pose challenges to biochemical processes. Studies on adaptations to such factors have largely focused on macromolecules, especially intrinsic adaptations in protein structure and function. However, micromolecular cosolutes can act as cytoprotectants in the cellular milieu to affect biochemical function and they are now recognized as important extrinsic adaptations. These solutes, both inorganic and organic, have been best characterized as osmolytes, which accumulate to reduce osmotic water loss. Singly, and in combination, many cosolutes have properties beyond simple osmotic effects, e.g. altering the stability and function of proteins in the face of numerous stressors. A key example is the marine osmolyte trimethylamine oxide (TMAO), which appears to enhance water structure and is excluded from peptide backbones, favoring protein folding and stability and counteracting destabilizers like urea and temperature. Co-evolution of intrinsic and extrinsic adaptations is illustrated with high hydrostatic pressure in deep-living organisms. Cytosolic and membrane proteins and G-protein-coupled signal transduction in fishes under pressure show inhibited function and stability, while revealing a number of intrinsic adaptations in deep species. Yet, intrinsic adaptations are often incomplete, and those fishes accumulate TMAO linearly with depth, suggesting a role for TMAO as an extrinsic 'piezolyte' or pressure cosolute. Indeed, TMAO is able to counteract the inhibitory effects of pressure on the stability and function of many proteins. Other cosolutes are cytoprotective in other ways, such as via antioxidation. Such observations highlight the importance of considering the cellular milieu in biochemical and cellular adaptation. © 2015. Published by The Company of Biologists Ltd.

Computing the origin and evolution of the ribosome from its structure — Uncovering processes of macromolecular accretion benefiting synthetic biology

PubMed Central

Caetano-Anollés, Gustavo; Caetano-Anollés, Derek

2015-01-01

Accretion occurs pervasively in nature at widely different timeframes. The process also manifests in the evolution of macromolecules. Here we review recent computational and structural biology studies of evolutionary accretion that make use of the ideographic (historical, retrodictive) and nomothetic (universal, predictive) scientific frameworks. Computational studies uncover explicit timelines of accretion of structural parts in molecular repertoires and molecules. Phylogenetic trees of protein structural domains and proteomes and their molecular functions were built from a genomic census of millions of encoded proteins and associated terminal Gene Ontology terms. Trees reveal a ‘metabolic-first’ origin of proteins, the late development of translation, and a patchwork distribution of proteins in biological networks mediated by molecular recruitment. Similarly, the natural history of ancient RNA molecules inferred from trees of molecular substructures built from a census of molecular features shows patchwork-like accretion patterns. Ideographic analyses of ribosomal history uncover the early appearance of structures supporting mRNA decoding and tRNA translocation, the coevolution of ribosomal proteins and RNA, and a first evolutionary transition that brings ribosomal subunits together into a processive protein biosynthetic complex. Nomothetic structural biology studies of tertiary interactions and ancient insertions in rRNA complement these findings, once concentric layering assumptions are removed. Patterns of coaxial helical stacking reveal a frustrated dynamics of outward and inward ribosomal growth possibly mediated by structural grafting. The early rise of the ribosomal ‘turnstile’ suggests an evolutionary transition in natural biological computation. Results make explicit the need to understand processes of molecular growth and information transfer of macromolecules. PMID:27096056

Protein 3D Structure Computed from Evolutionary Sequence Variation

PubMed Central

Sheridan, Robert; Hopf, Thomas A.; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

2011-01-01

The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. Deciphering the evolutionary record held in these sequences and exploiting it for predictive and engineering purposes presents a formidable challenge. The potential benefit of solving this challenge is amplified by the advent of inexpensive high-throughput genomic sequencing. In this paper we ask whether we can infer evolutionary constraints from a set of sequence homologs of a protein. The challenge is to distinguish true co-evolution couplings from the noisy set of observed correlations. We address this challenge using a maximum entropy model of the protein sequence, constrained by the statistics of the multiple sequence alignment, to infer residue pair couplings. Surprisingly, we find that the strength of these inferred couplings is an excellent predictor of residue-residue proximity in folded structures. Indeed, the top-scoring residue couplings are sufficiently accurate and well-distributed to define the 3D protein fold with remarkable accuracy. We quantify this observation by computing, from sequence alone, all-atom 3D structures of fifteen test proteins from different fold classes, ranging in size from 50 to 260 residues., including a G-protein coupled receptor. These blinded inferences are de novo, i.e., they do not use homology modeling or sequence-similar fragments from known structures. The co-evolution signals provide sufficient information to determine accurate 3D protein structure to 2.7–4.8 Å Cα-RMSD error relative to the observed structure, over at least two-thirds of the protein (method called EVfold, details at http://EVfold.org). This discovery provides insight into essential interactions constraining protein evolution and will facilitate a comprehensive survey of the universe of protein structures, new strategies in protein and drug design, and the identification of functional genetic variants in normal and disease genomes. PMID:22163331

Network Dynamics of Innovation Processes.

PubMed

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-26

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.

Network Dynamics of Innovation Processes

NASA Astrophysics Data System (ADS)

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-01

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.

Gene–culture coevolution and the nature of human sociality

PubMed Central

Gintis, Herbert

2011-01-01

Human characteristics are the product of gene–culture coevolution, which is an evolutionary dynamic involving the interaction of genes and culture over long time periods. Gene–culture coevolution is a special case of niche construction. Gene–culture coevolution is responsible for human other-regarding preferences, a taste for fairness, the capacity to empathize and salience of morality and character virtues. PMID:21320901

Conservation analysis and decomposition of residue correlation networks in the phospholipase A2 superfamily (PLA2s): Insights into the structure-function relationships of snake venom toxins.

PubMed

Oliveira, Alberto; Bleicher, Lucas; Schrago, Carlos G; Silva Junior, Floriano Paes

2018-05-01

Phospholipases A2 (PLA 2 s) comprise a superfamily of glycerophospholipids hydrolyzing enzymes present in many organisms in nature, whose catalytic activity was majorly unveiled by analysis of snake venoms. The latter have pharmaceutical and biotechnological interests and can be divided into different functional sub-classes. Our goal was to identify important residues and their relation to the functional and class-specific characteristics in the PLA 2 s family with special emphasis on snake venom PLA 2 s (svPLA 2 s). We identified such residues by conservation analysis and decomposition of residue coevolution networks (DRCN), annotated the results based on the available literature on PLA 2 s, structural analysis and molecular dynamics simulations, and related the results to the phylogenetic distribution of these proteins. A filtered alignment of PLA 2 s revealed 14 highly conserved positions and 3 sets of coevolved residues, which were annotated according to their structural or functional role. These residues are mostly involved in ligand binding and catalysis, calcium-binding, the formation of disulfide bridges and a hydrophobic cluster close to the binding site. An independent validation of the inference of structure-function relationships from our co-evolution analysis on the svPLA2s family was obtained by the analysis of the pattern of selection acting on the Viperidae and Elapidae lineages. Additionally, a molecular dynamics simulation on the Lys49 PLA 2 from Agkistrodon contortrix laticinctus was carried out to further investigate the correlation of the Lys49-Glu69 pair. Our results suggest this configuration can result in a novel conformation where the binding cavity collapses due to the approximation of two loops caused by a strong salt bridge between Glu69 and Arg34. Finally, phylogenetic analysis indicated a correlation between the presence of residues in the coevolved sets found in this analysis and the clade localization. The results provide a guide for important positions in the family of PLA 2 s, and potential new objects of investigation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling the coevolution of topology and traffic on weighted technological networks

NASA Astrophysics Data System (ADS)

Xie, Yan-Bo; Wang, Wen-Xu; Wang, Bing-Hong

2007-02-01

For many technological networks, the network structures and the traffic taking place on them mutually interact. The demands of traffic increment spur the evolution and growth of the networks to maintain their normal and efficient functioning. In parallel, a change of the network structure leads to redistribution of the traffic. In this paper, we perform an extensive numerical and analytical study, extending results of Wang [Phys. Rev. Lett. 94, 188702 (2005)]. By introducing a general strength-coupling interaction driven by the traffic increment between any pair of vertices, our model generates networks of scale-free distributions of strength, weight, and degree. In particular, the obtained nonlinear correlation between vertex strength and degree, and the disassortative property demonstrate that the model is capable of characterizing weighted technological networks. Moreover, the generated graphs possess both dense clustering structures and an anticorrelation between vertex clustering and degree, which are widely observed in real-world networks. The corresponding theoretical predictions are well consistent with simulation results.

Potential arms race in the coevolution of primates and angiosperms: brazzein sweet proteins and gorilla taste receptors.

PubMed

Guevara, Elaine E; Veilleux, Carrie C; Saltonstall, Kristin; Caccone, Adalgisa; Mundy, Nicholas I; Bradley, Brenda J

2016-09-01

We explored whether variation in the sweet taste receptor protein T1R3 in primates could contribute to differences in sweet taste repertoire among species, potentially reflecting coevolution with local plants. Specifically, we examined which primates are likely to be sweet "tasters" of brazzein, a protein found in the fruit of the African plant Pentadiplandra brazzeana that tastes intensely sweet to humans, but provides little energy. Sweet proteins like brazzein are thought to mimic the taste of sugars to entice seed dispersers. We examined the evolution of T1R3 and assessed whether primates are likely "deceived" by such biochemical mimicry. Using published and new sequence data for TAS1R3, we characterized 57 primates and other mammals at the two amino acid sites necessary to taste brazzein to determine which species are tasters. We further used dN/dS-based methods to look for statistical evidence of accelerated evolution in this protein across primate lineages. The taster genotype is shared across most catarrhines, suggesting that most African primates can be "tricked" into eating and dispersing P. brazzeana's seeds for little caloric gain. Western gorillas (Gorilla gorilla), however, exhibit derived mutations at the two brazzein-critical positions, and although fruit is a substantial portion of the western gorilla diet, they have not been observed to eat P. brazzeana. Our analyses of protein evolution found no signature of positive selection on TAS1R3 along the gorilla lineage. We propose that the gorilla-specific mutations at the TAS1R3 locus encoding T1R3 could be a counter-adaptation to the false sweet signal of brazzein. © 2016 Wiley Periodicals, Inc.

Metabolic basis for the self-referential genetic code.

PubMed

Guimarães, Romeu Cardoso

2011-08-01

An investigation of the biosynthesis pathways producing glycine and serine was necessary to clarify an apparent inconsistency between the self-referential model (SRM) for the formation of the genetic code and the model of coevolution of encodings and of amino acid biosynthesis routes. According to the SRM proposal, glycine was the first amino acid encoded, followed by serine. The coevolution model does not state precisely which the first encodings were, only presenting a list of about ten early assignments including the derivation of glycine from serine-this being derived from the glycolysis intermediate glycerate, which reverses the order proposed by the self-referential model. Our search identified the glycine-serine pathway of syntheses based on one-carbon sources, involving activities of the glycine decarboxylase complex and its associated serine hydroxymethyltransferase, which is consistent with the order proposed by the self-referential model and supports its rationale for the origin of the genetic code: protein synthesis was developed inside an early metabolic system, serving the function of a sink of amino acids; the first peptides were glycine-rich and fit for the function of building the early ribonucleoproteins; glycine consumption in proteins drove the fixation of the glycine-serine pathway.

Coevolution of strategy-selection time scale and cooperation in spatial prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Rong, Zhihai; Wu, Zhi-Xi; Chen, Guanrong

2013-06-01

In this paper, we investigate a networked prisoner's dilemma game where individuals' strategy-selection time scale evolves based on their historical learning information. We show that the more times the current strategy of an individual is learnt by his neighbors, the longer time he will stick on the successful behavior by adaptively adjusting the lifetime of the adopted strategy. Through characterizing the extent of success of the individuals with normalized payoffs, we show that properly using the learned information can form a positive feedback mechanism between cooperative behavior and its lifetime, which can boost cooperation on square lattices and scale-free networks.

Coupling effect of nodes popularity and similarity on social network persistence

PubMed Central

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-01-01

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology. PMID:28220840

Coupling effect of nodes popularity and similarity on social network persistence

NASA Astrophysics Data System (ADS)

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-01

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes’ popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Coupling effect of nodes popularity and similarity on social network persistence.

PubMed

Jin, Xiaogang; Jin, Cheng; Huang, Jiaxuan; Min, Yong

2017-02-21

Network robustness represents the ability of networks to withstand failures and perturbations. In social networks, maintenance of individual activities, also called persistence, is significant towards understanding robustness. Previous works usually consider persistence on pre-generated network structures; while in social networks, the network structure is growing with the cascading inactivity of existed individuals. Here, we address this challenge through analysis for nodes under a coevolution model, which characterizes individual activity changes under three network growth modes: following the descending order of nodes' popularity, similarity or uniform random. We show that when nodes possess high spontaneous activities, a popularity-first growth mode obtains highly persistent networks; otherwise, with low spontaneous activities, a similarity-first mode does better. Moreover, a compound growth mode, with the consecutive joining of similar nodes in a short period and mixing a few high popularity nodes, obtains the highest persistence. Therefore, nodes similarity is essential for persistent social networks, while properly coupling popularity with similarity further optimizes the persistence. This demonstrates the evolution of nodes activity not only depends on network topology, but also their connective typology.

Comparative study of the effectiveness and limitations of current methods for detecting sequence coevolution.

PubMed

Mao, Wenzhi; Kaya, Cihan; Dutta, Anindita; Horovitz, Amnon; Bahar, Ivet

2015-06-15

With rapid accumulation of sequence data on several species, extracting rational and systematic information from multiple sequence alignments (MSAs) is becoming increasingly important. Currently, there is a plethora of computational methods for investigating coupled evolutionary changes in pairs of positions along the amino acid sequence, and making inferences on structure and function. Yet, the significance of coevolution signals remains to be established. Also, a large number of false positives (FPs) arise from insufficient MSA size, phylogenetic background and indirect couplings. Here, a set of 16 pairs of non-interacting proteins is thoroughly examined to assess the effectiveness and limitations of different methods. The analysis shows that recent computationally expensive methods designed to remove biases from indirect couplings outperform others in detecting tertiary structural contacts as well as eliminating intermolecular FPs; whereas traditional methods such as mutual information benefit from refinements such as shuffling, while being highly efficient. Computations repeated with 2,330 pairs of protein families from the Negatome database corroborated these results. Finally, using a training dataset of 162 families of proteins, we propose a combined method that outperforms existing individual methods. Overall, the study provides simple guidelines towards the choice of suitable methods and strategies based on available MSA size and computing resources. Software is freely available through the Evol component of ProDy API. © The Author 2015. Published by Oxford University Press.

Diverse mechanisms evolved by DNA viruses to inhibit early host defenses

PubMed Central

Sheng, Xinlei; Song, Bokai; Cristea, Ileana M.

2016-01-01

In mammalian cells, early defenses against infection by pathogens are mounted through a complex network of signaling pathways shepherded by immune-modulatory pattern-recognition receptors. As obligate parasites, the survival of viruses is dependent upon the evolutionary acquisition of mechanisms that tactfully dismantle and subvert the cellular intrinsic and innate immune responses. Here, we review the diverse mechanisms by which viruses that accommodate DNA genomes are able to circumvent activation of cellular immunity. We start by discussing viral manipulation of host defense protein levels by either transcriptional regulation or protein degradation. We next review viral strategies used to repurpose or inhibit these cellular immune factors by molecular hijacking or by regulating their post-translational modification status. Additionally, we explore the infection-induced temporal modulation of apoptosis to facilitate viral replication and spread. Lastly, the co-evolution of viruses with their hosts is highlighted by the acquisition of elegant mechanisms for suppressing host defenses via viral mimicry of host factors. In closing, we present a perspective on how characterizing these viral evasion tactics both broadens the understanding of virus-host interactions and reveals essential functions of the immune system at the molecular level. This knowledge is critical in understanding the sources of viral pathogenesis, as well as for the design of antiviral therapeutics and autoimmunity treatments. PMID:27650455

Evol and ProDy for bridging protein sequence evolution and structural dynamics

PubMed Central

Mao, Wenzhi; Liu, Ying; Chennubhotla, Chakra; Lezon, Timothy R.; Bahar, Ivet

2014-01-01

Correlations between sequence evolution and structural dynamics are of utmost importance in understanding the molecular mechanisms of function and their evolution. We have integrated Evol, a new package for fast and efficient comparative analysis of evolutionary patterns and conformational dynamics, into ProDy, a computational toolbox designed for inferring protein dynamics from experimental and theoretical data. Using information-theoretic approaches, Evol coanalyzes conservation and coevolution profiles extracted from multiple sequence alignments of protein families with their inferred dynamics. Availability and implementation: ProDy and Evol are open-source and freely available under MIT License from http://prody.csb.pitt.edu/. Contact: bahar@pitt.edu PMID:24849577

Co-evolutionary constraints of globular proteins correlate with their folding rates.

PubMed

Mallik, Saurav; Kundu, Sudip

2015-08-04

Folding rates (lnkf) of globular proteins correlate with their biophysical properties, but relationship between lnkf and patterns of sequence evolution remains elusive. We introduce 'relative co-evolution order' (rCEO) as length-normalized average primary chain separation of co-evolving pairs (CEPs), which negatively correlates with lnkf. In addition to pairs in native 3D contact, indirectly connected and structurally remote CEPs probably also play critical roles in protein folding. Correlation between rCEO and lnkf is stronger in multi-state proteins than two-state proteins, contrasting the case of contact order (co), where stronger correlation is found in two-state proteins. Finally, rCEO, co and lnkf are fitted into a 3D linear correlation. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Bacterial Unculturability and the Formation of Intercellular Metabolic Networks.

PubMed

Pande, Samay; Kost, Christian

2017-05-01

The majority of known bacterial species cannot be cultivated under laboratory conditions. Here we argue that the adaptive emergence of obligate metabolic interactions in natural bacterial communities can explain this pattern. Bacteria commonly release metabolites into the external environment. Accumulating pools of extracellular metabolites create an ecological niche that benefits auxotrophic mutants, which have lost the ability to autonomously produce the corresponding metabolites. In addition to a diffusion-based metabolite transfer, auxotrophic cells can use contact-dependent means to obtain nutrients from other co-occurring cells. Spatial colocalisation and a continuous coevolution further increase the nutritional dependency and optimise fluxes through combined metabolic networks. Thus, bacteria likely function as networks of interacting cells that reciprocally exchange nutrients and biochemical functions rather than as physiologically autonomous units. Copyright © 2017 Elsevier Ltd. All rights reserved.

Origin of the cell nucleus, mitosis and sex: roles of intracellular coevolution.

PubMed

Cavalier-Smith, Thomas

2010-02-04

The transition from prokaryotes to eukaryotes was the most radical change in cell organisation since life began, with the largest ever burst of gene duplication and novelty. According to the coevolutionary theory of eukaryote origins, the fundamental innovations were the concerted origins of the endomembrane system and cytoskeleton, subsequently recruited to form the cell nucleus and coevolving mitotic apparatus, with numerous genetic eukaryotic novelties inevitable consequences of this compartmentation and novel DNA segregation mechanism. Physical and mutational mechanisms of origin of the nucleus are seldom considered beyond the long-standing assumption that it involved wrapping pre-existing endomembranes around chromatin. Discussions on the origin of sex typically overlook its association with protozoan entry into dormant walled cysts and the likely simultaneous coevolutionary, not sequential, origin of mitosis and meiosis. I elucidate nuclear and mitotic coevolution, explaining the origins of dicer and small centromeric RNAs for positionally controlling centromeric heterochromatin, and how 27 major features of the cell nucleus evolved in four logical stages, making both mechanisms and selective advantages explicit: two initial stages (origin of 30 nm chromatin fibres, enabling DNA compaction; and firmer attachment of endomembranes to heterochromatin) protected DNA and nascent RNA from shearing by novel molecular motors mediating vesicle transport, division, and cytoplasmic motility. Then octagonal nuclear pore complexes (NPCs) arguably evolved from COPII coated vesicle proteins trapped in clumps by Ran GTPase-mediated cisternal fusion that generated the fenestrated nuclear envelope, preventing lethal complete cisternal fusion, and allowing passive protein and RNA exchange. Finally, plugging NPC lumens by an FG-nucleoporin meshwork and adopting karyopherins for nucleocytoplasmic exchange conferred compartmentation advantages. These successive changes took place in naked growing cells, probably as indirect consequences of the origin of phagotrophy. The first eukaryote had 1-2 cilia and also walled resting cysts; I outline how encystation may have promoted the origin of meiotic sex. I also explain why many alternative ideas are inadequate. Nuclear pore complexes are evolutionary chimaeras of endomembrane- and mitosis-related chromatin-associated proteins. The keys to understanding eukaryogenesis are a proper phylogenetic context and understanding organelle coevolution: how innovations in one cell component caused repercussions on others.

Conflict RNA modification, host-parasite co-evolution, and the origins of DNA and DNA-binding proteins1.

PubMed

McLaughlin, Paul J; Keegan, Liam P

2014-08-01

Nearly 150 different enzymatically modified forms of the four canonical residues in RNA have been identified. For instance, enzymes of the ADAR (adenosine deaminase acting on RNA) family convert adenosine residues into inosine in cellular dsRNAs. Recent findings show that DNA endonuclease V enzymes have undergone an evolutionary transition from cleaving 3' to deoxyinosine in DNA and ssDNA to cleaving 3' to inosine in dsRNA and ssRNA in humans. Recent work on dsRNA-binding domains of ADARs and other proteins also shows that a degree of sequence specificity is achieved by direct readout in the minor groove. However, the level of sequence specificity observed is much less than that of DNA major groove-binding helix-turn-helix proteins. We suggest that the evolution of DNA-binding proteins following the RNA to DNA genome transition represents the major advantage that DNA genomes have over RNA genomes. We propose that a hypothetical RNA modification, a RRAR (ribose reductase acting on genomic dsRNA) produced the first stretches of DNA in RNA genomes. We discuss why this is the most satisfactory explanation for the origin of DNA. The evolution of this RNA modification and later steps to DNA genomes are likely to have been driven by cellular genome co-evolution with viruses and intragenomic parasites. RNA modifications continue to be involved in host-virus conflicts; in vertebrates, edited cellular dsRNAs with inosine-uracil base pairs appear to be recognized as self RNA and to suppress activation of innate immune sensors that detect viral dsRNA.

Mechanisms and Evidence of Genital Coevolution: The Roles of Natural Selection, Mate Choice, and Sexual Conflict

PubMed Central

Brennan, Patricia L.R.; Prum, Richard O.

2015-01-01

Genital coevolution between the sexes is expected to be common because of the direct interaction between male and female genitalia during copulation. Here we review the diverse mechanisms of genital coevolution that include natural selection, female mate choice, male–male competition, and how their interactions generate sexual conflict that can lead to sexually antagonistic coevolution. Natural selection on genital morphology will result in size coevolution to allow for copulation to be mechanically possible, even as other features of genitalia may reflect the action of other mechanisms of selection. Genital coevolution is explicitly predicted by at least three mechanisms of genital evolution: lock and key to prevent hybridization, female choice, and sexual conflict. Although some good examples exist in support of each of these mechanisms, more data on quantitative female genital variation and studies of functional morphology during copulation are needed to understand more general patterns. A combination of different approaches is required to continue to advance our understanding of genital coevolution. Knowledge of the ecology and behavior of the studied species combined with functional morphology, quantitative morphological tools, experimental manipulation, and experimental evolution have been provided in the best-studied species, all of which are invertebrates. Therefore, attention to vertebrates in any of these areas is badly needed. PMID:26134314

Evolution of p53 transactivation specificity through the lens of a yeast-based functional assay.

PubMed

Lion, Mattia; Raimondi, Ivan; Donati, Stefano; Jousson, Olivier; Ciribilli, Yari; Inga, Alberto

2015-01-01

Co-evolution of transcription factors (TFs) with their respective cis-regulatory network enhances functional diversity in the course of evolution. We present a new approach to investigate transactivation capacity of sequence-specific TFs in evolutionary studies. Saccharomyces cerevisiae was used as an in vivo test tube and p53 proteins derived from human and five commonly used animal models were chosen as proof of concept. p53 is a highly conserved master regulator of environmental stress responses. Previous reports indicated conserved p53 DNA binding specificity in vitro, even for evolutionary distant species. We used isogenic yeast strains where p53-dependent transactivation was measured towards chromosomally integrated p53 response elements (REs). Ten REs were chosen to sample a wide range of DNA binding affinity and transactivation capacity for human p53 and proteins were expressed at two levels using an inducible expression system. We showed that the assay is amenable to study thermo-sensitivity of frog p53, and that chimeric constructs containing an ectopic transactivation domain could be rapidly developed to enhance the activity of proteins, such as fruit fly p53, that are poorly effective in engaging the yeast transcriptional machinery. Changes in the profile of relative transactivation towards the ten REs were measured for each p53 protein and compared to the profile obtained with human p53. These results, which are largely independent from relative p53 protein levels, revealed widespread evolutionary divergence of p53 transactivation specificity, even between human and mouse p53. Fruit fly and human p53 exhibited the largest discrimination among REs while zebrafish p53 was the least selective.

Evolution of p53 Transactivation Specificity through the Lens of a Yeast-Based Functional Assay

PubMed Central

Lion, Mattia; Raimondi, Ivan; Donati, Stefano; Jousson, Olivier; Ciribilli, Yari; Inga, Alberto

2015-01-01

Co-evolution of transcription factors (TFs) with their respective cis-regulatory network enhances functional diversity in the course of evolution. We present a new approach to investigate transactivation capacity of sequence-specific TFs in evolutionary studies. Saccharomyces cerevisiae was used as an in vivo test tube and p53 proteins derived from human and five commonly used animal models were chosen as proof of concept. p53 is a highly conserved master regulator of environmental stress responses. Previous reports indicated conserved p53 DNA binding specificity in vitro, even for evolutionary distant species. We used isogenic yeast strains where p53-dependent transactivation was measured towards chromosomally integrated p53 response elements (REs). Ten REs were chosen to sample a wide range of DNA binding affinity and transactivation capacity for human p53 and proteins were expressed at two levels using an inducible expression system. We showed that the assay is amenable to study thermo-sensitivity of frog p53, and that chimeric constructs containing an ectopic transactivation domain could be rapidly developed to enhance the activity of proteins, such as fruit fly p53, that are poorly effective in engaging the yeast transcriptional machinery. Changes in the profile of relative transactivation towards the ten REs were measured for each p53 protein and compared to the profile obtained with human p53. These results, which are largely independent from relative p53 protein levels, revealed widespread evolutionary divergence of p53 transactivation specificity, even between human and mouse p53. Fruit fly and human p53 exhibited the largest discrimination among REs while zebrafish p53 was the least selective. PMID:25668429

Detecting sexually antagonistic coevolution with population crosses.

PubMed

Rowe, Locke; Cameron, Erin; Day, Troy

2003-10-07

The result of population crosses on traits such as mating rate, oviposition rate and survivorship are increasingly used to distinguish between modes of coevolution between the sexes. Two key hypotheses, erected from a verbal theory of sexually antagonistic coevolution, have been the subject of several recent tests. First, statistical interactions arising in population crosses are suggested to be indicative of a complex signal/receiver system. In the case of oviposition rates, an interaction between populations (x, y and z) would be indicated by the rank order of female oviposition rates achieved by x, y and z males changing depending upon the female (x, y or z) with which they mated. Second, under sexually antagonistic coevolution females will do 'best' when mated with their own males, where best is defined by the weakest response to the signal and the highest fitness. We test these hypotheses by crossing strains generated from a formal model of sexually antagonistic coevolution. Strains differ in the strength of natural selection acting on male and female traits. In our model, we assume sexually antagonistic coevolution of a single male signal and female receptor. The female receptor is treated as a preference function where both the slope and intercept of the function can evolve. Our results suggest that neither prediction is consistently supported. Interactions are not diagnostic of complex signal-receiver systems, and even under sexually antagonistic coevolution, females may do better mating with males of strains other than their own. These results suggest a reinterpretation of several recent experiments and have important implications for developing theories of speciation when sexually antagonistic coevolution is involved.

Full-Genome Characterisation of Orungo, Lebombo and Changuinola Viruses Provides Evidence for Co-Evolution of Orbiviruses with Their Arthropod Vectors

PubMed Central

Mohd Jaafar, Fauziah; Belhouchet, Mourad; Belaganahalli, Manjunatha; Tesh, Robert B.; Mertens, Peter P. C.; Attoui, Houssam

2014-01-01

The complete genomes of Orungo virus (ORUV), Lebombo virus (LEBV) and Changuinola virus (CGLV) were sequenced, confirming that they each encode 11 distinct proteins (VP1-VP7 and NS1-NS4). Phylogenetic analyses of cell-attachment protein ‘outer-capsid protein 1′ (OC1), show that orbiviruses fall into three large groups, identified as: VP2(OC1), in which OC1 is the 2nd largest protein, including the Culicoides transmitted orbiviruses; VP3(OC1), which includes the mosquito transmitted orbiviruses; and VP4(OC1) which includes the tick transmitted viruses. Differences in the size of OC1 between these groups, places the T2 ‘subcore-shell protein’ as the third largest protein ‘VP3(T2)’ in the first of these groups, but the second largest protein ‘VP3(T2)’ in the other two groups. ORUV, LEBV and CGLV all group with the Culicoides-borne VP2(OC1)/VP3(T2) viruses. The G+C content of the ORUV, LEBV and CGLV genomes is also similar to that of the Culicoides-borne, rather than the mosquito-borne, or tick borne orbiviruses. These data suggest that ORUV and LEBV are Culicoides- rather than mosquito-borne. Multiple isolations of CGLV from sand flies suggest that they are its primary vector. OC1 of the insect-borne orbiviruses is approximately twice the size of the equivalent protein of the tick borne viruses. Together with internal sequence similarities, this suggests its origin by duplication (concatermerisation) of a smaller OC1 from an ancestral tick-borne orbivirus. Phylogenetic comparisons showing linear relationships between the dates of evolutionary-separation of their vector species, and genetic-distances between tick-, mosquito- or Culicoides-borne virus-groups, provide evidence for co-evolution of the orbiviruses with their arthropod vectors. PMID:24475112

Multiple Phase Transitions in the Culture Dissemination

NASA Astrophysics Data System (ADS)

Wang, Bing; Han, Yuexing; Chen, Luonan; Aihara, Kazuyuki

We study the coevolution process in the Axelrod’s model with the consideration of agents’ abilities to access to the information. With a parameter to control the ability of communication, we observe two kinds of phase transitions both for cultural domains and network fragments, respectively. With the simulation results, we find the relationship between the critical value and the controlled parameter. The results indicate that the powerful ability to access to the information benefits the dissemination of culture in the system.

The aminoacyl-tRNA synthetases had only a marginal role in the origin of the organization of the genetic code: Evidence in favor of the coevolution theory.

PubMed

Di Giulio, Massimo

2017-11-07

The coevolution theory of the origin of the genetic code suggests that the organization of the genetic code coevolved with the biosynthetic relationships between amino acids. The mechanism that allowed this coevolution was based on tRNA-like molecules on which-this theory-would postulate the biosynthetic transformations between amino acids to have occurred. This mechanism makes a prediction on how the role conducted by the aminoacyl-tRNA synthetases (ARSs), in the origin of the genetic code, should have been. Indeed, if the biosynthetic transformations between amino acids occurred on tRNA-like molecules, then there was no need to link amino acids to these molecules because amino acids were already charged on tRNA-like molecules, as the coevolution theory suggests. In spite of the fact that ARSs make the genetic code responsible for the first interaction between a component of nucleic acids and that of proteins, for the coevolution theory the role of ARSs should have been entirely marginal in the genetic code origin. Therefore, I have conducted a further analysis of the distribution of the two classes of ARSs and of their subclasses-in the genetic code table-in order to perform a falsification test of the coevolution theory. Indeed, in the case in which the distribution of ARSs within the genetic code would have been highly significant, then the coevolution theory would be falsified since the mechanism on which it is based would not predict a fundamental role of ARSs in the origin of the genetic code. I found that the statistical significance of the distribution of the two classes of ARSs in the table of the genetic code is low or marginal, whereas that of the subclasses of ARSs statistically significant. However, this is in perfect agreement with the postulates of the coevolution theory. Indeed, the only case of statistical significance-regarding the classes of ARSs-is appreciable for the CAG code, whereas for its complement-the UNN/NUN code-only a marginal significance is measurable. These two codes codify roughly for the two ARS classes, in particular, the CAG code for the class II while the UNN/NUN code for the class I. Furthermore, the subclasses of ARSs show a statistical significance of their distribution in the genetic code table. Nevertheless, the more sensible explanation for these observations would be the following. The observation that would link the two classes of ARSs to the CAG and UNN/NUN codes, and the statistical significance of the distribution of the subclasses of ARSs in the genetic code table, would be only a secondary effect due to the highly significant distribution of the polarity of amino acids and their biosynthetic relationships in the genetic code. That is to say, the polarity of amino acids and their biosynthetic relationships would have conditioned the evolution of ARSs so that their presence in the genetic code would have been detectable. Even if the ARSs would not have-on their own-influenced directly the evolutionary organization of the genetic code. In other words, the role that ARSs had in the origin of the genetic code would have been entirely marginal. This conclusion would be in perfect accord with the predictions of the coevolution theory. Conversely, this conclusion would be in contrast-at least partially-with the physicochemical theories of the origin of the genetic code because they would foresee an absolutely more active role of ARSs in the origin of the organization of the genetic code. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characterization of C-ring component assembly in flagellar motors from amino acid coevolution

PubMed Central

dos Santos, Ricardo Nascimento; Khan, Shahid

2018-01-01

Bacterial flagellar motility, an important virulence factor, is energized by a rotary motor localized within the flagellar basal body. The rotor module consists of a large framework (the C-ring), composed of the FliG, FliM and FliN proteins. FliN and FliM contacts the FliG torque ring to control the direction of flagellar rotation. We report that structure-based models constrained only by residue coevolution can recover the binding interface of atomic X-ray dimer complexes with remarkable accuracy (approx. 1 Å RMSD). We propose a model for FliM–FliN heterodimerization, which agrees accurately with homologous interfaces as well as in situ cross-linking experiments, and hence supports a proposed architecture for the lower portion of the C-ring. Furthermore, this approach allowed the identification of two discrete and interchangeable homodimerization interfaces between FliM middle domains that agree with experimental measurements and might be associated with C-ring directional switching dynamics triggered upon binding of CheY signal protein. Our findings provide structural details of complex formation at the C-ring that have been difficult to obtain with previous methodologies and clarify the architectural principle that underpins the ultra-sensitive allostery exhibited by this ring assembly that controls the clockwise or counterclockwise rotation of flagella. PMID:29892378

Macroscopic description of complex adaptive networks coevolving with dynamic node states

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

The prisoner’s dilemma on co-evolving networks under perfect rationality

NASA Astrophysics Data System (ADS)

Biely, Christoly; Dragosits, Klaus; Thurner, Stefan

2007-04-01

We consider the prisoner’s dilemma being played repeatedly on a dynamic network, where agents may choose their actions as well as their co-players. This leads to co-evolution of network structure and strategy patterns of the players. Individual decisions are made fully rationally and are based on local information only. They are made such that links to defecting agents are resolved and that cooperating agents build up new links. The exact form of the updating scheme is motivated by profit maximization and not by imitation. If players update their decisions in a synchronized way the system exhibits oscillatory dynamics: Periods of growing cooperation (and total linkage) alternate with periods of increasing defection. The cyclical behavior is reduced and the system stabilizes at significant total cooperation levels when players are less synchronized. In this regime we find emergent network structures resembling ‘complex’ and hierarchical topology. The exponent of the power-law degree distribution ( γ∼8.6) perfectly matches empirical results for human communication networks.

Disentangling the role of floral sensory stimuli in pollination networks.

PubMed

Kantsa, Aphrodite; Raguso, Robert A; Dyer, Adrian G; Olesen, Jens M; Tscheulin, Thomas; Petanidou, Theodora

2018-03-12

Despite progress in understanding pollination network structure, the functional roles of floral sensory stimuli (visual, olfactory) have never been addressed comprehensively in a community context, even though such traits are known to mediate plant-pollinator interactions. Here, we use a comprehensive dataset of floral traits and a novel dynamic data-pooling methodology to explore the impacts of floral sensory diversity on the structure of a pollination network in a Mediterranean scrubland. Our approach tracks transitions in the network behaviour of each plant species throughout its flowering period and, despite dynamism in visitor composition, reveals significant links to floral scent, and/or colour as perceived by pollinators. Having accounted for floral phenology, abundance and phylogeny, the persistent association between floral sensory traits and visitor guilds supports a deeper role for sensory bias and diffuse coevolution in structuring plant-pollinator networks. This knowledge of floral sensory diversity, by identifying the most influential phenotypes, could help prioritize efforts for plant-pollinator community restoration.

Macroscopic description of complex adaptive networks coevolving with dynamic node states.

PubMed

Wiedermann, Marc; Donges, Jonathan F; Heitzig, Jobst; Lucht, Wolfgang; Kurths, Jürgen

2015-05-01

In many real-world complex systems, the time evolution of the network's structure and the dynamic state of its nodes are closely entangled. Here we study opinion formation and imitation on an adaptive complex network which is dependent on the individual dynamic state of each node and vice versa to model the coevolution of renewable resources with the dynamics of harvesting agents on a social network. The adaptive voter model is coupled to a set of identical logistic growth models and we mainly find that, in such systems, the rate of interactions between nodes as well as the adaptive rewiring probability are crucial parameters for controlling the sustainability of the system's equilibrium state. We derive a macroscopic description of the system in terms of ordinary differential equations which provides a general framework to model and quantify the influence of single node dynamics on the macroscopic state of the network. The thus obtained framework is applicable to many fields of study, such as epidemic spreading, opinion formation, or socioecological modeling.

Modeling Coevolution between Language and Memory Capacity during Language Origin

PubMed Central

Gong, Tao; Shuai, Lan

2015-01-01

Memory is essential to many cognitive tasks including language. Apart from empirical studies of memory effects on language acquisition and use, there lack sufficient evolutionary explorations on whether a high level of memory capacity is prerequisite for language and whether language origin could influence memory capacity. In line with evolutionary theories that natural selection refined language-related cognitive abilities, we advocated a coevolution scenario between language and memory capacity, which incorporated the genetic transmission of individual memory capacity, cultural transmission of idiolects, and natural and cultural selections on individual reproduction and language teaching. To illustrate the coevolution dynamics, we adopted a multi-agent computational model simulating the emergence of lexical items and simple syntax through iterated communications. Simulations showed that: along with the origin of a communal language, an initially-low memory capacity for acquired linguistic knowledge was boosted; and such coherent increase in linguistic understandability and memory capacities reflected a language-memory coevolution; and such coevolution stopped till memory capacities became sufficient for language communications. Statistical analyses revealed that the coevolution was realized mainly by natural selection based on individual communicative success in cultural transmissions. This work elaborated the biology-culture parallelism of language evolution, demonstrated the driving force of culturally-constituted factors for natural selection of individual cognitive abilities, and suggested that the degree difference in language-related cognitive abilities between humans and nonhuman animals could result from a coevolution with language. PMID:26544876

Mechanisms and Evidence of Genital Coevolution: The Roles of Natural Selection, Mate Choice, and Sexual Conflict.

PubMed

Brennan, Patricia L R; Prum, Richard O

2015-07-01

Genital coevolution between the sexes is expected to be common because of the direct interaction between male and female genitalia during copulation. Here we review the diverse mechanisms of genital coevolution that include natural selection, female mate choice, male-male competition, and how their interactions generate sexual conflict that can lead to sexually antagonistic coevolution. Natural selection on genital morphology will result in size coevolution to allow for copulation to be mechanically possible, even as other features of genitalia may reflect the action of other mechanisms of selection. Genital coevolution is explicitly predicted by at least three mechanisms of genital evolution: lock and key to prevent hybridization, female choice, and sexual conflict. Although some good examples exist in support of each of these mechanisms, more data on quantitative female genital variation and studies of functional morphology during copulation are needed to understand more general patterns. A combination of different approaches is required to continue to advance our understanding of genital coevolution. Knowledge of the ecology and behavior of the studied species combined with functional morphology, quantitative morphological tools, experimental manipulation, and experimental evolution have been provided in the best-studied species, all of which are invertebrates. Therefore, attention to vertebrates in any of these areas is badly needed. Copyright © 2015 Cold Spring Harbor Laboratory Press; all rights reserved.

Modeling Coevolution between Language and Memory Capacity during Language Origin.

PubMed

Gong, Tao; Shuai, Lan

2015-01-01

Memory is essential to many cognitive tasks including language. Apart from empirical studies of memory effects on language acquisition and use, there lack sufficient evolutionary explorations on whether a high level of memory capacity is prerequisite for language and whether language origin could influence memory capacity. In line with evolutionary theories that natural selection refined language-related cognitive abilities, we advocated a coevolution scenario between language and memory capacity, which incorporated the genetic transmission of individual memory capacity, cultural transmission of idiolects, and natural and cultural selections on individual reproduction and language teaching. To illustrate the coevolution dynamics, we adopted a multi-agent computational model simulating the emergence of lexical items and simple syntax through iterated communications. Simulations showed that: along with the origin of a communal language, an initially-low memory capacity for acquired linguistic knowledge was boosted; and such coherent increase in linguistic understandability and memory capacities reflected a language-memory coevolution; and such coevolution stopped till memory capacities became sufficient for language communications. Statistical analyses revealed that the coevolution was realized mainly by natural selection based on individual communicative success in cultural transmissions. This work elaborated the biology-culture parallelism of language evolution, demonstrated the driving force of culturally-constituted factors for natural selection of individual cognitive abilities, and suggested that the degree difference in language-related cognitive abilities between humans and nonhuman animals could result from a coevolution with language.

Balancing Selection at the Tomato RCR3 Guardee Gene Family Maintains Variation in Strength of Pathogen Defense

PubMed Central

Hörger, Anja C.; Ilyas, Muhammad; Stephan, Wolfgang; Tellier, Aurélien; van der Hoorn, Renier A. L.; Rose, Laura E.

2012-01-01

Coevolution between hosts and pathogens is thought to occur between interacting molecules of both species. This results in the maintenance of genetic diversity at pathogen antigens (or so-called effectors) and host resistance genes such as the major histocompatibility complex (MHC) in mammals or resistance (R) genes in plants. In plant–pathogen interactions, the current paradigm posits that a specific defense response is activated upon recognition of pathogen effectors via interaction with their corresponding R proteins. According to the “Guard-Hypothesis,” R proteins (the “guards”) can sense modification of target molecules in the host (the “guardees”) by pathogen effectors and subsequently trigger the defense response. Multiple studies have reported high genetic diversity at R genes maintained by balancing selection. In contrast, little is known about the evolutionary mechanisms shaping the guardee, which may be subject to contrasting evolutionary forces. Here we show that the evolution of the guardee RCR3 is characterized by gene duplication, frequent gene conversion, and balancing selection in the wild tomato species Solanum peruvianum. Investigating the functional characteristics of 54 natural variants through in vitro and in planta assays, we detected differences in recognition of the pathogen effector through interaction with the guardee, as well as substantial variation in the strength of the defense response. This variation is maintained by balancing selection at each copy of the RCR3 gene. Our analyses pinpoint three amino acid polymorphisms with key functional consequences for the coevolution between the guardee (RCR3) and its guard (Cf-2). We conclude that, in addition to coevolution at the “guardee-effector” interface for pathogen recognition, natural selection acts on the “guard-guardee” interface. Guardee evolution may be governed by a counterbalance between improved activation in the presence and prevention of auto-immune responses in the absence of the corresponding pathogen. PMID:22829777

A Combined Computational and Genetic Approach Uncovers Network Interactions of the Cyanobacterial Circadian Clock.

PubMed

Boyd, Joseph S; Cheng, Ryan R; Paddock, Mark L; Sancar, Cigdem; Morcos, Faruck; Golden, Susan S

2016-09-15

Two-component systems (TCS) that employ histidine kinases (HK) and response regulators (RR) are critical mediators of cellular signaling in bacteria. In the model cyanobacterium Synechococcus elongatus PCC 7942, TCSs control global rhythms of transcription that reflect an integration of time information from the circadian clock with a variety of cellular and environmental inputs. The HK CikA and the SasA/RpaA TCS transduce time information from the circadian oscillator to modulate downstream cellular processes. Despite immense progress in understanding of the circadian clock itself, many of the connections between the clock and other cellular signaling systems have remained enigmatic. To narrow the search for additional TCS components that connect to the clock, we utilized direct-coupling analysis (DCA), a statistical analysis of covariant residues among related amino acid sequences, to infer coevolution of new and known clock TCS components. DCA revealed a high degree of interaction specificity between SasA and CikA with RpaA, as expected, but also with the phosphate-responsive response regulator SphR. Coevolutionary analysis also predicted strong specificity between RpaA and a previously undescribed kinase, HK0480 (herein CikB). A knockout of the gene for CikB (cikB) in a sasA cikA null background eliminated the RpaA phosphorylation and RpaA-controlled transcription that is otherwise present in that background and suppressed cell elongation, supporting the notion that CikB is an interactor with RpaA and the clock network. This study demonstrates the power of DCA to identify subnetworks and key interactions in signaling pathways and of combinatorial mutagenesis to explore the phenotypic consequences. Such a combined strategy is broadly applicable to other prokaryotic systems. Signaling networks are complex and extensive, comprising multiple integrated pathways that respond to cellular and environmental cues. A TCS interaction model, based on DCA, independently confirmed known interactions and revealed a core set of subnetworks within the larger HK-RR set. We validated high-scoring candidate proteins via combinatorial genetics, demonstrating that DCA can be utilized to reduce the search space of complex protein networks and to infer undiscovered specific interactions for signaling proteins in vivo Significantly, new interactions that link circadian response to cell division and fitness in a light/dark cycle were uncovered. The combined analysis also uncovered a more basic core clock, illustrating the synergy and applicability of a combined computational and genetic approach for investigating prokaryotic signaling networks. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

The coevolution of partner switching and strategy updating in non-excludable public goods game

NASA Astrophysics Data System (ADS)

Li, Yixiao; Shen, Bin

2013-10-01

Spatial public goods game is a popular metaphor to model the dilemma of collective cooperation on graphs, yet the non-excludable property of public goods has seldom been considered in previous models. Based upon a coevolutionary model where agents play public goods games and adjust their partnerships, the present model incorporates the non-excludable property of public goods: agents are able to adjust their participation in the games hosted by others, whereas they cannot exclude others from their own games. In the coevolution, a directed and dynamical network which represents partnerships among autonomous agents is evolved. We find that non-excludable property counteracts the positive effect of partner switching, i.e., the equilibrium level of cooperation is lower than that in the situation of excludable public goods game. Therefore, we study the effect of individual punishment that cooperative agents pay a personal cost to decrease benefits of those defective neighbors who participate in their hosted games. It is found that the cooperation level in the whole population is heightened in the presence of such a costly behavior.

Solar radiation and landscape evolution: co-evolution of topography, vegetation, and erosion rates in a semi-arid ecosystem

NASA Astrophysics Data System (ADS)

Istanbulluoglu, Erkan; Yetemen, Omer

2016-04-01

In this study CHILD landscape evolution model (LEM) is used to study the role of solar radiation on the co-evolution of landscape morphology, vegetation patterns, and erosion rates in a central New Mexico catchment. In the study site north facing slopes (NFS) are characterized by steep diffusion-dominated planar hillslopes covered by co-exiting juniper pine and grass vegetation. South facing slopes (SFS) are characterized by shallow slopes and covered by sparse shrub vegetation. Measured short-term and Holocene-averaged erosion rates show higher soil loss on SFS than NFS. In this study CHILD LEM is first confirmed with ecohydrologic field data and used to systematically examine the co-evolution of topography, vegetation pattern, and erosion rates. Aspect- and network-control are identified as the two main topographic drivers of soil moisture and vegetation organization on the landscape. Landscape-scale and long-term implications of solar radiation driven ecohdrologic patterns emerged in modeled landscape: NFS supported denser vegetation cover and became steeper and planar, while on SFS vegetation grew sparser and slopes declined with more fluvial activity. At the landscape scale, these differential erosion processes led to asymmetric development of catchment forms, consistent with regional observations. While the general patterns of vegetation and topography were reproduced by the model using a stationary representation of the current climate, the observed differential Holocene erosion rates were captured by the model only when cyclic climate is used. This suggests sensitivity of Holocene erosion rates to long-term climate fluctuations.

Wing patterning genes and coevolution of Müllerian mimicry in Heliconius butterflies: Support from phylogeography, cophylogeny, and divergence times.

PubMed

Hoyal Cuthill, Jennifer F; Charleston, Michael

2015-12-01

Examples of long-term coevolution are rare among free-living organisms. Müllerian mimicry in Heliconius butterflies had been suggested as a key example of coevolution by early genetic studies. However, research over the last two decades has been dominated by the idea that the best-studied comimics, H. erato and H. melpomene, did not coevolve at all. Recently sequenced genes associated with wing color pattern phenotype offer a new opportunity to resolve this controversy. Here, we test the hypothesis of coevolution between H. erato and H. melpomene using Bayesian multilocus analysis of five color pattern genes and five neutral genetic markers. We first explore the extent of phylogenetic agreement versus conflict between the different genes. Coevolution is then tested against three aspects of the mimicry diversifications: phylogenetic branching patterns, divergence times, and, for the first time, phylogeographic histories. We show that all three lines of evidence are compatible with strict coevolution of the diverse mimicry wing patterns, contrary to some recent suggestions. Instead, these findings tally with a coevolutionary diversification driven primarily by the ecological force of Müllerian mimicry. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Phenotype selection reveals coevolution of muscle glycogen and protein and PTEN as a gate keeper for the accretion of muscle mass in adult female mice.

PubMed

Sawitzky, Mandy; Zeissler, Anja; Langhammer, Martina; Bielohuby, Maximilian; Stock, Peggy; Hammon, Harald M; Görs, Solvig; Metges, Cornelia C; Stoehr, Barbara J M; Bidlingmaier, Martin; Fromm-Dornieden, Carolin; Baumgartner, Bernhard G; Christ, Bruno; Brenig, Bertram; Binder, Gerhard; Metzger, Friedrich; Renne, Ulla; Hoeflich, Andreas

2012-01-01

We have investigated molecular mechanisms for muscle mass accretion in a non-inbred mouse model (DU6P mice) characterized by extreme muscle mass. This extreme muscle mass was developed during 138 generations of phenotype selection for high protein content. Due to the repeated trait selection a complex setting of different mechanisms was expected to be enriched during the selection experiment. In muscle from 29-week female DU6P mice we have identified robust increases of protein kinase B activation (AKT, Ser-473, up to 2-fold) if compared to 11- and 54-week DU6P mice or controls. While a number of accepted effectors of AKT activation, including IGF-I, IGF-II, insulin/IGF-receptor, myostatin or integrin-linked kinase (ILK), were not correlated with this increase, phosphatase and tensin homologue deleted on chromosome 10 (PTEN) was down-regulated in 29-week female DU6P mice. In addition, higher levels of PTEN phosphorylation were found identifying a second mechanism of PTEN inhibition. Inhibition of PTEN and activation of AKT correlated with specific activation of p70S6 kinase and ribosomal protein S6, reduced phosphorylation of eukaryotic initiation factor 2α (eIF2α) and higher rates of protein synthesis in 29-week female DU6P mice. On the other hand, AKT activation also translated into specific inactivation of glycogen synthase kinase 3ß (GSK3ß) and an increase of muscular glycogen. In muscles from 29-week female DU6P mice a significant increase of protein/DNA was identified, which was not due to a reduction of protein breakdown or to specific increases of translation initiation. Instead our data support the conclusion that a higher rate of protein translation is contributing to the higher muscle mass in mid-aged female DU6P mice. Our results further reveal coevolution of high protein and high glycogen content during the selection experiment and identify PTEN as gate keeper for muscle mass in mid-aged female DU6P mice.

Phenotype Selection Reveals Coevolution of Muscle Glycogen and Protein and PTEN as a Gate Keeper for the Accretion of Muscle Mass in Adult Female Mice

PubMed Central

Sawitzky, Mandy; Zeissler, Anja; Langhammer, Martina; Bielohuby, Maximilian; Stock, Peggy; Hammon, Harald M.; Görs, Solvig; Metges, Cornelia C.; Stoehr, Barbara J. M.; Bidlingmaier, Martin; Fromm-Dornieden, Carolin; Baumgartner, Bernhard G.; Christ, Bruno; Brenig, Bertram; Binder, Gerhard; Metzger, Friedrich; Renne, Ulla; Hoeflich, Andreas

2012-01-01

We have investigated molecular mechanisms for muscle mass accretion in a non-inbred mouse model (DU6P mice) characterized by extreme muscle mass. This extreme muscle mass was developed during 138 generations of phenotype selection for high protein content. Due to the repeated trait selection a complex setting of different mechanisms was expected to be enriched during the selection experiment. In muscle from 29-week female DU6P mice we have identified robust increases of protein kinase B activation (AKT, Ser-473, up to 2-fold) if compared to 11- and 54-week DU6P mice or controls. While a number of accepted effectors of AKT activation, including IGF-I, IGF-II, insulin/IGF-receptor, myostatin or integrin-linked kinase (ILK), were not correlated with this increase, phosphatase and tensin homologue deleted on chromosome 10 (PTEN) was down-regulated in 29-week female DU6P mice. In addition, higher levels of PTEN phosphorylation were found identifying a second mechanism of PTEN inhibition. Inhibition of PTEN and activation of AKT correlated with specific activation of p70S6 kinase and ribosomal protein S6, reduced phosphorylation of eukaryotic initiation factor 2α (eIF2α) and higher rates of protein synthesis in 29-week female DU6P mice. On the other hand, AKT activation also translated into specific inactivation of glycogen synthase kinase 3ß (GSK3ß) and an increase of muscular glycogen. In muscles from 29-week female DU6P mice a significant increase of protein/DNA was identified, which was not due to a reduction of protein breakdown or to specific increases of translation initiation. Instead our data support the conclusion that a higher rate of protein translation is contributing to the higher muscle mass in mid-aged female DU6P mice. Our results further reveal coevolution of high protein and high glycogen content during the selection experiment and identify PTEN as gate keeper for muscle mass in mid-aged female DU6P mice. PMID:22768110

Evolution of photorespiration from cyanobacteria to land plants, considering protein phylogenies and acquisition of carbon concentrating mechanisms.

PubMed

Hagemann, Martin; Kern, Ramona; Maurino, Veronica G; Hanson, David T; Weber, Andreas P M; Sage, Rowan F; Bauwe, Hermann

2016-05-01

Photorespiration and oxygenic photosynthesis are intimately linked processes. It has been shown that under the present day atmospheric conditions cyanobacteria and all eukaryotic phototrophs need functional photorespiration to grow autotrophically. The question arises as to when this essential partnership evolved, i.e. can we assume a coevolution of both processes from the beginning or did photorespiration evolve later to compensate for the generation of 2-phosphoglycolate (2PG) due to Rubisco's oxygenase reaction? This question is mainly discussed here using phylogenetic analysis of proteins involved in the 2PG metabolism and the acquisition of different carbon concentrating mechanisms (CCMs). The phylogenies revealed that the enzymes involved in the photorespiration of vascular plants have diverse origins, with some proteins acquired from cyanobacteria as ancestors of the chloroplasts and others from heterotrophic bacteria as ancestors of mitochondria in the plant cell. Only phosphoglycolate phosphatase was found to originate from Archaea. Notably glaucophyte algae, the earliest branching lineage of Archaeplastida, contain more photorespiratory enzymes of cyanobacterial origin than other algal lineages or land plants indicating a larger initial contribution of cyanobacterial-derived proteins to eukaryotic photorespiration. The acquisition of CCMs is discussed as a proxy for assessing the timing of periods when photorespiratory activity may have been enhanced. The existence of CCMs also had marked influence on the structure and function of photorespiration. Here, we discuss evidence for an early and continuous coevolution of photorespiration, CCMs and photosynthesis starting from cyanobacteria via algae, to land plants. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Coevolution of Epidemics, Social Networks, and Individual Behavior: A Case Study

NASA Astrophysics Data System (ADS)

Chen, Jiangzhuo; Marathe, Achla; Marathe, Madhav

This research shows how a limited supply of antivirals can be distributed optimally between the hospitals and the market so that the attack rate is minimized and enough revenue is generated to recover the cost of the antivirals. Results using an individual based model find that prevalence elastic demand behavior delays the epidemic and change in the social contact network induced by isolation reduces the peak of the epidemic significantly. A microeconomic analysis methodology combining behavioral economics and agent-based simulation is a major contribution of this work. In this paper we apply this methodology to analyze the fairness of the stockpile distribution, and the response of human behavior to disease prevalence level and its interaction with the market.

Predicting language diversity with complex networks.

PubMed

Raducha, Tomasz; Gubiec, Tomasz

2018-01-01

We analyze the model of social interactions with coevolution of the topology and states of the nodes. This model can be interpreted as a model of language change. We propose different rewiring mechanisms and perform numerical simulations for each. Obtained results are compared with the empirical data gathered from two online databases and anthropological study of Solomon Islands. We study the behavior of the number of languages for different system sizes and we find that only local rewiring, i.e. triadic closure, is capable of reproducing results for the empirical data in a qualitative manner. Furthermore, we cancel the contradiction between previous models and the Solomon Islands case. Our results demonstrate the importance of the topology of the network, and the rewiring mechanism in the process of language change.

Evol and ProDy for bridging protein sequence evolution and structural dynamics.

PubMed

Bakan, Ahmet; Dutta, Anindita; Mao, Wenzhi; Liu, Ying; Chennubhotla, Chakra; Lezon, Timothy R; Bahar, Ivet

2014-09-15

Correlations between sequence evolution and structural dynamics are of utmost importance in understanding the molecular mechanisms of function and their evolution. We have integrated Evol, a new package for fast and efficient comparative analysis of evolutionary patterns and conformational dynamics, into ProDy, a computational toolbox designed for inferring protein dynamics from experimental and theoretical data. Using information-theoretic approaches, Evol coanalyzes conservation and coevolution profiles extracted from multiple sequence alignments of protein families with their inferred dynamics. ProDy and Evol are open-source and freely available under MIT License from http://prody.csb.pitt.edu/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Coevolution can reverse predator–prey cycles

PubMed Central

Cortez, Michael H.; Weitz, Joshua S.

2014-01-01

A hallmark of Lotka–Volterra models, and other ecological models of predator–prey interactions, is that in predator–prey cycles, peaks in prey abundance precede peaks in predator abundance. Such models typically assume that species life history traits are fixed over ecologically relevant time scales. However, the coevolution of predator and prey traits has been shown to alter the community dynamics of natural systems, leading to novel dynamics including antiphase and cryptic cycles. Here, using an eco-coevolutionary model, we show that predator–prey coevolution can also drive population cycles where the opposite of canonical Lotka–Volterra oscillations occurs: predator peaks precede prey peaks. These reversed cycles arise when selection favors extreme phenotypes, predator offense is costly, and prey defense is effective against low-offense predators. We present multiple datasets from phage–cholera, mink–muskrat, and gyrfalcon–rock ptarmigan systems that exhibit reversed-peak ordering. Our results suggest that such cycles are a potential signature of predator–prey coevolution and reveal unique ways in which predator–prey coevolution can shape, and possibly reverse, community dynamics. PMID:24799689

Coevolution can reverse predator-prey cycles.

PubMed

Cortez, Michael H; Weitz, Joshua S

2014-05-20

A hallmark of Lotka-Volterra models, and other ecological models of predator-prey interactions, is that in predator-prey cycles, peaks in prey abundance precede peaks in predator abundance. Such models typically assume that species life history traits are fixed over ecologically relevant time scales. However, the coevolution of predator and prey traits has been shown to alter the community dynamics of natural systems, leading to novel dynamics including antiphase and cryptic cycles. Here, using an eco-coevolutionary model, we show that predator-prey coevolution can also drive population cycles where the opposite of canonical Lotka-Volterra oscillations occurs: predator peaks precede prey peaks. These reversed cycles arise when selection favors extreme phenotypes, predator offense is costly, and prey defense is effective against low-offense predators. We present multiple datasets from phage-cholera, mink-muskrat, and gyrfalcon-rock ptarmigan systems that exhibit reversed-peak ordering. Our results suggest that such cycles are a potential signature of predator-prey coevolution and reveal unique ways in which predator-prey coevolution can shape, and possibly reverse, community dynamics.

Interactions among human behavior, social networks, and societal infrastructures: A Case Study in Computational Epidemiology

NASA Astrophysics Data System (ADS)

Barrett, Christopher L.; Bisset, Keith; Chen, Jiangzhuo; Eubank, Stephen; Lewis, Bryan; Kumar, V. S. Anil; Marathe, Madhav V.; Mortveit, Henning S.

Human behavior, social networks, and the civil infrastructures are closely intertwined. Understanding their co-evolution is critical for designing public policies and decision support for disaster planning. For example, human behaviors and day to day activities of individuals create dense social interactions that are characteristic of modern urban societies. These dense social networks provide a perfect fabric for fast, uncontrolled disease propagation. Conversely, people’s behavior in response to public policies and their perception of how the crisis is unfolding as a result of disease outbreak can dramatically alter the normally stable social interactions. Effective planning and response strategies must take these complicated interactions into account. In this chapter, we describe a computer simulation based approach to study these issues using public health and computational epidemiology as an illustrative example. We also formulate game-theoretic and stochastic optimization problems that capture many of the problems that we study empirically.

Development blocks in innovation networks: The Swedish manufacturing industry, 1970-2007.

PubMed

Taalbi, Josef

2017-01-01

The notion of development blocks (Dahmén, 1950, 1991) suggests the co-evolution of technologies and industries through complementarities and the overcoming of imbalances. This study proposes and applies a methodology to analyse development blocks empirically. To assess the extent and character of innovational interdependencies between industries the study combines analysis of innovation biographies and statistical network analysis. This is made possible by using data from a newly constructed innovation output database for Sweden. The study finds ten communities of closely related industries in which innovation activity has been prompted by the emergence of technological imbalances or by the exploitation of new technological opportunities. The communities found in the Swedish network of innovation are shown to be stable over time and often characterized by strong user-supplier interdependencies. These findings serve to stress how historical imbalances and opportunities are key to understanding the dynamics of the long-run development of industries and new technologies.

Origin of the cell nucleus, mitosis and sex: roles of intracellular coevolution

PubMed Central

2010-01-01

Background The transition from prokaryotes to eukaryotes was the most radical change in cell organisation since life began, with the largest ever burst of gene duplication and novelty. According to the coevolutionary theory of eukaryote origins, the fundamental innovations were the concerted origins of the endomembrane system and cytoskeleton, subsequently recruited to form the cell nucleus and coevolving mitotic apparatus, with numerous genetic eukaryotic novelties inevitable consequences of this compartmentation and novel DNA segregation mechanism. Physical and mutational mechanisms of origin of the nucleus are seldom considered beyond the long-standing assumption that it involved wrapping pre-existing endomembranes around chromatin. Discussions on the origin of sex typically overlook its association with protozoan entry into dormant walled cysts and the likely simultaneous coevolutionary, not sequential, origin of mitosis and meiosis. Results I elucidate nuclear and mitotic coevolution, explaining the origins of dicer and small centromeric RNAs for positionally controlling centromeric heterochromatin, and how 27 major features of the cell nucleus evolved in four logical stages, making both mechanisms and selective advantages explicit: two initial stages (origin of 30 nm chromatin fibres, enabling DNA compaction; and firmer attachment of endomembranes to heterochromatin) protected DNA and nascent RNA from shearing by novel molecular motors mediating vesicle transport, division, and cytoplasmic motility. Then octagonal nuclear pore complexes (NPCs) arguably evolved from COPII coated vesicle proteins trapped in clumps by Ran GTPase-mediated cisternal fusion that generated the fenestrated nuclear envelope, preventing lethal complete cisternal fusion, and allowing passive protein and RNA exchange. Finally, plugging NPC lumens by an FG-nucleoporin meshwork and adopting karyopherins for nucleocytoplasmic exchange conferred compartmentation advantages. These successive changes took place in naked growing cells, probably as indirect consequences of the origin of phagotrophy. The first eukaryote had 1-2 cilia and also walled resting cysts; I outline how encystation may have promoted the origin of meiotic sex. I also explain why many alternative ideas are inadequate. Conclusion Nuclear pore complexes are evolutionary chimaeras of endomembrane- and mitosis-related chromatin-associated proteins. The keys to understanding eukaryogenesis are a proper phylogenetic context and understanding organelle coevolution: how innovations in one cell component caused repercussions on others. Reviewers This article was reviewed by Anthony Poole, Gáspár Jékely and Eugene Koonin. PMID:20132544

A Simulation of Cooperation and Competition in Insurgent Networks

NASA Astrophysics Data System (ADS)

Gabbay, Michael

2014-03-01

Insurgencies are often characterized by multiple groups who share a common foe in the national government but have independent organizations which may differ with respect to social identities, ideologies, strategies, and their use of violence. These groups may cooperate in various ways such as conducting joint attacks, pooling resources, and establishing formal alliances or mergers. However, they may also compete with each other over popular support, recruitment of fighters, funding, allies, and ultimately military dominance. A network coevolution model of insurgent factional dynamics is presented which accounts for factors driving cooperation and competition. The model is formulated as a system of coupled ODEs which evolves network ties between insurgent groups along with group policies concerning the targets of violence. Simulation results are presented showing sharp transitions in network structure as model parameters are varied. Connections are drawn between the model results and empirical data from the Iraqi insurgency. This work was supported by the Office of Naval Research under grant N00014-13-1-0381.

COUSCOus: improved protein contact prediction using an empirical Bayes covariance estimator.

PubMed

Rawi, Reda; Mall, Raghvendra; Kunji, Khalid; El Anbari, Mohammed; Aupetit, Michael; Ullah, Ehsan; Bensmail, Halima

2016-12-15

The post-genomic era with its wealth of sequences gave rise to a broad range of protein residue-residue contact detecting methods. Although various coevolution methods such as PSICOV, DCA and plmDCA provide correct contact predictions, they do not completely overlap. Hence, new approaches and improvements of existing methods are needed to motivate further development and progress in the field. We present a new contact detecting method, COUSCOus, by combining the best shrinkage approach, the empirical Bayes covariance estimator and GLasso. Using the original PSICOV benchmark dataset, COUSCOus achieves mean accuracies of 0.74, 0.62 and 0.55 for the top L/10 predicted long, medium and short range contacts, respectively. In addition, COUSCOus attains mean areas under the precision-recall curves of 0.25, 0.29 and 0.30 for long, medium and short contacts and outperforms PSICOV. We also observed that COUSCOus outperforms PSICOV w.r.t. Matthew's correlation coefficient criterion on full list of residue contacts. Furthermore, COUSCOus achieves on average 10% more gain in prediction accuracy compared to PSICOV on an independent test set composed of CASP11 protein targets. Finally, we showed that when using a simple random forest meta-classifier, by combining contact detecting techniques and sequence derived features, PSICOV predictions should be replaced by the more accurate COUSCOus predictions. We conclude that the consideration of superior covariance shrinkage approaches will boost several research fields that apply the GLasso procedure, amongst the presented one of residue-residue contact prediction as well as fields such as gene network reconstruction.

Widespread Positive Selection Drives Differentiation of Centromeric Proteins in the Drosophila melanogaster subgroup.

PubMed

Beck, Emily A; Llopart, Ana

2015-11-25

Rapid evolution of centromeric satellite repeats is thought to cause compensatory amino acid evolution in interacting centromere-associated kinetochore proteins. Cid, a protein that mediates kinetochore/centromere interactions, displays particularly high amino acid turnover. Rapid evolution of both Cid and centromeric satellite repeats led us to hypothesize that the apparent compensatory evolution may extend to interacting partners in the Condensin I complex (i.e., SMC2, SMC4, Cap-H, Cap-D2, and Cap-G) and HP1s. Missense mutations in these proteins often result in improper centromere formation and aberrant chromosome segregation, thus selection for maintained function and coevolution among proteins of the complex is likely strong. Here, we report evidence of rapid evolution and recurrent positive selection in seven centromere-associated proteins in species of the Drosophila melanogaster subgroup, and further postulate that positive selection on these proteins could be a result of centromere drive and compensatory changes, with kinetochore proteins competing for optimal spindle attachment.

Combinatorial pathway optimization in Escherichia coli by directed co-evolution of rate-limiting enzymes and modular pathway engineering.

PubMed

Lv, Xiaomei; Gu, Jiali; Wang, Fan; Xie, Wenping; Liu, Min; Ye, Lidan; Yu, Hongwei

2016-12-01

Metabolic engineering of microorganisms for heterologous biosynthesis is a promising route to sustainable chemical production which attracts increasing research and industrial interest. However, the efficiency of microbial biosynthesis is often restricted by insufficient activity of pathway enzymes and unbalanced utilization of metabolic intermediates. This work presents a combinatorial strategy integrating modification of multiple rate-limiting enzymes and modular pathway engineering to simultaneously improve intra- and inter-pathway balance, which might be applicable for a range of products, using isoprene as an example product. For intra-module engineering within the methylerythritol-phosphate (MEP) pathway, directed co-evolution of DXS/DXR/IDI was performed adopting a lycopene-indicated high-throughput screening method developed herein, leading to 60% improvement of isoprene production. In addition, inter-module engineering between the upstream MEP pathway and the downstream isoprene-forming pathway was conducted via promoter manipulation, which further increased isoprene production by 2.94-fold compared to the recombinant strain with solely protein engineering and 4.7-fold compared to the control strain containing wild-type enzymes. These results demonstrated the potential of pathway optimization in isoprene overproduction as well as the effectiveness of combining metabolic regulation and protein engineering in improvement of microbial biosynthesis. Biotechnol. Bioeng. 2016;113: 2661-2669. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Positive selection on human gamete-recognition genes

PubMed Central

Stover, Daryn A.; Guerra, Vanessa; Mozaffari, Sahar V.; Ober, Carole; Mugal, Carina F.; Kaj, Ingemar

2018-01-01

Coevolution of genes that encode interacting proteins expressed on the surfaces of sperm and eggs can lead to variation in reproductive compatibility between mates and reproductive isolation between members of different species. Previous studies in mice and other mammals have focused in particular on evidence for positive or diversifying selection that shapes the evolution of genes that encode sperm-binding proteins expressed in the egg coat or zona pellucida (ZP). By fitting phylogenetic models of codon evolution to data from the 1000 Genomes Project, we identified candidate sites evolving under diversifying selection in the human genes ZP3 and ZP2. We also identified one candidate site under positive selection in C4BPA, which encodes a repetitive protein similar to the mouse protein ZP3R that is expressed in the sperm head and binds to the ZP at fertilization. Results from several additional analyses that applied population genetic models to the same data were consistent with the hypothesis of selection on those candidate sites leading to coevolution of sperm- and egg-expressed genes. By contrast, we found no candidate sites under selection in a fourth gene (ZP1) that encodes an egg coat structural protein not directly involved in sperm binding. Finally, we found that two of the candidate sites (in C4BPA and ZP2) were correlated with variation in family size and birth rate among Hutterite couples, and those two candidate sites were also in linkage disequilibrium in the same Hutterite study population. All of these lines of evidence are consistent with predictions from a previously proposed hypothesis of balancing selection on epistatic interactions between C4BPA and ZP3 at fertilization that lead to the evolution of co-adapted allele pairs. Such patterns also suggest specific molecular traits that may be associated with both natural reproductive variation and clinical infertility. PMID:29340252

Modelling opinion formation driven communities in social networks

NASA Astrophysics Data System (ADS)

Iñiguez, Gerardo; Barrio, Rafael A.; Kertész, János; Kaski, Kimmo K.

2011-09-01

In a previous paper we proposed a model to study the dynamics of opinion formation in human societies by a co-evolution process involving two distinct time scales of fast transaction and slower network evolution dynamics. In the transaction dynamics we take into account short range interactions as discussions between individuals and long range interactions to describe the attitude to the overall mood of society. The latter is handled by a uniformly distributed parameter α, assigned randomly to each individual, as quenched personal bias. The network evolution dynamics is realised by rewiring the societal network due to state variable changes as a result of transaction dynamics. The main consequence of this complex dynamics is that communities emerge in the social network for a range of values in the ratio between time scales. In this paper we focus our attention on the attitude parameter α and its influence on the conformation of opinion and the size of the resulting communities. We present numerical studies and extract interesting features of the model that can be interpreted in terms of social behaviour.

Co-evolution with chicken class I genes.

PubMed

Kaufman, Jim

2015-09-01

The concept of co-evolution (or co-adaptation) has a long history, but application at molecular levels (e.g., 'supergenes' in genetics) is more recent, with a consensus definition still developing. One interesting example is the chicken major histocompatibility complex (MHC). In contrast to typical mammals that have many class I and class I-like genes, only two classical class I genes, two CD1 genes and some non-classical Rfp-Y genes are known in chicken, and all are found on the microchromosome that bears the MHC. Rarity of recombination between the closely linked and polymorphic genes encoding classical class I and TAPs allows co-evolution, leading to a single dominantly expressed class I molecule in each MHC haplotype, with strong functional consequences in terms of resistance to infectious pathogens. Chicken tapasin is highly polymorphic, but co-evolution with TAP and class I genes remains unclear. T-cell receptors, natural killer (NK) cell receptors, and CD8 co-receptor genes are found on non-MHC chromosomes, with some evidence for co-evolution of surface residues and number of genes along the avian and mammalian lineages. Over even longer periods, co-evolution has been invoked to explain how the adaptive immune system of jawed vertebrates arose from closely linked receptor, ligand, and antigen-processing genes in the primordial MHC. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Critical mass of public goods and its coevolution with cooperation

NASA Astrophysics Data System (ADS)

Shi, Dong-Mei; Wang, Bing-Hong

2017-07-01

In this study, the enhancing parameter represented the value of the public goods to the public in public goods game, and was rescaled to a Fermi-Dirac distribution function of critical mass. Public goods were divided into two categories, consumable and reusable public goods, and their coevolution with cooperative behavior was studied. We observed that for both types of public goods, cooperation was promoted as the enhancing parameter increased when the value of critical mass was not very large. An optimal value of critical mass which led to the best cooperation was identified. We also found that cooperations emerged earlier for reusable public goods, and defections became extinct earlier for the consumable public goods. Moreover, we observed that a moderate depreciation rate for public goods resulted in an optimal cooperation, and this range became wider as the enhancing parameter increased. The noise influence on cooperation was studied, and it was shown that cooperation density varied non-monotonically as noise amplitude increased for reusable public goods, whereas decreased monotonically for consumable public goods. Furthermore, existence of the optimal critical mass was also identified in other three regular networks. Finally, simulation results were utilized to analyze the provision of public goods in detail.

Darwin and the linguists: the coevolution of mind and language, part 2. The language-thought relationship.

PubMed

Alter, Stephen G

2008-03-01

This paper examines Charles Darwin's idea that language-use and humanity's unique cognitive abilities reinforced each other's evolutionary emergence-an idea Darwin sketched in his early notebooks, set forth in his Descent of man (1871), and qualified in Descent's second (1874) edition. Darwin understood this coevolution process in essentially Lockean terms, based on John Locke's hints about the way language shapes thinking itself. Ironically, the linguist Friedrich Max Müller attacked Darwin's human descent theory by invoking a similar thesis, the German romantic notion of an identity between language and thought. Although Darwin avoided outright contradiction, when he came to defend himself against Müller's attacks, he undercut some of his own argumentation in favor of the coevolution idea. That is, he found it difficult to counter Müller's argument while also making a case for coevolution. Darwin's efforts in this area were further complicated by British and American writers who held a naturalistic view of speech origins yet still taught that language had been invented by fully evolved homo sapiens, thus denying coevolution.

Predicting language diversity with complex networks

PubMed Central

Gubiec, Tomasz

2018-01-01

We analyze the model of social interactions with coevolution of the topology and states of the nodes. This model can be interpreted as a model of language change. We propose different rewiring mechanisms and perform numerical simulations for each. Obtained results are compared with the empirical data gathered from two online databases and anthropological study of Solomon Islands. We study the behavior of the number of languages for different system sizes and we find that only local rewiring, i.e. triadic closure, is capable of reproducing results for the empirical data in a qualitative manner. Furthermore, we cancel the contradiction between previous models and the Solomon Islands case. Our results demonstrate the importance of the topology of the network, and the rewiring mechanism in the process of language change. PMID:29702699

Beyond neutral and forbidden links: morphological matches and the assembly of mutualistic hawkmoth-plant networks.

PubMed

Sazatornil, Federico D; Moré, Marcela; Benitez-Vieyra, Santiago; Cocucci, Andrea A; Kitching, Ian J; Schlumpberger, Boris O; Oliveira, Paulo E; Sazima, Marlies; Amorim, Felipe W

2016-11-01

A major challenge in evolutionary ecology is to understand how co-evolutionary processes shape patterns of interactions between species at community level. Pollination of flowers with long corolla tubes by long-tongued hawkmoths has been invoked as a showcase model of co-evolution. Recently, optimal foraging models have predicted that there might be a close association between mouthparts' length and the corolla depth of the visited flowers, thus favouring trait convergence and specialization at community level. Here, we assessed whether hawkmoths more frequently pollinate plants with floral tube lengths similar to their proboscis lengths (morphological match hypothesis) against abundance-based processes (neutral hypothesis) and ecological trait mismatches constraints (forbidden links hypothesis), and how these processes structure hawkmoth-plant mutualistic networks from five communities in four biogeographical regions of South America. We found convergence in morphological traits across the five communities and that the distribution of morphological differences between hawkmoths and plants is consistent with expectations under the morphological match hypothesis in three of the five communities. In the two remaining communities, which are ecotones between two distinct biogeographical areas, interactions are better predicted by the neutral hypothesis. Our findings are consistent with the idea that diffuse co-evolution drives the evolution of extremely long proboscises and flower tubes, and highlight the importance of morphological traits, beyond the forbidden links hypothesis, in structuring interactions between mutualistic partners, revealing that the role of niche-based processes can be much more complex than previously known. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

The RNA-world and co-evolution hypotheses and the origin of life: Implications, research strategies and perspectives

NASA Astrophysics Data System (ADS)

Lahav, Noam

1993-12-01

The applicability of the RNA-world and co-evolution hypotheses to the study of the very first stages of the origin of life is discussed. The discussion focuses on the basic differences between the two hypotheses and their implications, with regard to the reconstruction methodology, ribosome emergence, balance between ribozymes and protein enzymes, and their major difficulties. Additional complexities of the two hypotheses, such as membranes and the energy source of the first reactions, are not treated in the present work. A central element in the proposed experimental strategies is the study of the catalytic activities of very small peptides and RNA-like oligomers, according to existing, as well as to yet-to-be-invented scenarios of the two hypotheses under consideration. It is suggested that the noveldirected molecular evolution technology, andmolecular computational modeling, can be applied to this research. This strategy is assumed to be essential for the suggested goal of future studies of the origin of life, namely, the establishment of a ‘Primordial Darwinian entity’.

The RNA-world and co-evolution hypothesis and the origin of life: Implications, research strategies and perspectives

NASA Technical Reports Server (NTRS)

Lahav, Noam

1993-01-01

The applicability of the RNA-world and co-evolution hypothesis to the study of the very first stages of the origin of life is discussed. The discussion focuses on the basic differences between the two hypotheses and their implications, with regard to the reconstruction methodology, ribosome emergence, balance between ribozymes and protein enzymes, and their major difficultites. Additional complexities of the two hypotheses, such as membranes and the energy source of the first reactions, are not treated in the present work. A central element in the proposed experimental strategies is the study of the catalytic activites of very small peptides and RNA-like oligomers, according to existing, as well as to yet-to-be-invented scenarios of the two hypothesis under consideration. It is suggested that the novel directed molecular evolution technology, and molecular computational modeling, can be applied to this research. This strategy is assumed to be essential for the suggested goal of future studies of the origin of life, namely, the establishment of a `Primordial Darwinian entity'.

Coevolution of Glauber-like Ising dynamics and topology

NASA Astrophysics Data System (ADS)

Mandrà, Salvatore; Fortunato, Santo; Castellano, Claudio

2009-11-01

We study the coevolution of a generalized Glauber dynamics for Ising spins with tunable threshold and of the graph topology where the dynamics takes place. This simple coevolution dynamics generates a rich phase diagram in the space of the two parameters of the model, the threshold and the rewiring probability. The diagram displays phase transitions of different types: spin ordering, percolation, and connectedness. At variance with traditional coevolution models, in which all spins of each connected component of the graph have equal value in the stationary state, we find that, for suitable choices of the parameters, the system may converge to a state in which spins of opposite sign coexist in the same component organized in compact clusters of like-signed spins. Mean field calculations enable one to estimate some features of the phase diagram.

Knowledge diffusion of dynamical network in terms of interaction frequency.

PubMed

Liu, Jian-Guo; Zhou, Qing; Guo, Qiang; Yang, Zhen-Hua; Xie, Fei; Han, Jing-Ti

2017-09-07

In this paper, we present a knowledge diffusion (SKD) model for dynamic networks by taking into account the interaction frequency which always used to measure the social closeness. A set of agents, which are initially interconnected to form a random network, either exchange knowledge with their neighbors or move toward a new location through an edge-rewiring procedure. The activity of knowledge exchange between agents is determined by a knowledge transfer rule that the target node would preferentially select one neighbor node to transfer knowledge with probability p according to their interaction frequency instead of the knowledge distance, otherwise, the target node would build a new link with its second-order neighbor preferentially or select one node in the system randomly with probability 1 - p. The simulation results show that, comparing with the Null model defined by the random selection mechanism and the traditional knowledge diffusion (TKD) model driven by knowledge distance, the knowledge would spread more fast based on SKD driven by interaction frequency. In particular, the network structure of SKD would evolve as an assortative one, which is a fundamental feature of social networks. This work would be helpful for deeply understanding the coevolution of the knowledge diffusion and network structure.

Evolution, Energy Landscapes and the Paradoxes of Protein Folding

PubMed Central

Wolynes, Peter G.

2014-01-01

Protein folding has been viewed as a difficult problem of molecular self-organization. The search problem involved in folding however has been simplified through the evolution of folding energy landscapes that are funneled. The funnel hypothesis can be quantified using energy landscape theory based on the minimal frustration principle. Strong quantitative predictions that follow from energy landscape theory have been widely confirmed both through laboratory folding experiments and from detailed simulations. Energy landscape ideas also have allowed successful protein structure prediction algorithms to be developed. The selection constraint of having funneled folding landscapes has left its imprint on the sequences of existing protein structural families. Quantitative analysis of co-evolution patterns allows us to infer the statistical characteristics of the folding landscape. These turn out to be consistent with what has been obtained from laboratory physicochemical folding experiments signalling a beautiful confluence of genomics and chemical physics. PMID:25530262

Evolution of a Novel Antiviral Immune-Signaling Interaction by Partial-Gene Duplication

PubMed Central

Korithoski, Bryan; Kolaczkowski, Oralia; Mukherjee, Krishanu; Kola, Reema; Earl, Chandra; Kolaczkowski, Bryan

2015-01-01

The RIG-like receptors (RLRs) are related proteins that identify viral RNA in the cytoplasm and activate cellular immune responses, primarily through direct protein-protein interactions with the signal transducer, IPS1. Although it has been well established that the RLRs, RIG-I and MDA5, activate IPS1 through binding between the twin caspase activation and recruitment domains (CARDs) on the RLR and a homologous CARD on IPS1, it is less clear which specific RLR CARD(s) are required for this interaction, and almost nothing is known about how the RLR-IPS1 interaction evolved. In contrast to what has been observed in the presence of immune-modulating K63-linked polyubiquitin, here we show that—in the absence of ubiquitin—it is the first CARD domain of human RIG-I and MDA5 (CARD1) that binds directly to IPS1 CARD, and not the second (CARD2). Although the RLRs originated in the earliest animals, both the IPS1 gene and the twin-CARD domain architecture of RIG-I and MDA5 arose much later in the deuterostome lineage, probably through a series of tandem partial-gene duplication events facilitated by tight clustering of RLRs and IPS1 in the ancestral deuterostome genome. Functional differentiation of RIG-I CARD1 and CARD2 appears to have occurred early during this proliferation of RLR and related CARDs, potentially driven by adaptive coevolution between RIG-I CARD domains and IPS1 CARD. However, functional differentiation of MDA5 CARD1 and CARD2 occurred later. These results fit a general model in which duplications of protein-protein interaction domains into novel gene contexts could facilitate the expansion of signaling networks and suggest a potentially important role for functionally-linked gene clusters in generating novel immune-signaling pathways. PMID:26356745

The co-evolution of networks and prisoner’s dilemma game by considering sensitivity and visibility

NASA Astrophysics Data System (ADS)

Li, Dandan; Ma, Jing; Han, Dun; Sun, Mei; Tian, Lixin; Stanley, H. Eugene

2017-03-01

Strategies adopted by individuals in a social network significantly impact the network, and they strongly affect relationships between individuals in the network. Links between individuals also heavily influence their levels of cooperation. Taking into account the evolution of each individual’s connection, we explore how sensitivity and visibility affect the prisoner’s dilemma game. The so-called ‘sensitivity’ and ‘visibility’ respectively present one’s self-protection consciousness and the ability of gaining information. We find that at moderate levels of player sensitivity cooperative behavior increases, but that at high levels it is inhibited. We also find that the heterogeneity of the weight of individuals at the end of the game is higher when sensitivity and visibility are increased, but that the successful-defection-payoff has less impact on the weight of individuals and on the relationship between the heterogeneity of the weight of individuals and the density of cooperators. This framework can be used to clarify the interaction mechanism between the micro-level of individual behavior and the macro-level of individual co-evolutionary processes.

The co-evolution of networks and prisoner's dilemma game by considering sensitivity and visibility.

PubMed

Li, Dandan; Ma, Jing; Han, Dun; Sun, Mei; Tian, Lixin; Stanley, H Eugene

2017-03-24

Strategies adopted by individuals in a social network significantly impact the network, and they strongly affect relationships between individuals in the network. Links between individuals also heavily influence their levels of cooperation. Taking into account the evolution of each individual's connection, we explore how sensitivity and visibility affect the prisoner's dilemma game. The so-called 'sensitivity' and 'visibility' respectively present one's self-protection consciousness and the ability of gaining information. We find that at moderate levels of player sensitivity cooperative behavior increases, but that at high levels it is inhibited. We also find that the heterogeneity of the weight of individuals at the end of the game is higher when sensitivity and visibility are increased, but that the successful-defection-payoff has less impact on the weight of individuals and on the relationship between the heterogeneity of the weight of individuals and the density of cooperators. This framework can be used to clarify the interaction mechanism between the micro-level of individual behavior and the macro-level of individual co-evolutionary processes.

The co-evolution of networks and prisoner’s dilemma game by considering sensitivity and visibility

PubMed Central

Li, Dandan; Ma, Jing; Han, Dun; Sun, Mei; Tian, Lixin; Stanley, H. Eugene

2017-01-01

Strategies adopted by individuals in a social network significantly impact the network, and they strongly affect relationships between individuals in the network. Links between individuals also heavily influence their levels of cooperation. Taking into account the evolution of each individual’s connection, we explore how sensitivity and visibility affect the prisoner’s dilemma game. The so-called ‘sensitivity’ and ‘visibility’ respectively present one’s self-protection consciousness and the ability of gaining information. We find that at moderate levels of player sensitivity cooperative behavior increases, but that at high levels it is inhibited. We also find that the heterogeneity of the weight of individuals at the end of the game is higher when sensitivity and visibility are increased, but that the successful-defection-payoff has less impact on the weight of individuals and on the relationship between the heterogeneity of the weight of individuals and the density of cooperators. This framework can be used to clarify the interaction mechanism between the micro-level of individual behavior and the macro-level of individual co-evolutionary processes. PMID:28338070

Coevolution in the Galapagos: An Example for the Biology Classroom.

ERIC Educational Resources Information Center

Biggs, Alton L.

1990-01-01

Several examples of coevolution which can be used in biology classes are presented. Discussed are evolutionary processes in general, giant cacti, and reptile and cacti association. The effects of human interference are briefly described. (CW)

A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice

PubMed Central

Snijders, Tom A.B.; Lomi, Alessandro; Torló, Vanina Jasmine

2012-01-01

We propose a new stochastic actor-oriented model for the co-evolution of two-mode and one-mode networks. The model posits that activities of a set of actors, represented in the two-mode network, co-evolve with exchanges and interactions between the actors, as represented in the one-mode network. The model assumes that the actors, not the activities, have agency. The empirical value of the model is demonstrated by examining how employment preferences co-evolve with friendship and advice relations in a group of seventy-five MBA students. The analysis shows that activity in the two-mode network, as expressed by number of employment preferences, is related to activity in the friendship network, as expressed by outdegrees. Further, advice ties between students lead to agreement with respect to employment preferences. In addition, considering the multiplexity of advice and friendship ties yields a better understanding of the dynamics of the advice relation: tendencies to reciprocation and homophily in advice relations are mediated to an important extent by friendship relations. The discussion pays attention to the implications of this study in the broader context of current efforts to model the co-evolutionary dynamics of social networks and individual behavior. PMID:23690653

Social selection and peer influence in an online social network.

PubMed

Lewis, Kevin; Gonzalez, Marco; Kaufman, Jason

2012-01-03

Disentangling the effects of selection and influence is one of social science's greatest unsolved puzzles: Do people befriend others who are similar to them, or do they become more similar to their friends over time? Recent advances in stochastic actor-based modeling, combined with self-reported data on a popular online social network site, allow us to address this question with a greater degree of precision than has heretofore been possible. Using data on the Facebook activity of a cohort of college students over 4 years, we find that students who share certain tastes in music and in movies, but not in books, are significantly likely to befriend one another. Meanwhile, we find little evidence for the diffusion of tastes among Facebook friends-except for tastes in classical/jazz music. These findings shed light on the mechanisms responsible for observed network homogeneity; provide a statistically rigorous assessment of the coevolution of cultural tastes and social relationships; and suggest important qualifications to our understanding of both homophily and contagion as generic social processes.

Duck Interferon-Inducible Transmembrane Protein 3 Mediates Restriction of Influenza Viruses.

PubMed

Blyth, Graham A D; Chan, Wing Fuk; Webster, Robert G; Magor, Katharine E

2016-01-01

Interferon-inducible transmembrane proteins (IFITMs) can restrict the entry of a wide range of viruses. IFITM3 localizes to endosomes and can potently restrict the replication of influenza A viruses (IAV) and several other viruses that also enter host cells through the endocytic pathway. Here, we investigate whether IFITMs are involved in protection in ducks, the natural host of influenza virus. We identify and sequence duck IFITM1, IFITM2, IFITM3, and IFITM5. Using quantitative PCR (qPCR), we demonstrate the upregulation of these genes in lung tissue in response to highly pathogenic IAV infection by 400-fold, 30-fold, 30-fold, and 5-fold, respectively. We express each IFITM in chicken DF-1 cells and show duck IFITM1 localizes to the cell surface, while IFITM3 localizes to LAMP1-containing compartments. DF-1 cells stably expressing duck IFITM3 (but not IFITM1 or IFITM2) show increased restriction of replication of H1N1, H6N2, and H11N9 IAV strains but not vesicular stomatitis virus. Although duck and human IFITM3 share only 38% identity, critical residues for viral restriction are conserved. We generate chimeric and mutant IFITM3 proteins and show duck IFITM3 does not require its N-terminal domain for endosomal localization or antiviral function; however, this N-terminal end confers endosomal localization and antiviral function on IFITM1. In contrast to mammalian IFITM3, the conserved YXXθ endocytosis signal sequence in the N-terminal domain of duck IFITM3 is not essential for correct endosomal localization. Despite significant structural and amino acid divergence, presumably due to host-virus coevolution, duck IFITM3 is functional against IAV. Immune IFITM genes are poorly conserved across species, suggesting that selective pressure from host-specific viruses has driven this divergence. We wondered whether coevolution between viruses and their natural host would result in the evasion of IFITM restriction. Ducks are the natural host of avian influenza A viruses and display few or no disease symptoms upon infection with most strains, including highly pathogenic avian influenza. We have characterized the duck IFITM locus and identified IFITM3 as an important restrictor of several influenza A viruses, including avian strains. With only 38% amino acid identity to human IFITM3, duck IFITM3 possesses antiviral function against influenza virus. Thus, despite long coevolution of virus and host effectors in the natural host, influenza virus evasion of IFITM3 restriction in ducks is not apparent. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Adaptive Evolution of Signaling Partners

PubMed Central

Urano, Daisuke; Dong, Taoran; Bennetzen, Jeffrey L.; Jones, Alan M.

2015-01-01

Proteins that interact coevolve their structures. When mutation disrupts the interaction, compensation by the partner occurs to restore interaction otherwise counterselection occurs. We show in this study how a destabilizing mutation in one protein is compensated by a stabilizing mutation in its protein partner and their coevolving path. The pathway in this case and likely a general principle of coevolution is that the compensatory change must tolerate both the original and derived structures with equivalence in function and activity. Evolution of the structure of signaling elements in a network is constrained by specific protein pair interactions, by requisite conformational changes, and by catalytic activity. The heterotrimeric G protein-coupled signaling is a paragon of this protein interaction/function complexity and our deep understanding of this pathway in diverse organisms lends itself to evolutionary study. Regulators of G protein Signaling (RGS) proteins accelerate the intrinsic GTP hydrolysis rate of the Gα subunit of the heterotrimeric G protein complex. An important RGS-contact site is a hydroxyl-bearing residue on the switch I region of Gα subunits in animals and most plants, such as Arabidopsis. The exception is the grasses (e.g., rice, maize, sugarcane, millets); these plants have Gα subunits that replaced the critical hydroxyl-bearing threonine with a destabilizing asparagine shown to disrupt interaction between Arabidopsis RGS protein (AtRGS1) and the grass Gα subunit. With one known exception (Setaria italica), grasses do not encode RGS genes. One parsimonious deduction is that the RGS gene was lost in the ancestor to the grasses and then recently acquired horizontally in the lineage S. italica from a nongrass monocot. Like all investigated grasses, S. italica has the Gα subunit with the destabilizing asparagine residue in the protein interface but, unlike other known grass genomes, still encodes an expressed RGS gene, SiRGS1. SiRGS1 accelerates GTP hydrolysis at similar concentration of both Gα subunits containing either the stabilizing (AtGPA1) or destabilizing (RGA1) interface residue. SiRGS1 does not use the hydroxyl-bearing residue on Gα to promote GAP activity and has a larger Gα-interface pocket fitting to the destabilizing Gα. These findings indicate that SiRGS1 adapted to a deleterious mutation on Gα using existing polymorphism in the RGS protein population. PMID:25568345

An extension of the coevolution theory of the origin of the genetic code

PubMed Central

Di Giulio, Massimo

2008-01-01

Background The coevolution theory of the origin of the genetic code suggests that the genetic code is an imprint of the biosynthetic relationships between amino acids. However, this theory does not seem to attribute a role to the biosynthetic relationships between the earliest amino acids that evolved along the pathways of energetic metabolism. As a result, the coevolution theory is unable to clearly define the very earliest phases of genetic code origin. In order to remove this difficulty, I here suggest an extension of the coevolution theory that attributes a crucial role to the first amino acids that evolved along these biosynthetic pathways and to their biosynthetic relationships, even when defined by the non-amino acid molecules that are their precursors. Results It is re-observed that the first amino acids to evolve along these biosynthetic pathways are predominantly those codified by codons of the type GNN, and this observation is found to be statistically significant. Furthermore, the close biosynthetic relationships between the sibling amino acids Ala-Ser, Ser-Gly, Asp-Glu, and Ala-Val are not random in the genetic code table and reinforce the hypothesis that the biosynthetic relationships between these six amino acids played a crucial role in defining the very earliest phases of genetic code origin. Conclusion All this leads to the hypothesis that there existed a code, GNS, reflecting the biosynthetic relationships between these six amino acids which, as it defines the very earliest phases of genetic code origin, removes the main difficulty of the coevolution theory. Furthermore, it is here discussed how this code might have naturally led to the code codifying only for the domains of the codons of precursor amino acids, as predicted by the coevolution theory. Finally, the hypothesis here suggested also removes other problems of the coevolution theory, such as the existence for certain pairs of amino acids with an unclear biosynthetic relationship between the precursor and product amino acids and the collocation of Ala between the amino acids Val and Leu belonging to the pyruvate biosynthetic family, which the coevolution theory considered as belonging to different biosyntheses. Reviewers This article was reviewed by Rob Knight, Paul Higgs (nominated by Laura Landweber), and Eugene Koonin. PMID:18775066

Quantifying the propagation of distress and mental disorders in social networks.

PubMed

Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro

2018-03-22

Heterogeneity of human beings leads to think and react differently to social phenomena. Awareness and homophily drive people to weigh interactions in social multiplex networks, influencing a potential contagion effect. To quantify the impact of heterogeneity on spreading dynamics, we propose a model of coevolution of social contagion and awareness, through the introduction of statistical estimators, in a weighted multiplex network. Multiplexity of networked individuals may trigger propagation enough to produce effects among vulnerable subjects experiencing distress, mental disorder, which represent some of the strongest predictors of suicidal behaviours. The exposure to suicide is emotionally harmful, since talking about it may give support or inadvertently promote it. To disclose the complex effect of the overlapping awareness on suicidal ideation spreading among disordered people, we also introduce a data-driven approach by integrating different types of data. Our modelling approach unveils the relationship between distress and mental disorders propagation and suicidal ideation spreading, shedding light on the role of awareness in a social network for suicide prevention. The proposed model is able to quantify the impact of overlapping awareness on suicidal ideation spreading and our findings demonstrate that it plays a dual role on contagion, either reinforcing or delaying the contagion outbreak.

Models for the modern power grid

NASA Astrophysics Data System (ADS)

Nardelli, Pedro H. J.; Rubido, Nicolas; Wang, Chengwei; Baptista, Murilo S.; Pomalaza-Raez, Carlos; Cardieri, Paulo; Latva-aho, Matti

2014-10-01

This article reviews different kinds of models for the electric power grid that can be used to understand the modern power system, the smart grid. From the physical network to abstract energy markets, we identify in the literature different aspects that co-determine the spatio-temporal multilayer dynamics of power system. We start our review by showing how the generation, transmission and distribution characteristics of the traditional power grids are already subject to complex behaviour appearing as a result of the the interplay between dynamics of the nodes and topology, namely synchronisation and cascade effects. When dealing with smart grids, the system complexity increases even more: on top of the physical network of power lines and controllable sources of electricity, the modernisation brings information networks, renewable intermittent generation, market liberalisation, prosumers, among other aspects. In this case, we forecast a dynamical co-evolution of the smart grid and other kind of networked systems that cannot be understood isolated. This review compiles recent results that model electric power grids as complex systems, going beyond pure technological aspects. From this perspective, we then indicate possible ways to incorporate the diverse co-evolving systems into the smart grid model using, for example, network theory and multi-agent simulation.

Coevolution of Cooperation and Partner Rewiring Range in Spatial Social Networks

NASA Astrophysics Data System (ADS)

Khoo, Tommy; Fu, Feng; Pauls, Scott

2016-11-01

In recent years, there has been growing interest in the study of coevolutionary games on networks. Despite much progress, little attention has been paid to spatially embedded networks, where the underlying geographic distance, rather than the graph distance, is an important and relevant aspect of the partner rewiring process. It thus remains largely unclear how individual partner rewiring range preference, local vs. global, emerges and affects cooperation. Here we explicitly address this issue using a coevolutionary model of cooperation and partner rewiring range preference in spatially embedded social networks. In contrast to local rewiring, global rewiring has no distance restriction but incurs a one-time cost upon establishing any long range link. We find that under a wide range of model parameters, global partner switching preference can coevolve with cooperation. Moreover, the resulting partner network is highly degree-heterogeneous with small average shortest path length while maintaining high clustering, thereby possessing small-world properties. We also discover an optimum availability of reputation information for the emergence of global cooperators, who form distant partnerships at a cost to themselves. From the coevolutionary perspective, our work may help explain the ubiquity of small-world topologies arising alongside cooperation in the real world.

Co-evolution and thresholds in arid floodplain wetland ecosystems.

NASA Astrophysics Data System (ADS)

Sandi, Steven; Rodriguez, Jose; Riccardi, Gerardo; Wen, Li; Saintilan, Neil

2017-04-01

Vegetation in arid floodplain wetlands consist of water dependent and flood tolerant species that rely on periodical floods in order to maintain healthy conditions. The floodplain often consist of a complex system of marshes, swamps and lagoons interconnected by a network of streams and poorly defined rills. Over time, feedbacks develop between vegetation and flow paths producing areas of flow obstruction and flow concentration, which combined with depositional and erosional process lead to a continuous change on the position and characteristics of inundation areas. This coevolution of flow paths and vegetation can reach a threshold that triggers major channel transformations and abandonment of wetland areas, in a process that is irreversible. The Macquarie Marshes is a floodplain wetland complex in the semi-arid region of north western NSW, Australia. The site is characterised by a low-gradient topography that leads to channel breakdown processes where the river network becomes practically non-existent and the flow extends over large areas of wetland that later re-join and reform channels exiting the system. Due to a combination of climatic and anthropogenic pressures, the wetland ecosystem in the Macquarie Marshes has deteriorated over the past few decades. This has been linked to decreasing inundation frequencies and extent, with whole areas of flood dependent species such as Water Couch and Common Reed undergoing complete succession to terrestrial species and dryland. In this presentation we provide an overview of an ecogeomorphological model that we have developed in order to simulate the complex dynamics of the marshes. The model combines hydrodynamic, vegetation and channel evolution modules. We focus on the vegetation component of the model and the transitional rules to predict wetland invasion by terrestrial vegetation.

Coevolution of a multilayer node-aligned network whose layers represent different social relations.

PubMed

Bahulkar, Ashwin; Szymanski, Boleslaw K; Chan, Kevin; Lizardo, Omar

2017-01-01

We examine the coevolution of three-layer node-aligned network of university students. The first layer is defined by nominations based on perceived prominence collected from repeated surveys during the first four semesters; the second is a behavioral layer representing actual students' interactions based on records of mobile calls and text messages; while the third is a behavioral layer representing potential face-to-face interactions suggested by bluetooth collocations. We address four interrelated questions. First, we ask whether the formation or dissolution of a link in one of the layers precedes or succeeds the formation or dissolution of the corresponding link in another layer (temporal dependencies). Second, we explore the causes of observed temporal dependencies between the layers. For those temporal dependencies that are confirmed, we measure the predictive capability of such dependencies. Third, we observe the progress towards nominations and the stages that lead to them. Finally, we examine whether the differences in dissolution rates of symmetric (undirected) versus asymmetric (directed) links co-exist in all layers. We find strong patterns of reciprocal temporal dependencies between the layers. In particular, the creation of an edge in either behavioral layer generally precedes the formation of a corresponding edge in the nomination layer. Conversely, the decay of a link in the nomination layer generally precedes a decline in the intensity of communication and collocation. Finally, nodes connected by asymmetric nomination edges have lower overall communication and collocation volumes and more asymmetric communication flows than the nodes linked by symmetric edges. We find that creation and dissolution of cognitively salient contacts have temporal dependencies with communication and collocation behavior.

The early phase of the SMBH-galaxy coevolution in low-z "young" galaxies

NASA Astrophysics Data System (ADS)

Nagao, Tohru

2014-01-01

It is now widely recognized that most galaxies have a supermassive black hole (SMBH) in their nucleus, and the evolution of SMBHs is closely related with that of their host galaxies (the SMBH-galaxy coevolution). This is suggested by the correlation in the mass of SMBHs and their host galaxies, that has been observed in low redshifts. However, the physics of the coevolution is totally unclear, that prevents us from complete understandings of the galaxy evolution. One possible strategy to tackle this issue is measuring the mass ratio between SMBHs and their host galaxies (M_BH/M_host) at high redshifs, since different scenarios predict different evolution of the ratio ofMBH/Mhost. However it is extremely challenging to measure the mass of the host of high-z quasars, given the faint surface brightness of the host at close to the glaring quasar nucleus. Here we propose a brand-new approach to assess the early phase of the SMBH-galaxy coevolution, by focusing on low-z AGN-hosting "young" galaxies. Specifically, we focus on some very metal-poor galaxies with broadline Balmer lines at z ~ 0.1 - 0.3. By examining the SMBH scaling relations in some low-z metal-poor AGNs through high-resolution IRCS imaging observations, we will discriminate various scenarios for the SMBH-galaxy coevolution.

The role of epigenetics in host-parasite coevolution: lessons from the model host insects Galleria mellonella and Tribolium castaneum.

PubMed

Vilcinskas, Andreas

2016-08-01

Recent studies addressing experimental host-parasite coevolution and transgenerational immune priming in insects provide evidence for heritable shifts in host resistance or parasite virulence. These rapid reciprocal adaptations may thus be transferred to offspring generations by either genetic changes or mechanisms that do not involve changes in the germline DNA sequence. Epigenetic inheritance refers to changes in gene expression that are heritable across generations and mediated by epigenetic modifications passed from parents to offspring. Highlighting the role of epigenetics in host-parasite coevolution, this review discusses the involvement of DNA methylation, histone acetylation/deacetylation and microRNAs in the interactions between bacterial or fungal parasites and model host insects such as the greater wax moth Galleria mellonella and the red flour beetle Tribolium castaneum. These epigenetic mechanisms are thought to participate in generation-spanning transcriptional reprogramming in the host insect, often linking immunity with developmentally related gene expression and contributing to the heredity of acquired adaptations. It is proposed that the interactions during host-parasite coevolution can therefore be expanded beyond reciprocal genetic changes to include reciprocal epigenetic changes. Epigenetics is thus a promising and prospering field in the context of host-parasite coevolution. Copyright © 2016 The Author. Published by Elsevier GmbH.. All rights reserved.

Host-parasite coevolution can promote the evolution of seed banking as a bet-hedging strategy.

PubMed

Verin, Mélissa; Tellier, Aurélien

2018-04-20

Seed (egg) banking is a common bet-hedging strategy maximizing the fitness of organisms facing environmental unpredictability by the delayed emergence of offspring. Yet, this condition often requires fast and drastic stochastic shifts between good and bad years. We hypothesize that the host seed banking strategy can evolve in response to coevolution with parasites because the coevolutionary cycles promote a gradually changing environment over longer times than seed persistence. We study the evolution of host germination fraction as a quantitative trait using both pairwise competition and multiple mutant competition methods, while the germination locus can be genetically linked or unlinked with the host locus under coevolution. In a gene-for-gene model of coevolution, hosts evolve a seed bank strategy under unstable coevolutionary cycles promoted by moderate to high costs of resistance or strong disease severity. Moreover, when assuming genetic linkage between coevolving and germination loci, the resistant genotype always evolves seed banking in contrast to susceptible hosts. Under a matching-allele interaction, both hosts' genotypes exhibit the same seed banking strategy irrespective of the genetic linkage between loci. We suggest host-parasite coevolution as an additional hypothesis for the evolution of seed banking as a temporal bet-hedging strategy. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

Flies and flowers in Darwin's race.

PubMed

Pauw, Anton; Stofberg, Jaco; Waterman, Richard J

2009-01-01

The idea of coevolution originated with Darwin's proposal that long-proboscid pollinators and long-tubed flowers might be engaged in reciprocal selection, but this has not been demonstrated. Here we test key aspects of Darwin's hypothesis of reciprocal selection in an experiment with naturally interacting populations of extremely long-proboscid flies (Moegistorhynchus longirostris: Nemestinidae) and long-tubed irises (Lapeirousia anceps: Iridaceae). We show that the benefit derived by both the fly (volume of nectar consumed) and the plant (number pollen grains received) depends on the relative length of their interacting organs. Each trait is shown to act both as agent and target in directional reciprocal selection, potentially leading to a race. This understanding of how fitness in both species varies in relation to the balance of their armament allows us to make tentative predictions about the nature of selection across multiple communities. We find that in each community a core group of long-tubed plant species might together be involved in diffuse coevolution with the fly. In poorly matched populations, the imbalance in armament is too great to allow reciprocal selection to act, and these species might instead experience one-sided selection that leads to convergence with the core species. Reciprocal selection drives the evolution of the community, then, additional species become attached to the network of interacting mutualists by convergence.

The Co-evolution of Neuroimaging and Psychiatric Neurosurgery.

PubMed

Dyster, Timothy G; Mikell, Charles B; Sheth, Sameer A

2016-01-01

The role of neuroimaging in psychiatric neurosurgery has evolved significantly throughout the field's history. Psychiatric neurosurgery initially developed without the benefit of information provided by modern imaging modalities, and thus lesion targets were selected based on contemporary theories of frontal lobe dysfunction in psychiatric disease. However, by the end of the 20th century, the availability of structural and functional magnetic resonance imaging (fMRI) allowed for the development of mechanistic theories attempting to explain the anatamofunctional basis of these disorders, as well as the efficacy of stereotactic neuromodulatory treatments. Neuroimaging now plays a central and ever-expanding role in the neurosurgical management of psychiatric disorders, by influencing the determination of surgical candidates, allowing individualized surgical targeting and planning, and identifying network-level changes in the brain following surgery. In this review, we aim to describe the coevolution of psychiatric neurosurgery and neuroimaging, including ways in which neuroimaging has proved useful in elucidating the therapeutic mechanisms of neuromodulatory procedures. We focus on ablative over stimulation-based procedures given their historical precedence and the greater opportunity they afford for post-operative re-imaging, but also discuss important contributions from the deep brain stimulation (DBS) literature. We conclude with a discussion of how neuroimaging will transition the field of psychiatric neurosurgery into the era of precision medicine.

Building toy models of proteins using coevolutionary information

NASA Astrophysics Data System (ADS)

Cheng, Ryan; Raghunathan, Mohit; Onuchic, Jose

2015-03-01

Recent developments in global statistical methodologies have advanced the analysis of large collections of protein sequences for coevolutionary information. Coevolution between amino acids in a protein arises from compensatory mutations that are needed to maintain the stability or function of a protein over the course of evolution. This gives rise to quantifiable correlations between amino acid positions within the multiple sequence alignment of a protein family. Here, we use Direct Coupling Analysis (DCA) to infer a Potts model Hamiltonian governing the correlated mutations in a protein family to obtain the sequence-dependent interaction energies of a toy protein model. We demonstrate that this methodology predicts residue-residue interaction energies that are consistent with experimental mutational changes in protein stabilities as well as other computational methodologies. Furthermore, we demonstrate with several examples that DCA could be used to construct a structure-based model that quantitatively agrees with experimental data on folding mechanisms. This work serves as a potential framework for generating models of proteins that are enriched by evolutionary data that can potentially be used to engineer key functional motions and interactions in protein systems. This research has been supported by the NSF INSPIRE award MCB-1241332 and by the CTBP sponsored by the NSF (Grant PHY-1427654).

Responses to olfactory signals reflect network structure of flower-visitor interactions.

PubMed

Junker, Robert R; Höcherl, Nicole; Blüthgen, Nico

2010-07-01

1. Network analyses provide insights into the diversity and complexity of ecological interactions and have motivated conclusions about community stability and co-evolution. However, biological traits and mechanisms such as chemical signals regulating the interactions between individual species--the microstructure of a network--are poorly understood. 2. We linked the responses of receivers (flower visitors) towards signals (flower scent) to the structure of a highly diverse natural flower-insect network. For each interaction, we define link temperature--a newly developed metric--as the deviation of the observed interaction strength from neutrality, assuming that animals randomly interact with flowers. 3. Link temperature was positively correlated to the specific visitors' responses to floral scents, experimentally examined in a mobile olfactometer. Thus, communication between plants and consumers via phytochemical signals reflects a significant part of the microstructure in a complex network. Negative as well as positive responses towards floral scents contributed to these results, where individual experience was important apart from innate behaviour. 4. Our results indicate that: (1) biological mechanisms have a profound impact on the microstructure of complex networks that underlies the outcome of aggregate statistics, and (2) floral scents act as a filter, promoting the visitation of some flower visitors, but also inhibiting the visitation of others.

Coevolution of CRISPR bacteria and phage in 2 dimensions

NASA Astrophysics Data System (ADS)

Han, Pu; Deem, Michael

2014-03-01

CRISPR (cluster regularly interspaced short palindromic repeats) is a newly discovered adaptive, heritable immune system of prokaryotes. It can prevent infection of prokaryotes by phage. Most bacteria and almost all archae have CRISPR. The CRISPR system incorporates short nucleotide sequences from viruses. These incorporated sequences provide a historical record of the host and predator coevolution. We simulate the coevolution of bacteria and phage in 2 dimensions. Each phage has multiple proto-spacers that the bacteria can incorporate. Each bacterium can store multiple spacers in its CRISPR. Phages can escape recognition by the CRISPR system via point mutation or recombination. We will discuss the different evolutionary consequences of point mutation or recombination on the coevolution of bacteria and phage. We will also discuss an intriguing ``dynamic phase transition'' in the number of phage as a function of time and mutation rate. We will show that due to the arm race between phages and bacteria, the frequency of spacers and proto-spacers in a population can oscillate quite rapidly.

Consumer co-evolution as an important component of the eco-evolutionary feedback.

PubMed

Hiltunen, Teppo; Becks, Lutz

2014-10-22

Rapid evolution in ecologically relevant traits has recently been recognized to significantly alter the interaction between consumers and their resources, a key interaction in all ecological communities. While these eco-evolutionary dynamics have been shown to occur when prey populations are evolving, little is known about the role of predator evolution and co-evolution between predator and prey in this context. Here, we investigate the role of consumer co-evolution for eco-evolutionary feedback in bacteria-ciliate microcosm experiments by manipulating the initial trait variation in the predator populations. With co-evolved predators, prey evolve anti-predatory defences faster, trait values are more variable, and predator and prey population sizes are larger at the end of the experiment compared with the non-co-evolved predators. Most importantly, differences in predator traits results in a shift from evolution driving ecology, to ecology driving evolution. Thus we demonstrate that predator co-evolution has important effects on eco-evolutionary dynamics.

Integrative View of the Diversity and Evolution of SWEET and SemiSWEET Sugar Transporters

PubMed Central

Jia, Baolei; Zhu, Xiao Feng; Pu, Zhong Ji; Duan, Yu Xi; Hao, Lu Jiang; Zhang, Jie; Chen, Li-Qing; Jeon, Che Ok; Xuan, Yuan Hu

2017-01-01

Sugars Will Eventually be Exported Transporter (SWEET) and SemiSWEET are recently characterized families of sugar transporters in eukaryotes and prokaryotes, respectively. SemiSWEETs contain 3 transmembrane helices (TMHs), while SWEETs contain 7. Here, we performed sequence-based comprehensive analyses for SWEETs and SemiSWEETs across the biosphere. In total, 3,249 proteins were identified and ≈60% proteins were found in green plants and Oomycota, which include a number of important plant pathogens. Protein sequence similarity networks indicate that proteins from different organisms are significantly clustered. Of note, SemiSWEETs with 3 or 4 TMHs that may fuse to SWEET were identified in plant genomes. 7-TMH SWEETs were found in bacteria, implying that SemiSWEET can be fused directly in prokaryote. 15-TMH extraSWEET and 25-TMH superSWEET were also observed in wild rice and oomycetes, respectively. The transporters can be classified into 4, 2, 2, and 2 clades in plants, Metazoa, unicellular eukaryotes, and prokaryotes, respectively. The consensus and coevolution of amino acids in SWEETs were identified by multiple sequence alignments. The functions of the highly conserved residues were analyzed by molecular dynamics analysis. The 19 most highly conserved residues in the SWEETs were further confirmed by point mutagenesis using SWEET1 from Arabidopsis thaliana. The results proved that the conserved residues located in the extrafacial gate (Y57, G58, G131, and P191), the substrate binding pocket (N73, N192, and W176), and the intrafacial gate (P43, Y83, F87, P145, M161, P162, and Q202) play important roles for substrate recognition and transport processes. Taken together, our analyses provide a foundation for understanding the diversity, classification, and evolution of SWEETs and SemiSWEETs using large-scale sequence analysis and further show that gene duplication and gene fusion are important factors driving the evolution of SWEETs. PMID:29326750

Integrative View of the Diversity and Evolution of SWEET and SemiSWEET Sugar Transporters.

PubMed

Jia, Baolei; Zhu, Xiao Feng; Pu, Zhong Ji; Duan, Yu Xi; Hao, Lu Jiang; Zhang, Jie; Chen, Li-Qing; Jeon, Che Ok; Xuan, Yuan Hu

2017-01-01

Sugars Will Eventually be Exported Transporter (SWEET) and SemiSWEET are recently characterized families of sugar transporters in eukaryotes and prokaryotes, respectively. SemiSWEETs contain 3 transmembrane helices (TMHs), while SWEETs contain 7. Here, we performed sequence-based comprehensive analyses for SWEETs and SemiSWEETs across the biosphere. In total, 3,249 proteins were identified and ≈60% proteins were found in green plants and Oomycota, which include a number of important plant pathogens. Protein sequence similarity networks indicate that proteins from different organisms are significantly clustered. Of note, SemiSWEETs with 3 or 4 TMHs that may fuse to SWEET were identified in plant genomes. 7-TMH SWEETs were found in bacteria, implying that SemiSWEET can be fused directly in prokaryote. 15-TMH extraSWEET and 25-TMH superSWEET were also observed in wild rice and oomycetes, respectively. The transporters can be classified into 4, 2, 2, and 2 clades in plants, Metazoa, unicellular eukaryotes, and prokaryotes, respectively. The consensus and coevolution of amino acids in SWEETs were identified by multiple sequence alignments. The functions of the highly conserved residues were analyzed by molecular dynamics analysis. The 19 most highly conserved residues in the SWEETs were further confirmed by point mutagenesis using SWEET1 from Arabidopsis thaliana . The results proved that the conserved residues located in the extrafacial gate (Y57, G58, G131, and P191), the substrate binding pocket (N73, N192, and W176), and the intrafacial gate (P43, Y83, F87, P145, M161, P162, and Q202) play important roles for substrate recognition and transport processes. Taken together, our analyses provide a foundation for understanding the diversity, classification, and evolution of SWEETs and SemiSWEETs using large-scale sequence analysis and further show that gene duplication and gene fusion are important factors driving the evolution of SWEETs.

MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins.

PubMed

Jones, David T; Singh, Tanya; Kosciolek, Tomasz; Tetchner, Stuart

2015-04-01

Recent developments of statistical techniques to infer direct evolutionary couplings between residue pairs have rendered covariation-based contact prediction a viable means for accurate 3D modelling of proteins, with no information other than the sequence required. To extend the usefulness of contact prediction, we have designed a new meta-predictor (MetaPSICOV) which combines three distinct approaches for inferring covariation signals from multiple sequence alignments, considers a broad range of other sequence-derived features and, uniquely, a range of metrics which describe both the local and global quality of the input multiple sequence alignment. Finally, we use a two-stage predictor, where the second stage filters the output of the first stage. This two-stage predictor is additionally evaluated on its ability to accurately predict the long range network of hydrogen bonds, including correctly assigning the donor and acceptor residues. Using the original PSICOV benchmark set of 150 protein families, MetaPSICOV achieves a mean precision of 0.54 for top-L predicted long range contacts-around 60% higher than PSICOV, and around 40% better than CCMpred. In de novo protein structure prediction using FRAGFOLD, MetaPSICOV is able to improve the TM-scores of models by a median of 0.05 compared with PSICOV. Lastly, for predicting long range hydrogen bonding, MetaPSICOV-HB achieves a precision of 0.69 for the top-L/10 hydrogen bonds compared with just 0.26 for the baseline MetaPSICOV. MetaPSICOV is available as a freely available web server at http://bioinf.cs.ucl.ac.uk/MetaPSICOV. Raw data (predicted contact lists and 3D models) and source code can be downloaded from http://bioinf.cs.ucl.ac.uk/downloads/MetaPSICOV. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Asynchronous diversification in a specialized plant-pollinator mutualism.

PubMed

Ramírez, Santiago R; Eltz, Thomas; Fujiwara, Mikiko K; Gerlach, Günter; Goldman-Huertas, Benjamin; Tsutsui, Neil D; Pierce, Naomi E

2011-09-23

Most flowering plants establish mutualistic associations with insect pollinators to facilitate sexual reproduction. However, the evolutionary processes that gave rise to these associations remain poorly understood. We reconstructed the times of divergence, diversification patterns, and interaction networks of a diverse group of specialized orchids and their bee pollinators. In contrast to a scenario of coevolution by race formation, we show that fragrance-producing orchids originated at least three times independently after their fragrance-collecting bee mutualists. Whereas orchid diversification has apparently tracked the diversification of orchids' bee pollinators, bees appear to have depended on the diverse chemical environment of neotropical forests. We corroborated this apparent asymmetrical dependency by simulating co-extinction cascades in real interaction networks that lacked reciprocal specialization. These results suggest that the diversification of insect-pollinated angiosperms may have been facilitated by the exploitation of preexisting sensory biases of insect pollinators.

Insect response to plant defensive protease inhibitors.

PubMed

Zhu-Salzman, Keyan; Zeng, Rensen

2015-01-07

Plant protease inhibitors (PIs) are natural plant defense proteins that inhibit proteases of invading insect herbivores. However, their anti-insect efficacy is determined not only by their potency toward a vulnerable insect system but also by the response of the insect to such a challenge. Through the long history of coevolution with their host plants, insects have developed sophisticated mechanisms to circumvent antinutritional effects of dietary challenges. Their response takes the form of changes in gene expression and the protein repertoire in cells lining the alimentary tract, the first line of defense. Research in insect digestive proteases has revealed the crucial roles they play in insect adaptation to plant PIs and has brought about a new appreciation of how phytophagous insects employ this group of molecules in both protein digestion and counterdefense. This review provides researchers in related fields an up-to-date summary of recent advances.

The Coevolution of Life and Environment on Mars: An Ecosystem Perspective on the Robotic Exploration of Biosignatures.

PubMed

Cabrol, Nathalie A

2018-01-01

Earth's biological and environmental evolution are intertwined and inseparable. This coevolution has become a fundamental concept in astrobiology and is key to the search for life beyond our planet. In the case of Mars, whether a coevolution took place is unknown, but analyzing the factors at play shows the uniqueness of each planetary experiment regardless of similarities. Early Earth and early Mars shared traits. However, biological processes on Mars, if any, would have had to proceed within the distinctive context of an irreversible atmospheric collapse, greater climate variability, and specific planetary characteristics. In that, Mars is an important test bed for comparing the effects of a unique set of spatiotemporal changes on an Earth-like, yet different, planet. Many questions remain unanswered about Mars' early environment. Nevertheless, existing data sets provide a foundation for an intellectual framework where notional coevolution models can be explored. In this framework, the focus is shifted from planetary-scale habitability to the prospect of habitats, microbial ecotones, pathways to biological dispersal, biomass repositories, and their meaning for exploration. Critically, as we search for biosignatures, this focus demonstrates the importance of starting to think of early Mars as a biosphere and vigorously integrating an ecosystem approach to landing site selection and exploration. Key Words: Astrobiology-Biosignatures-Coevolution of Earth and life-Mars. Astrobiology 18, 1-27.

The Coevolution of Life and Environment on Mars: An Ecosystem Perspective on the Robotic Exploration of Biosignatures

PubMed Central

2018-01-01

Abstract Earth's biological and environmental evolution are intertwined and inseparable. This coevolution has become a fundamental concept in astrobiology and is key to the search for life beyond our planet. In the case of Mars, whether a coevolution took place is unknown, but analyzing the factors at play shows the uniqueness of each planetary experiment regardless of similarities. Early Earth and early Mars shared traits. However, biological processes on Mars, if any, would have had to proceed within the distinctive context of an irreversible atmospheric collapse, greater climate variability, and specific planetary characteristics. In that, Mars is an important test bed for comparing the effects of a unique set of spatiotemporal changes on an Earth-like, yet different, planet. Many questions remain unanswered about Mars' early environment. Nevertheless, existing data sets provide a foundation for an intellectual framework where notional coevolution models can be explored. In this framework, the focus is shifted from planetary-scale habitability to the prospect of habitats, microbial ecotones, pathways to biological dispersal, biomass repositories, and their meaning for exploration. Critically, as we search for biosignatures, this focus demonstrates the importance of starting to think of early Mars as a biosphere and vigorously integrating an ecosystem approach to landing site selection and exploration. Key Words: Astrobiology—Biosignatures—Coevolution of Earth and life—Mars. Astrobiology 18, 1–27. PMID:29252008

Distinct Structural Elements Govern the Folding, Stability, and Catalysis in the Outer Membrane Enzyme PagP.

PubMed

Iyer, Bharat Ramasubramanian; Mahalakshmi, Radhakrishnan

2016-09-06

The outer membrane enzyme PagP is indispensable for lipid A palmitoylation in Gram-negative bacteria and has been implicated in resistance to host immune defenses. PagP possesses an unusual structure for an integral membrane protein, with a highly dynamic barrel domain that is tilted with respect to the membrane normal. In addition, it contains an N-terminal amphipathic helix. Recent functional and structural studies have shown that these molecular factors are critical for PagP to carry out its function in the challenging environment of the bacterial outer membrane. However, the precise contributions of the N-helix to folding and stability and residues that can influence catalytic rates remain to be addressed. Here, we identify a sequence-dependent stabilizing role for the N-terminal helix of PagP in the measured thermodynamic stability of the barrel. Using chimeric barrel sequences, we show that the Escherichia coli PagP N-terminal helix confers 2-fold greater stability to the Salmonella typhimurium barrel. Further, we find that the W78F substitution in S. typhimurium causes a nearly 20-fold increase in the specific activity in vitro for the phospholipase reaction, compared to that of E. coli PagP. Here, phenylalanine serves as a key regulator of catalysis, possibly by increasing the reaction rate. Through coevolution analysis, we detect an interaction network between seemingly unrelated segments of this membrane protein. Exchanging the structural and functional features between homologous PagP enzymes from E. coli and S. typhimurium has provided us with an understanding of the molecular factors governing PagP stability and function.

Conserved hypothetical protein Rv1977 in Mycobacterium tuberculosis strains contains sequence polymorphisms and might be involved in ongoing immune evasion.

PubMed

Jiang, Yi; Liu, Haican; Wang, Xuezhi; Li, Guilian; Qiu, Yan; Dou, Xiangfeng; Wan, Kanglin

2015-01-01

Host immune pressure and associated parasite immune evasion are key features of host-pathogen co-evolution. A previous study showed that human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved and thus it was deduced that M. tuberculosis lacks antigenic variation and immune evasion. Here, we selected 151 clinical Mycobacterium tuberculosis isolates from China, amplified gene encoding Rv1977 and compared the sequences. The results showed that Rv1977, a conserved hypothetical protein, is not conserved in M. tuberculosis strains and there are polymorphisms existed in the protein. Some mutations, especially one frameshift mutation, occurred in the antigen Rv1977, which is uncommon in M.tb strains and may lead to the protein function altering. Mutations and deletion in the gene all affect one of three T cell epitopes and the changed T cell epitope contained more than one variable position, which may suggest ongoing immune evasion.

Metabolic coevolution in the bacterial symbiosis of whiteflies and related plant sap-feeding insects

USDA-ARS?s Scientific Manuscript database

In animals dependent on intracellular bacteria with very small genomes, the host cell is adapted to support the function of its bacterial symbionts, but the molecular basis of these adaptations is poorly understood. We investigated the metabolic coevolution between the whitefly Bemisia tabaci and th...

Dynamical origins of the community structure of an online multi-layer society

NASA Astrophysics Data System (ADS)

Klimek, Peter; Diakonova, Marina; Eguíluz, Víctor M.; San Miguel, Maxi; Thurner, Stefan

2016-08-01

Social structures emerge as a result of individuals managing a variety of different social relationships. Societies can be represented as highly structured dynamic multiplex networks. Here we study the dynamical origins of the specific community structures of a large-scale social multiplex network of a human society that interacts in a virtual world of a massive multiplayer online game. There we find substantial differences in the community structures of different social actions, represented by the various layers in the multiplex network. Community sizes distributions are either fat-tailed or appear to be centered around a size of 50 individuals. To understand these observations we propose a voter model that is built around the principle of triadic closure. It explicitly models the co-evolution of node- and link-dynamics across different layers of the multiplex network. Depending on link and node fluctuation probabilities, the model exhibits an anomalous shattered fragmentation transition, where one layer fragments from one large component into many small components. The observed community size distributions are in good agreement with the predicted fragmentation in the model. This suggests that several detailed features of the fragmentation in societies can be traced back to the triadic closure processes.

Entropy and optimality in river deltas

NASA Astrophysics Data System (ADS)

Tejedor, Alejandro; Longjas, Anthony; Edmonds, Douglas A.; Zaliapin, Ilya; Georgiou, Tryphon T.; Rinaldo, Andrea; Foufoula-Georgiou, Efi

2017-10-01

The form and function of river deltas is intricately linked to the evolving structure of their channel networks, which controls how effectively deltas are nourished with sediments and nutrients. Understanding the coevolution of deltaic channels and their flux organization is crucial for guiding maintenance strategies of these highly stressed systems from a range of anthropogenic activities. To date, however, a unified theory explaining how deltas self-organize to distribute water and sediment up to the shoreline remains elusive. Here, we provide evidence for an optimality principle underlying the self-organized partition of fluxes in delta channel networks. By introducing a suitable nonlocal entropy rate (nER) and by analyzing field and simulated deltas, we suggest that delta networks achieve configurations that maximize the diversity of water and sediment flux delivery to the shoreline. We thus suggest that prograding deltas attain dynamically accessible optima of flux distributions on their channel network topologies, thus effectively decoupling evolutionary time scales of geomorphology and hydrology. When interpreted in terms of delta resilience, high nER configurations reflect an increased ability to withstand perturbations. However, the distributive mechanism responsible for both diversifying flux delivery to the shoreline and dampening possible perturbations might lead to catastrophic events when those perturbations exceed certain intensity thresholds.

The interplay of friendship networks and social networking sites: longitudinal analysis of selection and influence effects on adolescent smoking and alcohol use.

PubMed

Huang, Grace C; Soto, Daniel; Fujimoto, Kayo; Valente, Thomas W

2014-08-01

We examined the coevolution of adolescent friendships and peer influences with respect to their risk behaviors and social networking site use. Investigators of the Social Network Study collected longitudinal data during fall 2010 and spring 2011 from 10th-grade students in 5 Southern California high schools (n = 1434). We used meta-analyses of stochastic actor-based models to estimate changes in friendship ties and risk behaviors and the effects of Facebook and MySpace use. Significant shifts in adolescent smoking and drinking occurred despite little change in overall prevalence rates. Students with higher levels of alcohol use were more likely to send and receive friendship nominations and become friends with other drinkers. They were also more likely to increase alcohol use if their friends drank more. Adolescents selected friends with similar Facebook and MySpace use habits. Exposure to friends' risky online pictures increased smoking behaviors but had no significant effects on alcohol use. Our findings support a greater focus on friendship selection mechanisms in school-based alcohol use interventions. Social media platforms may help identify at-risk adolescent groups and foster positive norms about risk behaviors.

Artificial neuron-glia networks learning approach based on cooperative coevolution.

PubMed

Mesejo, Pablo; Ibáñez, Oscar; Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana B

2015-06-01

Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.

Social selection and peer influence in an online social network

PubMed Central

Lewis, Kevin; Gonzalez, Marco; Kaufman, Jason

2012-01-01

Disentangling the effects of selection and influence is one of social science's greatest unsolved puzzles: Do people befriend others who are similar to them, or do they become more similar to their friends over time? Recent advances in stochastic actor-based modeling, combined with self-reported data on a popular online social network site, allow us to address this question with a greater degree of precision than has heretofore been possible. Using data on the Facebook activity of a cohort of college students over 4 years, we find that students who share certain tastes in music and in movies, but not in books, are significantly likely to befriend one another. Meanwhile, we find little evidence for the diffusion of tastes among Facebook friends—except for tastes in classical/jazz music. These findings shed light on the mechanisms responsible for observed network homogeneity; provide a statistically rigorous assessment of the coevolution of cultural tastes and social relationships; and suggest important qualifications to our understanding of both homophily and contagion as generic social processes. PMID:22184242

The Beringian Coevolution Project: Holistic collections of mammals and associated parasites reveal novel perspectives on changing environments in the north

USDA-ARS?s Scientific Manuscript database

The Beringian Coevolution Project (BCP), a field program underway in the Arctic since 1999, has focused on building key scientific infrastructure for integrated specimen-based studies on mammals and their associated parasites. BCP has contributed new insights across temporal and spatial scales into...

The Coevolution of "Tyrannosaurus" & Its Prey: Could "Tyrannosaurus" Chase down & Kill a "Triceratops" for Lunch?

ERIC Educational Resources Information Center

May, S. Randolph

2014-01-01

Students will analyze the coevolution of the predator-prey relationships between "Tyrannosaurus rex" and its prey species using analyses of animal speeds from fossilized trackways, prey-animal armaments, adaptive behaviors, bite marks on prey-animal fossils, predator-prey ratios, and scavenger competition. The students will be asked to…

The Co-Evolution of Knowledge and Event Memory

ERIC Educational Resources Information Center

Nelson, Angela B.; Shiffrin, Richard M.

2013-01-01

We present a theoretical framework and a simplified simulation model for the co-evolution of knowledge and event memory, both termed SARKAE (Storing and Retrieving Knowledge and Events). Knowledge is formed through the accrual of individual events, a process that operates in tandem with the storage of individual event memories. In 2 studies, new…

A discriminative test among the different theories proposed to explain the origin of the genetic code: the coevolution theory finds additional support.

PubMed

Giulio, Massimo Di

2018-05-19

A discriminative statistical test among the different theories proposed to explain the origin of the genetic code is presented. Gathering the amino acids into polarity and biosynthetic classes that are the first expression of the physicochemical theory of the origin of the genetic code and the second expression of the coevolution theory, these classes are utilized in the Fisher's exact test to establish their significance within the genetic code table. Linking to the rows and columns of the genetic code of probabilities that express the statistical significance of these classes, I have finally been in the condition to be able to calculate a χ value to link to both the physicochemical theory and to the coevolution theory that would express the corroboration level referred to these theories. The comparison between these two χ values showed that the coevolution theory is able to explain - in this strictly empirical analysis - the origin of the genetic code better than that of the physicochemical theory. Copyright © 2018 Elsevier B.V. All rights reserved.

Evidence for parasite-mediated selection during short-lasting toxic algal blooms.

PubMed

Blanquart, François; Valero, Myriam; Alves-de-Souza, Catharina; Dia, Aliou; Lepelletier, Frédéric; Bigeard, Estelle; Jeanthon, Christian; Destombe, Christophe; Guillou, Laure

2016-10-26

Parasites play a role in the control of transient algal blooms, but it is not known whether parasite-mediated selection results in coevolution of the host and the parasites over this short time span. We investigated the presence of coevolution between the toxic dinoflagellate Alexandrium minutum and two naturally occurring endoparasites during blooms lasting a month in two river estuaries, using cross-inoculation experiments across time and space. Higher parasite abundance was associated with a large daily reduction in relative A. minutum abundances, demonstrating strong parasite-mediated selection. There was genetic variability in infectivity in both parasite species, and in resistance in the host. We found no evidence for coevolution in one estuary; however, in the other estuary, we found high genetic diversity in the two parasite species, fluctuations in infectivity and suggestion that the two parasites are well adapted to their host, as in 'Red Queen' dynamics. Thus, coevolution is possible over the short time span of a bloom, but geographically variable, and may feedback on community dynamics. © 2016 The Authors.

Coevolution between Male and Female Genitalia in the Drosophila melanogaster Species Subgroup

PubMed Central

Yassin, Amir; Orgogozo, Virginie

2013-01-01

In contrast to male genitalia that typically exhibit patterns of rapid and divergent evolution among internally fertilizing animals, female genitalia have been less well studied and are generally thought to evolve slowly among closely-related species. As a result, few cases of male-female genital coevolution have been documented. In Drosophila, female copulatory structures have been claimed to be mostly invariant compared to male structures. Here, we re-examined male and female genitalia in the nine species of the D. melanogaster subgroup. We describe several new species-specific female genital structures that appear to coevolve with male genital structures, and provide evidence that the coevolving structures contact each other during copulation. Several female structures might be defensive shields against apparently harmful male structures, such as cercal teeth, phallic hooks and spines. Evidence for male-female morphological coevolution in Drosophila has previously been shown at the post-copulatory level (e.g., sperm length and sperm storage organ size), and our results provide support for male-female coevolution at the copulatory level. PMID:23451172

Beyond topology: coevolution of structure and flux in metabolic networks.

PubMed

Morrison, E S; Badyaev, A V

2017-10-01

Interactions between the structure of a metabolic network and its functional properties underlie its evolutionary diversification, but the mechanism by which such interactions arise remains elusive. Particularly unclear is whether metabolic fluxes that determine the concentrations of compounds produced by a metabolic network, are causally linked to a network's structure or emerge independently of it. A direct empirical study of populations where both structural and functional properties vary among individuals' metabolic networks is required to establish whether changes in structure affect the distribution of metabolic flux. In a population of house finches (Haemorhous mexicanus), we reconstructed full carotenoid metabolic networks for 442 individuals and uncovered 11 structural variants of this network with different compounds and reactions. We examined the consequences of this structural diversity for the concentrations of plumage-bound carotenoids produced by flux in these networks. We found that concentrations of metabolically derived, but not dietary carotenoids, depended on network structure. Flux was partitioned similarly among compounds in individuals of the same network structure: within each network, compound concentrations were closely correlated. The highest among-individual variation in flux occurred in networks with the strongest among-compound correlations, suggesting that changes in the magnitude, but not the distribution of flux, underlie individual differences in compound concentrations on a static network structure. These findings indicate that the distribution of flux in carotenoid metabolism closely follows network structure. Thus, evolutionary diversification and local adaptations in carotenoid metabolism may depend more on the gain or loss of enzymatic reactions than on changes in flux within a network structure. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

The genetic basis of a plant–insect coevolutionary key innovation

PubMed Central

Wheat, Christopher W.; Vogel, Heiko; Wittstock, Ute; Braby, Michael F.; Underwood, Dessie; Mitchell-Olds, Thomas

2007-01-01

Ehrlich and Raven formally introduced the concept of stepwise coevolution using butterfly and angiosperm interactions in an attempt to account for the impressive biological diversity of these groups. However, many biologists currently envision butterflies evolving 50 to 30 million years (Myr) after the major angiosperm radiation and thus reject coevolutionary origins of butterfly biodiversity. The unresolved central tenet of Ehrlich and Raven's theory is that evolution of plant chemical defenses is followed closely by biochemical adaptation in insect herbivores, and that newly evolved detoxification mechanisms result in adaptive radiation of herbivore lineages. Using one of their original butterfly-host plant systems, the Pieridae, we identify a pierid glucosinolate detoxification mechanism, nitrile-specifier protein (NSP), as a key innovation. Larval NSP activity matches the distribution of glucosinolate in their host plants. Moreover, by using five different temporal estimates, NSP seems to have evolved shortly after the evolution of the host plant group (Brassicales) (≈10 Myr). An adaptive radiation of these glucosinolate-feeding Pierinae followed, resulting in significantly elevated species numbers compared with related clades. Mechanistic understanding in its proper historical context documents more ancient and dynamic plant–insect interactions than previously envisioned. Moreover, these mechanistic insights provide the tools for detailed molecular studies of coevolution from both the plant and insect perspectives. PMID:18077380

Seed dispersal in limber and southwestern white pine: Comparing core and peripheral populations

Treesearch

Diana F. Tomback; Sheridan Samano; Elizabeth L. Pruett; Anna W. Schoettle

2011-01-01

According to the geographic mosaic theory of coevolution (Thompson 2005), the potential for coevolutionary relationships between interacting species varies with the presence of other species within a community. This implies that the strength of coevolution between two species may vary geographically. In this study, we ask whether there is a shift in vertebrate seed...

Self-organizing behavior in a lattice model for co-evolution of virus and immune systems

NASA Astrophysics Data System (ADS)

Izmailian, N. Sh.; Papoyan, Vl. V.; Priezzhev, V. B.; Hu, Chin-Kun

2007-04-01

We propose a lattice model for the co-evolution of a virus population and an adaptive immune system. We show that, under some natural assumptions, both probability distribution of the virus population and the distribution of activity of the immune system tend during the evolution to a self-organized critical state.

Tracing the role of human civilization in the globalization of plant pathogens

Treesearch

Alberto Santini; Andrew Liebhold; Duccio Migliorini; Steve Woodward

2018-01-01

Co-evolution between plants and parasites, including herbivores and pathogens, has arguably generated much of Earth’s biological diversity. Within an ecosystem, coevolution of plants and pathogens is a stepwise reciprocal evolutionary interaction: epidemics result in intense selection pressures on both host and pathogen populations, ultimately allowing long-term...

ProtPhylo: identification of protein-phenotype and protein-protein functional associations via phylogenetic profiling.

PubMed

Cheng, Yiming; Perocchi, Fabiana

2015-07-01

ProtPhylo is a web-based tool to identify proteins that are functionally linked to either a phenotype or a protein of interest based on co-evolution. ProtPhylo infers functional associations by comparing protein phylogenetic profiles (co-occurrence patterns of orthology relationships) for more than 9.7 million non-redundant protein sequences from all three domains of life. Users can query any of 2048 fully sequenced organisms, including 1678 bacteria, 255 eukaryotes and 115 archaea. In addition, they can tailor ProtPhylo to a particular kind of biological question by choosing among four main orthology inference methods based either on pair-wise sequence comparisons (One-way Best Hits and Best Reciprocal Hits) or clustering of orthologous proteins across multiple species (OrthoMCL and eggNOG). Next, ProtPhylo ranks phylogenetic neighbors of query proteins or phenotypic properties using the Hamming distance as a measure of similarity between pairs of phylogenetic profiles. Candidate hits can be easily and flexibly prioritized by complementary clues on subcellular localization, known protein-protein interactions, membrane spanning regions and protein domains. The resulting protein list can be quickly exported into a csv text file for further analyses. ProtPhylo is freely available at http://www.protphylo.org. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Transition Metals and Virulence in Bacteria

PubMed Central

Palmer, Lauren D.; Skaar, Eric P.

2016-01-01

Transition metals are required trace elements for all forms of life. Due to their unique inorganic and redox properties, transition metals serve as cofactors for enzymes and other proteins. In bacterial pathogenesis, the vertebrate host represents a rich source of nutrient metals, and bacteria have evolved diverse metal acquisition strategies. Host metal homeostasis changes dramatically in response to bacterial infections, including production of metal sequestering proteins and the bombardment of bacteria with toxic levels of metals. Presumably, in response, bacteria have evolved systems to subvert metal sequestration and toxicity. The coevolution of hosts and their bacterial pathogens in the battle for metals has uncovered emerging paradigms in social microbiology, rapid evolution, host specificity, and metal homeostasis across domains. This review focuses on recent advances and open questions in our understanding of the complex role of transition metals at the host-pathogen interface. PMID:27617971

Transition Metals and Virulence in Bacteria.

PubMed

Palmer, Lauren D; Skaar, Eric P

2016-11-23

Transition metals are required trace elements for all forms of life. Due to their unique inorganic and redox properties, transition metals serve as cofactors for enzymes and other proteins. In bacterial pathogenesis, the vertebrate host represents a rich source of nutrient metals, and bacteria have evolved diverse metal acquisition strategies. Host metal homeostasis changes dramatically in response to bacterial infections, including production of metal sequestering proteins and the bombardment of bacteria with toxic levels of metals. In response, bacteria have evolved systems to subvert metal sequestration and toxicity. The coevolution of hosts and their bacterial pathogens in the battle for metals has uncovered emerging paradigms in social microbiology, rapid evolution, host specificity, and metal homeostasis across domains. This review focuses on recent advances and open questions in our understanding of the complex role of transition metals at the host-pathogen interface.

Coevolution of nutrigenomics and society: ethical considerations.

PubMed

Korthals, Michiel

2011-12-01

To optimize the coevolution of nutrigenomics and society (ie, the reciprocal stimulation of both developments), I analyzed chances for a fruitful match between normative concepts and strategies of both developments. Nutrigenomics embodies ≥ 3 normative concepts. First, food is exclusively interpreted in terms of disease prevention. Second, striving for health is interpreted as the quantification of risks and prevention of diseases through positive food-gene interactions. The third normative idea is that disease prevention by the minimization of risks is an individual's task. My thesis was that these concepts of nutrigenomics would not easily match with concepts of food and health of various food styles in Western societies, which, for instance, parents in the case of metabolic programming endorse and with a philosophical view of the relation between food, health, and the meaning of life. Next, I reflected on the nonsynchronized coevolution of nutrigenomics and society because of this mismatch and introduced the concept of the fair representation of food styles in nutrigenomic developments. To synchronize and optimize the coevolution of nutrigenomics and society, I propose that the research policy of nutrigenomics should change to a research partnership with society on the basis of fair representation.

Transcriptome Reprogramming by Plasmid-Encoded Transcriptional Regulators Is Required for Host Niche Adaption of a Macrophage Pathogen

PubMed Central

Coulson, Garry B.; Miranda-CasoLuengo, Aleksandra A.; Miranda-CasoLuengo, Raúl; Wang, Xiaoguang; Oliver, Jenna; Willingham-Lane, Jennifer M.

2015-01-01

Rhodococcus equi is a facultative intracellular pathogen of macrophages, relying on the presence of a conjugative virulence plasmid harboring a 21-kb pathogenicity island (PAI) for growth in host macrophages. The PAI encodes a family of 6 virulence-associated proteins (Vaps) in addition to 20 other proteins. The contribution of these to virulence has remained unclear. We show that the presence of only 3 virulence plasmid genes (of 73 in total) is required and sufficient for intracellular growth. These include a single vap family member, vapA, and two PAI-located transcriptional regulators, virR and virS. Both transcriptional regulators are essential for wild-type-level expression of vapA, yet vapA expression alone is not sufficient to allow intracellular growth. A whole-genome microarray analysis revealed that VirR and VirS substantially integrate themselves into the chromosomal regulatory network, significantly altering the transcription of 18% of all chromosomal genes. This pathoadaptation involved significant enrichment of select gene ontologies, in particular, enrichment of genes involved in transport processes, energy production, and cellular metabolism, suggesting a major change in cell physiology allowing the bacterium to grow in the hostile environment of the host cell. The results suggest that following the acquisition of the virulence plasmid by an avirulent ancestor of R. equi, coevolution between the plasmid and the chromosome took place, allowing VirR and VirS to regulate the transcription of chromosomal genes in a process that ultimately promoted intracellular growth. Our findings suggest a mechanism for cooption of existing chromosomal traits during the evolution of a pathogenic bacterium from an avirulent saprophyte. PMID:26015480

Type III secretion system effector proteins: double agents in bacterial disease and plant defense.

PubMed

Alfano, James R; Collmer, Alan

2004-01-01

Many phytopathogenic bacteria inject virulence effector proteins into plant cells via a Hrp type III secretion system (TTSS). Without the TTSS, these pathogens cannot defeat basal defenses, grow in plants, produce disease lesions in hosts, or elicit the hypersensitive response (HR) in nonhosts. Pathogen genome projects employing bioinformatic methods to identify TTSS Hrp regulon promoters and TTSS pathway targeting signals suggest that phytopathogenic Pseudomonas, Xanthomonas, and Ralstonia spp. harbor large arsenals of effectors. The Hrp TTSS employs customized cytoplasmic chaperones, conserved export components in the bacterial envelope (also used by the TTSS of animal pathogens), and a more specialized set of TTSS-secreted proteins to deliver effectors across the plant cell wall and plasma membrane. Many effectors can act as molecular double agents that betray the pathogen to plant defenses in some interactions and suppress host defenses in others. Investigations of the functions of effectors within plant cells have demonstrated the plasma membrane and nucleus as subcellular sites for several effectors, revealed some effectors to possess cysteine protease or protein tyrosine phosphatase activity, and provided new clues to the coevolution of bacterium-plant interactions.

Coevolution of Synchronization and Cooperation in Costly Networked Interactions

NASA Astrophysics Data System (ADS)

Antonioni, Alberto; Cardillo, Alessio

2017-06-01

Despite the large number of studies on synchronization, the hypothesis that interactions bear a cost for involved individuals has seldom been considered. The introduction of costly interactions leads, instead, to the formulation of a dichotomous scenario in which an individual may decide to cooperate and pay the cost in order to get synchronized with the rest of the population. Alternatively, the same individual can decide to free ride, without incurring any cost, waiting for others to get synchronized to his or her state. Thus, the emergence of synchronization may be seen as the byproduct of an evolutionary game in which individuals decide their behavior according to the benefit-to-cost ratio they accrued in the past. We study the onset of cooperation and synchronization in networked populations of Kuramoto oscillators and report how topology is essential in order for cooperation to thrive. We also display how different classes of topology foster synchronization differently both at microscopic and macroscopic levels.

Modeling the influence of information on the coevolution of contact networks and the dynamics of infectious diseases

NASA Astrophysics Data System (ADS)

Zhang, Haifeng; Small, Michael; Fu, Xinchu; Sun, Guiquan; Wang, Binghong

2012-09-01

Outbreaks of infectious diseases may awaken the awareness of individuals, consequently, they may adjust their contact patterns according to the perceived risk from disease. In this paper, we assume that individuals make decisions on breaking or recovering links according to the information of diseases spreading which they have acquired. They will reduce some links when diseases are prevalent and have high risks; otherwise, they will recover some original links when the diseases are controlled or present minimal risk. Under such an assumption, we study the effects of information of diseases on the contact patterns within the population and on the dynamics of epidemics. By extensive simulations and theoretical analysis, we find that, due to the time-delayed information of diseases, both the density of the disease and the topology of the network vary with time in a periodic form. Our results indicate that the quality of information available to individuals can have an important effect on the spreading of infectious diseases and implications for related problems.

[Response of arbuscular mycorrhizal fungal lipid metabolism to symbiotic signals in mycorrhiza].

PubMed

Tian, Lei; Li, Yuanjing; Tian, Chunjie

2016-01-04

Arbuscular mycorrhizal (AM) fungi play an important role in energy flow and nutrient cycling, besides their wide distribution in the cosystem. With a long co-evolution, AM fungi and host plant have formed a symbiotic relationship, and fungal lipid metabolism may be the key point to find the symbiotic mechanism in arbusculart mycorrhiza. Here, we reviewed the most recent progress on the interaction between AM fungal lipid metabolism and symbiotic signaling networks, especially the response of AM fungal lipid metabolism to symbiotic signals. Furthermore, we discussed the response of AM fungal lipid storage and release to symbiotic or non-symbiotic status, and the correlation between fungal lipid metabolism and nutrient transfer in mycorrhiza. In addition, we explored the feedback of the lipolysis process to molecular signals during the establishment of symbiosis, and the corresponding material conversion and energy metabolism besides the crosstalk of fungal lipid metabolism and signaling networks. This review will help understand symbiotic mechanism of arbuscular mycorrhiza fungi and further application in ecosystem.

The Impact of Heterogeneity and Awareness in Modeling Epidemic Spreading on Multiplex Networks

PubMed Central

Scatà, Marialisa; Di Stefano, Alessandro; Liò, Pietro; La Corte, Aurelio

2016-01-01

In the real world, dynamic processes involving human beings are not disjoint. To capture the real complexity of such dynamics, we propose a novel model of the coevolution of epidemic and awareness spreading processes on a multiplex network, also introducing a preventive isolation strategy. Our aim is to evaluate and quantify the joint impact of heterogeneity and awareness, under different socioeconomic conditions. Considering, as case study, an emerging public health threat, Zika virus, we introduce a data-driven analysis by exploiting multiple sources and different types of data, ranging from Big Five personality traits to Google Trends, related to different world countries where there is an ongoing epidemic outbreak. Our findings demonstrate how the proposed model allows delaying the epidemic outbreak and increasing the resilience of nodes, especially under critical economic conditions. Simulation results, using data-driven approach on Zika virus, which has a growing scientific research interest, are coherent with the proposed analytic model. PMID:27848978

Phylogeny and micro-habitats utilized by lizards determine the composition of their endoparasites in the semiarid Caatinga of Northeast Brazil.

PubMed

Brito, S V; Corso, G; Almeida, A M; Ferreira, F S; Almeida, W O; Anjos, L A; Mesquita, D O; Vasconcellos, A

2014-11-01

Trophic networks can have architectonic configurations influenced by historical and ecological factors. The objective of this study was to analyze the architecture of networks between lizards, their endoparasites, diet, and micro-habitat, aiming to understand which factors exert an influence on the composition of the species of parasites. All networks showed a compartmentalized pattern. There was a positive relation between diet and the diversity of endoparasites. Our analyses also demonstrated that phylogeny and the use of micro-habitat influenced the composition of species of endoparasites and diet pattern of lizards. The principal factor that explained the modularity of the network was the foraging strategy, with segregation between the "active foragers" and "sit-and-wait" lizards. Our analyses also demonstrated that historical (phylogeny) and ecological factors (use of micro-habitat by the lizards) influenced the composition of parasite communities. These results corroborate other studies with ectoparasites, which indicate phylogeny and micro-habitat as determinants in the composition of parasitic fauna. The influence of phylogeny can be the result of coevolution between parasites and lizards in the Caatinga, and the influence of micro-habitat should be a result of adaptations of species of parasites to occupy the same categories of micro-habitats as hosts, thus favoring contagion.

The Interplay of Friendship Networks and Social Networking Sites: Longitudinal Analysis of Selection and Influence Effects on Adolescent Smoking and Alcohol Use

PubMed Central

Soto, Daniel; Fujimoto, Kayo; Valente, Thomas W.

2014-01-01

Objectives. We examined the coevolution of adolescent friendships and peer influences with respect to their risk behaviors and social networking site use. Methods. Investigators of the Social Network Study collected longitudinal data during fall 2010 and spring 2011 from 10th-grade students in 5 Southern California high schools (n = 1434). We used meta-analyses of stochastic actor-based models to estimate changes in friendship ties and risk behaviors and the effects of Facebook and MySpace use. Results. Significant shifts in adolescent smoking and drinking occurred despite little change in overall prevalence rates. Students with higher levels of alcohol use were more likely to send and receive friendship nominations and become friends with other drinkers. They were also more likely to increase alcohol use if their friends drank more. Adolescents selected friends with similar Facebook and MySpace use habits. Exposure to friends’ risky online pictures increased smoking behaviors but had no significant effects on alcohol use. Conclusions. Our findings support a greater focus on friendship selection mechanisms in school-based alcohol use interventions. Social media platforms may help identify at-risk adolescent groups and foster positive norms about risk behaviors. PMID:24922126

[Origination and evolution of plastids].

PubMed

Mukhina, V S

2014-01-01

Plastids are photosynthetic DNA-containing organelles of plants and algae. In the review, the history of their origination and evolution within different taxa is considered. All of the plastids appear to be descendants of cyanobacteria that colonized eukaryotic cells. The first plastids arose through symbiosis of cyanobacteria with algal ancestors from Archaeplastida kingdom. Later, there occurred repeated secondary symbioses of other eukariotes with photosynthetic protists: in this way plastids emerged in organisms of other taxa. Co-evolution of cyanobacteria and ancestral algae led to extensive transformation of both: reduction of endosymbiont, mass transfer of cyanobacteria genes into karyogenome, formation of complex system of proteins transportation to plastids and their functioning regulation.

Co-Evolution of User and Organizational Interfaces: A Longitudinal Case Study of WWW Dissemination of National Statistics.

ERIC Educational Resources Information Center

Marchionini, Gary

2002-01-01

Describes how user interfaces for the Bureau of Labor Statistics (BLS) web site evolved over a 5-year period along with the larger organizational interface and how this co-evolution has influenced the institution. Interviews with BLS staff and transaction log analysis are the foci of this study, as well as user information-seeking studies and user…

Emergent inequality and self-organized social classes in a network of power and frustration

DOE PAGES

Mahault, Benoit; Saxena, Avadh; Nisoli, Cristiano

2017-02-17

We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution ofmore » wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes.« less

Emergent inequality and self-organized social classes in a network of power and frustration

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

Mahault, Benoit; Saxena, Avadh; Nisoli, Cristiano

We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution ofmore » wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes.« less

The co-evolution of cultures, social network communities, and agent locations in an extension of Axelrod’s model of cultural dissemination

NASA Astrophysics Data System (ADS)

Pfau, Jens; Kirley, Michael; Kashima, Yoshihisa

2013-01-01

We introduce a variant of the Axelrod model of cultural dissemination in which agents change their physical locations, social links, and cultures. Numerical simulations are used to investigate the evolution of social network communities and the cultural diversity within and between these communities. An analysis of the simulation results shows that an initial peak in the cultural diversity within network communities is evident before agents segregate into a final configuration of culturally homogeneous communities. Larger long-range interaction probabilities facilitate the initial emergence of culturally diverse network communities, which leads to a more pronounced initial peak in cultural diversity within communities. At equilibrium, the number of communities, and hence cultures, increases when the initial cultural diversity increases. However, the number of communities decreases when the lattice size or population density increases. A phase transition between two regimes of initial cultural diversity is evident. For initial diversities below a critical value, a single network community and culture emerges that dominates the population. For initial diversities above the critical value, multiple culturally homogeneous communities emerge. The critical value of initial diversity at which this transition occurs increases with increasing lattice size and population density and generally with increasing absolute population size. We conclude that larger initial diversities promote cultural heterogenization, while larger lattice sizes, population densities, and in fact absolute population sizes promote homogenization.

Emergent inequality and self-organized social classes in a network of power and frustration

PubMed Central

Mahault, Benoit; Saxena, Avadh

2017-01-01

We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes. PMID:28212440

Emergent inequality and self-organized social classes in a network of power and frustration.

PubMed

Mahault, Benoit; Saxena, Avadh; Nisoli, Cristiano

2017-01-01

We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes.

TSEMA: interactive prediction of protein pairings between interacting families

PubMed Central

Izarzugaza, José M. G.; Juan, David; Pons, Carles; Ranea, Juan A. G.; Valencia, Alfonso; Pazos, Florencio

2006-01-01

An entire family of methodologies for predicting protein interactions is based on the observed fact that families of interacting proteins tend to have similar phylogenetic trees due to co-evolution. One application of this concept is the prediction of the mapping between the members of two interacting protein families (which protein within one family interacts with which protein within the other). The idea is that the real mapping would be the one maximizing the similarity between the trees. Since the exhaustive exploration of all possible mappings is not feasible for large families, current approaches use heuristic techniques which do not ensure the best solution to be found. This is why it is important to check the results proposed by heuristic techniques and to manually explore other solutions. Here we present TSEMA, the server for efficient mapping assessment. This system calculates an initial mapping between two families of proteins based on a Monte Carlo approach and allows the user to interactively modify it based on performance figures and/or specific biological knowledge. All the explored mappings are graphically shown over a representation of the phylogenetic trees. The system is freely available at . Standalone versions of the software behind the interface are available upon request from the authors. PMID:16845017

Coevolution of MHC genes (LMP/TAP/class Ia; NKT-class Ib; NKp30-B7H6): Lessons from cold-blooded vertebrates

PubMed Central

Ohta, Yuko; Flajnik, Martin F.

2015-01-01

Summary Comparative immunology provides the long view of what is conserved across all vertebrate taxa versus what is specific to particular organisms or group of organisms. Regarding the major histocompatibility complex (MHC) and coevolution, three striking cases have been revealed in cold-blooded vertebrates: lineages of class Ia antigen-processing and -presenting genes, evolutionary conservation of NKT-class Ib recognition, and the ancient emergence of the natural cytotoxicity receptor NKp30 and its ligand B7H6. While coevolution of transporter associated with antigen processing (TAP) and class Ia has been documented in endothermic birds and two mammals, lineages of LMP7 are restricted to ectotherms. The unambiguous discovery of natural killer T (NKT) cells in Xenopus demonstrated that NKT cells are not restricted to mammals and are likely to have emerged at the same time in evolution as classical α/β and γ/δ T cells. NK cell receptors evolve at a rapid rate, and orthologues are nearly impossible to identify in different vertebrate classes. By contrast, we have detected NKp30 in all gnathostomes, except in species where it was lost. The recently discovered ligand of NKp30, B7H6, shows strong signs of coevolution with NKp30 throughout evolution, i.e. coincident loss or expansion of both genes in some species. NKp30 also offers an attractive IgSF candidate for the invasion of the RAG transposon, which is believed to have initiated T-cell receptor/immunoglobulin adaptive immunity. Besides reviewing these intriguing features of MHC evolution and coevolution, we offer suggestions for future studies and propose a model for the primordial or proto MHC. PMID:26284468

Molecular mechanisms of adaptation emerging from the physics and evolution of nucleic acids and proteins.

PubMed

Goncearenco, Alexander; Ma, Bin-Guang; Berezovsky, Igor N

2014-03-01

DNA, RNA and proteins are major biological macromolecules that coevolve and adapt to environments as components of one highly interconnected system. We explore here sequence/structure determinants of mechanisms of adaptation of these molecules, links between them, and results of their mutual evolution. We complemented statistical analysis of genomic and proteomic sequences with folding simulations of RNA molecules, unraveling causal relations between compositional and sequence biases reflecting molecular adaptation on DNA, RNA and protein levels. We found many compositional peculiarities related to environmental adaptation and the life style. Specifically, thermal adaptation of protein-coding sequences in Archaea is characterized by a stronger codon bias than in Bacteria. Guanine and cytosine load in the third codon position is important for supporting the aerobic life style, and it is highly pronounced in Bacteria. The third codon position also provides a tradeoff between arginine and lysine, which are favorable for thermal adaptation and aerobicity, respectively. Dinucleotide composition provides stability of nucleic acids via strong base-stacking in ApG dinucleotides. In relation to coevolution of nucleic acids and proteins, thermostability-related demands on the amino acid composition affect the nucleotide content in the second codon position in Archaea.

Molecular mechanisms of adaptation emerging from the physics and evolution of nucleic acids and proteins

PubMed Central

Goncearenco, Alexander; Ma, Bin-Guang; Berezovsky, Igor N.

2014-01-01

DNA, RNA and proteins are major biological macromolecules that coevolve and adapt to environments as components of one highly interconnected system. We explore here sequence/structure determinants of mechanisms of adaptation of these molecules, links between them, and results of their mutual evolution. We complemented statistical analysis of genomic and proteomic sequences with folding simulations of RNA molecules, unraveling causal relations between compositional and sequence biases reflecting molecular adaptation on DNA, RNA and protein levels. We found many compositional peculiarities related to environmental adaptation and the life style. Specifically, thermal adaptation of protein-coding sequences in Archaea is characterized by a stronger codon bias than in Bacteria. Guanine and cytosine load in the third codon position is important for supporting the aerobic life style, and it is highly pronounced in Bacteria. The third codon position also provides a tradeoff between arginine and lysine, which are favorable for thermal adaptation and aerobicity, respectively. Dinucleotide composition provides stability of nucleic acids via strong base-stacking in ApG dinucleotides. In relation to coevolution of nucleic acids and proteins, thermostability-related demands on the amino acid composition affect the nucleotide content in the second codon position in Archaea. PMID:24371267

Identification of positive selection in disease response genes within members of the Poaceae.

PubMed

Rech, Gabriel E; Vargas, Walter A; Sukno, Serenella A; Thon, Michael R

2012-12-01

Millions of years of coevolution between plants and pathogens can leave footprints on their genomes and genes involved on this interaction are expected to show patterns of positive selection in which novel, beneficial alleles are rapidly fixed within the population. Using information about upregulated genes in maize during Colletotrichum graminicola infection and resources available in the Phytozome database, we looked for evidence of positive selection in the Poaceae lineage, acting on protein coding sequences related with plant defense. We found six genes with evidence of positive selection and another eight with sites showing episodic selection. Some of them have already been described as evolving under positive selection, but others are reported here for the first time including genes encoding isocitrate lyase, dehydrogenases, a multidrug transporter, a protein containing a putative leucine-rich repeat and other proteins with unknown functions. Mapping positively selected residues onto the predicted 3-D structure of proteins showed that most of them are located on the surface, where proteins are in contact with other molecules. We present here a set of Poaceae genes that are likely to be involved in plant defense mechanisms and have evidence of positive selection. These genes are excellent candidates for future functional validation.

Coevolutionary diversification creates nested-modular structure in phage–bacteria interaction networks

PubMed Central

Beckett, Stephen J.; Williams, Hywel T. P.

2013-01-01

Phage and their bacterial hosts are the most diverse and abundant biological entities in the oceans, where their interactions have a major impact on marine ecology and ecosystem function. The structure of interaction networks for natural phage–bacteria communities offers insight into their coevolutionary origin. At small phylogenetic scales, observed communities typically show a nested structure, in which both hosts and phages can be ranked by their range of resistance and infectivity, respectively. A qualitatively different multi-scale structure is seen at larger phylogenetic scales; a natural assemblage sampled from the Atlantic Ocean displays large-scale modularity and local nestedness within each module. Here, we show that such ‘nested-modular’ interaction networks can be produced by a simple model of host–phage coevolution in which infection depends on genetic matching. Negative frequency-dependent selection causes diversification of hosts (to escape phages) and phages (to track their evolving hosts). This creates a diverse community of bacteria and phage, maintained by kill-the-winner ecological dynamics. When the resulting communities are visualized as bipartite networks of who infects whom, they show the nested-modular structure characteristic of the Atlantic sample. The statistical significance and strength of this observation varies depending on whether the interaction networks take into account the density of the interacting strains, with implications for interpretation of interaction networks constructed by different methods. Our results suggest that the apparently complex community structures associated with marine bacteria and phage may arise from relatively simple coevolutionary origins. PMID:24516719

Emerging Interaction Patterns in the Emiliania huxleyi-EhV System

PubMed Central

Ruiz, Eliana; Oosterhof, Monique; Sandaa, Ruth-Anne; Larsen, Aud; Pagarete, António

2017-01-01

Viruses are thought to be fundamental in driving microbial diversity in the oceanic planktonic realm. That role and associated emerging infection patterns remain particularly elusive for eukaryotic phytoplankton and their viruses. Here we used a vast number of strains from the model system Emiliania huxleyi/Emiliania huxleyi Virus to quantify parameters such as growth rate (µ), resistance (R), and viral production (Vp) capacities. Algal and viral abundances were monitored by flow cytometry during 72-h incubation experiments. The results pointed out higher viral production capacity in generalist EhV strains, and the virus-host infection network showed a strong co-evolution pattern between E. huxleyi and EhV populations. The existence of a trade-off between resistance and growth capacities was not confirmed. PMID:28327527

Emerging Interaction Patterns in the Emiliania huxleyi-EhV System.

PubMed

Ruiz, Eliana; Oosterhof, Monique; Sandaa, Ruth-Anne; Larsen, Aud; Pagarete, António

2017-03-22

Viruses are thought to be fundamental in driving microbial diversity in the oceanic planktonic realm. That role and associated emerging infection patterns remain particularly elusive for eukaryotic phytoplankton and their viruses. Here we used a vast number of strains from the model system Emiliania huxleyi /Emiliania huxleyi Virus to quantify parameters such as growth rate (µ), resistance (R), and viral production (Vp) capacities. Algal and viral abundances were monitored by flow cytometry during 72-h incubation experiments. The results pointed out higher viral production capacity in generalist EhV strains, and the virus-host infection network showed a strong co-evolution pattern between E. huxleyi and EhV populations. The existence of a trade-off between resistance and growth capacities was not confirmed.

More Opportunities than Wealth: Inequality and Emergent Social Classes in a Network of Power and Frustration

NASA Astrophysics Data System (ADS)

Nisoli, Cristiano; Mahault, Benoit; Saxena, Avadh

We introduce a minimal agent-based model to qualitatively conceptualize the allocation of limited wealth among more abundant opportunities. There the interplay of power, satisfaction and frustration determines the distribution, concentration, and inequality of wealth. Our framework allows us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from, or lose wealth to, anybody else invariably leads to large inequality. The picture is however dramatically modified when hard constraints are imposed over agents, and they are limited to share wealth with neighbors on a network. We address dynamical societies via an out of equilibrium coevolution of the network, driven by a competition between power and frustration. The ratio between power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of the indices of equality. In particular, it leads to the emergence of three self-organized social classes, lower, middle, and upper class, whose interactions drive a cyclical regime.

Social networks and smoking: exploring the effects of peer influence and smoker popularity through simulations.

PubMed

Schaefer, David R; Adams, Jimi; Haas, Steven A

2013-10-01

Adolescent smoking and friendship networks are related in many ways that can amplify smoking prevalence. Understanding and developing interventions within such a complex system requires new analytic approaches. We draw on recent advances in dynamic network modeling to develop a technique that explores the implications of various intervention strategies targeted toward micro-level processes. Our approach begins by estimating a stochastic actor-based model using data from one school in the National Longitudinal Study of Adolescent Health. The model provides estimates of several factors predicting friendship ties and smoking behavior. We then use estimated model parameters to simulate the coevolution of friendship and smoking behavior under potential intervention scenarios. Namely, we manipulate the strength of peer influence on smoking and the popularity of smokers relative to nonsmokers. We measure how these manipulations affect smoking prevalence, smoking initiation, and smoking cessation. Results indicate that both peer influence and smoking-based popularity affect smoking behavior and that their joint effects are nonlinear. This study demonstrates how a simulation-based approach can be used to explore alternative scenarios that may be achievable through intervention efforts and offers new hypotheses about the association between friendship and smoking.

Social Networks and Smoking: Exploring the Effects of Influence and Smoker Popularity through Simulations

PubMed Central

Schaefer, David R.; adams, jimi; Haas, Steven A.

2015-01-01

Adolescent smoking and friendship networks are related in many ways that can amplify smoking prevalence. Understanding and developing interventions within such a complex system requires new analytic approaches. We draw upon recent advances in dynamic network modeling to develop a technique that explores the implications of various intervention strategies targeted toward micro-level processes. Our approach begins by estimating a stochastic actor-based model using data from one school in the National Longitudinal Study of Adolescent Health. The model provides estimates of several factors predicting friendship ties and smoking behavior. We then use estimated model parameters to simulate the co-evolution of friendship and smoking behavior under potential intervention scenarios. Namely, we manipulate the strength of peer influence on smoking and the popularity of smokers relative to nonsmokers. We measure how these manipulations affect smoking prevalence, smoking initiation, and smoking cessation. Results indicate that both peer influence and smoking-based popularity affect smoking behavior, and that their joint effects are nonlinear. This study demonstrates how a simulation-based approach can be used to explore alternative scenarios that may be achievable through intervention efforts and offers new hypotheses about the association between friendship and smoking. PMID:24084397

Our teacher likes you, so I like you: A social network approach to social referencing.

PubMed

Hendrickx, Marloes M H G; Mainhard, Tim; Boor-Klip, Henrike J; Brekelmans, Mieke

2017-08-01

A teacher is a social referent for peer liking and disliking when students adjust their evaluations of a peer based on their perceptions of teacher liking and disliking for this peer. The present study investigated social referencing as an intra-individual process that occurs over time, using stochastic actor-oriented modeling with RSiena. The co-evolution of peer-perceived teacher liking and disliking networks with peer liking and disliking networks was analyzed in 52 fifth-grade classes in the Netherlands, with 1370 students (M age =10.60). Results showed that when a student viewed the teacher to like a peer, this student would also like this peer. Regarding disliking, there was a stronger effect in the opposite direction, indicating that students' disliking a peer increased the likelihood that they would view the peer as disliked by the teacher as well. In sum, partial evidence for social referencing as an intra-individual process was found. For teachers this implies that the cues they provide regarding their liking of a student, and not necessarily their disliking, may affect individual peers' liking of this student. Copyright © 2017 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Phylogenetic placement of an unusual coral mushroom challenges the classic hypothesis of strict coevolution in the Apterostigma pilosum group ant-fungus mutualism

Treesearch

Bryn T.M. Dentinger; D.Jean Lodge; Andrew B. Munkacsi; Dennis E. Desjardin; David J. McLaughlin

2009-01-01

The ~50 million-year-old fungus-farming ant mutualism is a classic example of coevolution, involving ants that subsist on asexual, fungal biomass, in turn propagating the fungus clonally through nest-to-nest transmission. Most mutualistic ants cultivate two closely related groups of gilled mushrooms, whereas one small group of ants in the genus ...

Phylogenetic placement of an unusual coral mushroom challenges the classic hypothesis of strict coevolution in the apterostigma pilosum group ant-fungus mutualism.

PubMed

Dentinger, Bryn T M; Lodge, D Jean; Munkacsi, Andrew B; Desjardin, Dennis E; McLaughlin, David J

2009-08-01

The approximately 50 million-year-old fungus-farming ant mutualism is a classic example of coevolution, involving ants that subsist on asexual, fungal biomass, in turn propagating the fungus clonally through nest-to-nest transmission. Most mutualistic ants cultivate two closely related groups of gilled mushrooms, whereas one small group of ants in the genus Apterostigma cultivates a distantly related lineage comprised of the G2 and G4 groups. The G2 and G4 fungi were previously shown to form a monophyletic group sister to the thread-like coral mushroom family Pterulaceae. Here, we identify an enigmatic coral mushroom that produces both fertile and sterile fruiting structures as the closest free-living relative of the G4 fungi, challenging the monophyly of the Apterostigma-cultivated fungi for the first time. Both nonparametric bootstrap and Bayesian posterior probability support the node leading to the G4 cultivars and a free-living Pterula mushroom. These data suggest three scenarios that contradict the hypothesis of strict coevolution: (1) multiple domestications, (2) escape from domestication, (3) selection of single cultivar lineages from an ancestral mixed-fungus garden. These results illustrate how incomplete phylogenies for coevolved symbionts impede our understanding of the patterns and processes of coevolution.

The Coevolution of Life and Environment on Mars: An Ecosystem Perspective on the Robotic Exploration of Biosignatures

NASA Astrophysics Data System (ADS)

Cabrol, Nathalie A.

2018-01-01

Earth's biological and environmental evolution are intertwined and inseparable. This coevolution has become a fundamental concept in astrobiology and is key to the search for life beyond our planet. In the case of Mars, whether a coevolution took place is unknown, but analyzing the factors at play shows the uniqueness of each planetary experiment regardless of similarities. Early Earth and early Mars shared traits. However, biological processes on Mars, if any, would have had to proceed within the distinctive context of an irreversible atmospheric collapse, greater climate variability, and specific planetary characteristics. In that, Mars is an important test bed for comparing the effects of a unique set of spatiotemporal changes on an Earth-like, yet different, planet. Many questions remain unanswered about Mars' early environment. Nevertheless, existing data sets provide a foundation for an intellectual framework where notional coevolution models can be explored. In this framework, the focus is shifted from planetary-scale habitability to the prospect of habitats, microbial ecotones, pathways to biological dispersal, biomass repositories, and their meaning for exploration. Critically, as we search for biosignatures, this focus demonstrates the importance of starting to think of early Mars as a biosphere and vigorously integrating an ecosystem approach to landing site selection and exploration.

Sex Steroids Effects on the Molting Process of the Helminth Human Parasite Trichinella spiralis

PubMed Central

Hernández-Bello, Romel; Ramirez-Nieto, Ricardo; Muñiz-Hernández, Saé; Nava-Castro, Karen; Pavón, Lenin; Sánchez-Acosta, Ana Gabriela; Morales-Montor, Jorge

2011-01-01

We evaluated the in vitro effects of estradiol, progesterone, and testosterone on the molting process, which is the initial and crucial step in the development of the muscular larvae (ML or L1) to adult worm. Testosterone had no significative effect on the molting rate of the parasite, however, progesterone decreased the molting rate about a 50% in a concentration- and time-independent pattern, while estradiol had a slight effect (10%). The gene expression of caveolin-1, a specific gene used as a marker of parasite development, showed that progesterone and estradiol downregulated its expression, while protein expression was unaffected. By using flow citometry, a possible protein that is recognized by a commercial antiprogesterone receptor antibody was detected. These findings may have strong implications in the host-parasite coevolution, in the sex-associated susceptibility to this infection and could point out to possibilities to use antihormones to inhibit parasite development. PMID:22162638

Lineage-specific expansion of IFIT gene family: an insight into coevolution with IFN gene family.

PubMed

Liu, Ying; Zhang, Yi-Bing; Liu, Ting-Kai; Gui, Jian-Fang

2013-01-01

In mammals, IFIT (Interferon [IFN]-induced proteins with Tetratricopeptide Repeat [TPR] motifs) family genes are involved in many cellular and viral processes, which are tightly related to mammalian IFN response. However, little is known about non-mammalian IFIT genes. In the present study, IFIT genes are identified in the genome databases from the jawed vertebrates including the cartilaginous elephant shark but not from non-vertebrates such as lancelet, sea squirt and acorn worm, suggesting that IFIT gene family originates from a vertebrate ancestor about 450 million years ago. IFIT family genes show conserved gene structure and gene arrangements. Phylogenetic analyses reveal that this gene family has expanded through lineage-specific and species-specific gene duplication. Interestingly, IFN gene family seem to share a common ancestor and a similar evolutionary mechanism; the function link of IFIT genes to IFN response is present early since the origin of both gene families, as evidenced by the finding that zebrafish IFIT genes are upregulated by fish IFNs, poly(I:C) and two transcription factors IRF3/IRF7, likely via the IFN-stimulated response elements (ISRE) within the promoters of vertebrate IFIT family genes. These coevolution features creates functional association of both family genes to fulfill a common biological process, which is likely selected by viral infection during evolution of vertebrates. Our results are helpful for understanding of evolution of vertebrate IFN system.

Host-parasite coevolution: genetic variation in a virus population and the interaction with a host gene.

PubMed

Wilfert, L; Jiggins, F M

2010-07-01

Host-parasite coevolution is considered to be an important factor in maintaining genetic variation in resistance to pathogens. Drosophila melanogaster is naturally infected by the sigma virus, a vertically transmitted and host-specific pathogen. In fly populations, there is a large amount of genetic variation in the transmission rate from parent to offspring, much of which is caused by major-effect resistance polymorphisms. We have found that there are similarly high levels of genetic variation in the rate of paternal transmission among 95 different isolates of the virus as in the host. However, when we examined a transmission-blocking gene in the host, we found that it was effective across virus isolates. Therefore, the high levels of genetic variation observed in this system do not appear to be maintained because of coevolution resulting from interactions between this host gene and parasite genes.

Physical mode of bacteria and virus coevolution

NASA Astrophysics Data System (ADS)

Han, Pu; Niestemski, Liang; Deem, Michael

2013-03-01

Single-cell hosts such as bacteria or archaea possess an adaptive, heritable immune system that protects them from viral invasion. This system, known as the CRISPR-Cas system, allows the host to recognize and incorporate short foreign DNA or RNA sequences from viruses or plasmids. The sequences form what are called ``spacers'' in the CRISPR. Spacers in the CRISPR loci provide a record of the host and predator coevolution history. We develop a physical model to study the dynamics of this coevolution due to immune pressure. Hosts and viruses reproduce, die, and evolve due to viral infection pressure, host immune pressure, and mutation. We will discuss the differing effects of point mutation and recombination on CRISPR evolution. We will also discuss the effect of different spacer deletion mechanisms. We will describe population structure of hosts and viruses, how spacer diversity depends on position within CRISPR, and match of the CRISPR spacers to the virus population.

The role of ecology, neutral processes and antagonistic coevolution in an apparent sexual arms race.

PubMed

Perry, Jennifer C; Garroway, Colin J; Rowe, Locke

2017-09-01

Some of the strongest examples of a sexual 'arms race' come from observations of correlated evolution in sexually antagonistic traits among populations. However, it remains unclear whether these cases truly represent sexually antagonistic coevolution; alternatively, ecological or neutral processes might also drive correlated evolution. To investigate these alternatives, we evaluated the contributions of intersex genetic correlations, ecological context, neutral genetic divergence and sexual coevolution in the correlated evolution of antagonistic traits among populations of Gerris incognitus water striders. We could not detect intersex genetic correlations for these sexually antagonistic traits. Ecological variation was related to population variation in the key female antagonistic trait (spine length, a defence against males), as well as body size. Nevertheless, population covariation between sexually antagonistic traits remained substantial and significant even after accounting for all of these processes. Our results therefore provide strong evidence for a contemporary sexual arms race. © 2017 John Wiley & Sons Ltd/CNRS.

Smart social adaptation prevents catastrophic ecological regime shifts in networks of myopic harvesters

NASA Astrophysics Data System (ADS)

Donges, Jonathan; Lucht, Wolfgang; Wiedermann, Marc; Heitzig, Jobst; Kurths, Jürgen

2015-04-01

In the anthropocene, the rise of global social and economic networks with ever increasing connectivity and speed of interactions, e.g., the internet or global financial markets, is a key challenge for sustainable development. The spread of opinions, values or technologies on these networks, in conjunction with the coevolution of the network structures themselves, underlies nexuses of current concern such as anthropogenic climate change, biodiversity loss or global land use change. To isolate and quantitatively study the effects and implications of network dynamics for sustainable development, we propose an agent-based model of information flow on adaptive networks between myopic harvesters that exploit private renewable resources. In this conceptual model of a network of socio-ecological systems, information on management practices flows between agents via boundedly rational imitation depending on the state of the resource stocks involved in an interaction. Agents can also adapt the structure of their social network locally by preferentially connecting to culturally similar agents with identical management practices and, at the same time, disconnecting from culturally dissimilar agents. Investigating in detail the statistical mechanics of this model, we find that an increasing rate of information flow through faster imitation dynamics or growing density of network connectivity leads to a marked increase in the likelihood of environmental resource collapse. However, we show that an optimal rate of social network adaptation can mitigate this negative effect without loss of social cohesion through network fragmentation. Our results highlight that seemingly immaterial network dynamics of spreading opinions or values can be of large relevance for the sustainable management of socio-ecological systems and suggest smartly conservative network adaptation as a strategy for mitigating environmental collapse. Hence, facing the great acceleration, these network dynamics should be more routinely incorporated in standard models of economic development or integrated assessment models used for evaluating anthropogenic climate change.

Human initiated cascading failures in societal infrastructures.

PubMed

Barrett, Chris; Channakeshava, Karthik; Huang, Fei; Kim, Junwhan; Marathe, Achla; Marathe, Madhav V; Pei, Guanhong; Saha, Sudip; Subbiah, Balaaji S P; Vullikanti, Anil Kumar S

2012-01-01

In this paper, we conduct a systematic study of human-initiated cascading failures in three critical inter-dependent societal infrastructures due to behavioral adaptations in response to a crisis. We focus on three closely coupled socio-technical networks here: (i) cellular and mesh networks, (ii) transportation networks and (iii) mobile call networks. In crises, changes in individual behaviors lead to altered travel, activity and calling patterns, which influence the transport network and the loads on wireless networks. The interaction between these systems and their co-evolution poses significant technical challenges for representing and reasoning about these systems. In contrast to system dynamics models for studying these interacting infrastructures, we develop interaction-based models in which individuals and infrastructure elements are represented in detail and are placed in a common geographic coordinate system. Using the detailed representation, we study the impact of a chemical plume that has been released in a densely populated urban region. Authorities order evacuation of the affected area, and this leads to individual behavioral adaptation wherein individuals drop their scheduled activities and drive to home or pre-specified evacuation shelters as appropriate. They also revise their calling behavior to communicate and coordinate among family members. These two behavioral adaptations cause flash-congestion in the urban transport network and the wireless network. The problem is exacerbated with a few, already occurring, road closures. We analyze how extended periods of unanticipated road congestion can result in failure of infrastructures, starting with the servicing base stations in the congested area. A sensitivity analysis on the compliance rate of evacuees shows non-intuitive effect on the spatial distribution of people and on the loading of the base stations. For example, an evacuation compliance rate of 70% results in higher number of overloaded base stations than the evacuation compliance rate of 90%.

Rapid molecular evolution across amniotes of the IIS/TOR network

PubMed Central

McGaugh, Suzanne E.; Bronikowski, Anne M.; Kuo, Chih-Horng; Reding, Dawn M.; Addis, Elizabeth A.; Flagel, Lex E.; Janzen, Fredric J.

2015-01-01

The insulin/insulin-like signaling and target of rapamycin (IIS/TOR) network regulates lifespan and reproduction, as well as metabolic diseases, cancer, and aging. Despite its vital role in health, comparative analyses of IIS/TOR have been limited to invertebrates and mammals. We conducted an extensive evolutionary analysis of the IIS/TOR network across 66 amniotes with 18 newly generated transcriptomes from nonavian reptiles and additional available genomes/transcriptomes. We uncovered rapid and extensive molecular evolution between reptiles (including birds) and mammals: (i) the IIS/TOR network, including the critical nodes insulin receptor substrate (IRS) and phosphatidylinositol 3-kinase (PI3K), exhibit divergent evolutionary rates between reptiles and mammals; (ii) compared with a proxy for the rest of the genome, genes of the IIS/TOR extracellular network exhibit exceptionally fast evolutionary rates; and (iii) signatures of positive selection and coevolution of the extracellular network suggest reptile- and mammal-specific interactions between members of the network. In reptiles, positively selected sites cluster on the binding surfaces of insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and insulin receptor (INSR); whereas in mammals, positively selected sites clustered on the IGF2 binding surface, suggesting that these hormone-receptor binding affinities are targets of positive selection. Further, contrary to reports that IGF2R binds IGF2 only in marsupial and placental mammals, we found positively selected sites clustered on the hormone binding surface of reptile IGF2R that suggest that IGF2R binds to IGF hormones in diverse taxa and may have evolved in reptiles. These data suggest that key IIS/TOR paralogs have sub- or neofunctionalized between mammals and reptiles and that this network may underlie fundamental life history and physiological differences between these amniote sister clades. PMID:25991861

Human Initiated Cascading Failures in Societal Infrastructures

PubMed Central

Barrett, Chris; Channakeshava, Karthik; Huang, Fei; Kim, Junwhan; Marathe, Achla; Marathe, Madhav V.; Pei, Guanhong; Saha, Sudip; Subbiah, Balaaji S. P.; Vullikanti, Anil Kumar S.

2012-01-01

In this paper, we conduct a systematic study of human-initiated cascading failures in three critical inter-dependent societal infrastructures due to behavioral adaptations in response to a crisis. We focus on three closely coupled socio-technical networks here: (i) cellular and mesh networks, (ii) transportation networks and (iii) mobile call networks. In crises, changes in individual behaviors lead to altered travel, activity and calling patterns, which influence the transport network and the loads on wireless networks. The interaction between these systems and their co-evolution poses significant technical challenges for representing and reasoning about these systems. In contrast to system dynamics models for studying these interacting infrastructures, we develop interaction-based models in which individuals and infrastructure elements are represented in detail and are placed in a common geographic coordinate system. Using the detailed representation, we study the impact of a chemical plume that has been released in a densely populated urban region. Authorities order evacuation of the affected area, and this leads to individual behavioral adaptation wherein individuals drop their scheduled activities and drive to home or pre-specified evacuation shelters as appropriate. They also revise their calling behavior to communicate and coordinate among family members. These two behavioral adaptations cause flash-congestion in the urban transport network and the wireless network. The problem is exacerbated with a few, already occurring, road closures. We analyze how extended periods of unanticipated road congestion can result in failure of infrastructures, starting with the servicing base stations in the congested area. A sensitivity analysis on the compliance rate of evacuees shows non-intuitive effect on the spatial distribution of people and on the loading of the base stations. For example, an evacuation compliance rate of 70% results in higher number of overloaded base stations than the evacuation compliance rate of 90%. PMID:23118847

Ecological modules and roles of species in heathland plant-insect flower visitor networks.

PubMed

Dupont, Yoko L; Olesen, Jens M

2009-03-01

1. Co-existing plants and flower-visiting animals often form complex interaction networks. A long-standing question in ecology and evolutionary biology is how to detect nonrandom subsets (compartments, blocks, modules) of strongly interacting species within such networks. Here we use a network analytical approach to (i) detect modularity in pollination networks, (ii) investigate species composition of modules, and (iii) assess the stability of modules across sites. 2. Interactions between entomophilous plants and their flower-visitors were recorded throughout the flowering season at three heathland sites in Denmark, separated by >or= 10 km. Among sites, plant communities were similar, but composition of flower-visiting insect faunas differed. Visitation frequencies of visitor species were recorded as a measure of insect abundance. 3. Qualitative (presence-absence) interaction networks were tested for modularity. Modules were identified, and species classified into topological roles (peripherals, connectors, or hubs) using 'functional cartography by simulated annealing', a method recently developed by Guimerà & Amaral (2005a). 4. All networks were significantly modular. Each module consisted of 1-6 plant species and 18-54 insect species. Interactions aggregated around one or two hub plant species, which were largely identical at the three study sites. 5. Insect species were categorized in taxonomic groups, mostly at the level of orders. When weighted by visitation frequency, each module was dominated by one or few insect groups. This pattern was consistent across sites. 6. Our study adds support to the conclusion that certain plant species and flower-visitor groups are nonrandomly and repeatedly associated. Within a network, these strongly interacting subgroups of species may exert reciprocal selection pressures on each other. Thus, modules may be candidates for the long-sought key units of co-evolution.

Rapid molecular evolution across amniotes of the IIS/TOR network.

PubMed

McGaugh, Suzanne E; Bronikowski, Anne M; Kuo, Chih-Horng; Reding, Dawn M; Addis, Elizabeth A; Flagel, Lex E; Janzen, Fredric J; Schwartz, Tonia S

2015-06-02

The insulin/insulin-like signaling and target of rapamycin (IIS/TOR) network regulates lifespan and reproduction, as well as metabolic diseases, cancer, and aging. Despite its vital role in health, comparative analyses of IIS/TOR have been limited to invertebrates and mammals. We conducted an extensive evolutionary analysis of the IIS/TOR network across 66 amniotes with 18 newly generated transcriptomes from nonavian reptiles and additional available genomes/transcriptomes. We uncovered rapid and extensive molecular evolution between reptiles (including birds) and mammals: (i) the IIS/TOR network, including the critical nodes insulin receptor substrate (IRS) and phosphatidylinositol 3-kinase (PI3K), exhibit divergent evolutionary rates between reptiles and mammals; (ii) compared with a proxy for the rest of the genome, genes of the IIS/TOR extracellular network exhibit exceptionally fast evolutionary rates; and (iii) signatures of positive selection and coevolution of the extracellular network suggest reptile- and mammal-specific interactions between members of the network. In reptiles, positively selected sites cluster on the binding surfaces of insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and insulin receptor (INSR); whereas in mammals, positively selected sites clustered on the IGF2 binding surface, suggesting that these hormone-receptor binding affinities are targets of positive selection. Further, contrary to reports that IGF2R binds IGF2 only in marsupial and placental mammals, we found positively selected sites clustered on the hormone binding surface of reptile IGF2R that suggest that IGF2R binds to IGF hormones in diverse taxa and may have evolved in reptiles. These data suggest that key IIS/TOR paralogs have sub- or neofunctionalized between mammals and reptiles and that this network may underlie fundamental life history and physiological differences between these amniote sister clades.

Cooperation prevails when individuals adjust their social ties.

PubMed

Santos, Francisco C; Pacheco, Jorge M; Lenaerts, Tom

2006-10-20

Conventional evolutionary game theory predicts that natural selection favours the selfish and strong even though cooperative interactions thrive at all levels of organization in living systems. Recent investigations demonstrated that a limiting factor for the evolution of cooperative interactions is the way in which they are organized, cooperators becoming evolutionarily competitive whenever individuals are constrained to interact with few others along the edges of networks with low average connectivity. Despite this insight, the conundrum of cooperation remains since recent empirical data shows that real networks exhibit typically high average connectivity and associated single-to-broad-scale heterogeneity. Here, a computational model is constructed in which individuals are able to self-organize both their strategy and their social ties throughout evolution, based exclusively on their self-interest. We show that the entangled evolution of individual strategy and network structure constitutes a key mechanism for the sustainability of cooperation in social networks. For a given average connectivity of the population, there is a critical value for the ratio W between the time scales associated with the evolution of strategy and of structure above which cooperators wipe out defectors. Moreover, the emerging social networks exhibit an overall heterogeneity that accounts very well for the diversity of patterns recently found in acquired data on social networks. Finally, heterogeneity is found to become maximal when W reaches its critical value. These results show that simple topological dynamics reflecting the individual capacity for self-organization of social ties can produce realistic networks of high average connectivity with associated single-to-broad-scale heterogeneity. On the other hand, they show that cooperation cannot evolve as a result of "social viscosity" alone in heterogeneous networks with high average connectivity, requiring the additional mechanism of topological co-evolution to ensure the survival of cooperative behaviour.

Coexistence via coevolution driven by reduced allelochemical effects and increased tolerance to competition between invasive and native plants.

PubMed

Huang, Fangfang; Lankau, Richard; Peng, Shaolin

2018-04-01

Coevolution can promote long-term coexistence of two competing species if selection acts to reduce the fitness inequality between competitors and/or strengthen negative frequency dependence within each population. However, clear coevolution between plant competitors has been rarely documented. Plant invasions offer opportunities to capture the process of coevolution. Here we investigated how the developing relationship between an invasive forb, Alliaria petiolata, and a native competitor, Pilea pumila, may affect their long-term coexistence, by testing the competitive effects of populations of varying lengths of co-occurrence on each other across a chronosequence of invasion history. Alliaria petiolata and P. pumila tended to develop greater tolerance to competition over invasion history. Their coexistence was promoted more by increases in stabilizing relative to equalizing processes. These changes likely stem in part from reductions in allelopathic traits in the invader and evolution of tolerance in the native. These results suggested that some native species can evolve tolerance against the competitive effects of strong invaders, which likely promoted their persistence in invaded communities. However, the potential for coevolutionary rescue of competing populations is likely to vary across native species, and evolutionary processes should not be expected to compensate for the ecological consequences of exotic invasions. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

The Red Queen in mitochondria: cyto-nuclear co-evolution, hybrid breakdown and human disease

PubMed Central

Chou, Jui-Yu; Leu, Jun-Yi

2015-01-01

Cyto-nuclear incompatibility, a specific form of Dobzhansky-Muller incompatibility caused by incompatible alleles between mitochondrial and nuclear genomes, has been suggested to play a critical role during speciation. Several features of the mitochondrial genome (mtDNA), including high mutation rate, dynamic genomic structure, and uniparental inheritance, make mtDNA more likely to accumulate mutations in the population. Once mtDNA has changed, the nuclear genome needs to play catch-up due to the intimate interactions between these two genomes. In two populations, if cyto-nuclear co-evolution is driven in different directions, it may eventually lead to hybrid incompatibility. Although cyto-nuclear incompatibility has been observed in a wide range of organisms, it remains unclear what type of mutations drives the co-evolution. Currently, evidence supporting adaptive mutations in mtDNA remains limited. On the other hand, it has been known that some mutations allow mtDNA to propagate more efficiently but compromise the host fitness (described as selfish mtDNA). Arms races between such selfish mtDNA and host nuclear genomes can accelerate cyto-nuclear co-evolution and lead to a phenomenon called the Red Queen Effect. Here, we discuss how the Red Queen Effect may contribute to the frequent observation of cyto-nuclear incompatibility and be the underlying driving force of some human mitochondrial diseases. PMID:26042149

Optimality and self-organization in river deltas

NASA Astrophysics Data System (ADS)

Tejedor, A.; Longjas, A.; Edmonds, D. A.; Zaliapin, I. V.; Georgiou, T. T.; Rinaldo, A.; Foufoula-Georgiou, E.

2017-12-01

Deltas are nourished by channel networks, whose connectivity constrains, if not drives, the evolution, functionality and resilience of these systems. Understanding the coevolution of deltaic channels and their flux organization is crucial for guiding maintenance strategies of these highly stressed systems from a range of anthropogenic activities. However, in contrast to tributary channel networks, to date, no theory has been proposed to explain how deltas self-organize to distribute water and sediment to the delta top and the shoreline. Here, we hypothesize the existence of an optimality principle underlying the self-organized partition of fluxes in delta channel networks. Specifically, we hypothesize that deltas distribute water and sediment fluxes on a given delta topology such as to maximize the diversity of flux delivery to the shoreline. By introducing the concept of nonlocal Entropy Rate (nER) and analyzing ten field deltas in diverse environments, we present evidence that supports our hypothesis, suggesting that delta networks achieve dynamically accessible maxima of their nER. Furthermore, by analyzing six simulated deltas using the Delf3D model and following their topologic and flux re-organization before and after major avulsions, we further study the evolution of nER and confirm our hypothesis. We discuss how optimal flux distributions in terms of nER, when interpreted in terms of resilience, are configurations that reflect an increased ability to withstand perturbations.

Anatomical Network Analysis Shows Decoupling of Modular Lability and Complexity in the Evolution of the Primate Skull

PubMed Central

Esteve-Altava, Borja; Boughner, Julia C.; Diogo, Rui; Villmoare, Brian A.; Rasskin-Gutman, Diego

2015-01-01

Modularity and complexity go hand in hand in the evolution of the skull of primates. Because analyses of these two parameters often use different approaches, we do not know yet how modularity evolves within, or as a consequence of, an also-evolving complex organization. Here we use a novel network theory-based approach (Anatomical Network Analysis) to assess how the organization of skull bones constrains the co-evolution of modularity and complexity among primates. We used the pattern of bone contacts modeled as networks to identify connectivity modules and quantify morphological complexity. We analyzed whether modularity and complexity evolved coordinately in the skull of primates. Specifically, we tested Herbert Simon’s general theory of near-decomposability, which states that modularity promotes the evolution of complexity. We found that the skulls of extant primates divide into one conserved cranial module and up to three labile facial modules, whose composition varies among primates. Despite changes in modularity, statistical analyses reject a positive feedback between modularity and complexity. Our results suggest a decoupling of complexity and modularity that translates to varying levels of constraint on the morphological evolvability of the primate skull. This study has methodological and conceptual implications for grasping the constraints that underlie the developmental and functional integration of the skull of humans and other primates. PMID:25992690

The evolution of resistance genes in multi-protein plant resistance systems.

PubMed

Friedman, Aaron R; Baker, Barbara J

2007-12-01

The genomic perspective aids in integrating the analysis of single resistance (R-) genes into a higher order model of complex plant resistance systems. The majority of R-genes encode a class of proteins with nucleotide binding (NB) and leucine-rich repeat (LRR) domains. Several R-proteins act in multi-protein R-complexes that mediate interaction with pathogen effectors to induce resistance signaling. The complexity of these systems seems to have resulted from multiple rounds of plant-pathogen co-evolution. R-gene evolution is thought to be facilitated by the formation of R-gene clusters, which permit sequence exchanges via recombinatorial mispairing and generate high haplotypic diversity. This pattern of evolution may also generate diversity at other loci that contribute to the R-complex. The rate of recombination at R-clusters is not necessarily homogeneous or consistent over evolutionary time: recent evidence suggests that recombination at R-clusters is increased following pathogen infection, suggesting a mechanism that induces temporary genome instability in response to extreme stress. DNA methylation and chromatin modifications may allow this instability to be conditionally regulated and targeted to specific genome regions. Knowledge of natural R-gene evolution may contribute to strategies for artificial evolution of novel resistance specificities.

The functional readthrough extension of malate dehydrogenase reveals a modification of the genetic code

PubMed Central

Hofhuis, Julia; Schueren, Fabian; Nötzel, Christopher; Lingner, Thomas; Gärtner, Jutta; Jahn, Olaf

2016-01-01

Translational readthrough gives rise to C-terminally extended proteins, thereby providing the cell with new protein isoforms. These may have different properties from the parental proteins if the extensions contain functional domains. While for most genes amino acid incorporation at the stop codon is far lower than 0.1%, about 4% of malate dehydrogenase (MDH1) is physiologically extended by translational readthrough and the actual ratio of MDH1x (extended protein) to ‘normal' MDH1 is dependent on the cell type. In human cells, arginine and tryptophan are co-encoded by the MDH1x UGA stop codon. Readthrough is controlled by the 7-nucleotide high-readthrough stop codon context without contribution of the subsequent 50 nucleotides encoding the extension. All vertebrate MDH1x is directed to peroxisomes via a hidden peroxisomal targeting signal (PTS) in the readthrough extension, which is more highly conserved than the extension of lactate dehydrogenase B. The hidden PTS of non-mammalian MDH1x evolved to be more efficient than the PTS of mammalian MDH1x. These results provide insight into the genetic and functional co-evolution of these dually localized dehydrogenases. PMID:27881739

'Drugs from bugs': bacterial effector proteins as promising biological (immune-) therapeutics.

PubMed

Rüter, Christian; Hardwidge, Philip R

2014-02-01

Immune system malfunctions cause many of the most severe human diseases. The immune system has evolved primarily to control bacterial, viral, fungal, and parasitic infections. In turn, over millions of years of coevolution, microbial pathogens have evolved various mechanisms to control and modulate the host immune system for their own benefit and survival. For example, many bacterial pathogens use virulence proteins to modulate and exploit target cell mechanisms. Our understanding of these bacterial strategies opens novel possibilities to exploit 'microbial knowledge' to control excessive immune reactions. Gaining access to strategies of microbial pathogens could lead to potentially huge benefits for the therapy of inflammatory diseases. Most work on bacterial pathogen effector proteins has the long-term aim of neutralizing the infectious capabilities of the pathogen. However, attenuated pathogens and microbial products have been used for over a century with overwhelming success in the form of vaccines to induce specific immune responses that protect against the respective infectious diseases. In this review, we focus on bacterial effector and virulence proteins capable of modulating and suppressing distinct signaling pathways with potentially desirable immune-modulating effects for treating unrelated inflammatory diseases. © 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

HIV-1 protease-substrate coevolution in nelfinavir resistance.

PubMed

Kolli, Madhavi; Ozen, Ayşegül; Kurt-Yilmaz, Nese; Schiffer, Celia A

2014-07-01

Resistance to various human immunodeficiency virus type 1 (HIV-1) protease inhibitors (PIs) challenges the effectiveness of therapies in treating HIV-1-infected individuals and AIDS patients. The virus accumulates mutations within the protease (PR) that render the PIs less potent. Occasionally, Gag sequences also coevolve with mutations at PR cleavage sites contributing to drug resistance. In this study, we investigated the structural basis of coevolution of the p1-p6 cleavage site with the nelfinavir (NFV) resistance D30N/N88D protease mutations by determining crystal structures of wild-type and NFV-resistant HIV-1 protease in complex with p1-p6 substrate peptide variants with L449F and/or S451N. Alterations of residue 30's interaction with the substrate are compensated by the coevolving L449F and S451N cleavage site mutations. This interdependency in the PR-p1-p6 interactions enhances intermolecular contacts and reinforces the overall fit of the substrate within the substrate envelope, likely enabling coevolution to sustain substrate recognition and cleavage in the presence of PR resistance mutations. Resistance to human immunodeficiency virus type 1 (HIV-1) protease inhibitors challenges the effectiveness of therapies in treating HIV-1-infected individuals and AIDS patients. Mutations in HIV-1 protease selected under the pressure of protease inhibitors render the inhibitors less potent. Occasionally, Gag sequences also mutate and coevolve with protease, contributing to maintenance of viral fitness and to drug resistance. In this study, we investigated the structural basis of coevolution at the Gag p1-p6 cleavage site with the nelfinavir (NFV) resistance D30N/N88D protease mutations. Our structural analysis reveals the interdependency of protease-substrate interactions and how coevolution may restore substrate recognition and cleavage in the presence of protease drug resistance mutations. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Detection of protein complex from protein-protein interaction network using Markov clustering

NASA Astrophysics Data System (ADS)

Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.

2017-05-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.

Reciprocal Influence of Protein Domains in the Cold-Adapted Acyl Aminoacyl Peptidase from Sporosarcina psychrophila

PubMed Central

Parravicini, Federica; Natalello, Antonino; Papaleo, Elena; De Gioia, Luca; Doglia, Silvia Maria; Lotti, Marina; Brocca, Stefania

2013-01-01

Acyl aminoacyl peptidases are two-domain proteins composed by a C-terminal catalytic α/β-hydrolase domain and by an N-terminal β-propeller domain connected through a structural element that is at the N-terminus in sequence but participates in the 3D structure of the C-domain. We investigated about the structural and functional interplay between the two domains and the bridge structure (in this case a single helix named α1-helix) in the cold-adapted enzyme from Sporosarcina psychrophila (SpAAP) using both protein variants in which entire domains were deleted and proteins carrying substitutions in the α1-helix. We found that in this enzyme the inter-domain connection dramatically affects the stability of both the whole enzyme and the β-propeller. The α1-helix is required for the stability of the intact protein, as in other enzymes of the same family; however in this psychrophilic enzyme only, it destabilizes the isolated β-propeller. A single charged residue (E10) in the α1-helix plays a major role for the stability of the whole structure. Overall, a strict interaction of the SpAAP domains seems to be mandatory for the preservation of their reciprocal structural integrity and may witness their co-evolution. PMID:23457536

Reciprocal influence of protein domains in the cold-adapted acyl aminoacyl peptidase from Sporosarcina psychrophila.

PubMed

Parravicini, Federica; Natalello, Antonino; Papaleo, Elena; De Gioia, Luca; Doglia, Silvia Maria; Lotti, Marina; Brocca, Stefania

2013-01-01

Acyl aminoacyl peptidases are two-domain proteins composed by a C-terminal catalytic α/β-hydrolase domain and by an N-terminal β-propeller domain connected through a structural element that is at the N-terminus in sequence but participates in the 3D structure of the C-domain. We investigated about the structural and functional interplay between the two domains and the bridge structure (in this case a single helix named α1-helix) in the cold-adapted enzyme from Sporosarcina psychrophila (SpAAP) using both protein variants in which entire domains were deleted and proteins carrying substitutions in the α1-helix. We found that in this enzyme the inter-domain connection dramatically affects the stability of both the whole enzyme and the β-propeller. The α1-helix is required for the stability of the intact protein, as in other enzymes of the same family; however in this psychrophilic enzyme only, it destabilizes the isolated β-propeller. A single charged residue (E10) in the α1-helix plays a major role for the stability of the whole structure. Overall, a strict interaction of the SpAAP domains seems to be mandatory for the preservation of their reciprocal structural integrity and may witness their co-evolution.

Towards rationally redesigning bacterial signaling systems using information encoded in abundant sequence data

NASA Astrophysics Data System (ADS)

Cheng, Ryan; Morcos, Faruck; Levine, Herbert; Onuchic, Jose

2014-03-01

An important challenge in biology is to distinguish the subset of residues that allow bacterial two-component signaling (TCS) proteins to preferentially interact with their correct TCS partner such that they can bind and transfer signal. Detailed knowledge of this information would allow one to search sequence-space for mutations that can systematically tune the signal transmission between TCS partners as well as re-encode a TCS protein to preferentially transfer signals to a non-partner. Motivated by the notion that this detailed information is found in sequence data, we explore the mutual sequence co-evolution between signaling partners to infer how mutations can positively or negatively alter their interaction. Using Direct Coupling Analysis (DCA) for determining evolutionarily conserved interprotein interactions, we apply a DCA-based metric to quantify mutational changes in the interaction between TCS proteins and demonstrate that it accurately correlates with experimental mutagenesis studies probing the mutational change in the in vitro phosphotransfer. Our methodology serves as a potential framework for the rational design of TCS systems as well as a framework for the system-level study of protein-protein interactions in sequence-rich systems. This research has been supported by the NSF INSPIRE award MCB-1241332 and by the CTBP sponsored by the NSF (Grant PHY-1308264).

Structural Phylogenomics Retrodicts the Origin of the Genetic Code and Uncovers the Evolutionary Impact of Protein Flexibility

PubMed Central

Caetano-Anollés, Gustavo; Wang, Minglei; Caetano-Anollés, Derek

2013-01-01

The genetic code shapes the genetic repository. Its origin has puzzled molecular scientists for over half a century and remains a long-standing mystery. Here we show that the origin of the genetic code is tightly coupled to the history of aminoacyl-tRNA synthetase enzymes and their interactions with tRNA. A timeline of evolutionary appearance of protein domain families derived from a structural census in hundreds of genomes reveals the early emergence of the ‘operational’ RNA code and the late implementation of the standard genetic code. The emergence of codon specificities and amino acid charging involved tight coevolution of aminoacyl-tRNA synthetases and tRNA structures as well as episodes of structural recruitment. Remarkably, amino acid and dipeptide compositions of single-domain proteins appearing before the standard code suggest archaic synthetases with structures homologous to catalytic domains of tyrosyl-tRNA and seryl-tRNA synthetases were capable of peptide bond formation and aminoacylation. Results reveal that genetics arose through coevolutionary interactions between polypeptides and nucleic acid cofactors as an exacting mechanism that favored flexibility and folding of the emergent proteins. These enhancements of phenotypic robustness were likely internalized into the emerging genetic system with the early rise of modern protein structure. PMID:23991065

Cryo-EM structure of the spinach chloroplast ribosome reveals the location of plastid-specific ribosomal proteins and extensions

PubMed Central

Graf, Michael; Arenz, Stefan; Huter, Paul; Dönhöfer, Alexandra; Nováček, Jiří

2017-01-01

Abstract Ribosomes are the protein synthesizing machines of the cell. Recent advances in cryo-EM have led to the determination of structures from a variety of species, including bacterial 70S and eukaryotic 80S ribosomes as well as mitoribosomes from eukaryotic mitochondria, however, to date high resolution structures of plastid 70S ribosomes have been lacking. Here we present a cryo-EM structure of the spinach chloroplast 70S ribosome, with an average resolution of 5.4 Å for the small 30S subunit and 3.6 Å for the large 50S ribosomal subunit. The structure reveals the location of the plastid-specific ribosomal proteins (RPs) PSRP1, PSRP4, PSRP5 and PSRP6 as well as the numerous plastid-specific extensions of the RPs. We discover many features by which the plastid-specific extensions stabilize the ribosome via establishing additional interactions with surrounding ribosomal RNA and RPs. Moreover, we identify a large conglomerate of plastid-specific protein mass adjacent to the tunnel exit site that could facilitate interaction of the chloroplast ribosome with the thylakoid membrane and the protein-targeting machinery. Comparing the Escherichia coli 70S ribosome with that of the spinach chloroplast ribosome provides detailed insight into the co-evolution of RP and rRNA. PMID:27986857

Origins of coevolution between residues distant in protein 3D structures

PubMed Central

Ovchinnikov, Sergey; Kamisetty, Hetunandan; Baker, David

2017-01-01

Residue pairs that directly coevolve in protein families are generally close in protein 3D structures. Here we study the exceptions to this general trend—directly coevolving residue pairs that are distant in protein structures—to determine the origins of evolutionary pressure on spatially distant residues and to understand the sources of error in contact-based structure prediction. Over a set of 4,000 protein families, we find that 25% of directly coevolving residue pairs are separated by more than 5 Å in protein structures and 3% by more than 15 Å. The majority (91%) of directly coevolving residue pairs in the 5–15 Å range are found to be in contact in at least one homologous structure—these exceptions arise from structural variation in the family in the region containing the residues. Thirty-five percent of the exceptions greater than 15 Å are at homo-oligomeric interfaces, 19% arise from family structural variation, and 27% are in repeat proteins likely reflecting alignment errors. Of the remaining long-range exceptions (<1% of the total number of coupled pairs), many can be attributed to close interactions in an oligomeric state. Overall, the results suggest that directly coevolving residue pairs not in repeat proteins are spatially proximal in at least one biologically relevant protein conformation within the family; we find little evidence for direct coupling between residues at spatially separated allosteric and functional sites or for increased direct coupling between residue pairs on putative allosteric pathways connecting them. PMID:28784799

Novel Drosophila Viruses Encode Host-Specific Suppressors of RNAi

PubMed Central

van Mierlo, Joël T.; Overheul, Gijs J.; Obadia, Benjamin; van Cleef, Koen W. R.; Webster, Claire L.; Saleh, Maria-Carla; Obbard, Darren J.; van Rij, Ronald P.

2014-01-01

The ongoing conflict between viruses and their hosts can drive the co-evolution between host immune genes and viral suppressors of immunity. It has been suggested that an evolutionary ‘arms race’ may occur between rapidly evolving components of the antiviral RNAi pathway of Drosophila and viral genes that antagonize it. We have recently shown that viral protein 1 (VP1) of Drosophila melanogaster Nora virus (DmelNV) suppresses Argonaute-2 (AGO2)-mediated target RNA cleavage (slicer activity) to antagonize antiviral RNAi. Here we show that viral AGO2 antagonists of divergent Nora-like viruses can have host specific activities. We have identified novel Nora-like viruses in wild-caught populations of D. immigrans (DimmNV) and D. subobscura (DsubNV) that are 36% and 26% divergent from DmelNV at the amino acid level. We show that DimmNV and DsubNV VP1 are unable to suppress RNAi in D. melanogaster S2 cells, whereas DmelNV VP1 potently suppresses RNAi in this host species. Moreover, we show that the RNAi suppressor activity of DimmNV VP1 is restricted to its natural host species, D. immigrans. Specifically, we find that DimmNV VP1 interacts with D. immigrans AGO2, but not with D. melanogaster AGO2, and that it suppresses slicer activity in embryo lysates from D. immigrans, but not in lysates from D. melanogaster. This species-specific interaction is reflected in the ability of DimmNV VP1 to enhance RNA production by a recombinant Sindbis virus in a host-specific manner. Our results emphasize the importance of analyzing viral RNAi suppressor activity in the relevant host species. We suggest that rapid co-evolution between RNA viruses and their hosts may result in host species-specific activities of RNAi suppressor proteins, and therefore that viral RNAi suppressors could be host-specificity factors. PMID:25032815

Coevolution of the ATPase ClpV, the Sheath Proteins TssB and TssC, and the Accessory Protein TagJ/HsiE1 Distinguishes Type VI Secretion Classes*

PubMed Central

Förster, Andreas; Planamente, Sara; Manoli, Eleni; Lossi, Nadine S.; Freemont, Paul S.; Filloux, Alain

2014-01-01

The type VI secretion system (T6SS) is a bacterial nanomachine for the transport of effector molecules into prokaryotic and eukaryotic cells. It involves the assembly of a tubular structure composed of TssB and TssC that is similar to the tail sheath of bacteriophages. The sheath contracts to provide the energy needed for effector delivery. The AAA+ ATPase ClpV disassembles the contracted sheath, which resets the systems for reassembly of an extended sheath that is ready to fire again. This mechanism is crucial for T6SS function. In Vibrio cholerae, ClpV binds the N terminus of TssC within a hydrophobic groove. In this study, we resolved the crystal structure of the N-terminal domain of Pseudomonas aeruginosa ClpV1 and observed structural alterations in the hydrophobic groove. The modification in the ClpV1 groove is matched by a change in the N terminus of TssC, suggesting the existence of distinct T6SS classes. An accessory T6SS component, TagJ/HsiE, exists predominantly in one of the classes. Using bacterial two-hybrid approaches, we showed that the P. aeruginosa homolog HsiE1 interacts strongly with ClpV1. We then resolved the crystal structure of HsiE1 in complex with the N terminus of HsiB1, a TssB homolog and component of the contractile sheath. Phylogenetic analysis confirmed that these differences distinguish T6SS classes that resulted from a functional co-evolution between TssB, TssC, TagJ/HsiE, and ClpV. The interaction of TagJ/HsiE with the sheath as well as with ClpV suggests an alternative mode of disassembly in which HsiE recruits the ATPase to the sheath. PMID:25305017

Development of structural correlations and synchronization from adaptive rewiring in networks of Kuramoto oscillators

NASA Astrophysics Data System (ADS)

Papadopoulos, Lia; Kim, Jason Z.; Kurths, Jürgen; Bassett, Danielle S.

2017-07-01

Synchronization of non-identical oscillators coupled through complex networks is an important example of collective behavior, and it is interesting to ask how the structural organization of network interactions influences this process. Several studies have explored and uncovered optimal topologies for synchronization by making purposeful alterations to a network. On the other hand, the connectivity patterns of many natural systems are often not static, but are rather modulated over time according to their dynamics. However, this co-evolution and the extent to which the dynamics of the individual units can shape the organization of the network itself are less well understood. Here, we study initially randomly connected but locally adaptive networks of Kuramoto oscillators. In particular, the system employs a co-evolutionary rewiring strategy that depends only on the instantaneous, pairwise phase differences of neighboring oscillators, and that conserves the total number of edges, allowing the effects of local reorganization to be isolated. We find that a simple rule—which preserves connections between more out-of-phase oscillators while rewiring connections between more in-phase oscillators—can cause initially disordered networks to organize into more structured topologies that support enhanced synchronization dynamics. We examine how this process unfolds over time, finding a dependence on the intrinsic frequencies of the oscillators, the global coupling, and the network density, in terms of how the adaptive mechanism reorganizes the network and influences the dynamics. Importantly, for large enough coupling and after sufficient adaptation, the resulting networks exhibit interesting characteristics, including degree-frequency and frequency-neighbor frequency correlations. These properties have previously been associated with optimal synchronization or explosive transitions in which the networks were constructed using global information. On the contrary, by considering a time-dependent interplay between structure and dynamics, this work offers a mechanism through which emergent phenomena and organization can arise in complex systems utilizing local rules.

Rapidly evolving zona pellucida domain proteins are a major component of the vitelline envelope of abalone eggs

PubMed Central

Aagaard, Jan E.; Yi, Xianhua; MacCoss, Michael J.; Swanson, Willie J.

2006-01-01

Proteins harboring a zona pellucida (ZP) domain are prominent components of vertebrate egg coats. Although less well characterized, the egg coat of the non-vertebrate marine gastropod abalone (Haliotis spp.) is also known to contain a ZP domain protein, raising the possibility of a common molecular basis of metazoan egg coat structures. Egg coat proteins from vertebrate as well as non-vertebrate taxa have been shown to evolve under positive selection. Studied most extensively in the abalone system, coevolution between adaptively diverging egg coat and sperm proteins may contribute to the rapid development of reproductive isolation. Thus, identifying the pattern of evolution among egg coat proteins is important in understanding the role these genes may play in the speciation process. The purpose of the present study is to characterize the constituent proteins of the egg coat [vitelline envelope (VE)] of abalone eggs and to provide preliminary evidence regarding how selection has acted on VE proteins during abalone evolution. A proteomic approach is used to match tandem mass spectra of peptides from purified VE proteins with abalone ovary EST sequences, identifying 9 of 10 ZP domain proteins as components of the VE. Maximum likelihood models of codon evolution suggest positive selection has acted among a subset of amino acids for 6 of these genes. This work provides further evidence of the prominence of ZP proteins as constituents of the egg coat, as well as the prominent role of positive selection in diversification of these reproductive proteins. PMID:17085584

Characterization of essential proteins based on network topology in proteins interaction networks

NASA Astrophysics Data System (ADS)

Bakar, Sakhinah Abu; Taheri, Javid; Zomaya, Albert Y.

2014-06-01

The identification of essential proteins is theoretically and practically important as (1) it is essential to understand the minimal surviving requirements for cellular lives, and (2) it provides fundamental for development of drug. As conducting experimental studies to identify essential proteins are both time and resource consuming, here we present a computational approach in predicting them based on network topology properties from protein-protein interaction networks of Saccharomyces cerevisiae. The proposed method, namely EP3NN (Essential Proteins Prediction using Probabilistic Neural Network) employed a machine learning algorithm called Probabilistic Neural Network as a classifier to identify essential proteins of the organism of interest; it uses degree centrality, closeness centrality, local assortativity and local clustering coefficient of each protein in the network for such predictions. Results show that EP3NN managed to successfully predict essential proteins with an accuracy of 95% for our studied organism. Results also show that most of the essential proteins are close to other proteins, have assortativity behavior and form clusters/sub-graph in the network.

Dynamical trade-offs arise from antagonistic coevolution and decrease intraspecific diversity.

PubMed

Huang, Weini; Traulsen, Arne; Werner, Benjamin; Hiltunen, Teppo; Becks, Lutz

2017-12-12

Trade-offs play an important role in evolution. Without trade-offs, evolution would maximize fitness of all traits leading to a "master of all traits". The shape of trade-offs has been shown to determine evolutionary trajectories and is often assumed to be static and independent of the actual evolutionary process. Here we propose that coevolution leads to a dynamical trade-off. We test this hypothesis in a microbial predator-prey system and show that the bacterial growth-defense trade-off changes from concave to convex, i.e., defense is effective and cheap initially, but gets costly when predators coevolve. We further explore the impact of such dynamical trade-offs by a novel mathematical model incorporating de novo mutations for both species. Predator and prey populations diversify rapidly leading to higher prey diversity when the trade-off is concave (cheap). Coevolution results in more convex (costly) trade-offs and lower prey diversity compared to the scenario where only the prey evolves.

Co-evolution of upstream waves and accelerated ions at parallel shocks

NASA Astrophysics Data System (ADS)

Fujimoto, M.; Sugiyama, T.

2016-12-01

Shock waves in space plasmas have been considered as the agents for various particle acceleration phenomena. The basic idea behind shock acceleration is that particles are accelerated as they move back-and-forth across a shock front. Detailed studies of ion acceleration at the terrestrial bow shock have been performed, however, the restricted maximum energies attained prevent a straight-forward application of obtained knowledge to more energetic astrophysical situations. Here we show by a large-scale self-consistent particle simulation that the co-evolution of magnetic turbulence and accelerated ion population is the foundation for continuous operation of shock acceleration to ever higher energies. Magnetic turbulence is created by ions reflected back upstream of a parallel shock front. The co-evolution arises because more energetic ions excite waves of longer wavelengths, and because longer wavelength modes are capable of scattering (in the upstream) and reflecting (at the shock front) more energetic ions. Via carefully designed numerical experiments, we show very clearly that this picture is true.

Parallel arms races between garter snakes and newts involving tetrodotoxin as the phenotypic interface of coevolution.

PubMed

Brodie, Edmund D; Feldman, Chris R; Hanifin, Charles T; Motychak, Jeffrey E; Mulcahy, Daniel G; Williams, Becky L; Brodie, Edmund D

2005-02-01

Parallel "arms races" involving the same or similar phenotypic interfaces allow inference about selective forces driving coevolution, as well as the importance of phylogenetic and phenotypic constraints in coevolution. Here, we report the existence of apparent parallel arms races between species pairs of garter snakes and their toxic newt prey that indicate independent evolutionary origins of a key phenotype in the interface. In at least one area of sympatry, the aquatic garter snake, Thamnophis couchii, has evolved elevated resistance to the neurotoxin tetrodotoxin (TTX), present in the newt Taricha torosa. Previous studies have shown that a distantly related garter snake, Thamnophis sirtalis, has coevolved with another newt species that possesses TTX, Taricha granulosa. Patterns of within population variation and phenotypic tradeoffs between TTX resistance and sprint speed suggest that the mechanism of resistance is similar in both species of snake, yet phylogenetic evidence indicates the independent origins of elevated resistance to TTX.

Sex uncovered special issue: The ecology of sexual reproduction

PubMed Central

LIVELY, C. M.; MORRAN, L. T.

2014-01-01

Sexual reproduction is widely regarded as one of the major unexplained phenomena in biology. Nonetheless, while a general answer may remain elusive, considerable progress has been made in the last few decades. Here we fist review the genesis of, and support for, the major ecological hypotheses for biparental sexual reproduction. We then focus on the idea that host-parasite coevolution can favor cross fertilization over uniparental forms of reproduction, as this hypothesis currently has the most support from natural populations. We also review the results from experimental evolution studies, which tend to show that exposure to novel environments can select for higher levels of sexual reproduction, but that sex decreases in frequency after populations become adapted to the previously novel conditions. In contrast, experimental coevolution studies suggest that host-parasite interactions can lead to the long-term persistence of sex. Taken together, the evidence from natural populations and from laboratory experiments point to antagonistic coevolution as a potent and possibly ubiquitous force of selection favoring cross-fertilization and recombination. PMID:24617324

A Strategy Based on Protein-Protein Interface Motifs May Help in Identifying Drug Off-Targets

PubMed Central

Engin, H. Billur; Keskin, Ozlem; Nussinov, Ruth; Gursoy, Attila

2014-01-01

Networks are increasingly used to study the impact of drugs at the systems level. From the algorithmic standpoint, a drug can ‘attack’ nodes or edges of a protein-protein interaction network. In this work, we propose a new network strategy, “The Interface Attack”, based on protein-protein interfaces. Similar interface architectures can occur between unrelated proteins. Consequently, in principle, a drug that binds to one has a certain probability of binding others. The interface attack strategy simultaneously removes from the network all interactions that consist of similar interface motifs. This strategy is inspired by network pharmacology and allows inferring potential off-targets. We introduce a network model which we call “Protein Interface and Interaction Network (P2IN)”, which is the integration of protein-protein interface structures and protein interaction networks. This interface-based network organization clarifies which protein pairs have structurally similar interfaces, and which proteins may compete to bind the same surface region. We built the P2IN of p53 signaling network and performed network robustness analysis. We show that (1) ‘hitting’ frequent interfaces (a set of edges distributed around the network) might be as destructive as eleminating high degree proteins (hub nodes); (2) frequent interfaces are not always topologically critical elements in the network; and (3) interface attack may reveal functional changes in the system better than attack of single proteins. In the off-target detection case study, we found that drugs blocking the interface between CDK6 and CDKN2D may also affect the interaction between CDK4 and CDKN2D. PMID:22817115

Coevolution of the Toll-Like Receptor 4 Complex with Calgranulins and Lipopolysaccharide

PubMed Central

Loes, Andrea N.; Bridgham, Jamie T.; Harms, Michael J.

2018-01-01

Toll-like receptor 4 (TLR4) induces inflammation in response to both pathogen- and host-derived molecules. Lipopolysaccharide (LPS) recognition by TLR4 has been shown to occur across the amniotes, but endogenous signaling through TLR4 has not been validated outside of placental mammals. To determine whether endogenous danger signaling is also shared across amniotes, we studied the evolution of TLR4-activation by the calgranulin proteins (S100A8, S100A9, and S100A12), a clade of host molecules that potently activate TLR4 in placental mammals. We performed phylogenetic and syntenic analysis and found MRP-126—a gene in birds and reptiles—is likely orthologous to the mammalian calgranulins. We then used an ex vivo TLR4 activation assay to establish that calgranulin pro-inflammatory activity is not specific to placental mammals, but is also exhibited by representative marsupial and sauropsid species. This activity is strongly dependent on the cofactors CD14 and MD-2 for all species studied, suggesting a conserved mode of activation across the amniotes. Ortholog complementation experiments between the calgranulins, TLR4, CD14, and MD-2 revealed extensive lineage specific-coevolution and multi-way interactions between components that are necessary for the activation of NF-κB signaling by calgranulins and LPS. Our work demonstrates that calgranulin activation of TLR4 evolved at least ~320 million years ago and has been conserved in the amniote innate immune system. PMID:29515592

Interspecific studies of circadian genes period and timeless in Drosophila.

PubMed

Noreen, Shumaila; Pegoraro, Mirko; Nouroz, Faisal; Tauber, Eran; Kyriacou, Charalambos P

2018-03-30

The level of rescue of clock function in genetically arrhythmic Drosophila melanogaster hosts using interspecific clock gene transformation was used to study the putative intermolecular coevolution between interacting clock proteins. Among them PER and TIM are the two important negative regulators of the circadian clock feedback loop. We transformed either the D. pseudoobscura per or tim transgenes into the corresponding arrhythmic D. melanogaster mutant (per01 or tim01) and observed >50% rhythmicity but the period of activity rhythm was either longer (D. pseudoobscura-per) or shorter than 24 h (D. pseudoobscura-tim) compared to controls. By introducing both transgenes simultaneously into double mutants, we observed that the period of the activity rhythm was rescued by the pair of hemizygous transgenes (~24 h). These flies also showed a more optimal level of temperature compensation for the period. Under LD 12:12 these flies have a D. pseudoobscura like activity profile with the absence of morning anticipation as well as a very prominent earlier evening peak of activity rhythm. These observation are consistent with the view that TIM and PER form a heterospecific coevolved module at least for the circadian period of activity rhythms. However the strength of rhythmicity was reduced by having both transgenes present, so while evidence for a coevolution between PER and TIM is observed for some characters it is not for others. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Inference, simulation, modeling, and analysis of complex networks, with special emphasis on complex networks in systems biology

NASA Astrophysics Data System (ADS)

Christensen, Claire Petra

Across diverse fields ranging from physics to biology, sociology, and economics, the technological advances of the past decade have engendered an unprecedented explosion of data on highly complex systems with thousands, if not millions of interacting components. These systems exist at many scales of size and complexity, and it is becoming ever-more apparent that they are, in fact, universal, arising in every field of study. Moreover, they share fundamental properties---chief among these, that the individual interactions of their constituent parts may be well-understood, but the characteristic behaviour produced by the confluence of these interactions---by these complex networks---is unpredictable; in a nutshell, the whole is more than the sum of its parts. There is, perhaps, no better illustration of this concept than the discoveries being made regarding complex networks in the biological sciences. In particular, though the sequencing of the human genome in 2003 was a remarkable feat, scientists understand that the "cellular-level blueprints" for the human being are cellular-level parts lists, but they say nothing (explicitly) about cellular-level processes. The challenge of modern molecular biology is to understand these processes in terms of the networks of parts---in terms of the interactions among proteins, enzymes, genes, and metabolites---as it is these processes that ultimately differentiate animate from inanimate, giving rise to life! It is the goal of systems biology---an umbrella field encapsulating everything from molecular biology to epidemiology in social systems---to understand processes in terms of fundamental networks of core biological parts, be they proteins or people. By virtue of the fact that there are literally countless complex systems, not to mention tools and techniques used to infer, simulate, analyze, and model these systems, it is impossible to give a truly comprehensive account of the history and study of complex systems. The author's own publications have contributed network inference, simulation, modeling, and analysis methods to the much larger body of work in systems biology, and indeed, in network science. The aim of this thesis is therefore twofold: to present this original work in the historical context of network science, but also to provide sufficient review and reference regarding complex systems (with an emphasis on complex networks in systems biology) and tools and techniques for their inference, simulation, analysis, and modeling, such that the reader will be comfortable in seeking out further information on the subject. The review-like Chapters 1, 2, and 4 are intended to convey the co-evolution of network science and the slow but noticeable breakdown of boundaries between disciplines in academia as research and comparison of diverse systems has brought to light the shared properties of these systems. It is the author's hope that theses chapters impart some sense of the remarkable and rapid progress in complex systems research that has led to this unprecedented academic synergy. Chapters 3 and 5 detail the author's original work in the context of complex systems research. Chapter 3 presents the methods and results of a two-stage modeling process that generates candidate gene-regulatory networks of the bacterium B.subtilis from experimentally obtained, yet mathematically underdetermined microchip array data. These networks are then analyzed from a graph theoretical perspective, and their biological viability is critiqued by comparing the networks' graph theoretical properties to those of other biological systems. The results of topological perturbation analyses revealing commonalities in behavior at multiple levels of complexity are also presented, and are shown to be an invaluable means by which to ascertain the level of complexity to which the network inference process is robust to noise. Chapter 5 outlines a learning algorithm for the development of a realistic, evolving social network (a city) into which a disease is introduced. The results of simulations in populations spanning two orders of magnitude are compared to prevaccine era measles data for England and Wales and demonstrate that the simulations are able to capture the quantitative and qualitative features of epidemics in populations as small as 10,000 people. The work presented in Chapter 5 validates the utility of network simulation in concurrently probing contact network dynamics and disease dynamics.

SigFlux: a novel network feature to evaluate the importance of proteins in signal transduction networks.

PubMed

Liu, Wei; Li, Dong; Zhang, Jiyang; Zhu, Yunping; He, Fuchu

2006-11-27

Measuring each protein's importance in signaling networks helps to identify the crucial proteins in a cellular process, find the fragile portion of the biology system and further assist for disease therapy. However, there are relatively few methods to evaluate the importance of proteins in signaling networks. We developed a novel network feature to evaluate the importance of proteins in signal transduction networks, that we call SigFlux, based on the concept of minimal path sets (MPSs). An MPS is a minimal set of nodes that can perform the signal propagation from ligands to target genes or feedback loops. We define SigFlux as the number of MPSs in which each protein is involved. We applied this network feature to the large signal transduction network in the hippocampal CA1 neuron of mice. Significant correlations were simultaneously observed between SigFlux and both the essentiality and evolutionary rate of genes. Compared with another commonly used network feature, connectivity, SigFlux has similar or better ability as connectivity to reflect a protein's essentiality. Further classification according to protein function demonstrates that high SigFlux, low connectivity proteins are abundant in receptors and transcriptional factors, indicating that SigFlux candescribe the importance of proteins within the context of the entire network. SigFlux is a useful network feature in signal transduction networks that allows the prediction of the essentiality and conservation of proteins. With this novel network feature, proteins that participate in more pathways or feedback loops within a signaling network are proved far more likely to be essential and conserved during evolution than their counterparts.

Contrasting effects of intralocus sexual conflict on sexually antagonistic coevolution

PubMed Central

Pennell, Tanya M.; de Haas, Freek J. H.; Morrow, Edward H.; van Doorn, G. Sander

2016-01-01

Evolutionary conflict between the sexes can induce arms races in which males evolve traits that are detrimental to the fitness of their female partners, and vice versa. This interlocus sexual conflict (IRSC) has been proposed as a cause of perpetual intersexual antagonistic coevolution with wide-ranging evolutionary consequences. However, theory suggests that the scope for perpetual coevolution is limited, if traits involved in IRSC are subject to pleiotropic constraints. Here, we consider a biologically plausible form of pleiotropy that has hitherto been ignored in treatments of IRSC and arrive at drastically different conclusions. Our analysis is based on a quantitative genetic model of sexual conflict, in which genes controlling IRSC traits have side effects in the other sex, due to incompletely sex-limited gene expression. As a result, the genes are exposed to intralocus sexual conflict (IASC), a tug-of-war between opposing male- and female-specific selection pressures. We find that the interaction between the two forms of sexual conflict has contrasting effects on antagonistic coevolution: Pleiotropic constraints stabilize the dynamics of arms races if the mating traits are close to evolutionary equilibrium but can prevent populations from ever reaching such a state. Instead, the sexes are drawn into a continuous cycle of arms races, causing the buildup of IASC, alternated by phases of IASC resolution that trigger the next arms race. These results encourage an integrative perspective on the biology of sexual conflict and generally caution against relying exclusively on equilibrium stability analysis. PMID:26755609

Secretome Analysis of the Pine Wood Nematode Bursaphelenchus xylophilus Reveals the Tangled Roots of Parasitism and Its Potential for Molecular Mimicry.

PubMed

Shinya, Ryoji; Morisaka, Hironobu; Kikuchi, Taisei; Takeuchi, Yuko; Ueda, Mitsuyoshi; Futai, Kazuyoshi

2013-01-01

Since it was first introduced into Asia from North America in the early 20(th) century, the pine wood nematode Bursaphelenchus xylophilus has caused the devastating forest disease called pine wilt. The emerging pathogen spread to parts of Europe and has since been found as the causal agent of pine wilt disease in Portugal and Spain. In 2011, the entire genome sequence of B. xylophilus was determined, and it allowed us to perform a more detailed analysis of B. xylophilus parasitism. Here, we identified 1,515 proteins secreted by B. xylophilus using a highly sensitive proteomics method combined with the available genomic sequence. The catalogue of secreted proteins contained proteins involved in nutrient uptake, migration, and evasion from host defenses. A comparative functional analysis of the secretome profiles among parasitic nematodes revealed a marked expansion of secreted peptidases and peptidase inhibitors in B. xylophilus via gene duplication and horizontal gene transfer from fungi and bacteria. Furthermore, we showed that B. xylophilus secreted the potential host mimicry proteins that closely resemble the host pine's proteins. These proteins could have been acquired by host-parasite co-evolution and might mimic the host defense systems in susceptible pine trees during infection. This study contributes to an understanding of their unique parasitism and its tangled roots, and provides new perspectives on the evolution of plant parasitism among nematodes.

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

Construction of ontology augmented networks for protein complex prediction.

PubMed

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

2013-01-01

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks.

PubMed

Lin, Wen-Hsien; Liu, Wei-Chung; Hwang, Ming-Jing

2009-03-11

Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene-encoded proteins are attached to the core at more peripheral positions of the networks.

Evolution of olfactory receptor in oriental fruit fly Dacus dorsalis

PubMed Central

Metcalf, Robert L.; Metcalf, Esther R.; Mitchell, W. C.; Lee, Lena W. Y.

1979-01-01

Male oriental fruit flies (Dacus dorsalis) from colonies in Taiwan and Hawaii were evaluated for limit of response to various analogues of methyl eugenol. The results are interpreted in terms of the geometry and allosteric requirements of the antennal receptor that triggers the characteristic methyl eugenol reflex. This receptor has evolved for complementarity to all portions of the methyl eugenol molecule and responds only to ortho-substituted benzenes with adjacent oxygen atoms or isoelectronic equivalents. Substantial differences in responses of Taiwan and Hawaiian D. dorsalis suggest that perceptible evolution of the receptor protein has occurred during the past 50 years. A plausible scheme for the coevolution of dacini flies with plants containing phenylpropionoid essential oils is outlined. Images PMID:16592640

Viral evasion of intracellular DNA and RNA sensing

PubMed Central

Chan, Ying Kai; Gack, Michaela U.

2016-01-01

The co-evolution of viruses with their hosts has led to the emergence of viral pathogens that are adept at evading or actively suppressing host immunity. Pattern recognition receptors (PRRs) are key components of antiviral immunity that detect conserved molecular features of viral pathogens and initiate signalling that results in the expression of antiviral genes. In this Review, we discuss the strategies that viruses use to escape immune surveillance by key intracellular sensors of viral RNA or DNA, with a focus on RIG-I-like receptors (RLRs), cyclic GMP–AMP synthase (cGAS) and interferon-γ (IFNγ)-inducible protein 16 (IFI16). Such viral strategies include the sequestration or modification of viral nucleic acids, interference with specific post-translational modifications of PRRs or their adaptor proteins, the degradation or cleavage of PRRs or their adaptors, and the sequestration or relocalization of PRRs. An understanding of viral immune-evasion mechanisms at the molecular level may guide the development of vaccines and antivirals. PMID:27174148

Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family

PubMed Central

Uhart, Marina; Flores, Gabriel; Bustos, Diego M.

2016-01-01

Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems. PMID:27195976

How Many Protein Sequences Fold to a Given Structure? A Coevolutionary Analysis.

PubMed

Tian, Pengfei; Best, Robert B

2017-10-17

Quantifying the relationship between protein sequence and structure is key to understanding the protein universe. A fundamental measure of this relationship is the total number of amino acid sequences that can fold to a target protein structure, known as the "sequence capacity," which has been suggested as a proxy for how designable a given protein fold is. Although sequence capacity has been extensively studied using lattice models and theory, numerical estimates for real protein structures are currently lacking. In this work, we have quantitatively estimated the sequence capacity of 10 proteins with a variety of different structures using a statistical model based on residue-residue co-evolution to capture the variation of sequences from the same protein family. Remarkably, we find that even for the smallest protein folds, such as the WW domain, the number of foldable sequences is extremely large, exceeding the Avogadro constant. In agreement with earlier theoretical work, the calculated sequence capacity is positively correlated with the size of the protein, or better, the density of contacts. This allows the absolute sequence capacity of a given protein to be approximately predicted from its structure. On the other hand, the relative sequence capacity, i.e., normalized by the total number of possible sequences, is an extremely tiny number and is strongly anti-correlated with the protein length. Thus, although there may be more foldable sequences for larger proteins, it will be much harder to find them. Lastly, we have correlated the evolutionary age of proteins in the CATH database with their sequence capacity as predicted by our model. The results suggest a trade-off between the opposing requirements of high designability and the likelihood of a novel fold emerging by chance. Published by Elsevier Inc.

Predicting disease-related proteins based on clique backbone in protein-protein interaction network.

PubMed

Yang, Lei; Zhao, Xudong; Tang, Xianglong

2014-01-01

Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.

Network-based study reveals potential infection pathways of hepatitis-C leading to various diseases.

PubMed

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement.

Network-Based Study Reveals Potential Infection Pathways of Hepatitis-C Leading to Various Diseases

PubMed Central

Mukhopadhyay, Anirban; Maulik, Ujjwal

2014-01-01

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement. PMID:24743187

Political opinion formation: Initial opinion distribution and individual heterogeneity of tolerance

NASA Astrophysics Data System (ADS)

Jin, Cheng; Li, Yifu; Jin, Xiaogang

2017-02-01

Opinion dynamics on networks have received serious attention for its profound prospects in social behaviours and self-organized systems. However, political opinion formation, as one typical and significant case, remains lacking in discussion. Previous agent-based simulations propose various models that are based on different mechanisms like the coevolution between network topology and status transition. Nonetheless, even under the same network topology and with the same simple mechanism, forming opinions can still be uncertain. In this work, we propose two features, the initial distribution of opinions and the individual heterogeneity of tolerances on opinion changing, in political opinion formation. These two features are imbedded in the network construction phase of a classical model. By comparing multi simple-party systems, along with a detailed analysis on the two-party system, we capture the critical phenomenon of fragmentation, polarization and consensus both in the persistent stable stage and in-process. We further introduce the average ratio of nearest neighbours to characterize the stage of opinion formation. The results show that the initial distribution of opinions leads to different evolution results on similar random networks. In addition, the existence of stubborn nodes plays a special role: only nodes that are extremely stubborn can cause the change of final opinion distribution while in other cases they only delay the time to reach stability. If stubborn nodes are small in number, their effects are confined within a small range. This theoretical work goes deeper on an existing model, it is an early exploration on qualitative and quantitative simulation of party competition.

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network.

PubMed

Mistry, Divya; Wise, Roger P; Dickerson, Julie A

2017-01-01

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures helped identify critical genes and proteins in biomolecular networks. The proposed centrality measure, DiffSLC, combines the number of interactions of a protein and the gene coexpression values of genes from which those proteins were translated, as a weighting factor to bias the identification of essential proteins in a protein interaction network. Potentially essential proteins with low node degree are promoted through eigenvector centrality. Thus, the gene coexpression values are used in conjunction with the eigenvector of the network's adjacency matrix and edge clustering coefficient to improve essentiality prediction. The outcome of this prediction is shown using three variations: (1) inclusion or exclusion of gene co-expression data, (2) impact of different coexpression measures, and (3) impact of different gene expression data sets. For a total of seven networks, DiffSLC is compared to other centrality measures using Saccharomyces cerevisiae protein interaction networks and gene expression data. Comparisons are also performed for the top ranked proteins against the known essential genes from the Saccharomyces Gene Deletion Project, which show that DiffSLC detects more essential proteins and has a higher area under the ROC curve than other compared methods. This makes DiffSLC a stronger alternative to other centrality methods for detecting essential genes using a protein-protein interaction network that obeys centrality-lethality principle. DiffSLC is implemented using the igraph package in R, and networkx package in Python. The python package can be obtained from git.io/diffslcpy. The R implementation and code to reproduce the analysis is available via git.io/diffslc.

DiffSLc: A graph centrality method to detect essential proteins of a protein-protein interaction network

USDA-ARS?s Scientific Manuscript database

Network centrality measures prioritize nodes and edges based on their importance to the network topology. These measures have been helpful in identifying critical genes and proteins in biomolecular networks. The proposed centrality measure DiffSLc uses the number of interactions of a protein and gen...

On Budyko curve as a consequence of climate-soil-vegetation equilibrium hypothesis

NASA Astrophysics Data System (ADS)

Pande, S.

2012-04-01

A hypothesis that Budyko curve is a consequence of stable equilibriums of climate-soil-vegetation co-evolution is tested at biome scale. We assume that i) distribution of vegetation, soil and climate within a biome is a distribution of equilibriums of similar soil-vegetation dynamics and that this dynamics is different across different biomes and ii) soil and vegetation are in dynamic equilibrium with climate while in static equilibrium with each other. In order to test the hypothesis, a two stage regression is considered using MOPEX/Hydrologic Synthesis Project dataset for basins in eastern United States. In the first stage, multivariate regression (Seemingly Unrelated Regression) is performed for each biome with soil (estimated porosity and slope of soil water retention curve) and vegetation characteristics (5-week NDVI gradient) as dependent variables and aridity index, vegetation and soil characteristics as independent variables for respective dependent variables. The regression residuals of the first stage along with aridity index then serve as second stage independent variables while actual vaporization to precipitation ratio (vapor index) serving as dependent variable. Insignificance, if revealed, of a first stage parameter allows us to reject the role of corresponding soil or vegetation characteristics in the co-evolution hypothesis. Meanwhile the significance of second stage regression parameter corresponding to a first stage residual allow us to reject the hypothesis that Budyko curve is a locus "solely" of climate-soil-vegetation co-evolution equilibrium points. Results suggest lack of evidence for soil-vegetation co-evolution in Prairies and Mixed/SouthEast Forests (unlike in Deciduous Forests) though climate plays a dominant role in explaining within biome soil and vegetation characteristics across all the biomes. Preliminary results indicate absence of effects beyond climate-soil-vegetation co-evolution in explaining the ratio of annual total minimum monthly flows to precipitation in Deciduous Forests though other three biome types show presence of effects beyond co-evolutionary. Such an analysis can yield insights into the nature of hydrologic change when assessed along the Budyko curve as well as non co-evolutionary effects such as anthropogenic effects on basin scale annual water balances.

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

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.

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.

FreeContact: fast and free software for protein contact prediction from residue co-evolution.

PubMed

Kaján, László; Hopf, Thomas A; Kalaš, Matúš; Marks, Debora S; Rost, Burkhard

2014-03-26

20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions of protein three-dimensional structure. The method EVfold broke new ground using mean-field Direct Coupling Analysis (EVfold-mfDCA); the method PSICOV applied a related concept by estimating a sparse inverse covariance matrix. Both methods (EVfold-mfDCA and PSICOV) are publicly available, but both require too much CPU time for interactive applications. On top, EVfold-mfDCA depends on proprietary software. Here, we present FreeContact, a fast, open source implementation of EVfold-mfDCA and PSICOV. On a test set of 140 proteins, FreeContact was almost eight times faster than PSICOV without decreasing prediction performance. The EVfold-mfDCA implementation of FreeContact was over 220 times faster than PSICOV with negligible performance decrease. EVfold-mfDCA was unavailable for testing due to its dependency on proprietary software. FreeContact is implemented as the free C++ library "libfreecontact", complete with command line tool "freecontact", as well as Perl and Python modules. All components are available as Debian packages. FreeContact supports the BioXSD format for interoperability. FreeContact provides the opportunity to compute reliable contact predictions in any environment (desktop or cloud).

Endophytic Epichloë species and their grass hosts: from evolution to applications.

PubMed

Saikkonen, Kari; Young, Carolyn A; Helander, Marjo; Schardl, Christopher L

2016-04-01

The closely linked fitness of the Epichloë symbiont and the host grass is presumed to align the coevolution of the species towards specialization and mutually beneficial cooperation. Ecological observations demonstrating that Epichloë-grass symbioses can modulate grassland ecosystems via both above- and belowground ecosystem processes support this. In many cases the detected ecological importance of Epichloë species is directly or indirectly linked to defensive mutualism attributable to alkaloids of fungal-origin. Now, modern genetic and molecular techniques enable the precise studies on evolutionary origin of endophytic Epichloë species, their coevolution with host grasses and identification the genetic variation that explains phenotypic diversity in ecologically relevant characteristics of Epichloë-grass associations. Here we briefly review the most recent findings in these areas of research using the present knowledge of the genetic variation that explains the biosynthetic pathways driving the diversity of alkaloids produced by the endophyte. These findings underscore the importance of genetic interplay between the fungus and the host in shaping their coevolution and ecological role in both natural grass ecosystems, and in the agricultural arena.

Within-host co-evolution of chronic viruses and the adaptive immune system

NASA Astrophysics Data System (ADS)

Nourmohammad, Armita

We normally think of evolution occurring in a population of organisms, in response to their external environment. Rapid evolution of cellular populations also occurs within our bodies, as the adaptive immune system works to eliminate infection. Some pathogens, such as HIV, are able to persist in a host for extended periods of time, during which they also evolve to evade the immune response. In this talk I will introduce an analytical framework for the rapid co-evolution of B-cell and viral populations, based on the molecular interactions between them. Since the co-evolution of antibodies and viruses is perpetually out of equilibrium, I will show how to quantify the amount of adaptation in each of the two populations by analysis of their co-evolutionary history. I will discuss the consequences of competition between lineages of antibodies, and characterize the fate of a given lineage dependent on the state of the antibody and viral populations. In particular, I will discuss the conditions for emergence of highly potent broadly neutralizing antibodies, which are now recognized as critical for designing an effective vaccine against HIV.

Cooperation enhanced by the coevolution of teaching activity in evolutionary prisoner's dilemma games with voluntary participation.

PubMed

Shen, Chen; Chu, Chen; Geng, Yini; Jin, Jiahua; Chen, Fei; Shi, Lei

2018-01-01

Voluntary participation, as an additional strategy involved in repeated games, has been proved to be an efficient way to promote the evolution of cooperation theoretically and empirically. Besides, current studies show that the coevolution of teaching activity can promote cooperation. Thus, inspired by aforementioned above, we investigate the effect of coevolution of teaching activity on the evolution of cooperation for prisoner's dilemma game with voluntary participation: when the focal player successfully enforces its strategy on the opponent, his teaching ability will get an increase. Through numerical simulation, we have shown that voluntary participation could effectively promote the fraction of cooperation, which is also affected by the value of increment. Furthermore, we investigate the influence of the increment value on the density of different strategies and find that there exists an optimal increment value that plays an utmost role on the evolutionary dynamics. With regard to this observation, we unveil that an optimal value of increment can lead to strongest heterogeneity in agents' teaching ability, further promoting the evolution of cooperation.

Divergence in an obligate mutualism is not explained by divergent climatic factors

USGS Publications Warehouse

Godsoe, W.; Strand, Espen; Smith, C.I.; Yoder, J.B.; Esque, T.C.; Pellmyr, O.

2009-01-01

Adaptation to divergent environments creates and maintains biological diversity, but we know little about the importance of different agents of ecological divergence. Coevolution in obligate mutualisms has been hypothesized to drive divergence, but this contention has rarely been tested against alternative ecological explanations. Here, we use a well-established example of coevolution in an obligate pollination mutualism, Yucca brevifolia and its two pollinating yucca moths, to test the hypothesis that divergence in this system is the result of mutualists adapting to different abiotic environments as opposed to coevolution between mutualists. ??? We used a combination of principal component analyses and ecological niche modeling to determine whether varieties of Y. brevifolia associated with different pollinators specialize on different environments. ??? Yucca brevifolia occupies a diverse range of climates. When the two varieties can disperse to similar environments, they occupy similar habitats. ??? This suggests that the two varieties have not specialized on distinct habitats. In turn, this suggests that nonclimatic factors, such as the biotic interaction between Y. brevifolia and its pollinators, are responsible for evolutionary divergence in this system. ?? New Phytologist (2009).

Recognition of RNA Editing Sites Is Directed by Unique Proteins in Chloroplasts: Biochemical Identification of cis-Acting Elements and trans-Acting Factors Involved in RNA Editing in Tobacco and Pea Chloroplasts

PubMed Central

Miyamoto, Tetsuya; Obokata, Junichi; Sugiura, Masahiro

2002-01-01

RNA editing in higher-plant chloroplasts involves C-to-U conversions at specific sites. Although in vivo analyses have been performed, little is known about the biochemical aspects of chloroplast editing reactions. Here we improved our original in vitro system and devised a procedure for preparing active chloroplast extracts not only from tobacco plants but also from pea plants. Using our tobacco in vitro system, cis-acting elements were defined for psbE and petB mRNAs. Distinct proteins were found to bind specifically to each cis-element, a 56-kDa protein to the psbE site and a 70-kDa species to the petB site. Pea chloroplasts lack the corresponding editing site in psbE since T is already present in the DNA. Parallel in vitro analyses with tobacco and pea extracts revealed that the pea plant has no editing activity for psbE mRNAs and lacks the 56-kDa protein, whereas petB mRNAs are edited and the 70-kDa protein is also present. Therefore, coevolution of an editing site and its cognate trans-factor was demonstrated biochemically in psbE mRNA editing between tobacco and pea plants. PMID:12215530

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.

Modeling and simulating networks of interdependent protein interactions.

PubMed

Stöcker, Bianca K; Köster, Johannes; Zamir, Eli; Rahmann, Sven

2018-05-21

Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of these systems emerge not only from the protein interactions themselves but also from the dependencies between these interactions, as generated by allosteric effects or mutual exclusion due to steric hindrance. Therefore, formal models for integrating and utilizing information about interaction dependencies are of high interest. Here, we describe an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining constrained protein interaction networks ("constrained networks"). The construction of these networks is based on public interaction databases as well as text-mined information about interaction dependencies. We present an efficient data structure and algorithm to simulate protein complex formation in constrained networks. The efficiency of the model allows fast simulation and facilitates the analysis of many proteins in large networks. In addition, this approach enables the simulation of perturbation effects, such as knockout of single or multiple proteins and changes of protein concentrations. We illustrate how our model can be used to analyze a constrained human adhesome protein network, which is responsible for the formation of diverse and dynamic cell-matrix adhesion sites. By comparing protein complex formation under known interaction dependencies versus without dependencies, we investigate how these dependencies shape the resulting repertoire of protein complexes. Furthermore, our model enables investigating how the interplay of network topology with interaction dependencies influences the propagation of perturbation effects across a large biochemical system. Our simulation software CPINSim (for Constrained Protein Interaction Network Simulator) is available under the MIT license at http://github.com/BiancaStoecker/cpinsim and as a Bioconda package (https://bioconda.github.io).

Secretome Analysis of the Pine Wood Nematode Bursaphelenchus xylophilus Reveals the Tangled Roots of Parasitism and Its Potential for Molecular Mimicry

PubMed Central

Shinya, Ryoji; Takeuchi, Yuko; Ueda, Mitsuyoshi; Futai, Kazuyoshi

2013-01-01

Since it was first introduced into Asia from North America in the early 20th century, the pine wood nematode Bursaphelenchus xylophilus has caused the devastating forest disease called pine wilt. The emerging pathogen spread to parts of Europe and has since been found as the causal agent of pine wilt disease in Portugal and Spain. In 2011, the entire genome sequence of B. xylophilus was determined, and it allowed us to perform a more detailed analysis of B. xylophilus parasitism. Here, we identified 1,515 proteins secreted by B. xylophilus using a highly sensitive proteomics method combined with the available genomic sequence. The catalogue of secreted proteins contained proteins involved in nutrient uptake, migration, and evasion from host defenses. A comparative functional analysis of the secretome profiles among parasitic nematodes revealed a marked expansion of secreted peptidases and peptidase inhibitors in B. xylophilus via gene duplication and horizontal gene transfer from fungi and bacteria. Furthermore, we showed that B. xylophilus secreted the potential host mimicry proteins that closely resemble the host pine’s proteins. These proteins could have been acquired by host–parasite co-evolution and might mimic the host defense systems in susceptible pine trees during infection. This study contributes to an understanding of their unique parasitism and its tangled roots, and provides new perspectives on the evolution of plant parasitism among nematodes. PMID:23805310

LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris

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

Zhang, Weiwen; Culley, David E.; Gritsenko, Marina A.

2006-11-03

ABSTRACT In the previous study, the whole-genome gene expression profiles of D. vulgaris in response to oxidative stress and heat shock were determined. The results showed 24-28% of the responsive genes were hypothetical proteins that have not been experimentally characterized or whose function can not be deduced by simple sequence comparison. To further explore the protecting mechanisms employed in D. vulgaris against the oxidative stress and heat shock, attempt was made in this study to infer functions of these hypothetical proteins by phylogenomic profiling along with detailed sequence comparison against various publicly available databases. By this approach we were abletomore » assign possible functions to 25 responsive hypothetical proteins. The findings included that DVU0725, induced by oxidative stress, may be involved in lipopolysaccharide biosynthesis, implying that the alternation of lipopolysaccharide on cell surface might service as a mechanism against oxidative stress in D. vulgaris. In addition, two responsive proteins, DVU0024 encoding a putative transcriptional regulator and DVU1670 encoding predicted redox protein, were sharing co-evolution atterns with rubrerythrin in Archaeoglobus fulgidus and Clostridium perfringens, respectively, implying that they might be part of the stress response and protective systems in D. vulgaris. The study demonstrated that phylogenomic profiling is a useful tool in interpretation of experimental genomics data, and also provided further insight on cellular response to oxidative stress and heat shock in D. vulgaris.« less

Haptoglobin Preserves Vascular Nitric Oxide Signaling during Hemolysis.

PubMed

Schaer, Christian A; Deuel, Jeremy W; Schildknecht, Daniela; Mahmoudi, Leila; Garcia-Rubio, Ines; Owczarek, Catherine; Schauer, Stefan; Kissner, Reinhard; Banerjee, Uddyalok; Palmer, Andre F; Spahn, Donat R; Irwin, David C; Vallelian, Florence; Buehler, Paul W; Schaer, Dominik J

2016-05-15

Hemolysis occurs not only in conditions such as sickle cell disease and malaria but also during transfusion of stored blood, extracorporeal circulation, and sepsis. Cell-free Hb depletes nitric oxide (NO) in the vasculature, causing vasoconstriction and eventually cardiovascular complications. We hypothesize that Hb-binding proteins may preserve vascular NO signaling during hemolysis. Characterization of an archetypical function by which Hb scavenger proteins could preserve NO signaling during hemolysis. We investigated NO reaction kinetics, effects on arterial NO signaling, and tissue distribution of cell-free Hb and its scavenger protein complexes. Extravascular translocation of cell-free Hb into interstitial spaces, including the vascular smooth muscle cell layer of rat and pig coronary arteries, promotes vascular NO resistance. This critical disease process is blocked by haptoglobin. Haptoglobin does not change NO dioxygenation rates of Hb; rather, the large size of the Hb:haptoglobin complex prevents Hb extravasation, which uncouples NO/Hb interaction and vasoconstriction. Size-selective compartmentalization of Hb functions as a substitute for red blood cells after hemolysis and preserves NO signaling in the vasculature. We found that evolutionarily and structurally unrelated Hb-binding proteins, such as PIT54 found in avian species, functionally converged with haptoglobin to protect NO signaling by sequestering cell-free Hb in large protein complexes. Sequential compartmentalization of Hb by erythrocytes and scavenger protein complexes is an archetypical mechanism, which may have supported coevolution of hemolysis and normal vascular function. Therapeutic supplementation of Hb scavengers may restore vascular NO signaling and attenuate disease complications in patients with hemolysis.

Partner switching promotes cooperation among myopic agents on a geographical plane

NASA Astrophysics Data System (ADS)

Li, Yixiao; Min, Yong; Zhu, Xiaodong; Cao, Jie

2013-02-01

We study the coupling dynamics between the evolution of cooperation and the evolution of partnership network on a geographical plane. While agents play networked prisoner’s dilemma games, they can dynamically adjust their partnerships based on local information about reputation. We incorporate geographical features into the process of the agent’s partner switching and investigate the corresponding effects. At each time step of the coevolution, a random agent can either update his strategy by imitation or adjust his partnership by switching from the lowest reputation partner to the highest reputation one among his neighbors. We differentiate two types of neighbors: geographical neighbors (i.e., the set of agents who are close to the focal agent in terms of geographical distance) and connectivity neighbors (i.e., the set of agents who are close to the focal agent in the partnership network in terms of geodesic distance). We find that switching to either geographical neighbors or connectivity neighbors enhances cooperation greatly in a wide parameter range. Cooperation can be favored in a much stricter condition when agents switch to connectivity neighbors more frequently. However, an increasing tendency of reconnecting to geographical neighbors shortens the geographical distance between a pair of partners on average. When agents consider the cost of geographical distance in adjusting the partnership, they are prone to reconnect to geographical neighbors.

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

NASA Astrophysics Data System (ADS)

Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

2015-11-01

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

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.

Visualizing Complex Environments in the Geo- and BioSciences

NASA Astrophysics Data System (ADS)

Prabhu, A.; Fox, P. A.; Zhong, H.; Eleish, A.; Ma, X.; Zednik, S.; Morrison, S. M.; Moore, E. K.; Muscente, D.; Meyer, M.; Hazen, R. M.

2017-12-01

Earth's living and non-living components have co-evolved for 4 billion years through numerous positive and negative feedbacks. Earth and life scientists have amassed vast amounts of data in diverse fields related to planetary evolution through deep time-mineralogy and petrology, paleobiology and paleontology, paleotectonics and paleomagnetism, geochemistry and geochrononology, genomics and proteomics, and more. Integrating the data from these complimentary disciplines is very useful in gaining an understanding of the evolution of our planet's environment. The integrated data however, represent many extremely complex environments. In order to gain insights and make discoveries using this data, it is important for us to model and visualize these complex environments. As part of work in understanding the "Co-Evolution of Geo and Biospheres using Data Driven Methodologies," we have developed several visualizations to help represent the information stored in the datasets from complimentary disciplines. These visualizations include 2D and 3D force directed Networks, Chord Diagrams, 3D Klee Diagrams. Evolving Network Diagrams, Skyline Diagrams and Tree Diagrams. Combining these visualizations with the results of machine learning and data analysis methods leads to a powerful way to discover patterns and relationships about the Earth's past and today's changing environment.

A novel method for identifying disease associated protein complexes based on functional similarity protein complex networks.

PubMed

Le, Duc-Hau

2015-01-01

Protein complexes formed by non-covalent interaction among proteins play important roles in cellular functions. Computational and purification methods have been used to identify many protein complexes and their cellular functions. However, their roles in terms of causing disease have not been well discovered yet. There exist only a few studies for the identification of disease-associated protein complexes. However, they mostly utilize complicated heterogeneous networks which are constructed based on an out-of-date database of phenotype similarity network collected from literature. In addition, they only apply for diseases for which tissue-specific data exist. In this study, we propose a method to identify novel disease-protein complex associations. First, we introduce a framework to construct functional similarity protein complex networks where two protein complexes are functionally connected by either shared protein elements, shared annotating GO terms or based on protein interactions between elements in each protein complex. Second, we propose a simple but effective neighborhood-based algorithm, which yields a local similarity measure, to rank disease candidate protein complexes. Comparing the predictive performance of our proposed algorithm with that of two state-of-the-art network propagation algorithms including one we used in our previous study, we found that it performed statistically significantly better than that of these two algorithms for all the constructed functional similarity protein complex networks. In addition, it ran about 32 times faster than these two algorithms. Moreover, our proposed method always achieved high performance in terms of AUC values irrespective of the ways to construct the functional similarity protein complex networks and the used algorithms. The performance of our method was also higher than that reported in some existing methods which were based on complicated heterogeneous networks. Finally, we also tested our method with prostate cancer and selected the top 100 highly ranked candidate protein complexes. Interestingly, 69 of them were evidenced since at least one of their protein elements are known to be associated with prostate cancer. Our proposed method, including the framework to construct functional similarity protein complex networks and the neighborhood-based algorithm on these networks, could be used for identification of novel disease-protein complex associations.

The Not4 E3 Ligase and CCR4 Deadenylase Play Distinct Roles in Protein Quality Control

PubMed Central

Halter, David; Collart, Martine A.; Panasenko, Olesya O.

2014-01-01

Eukaryotic cells control their proteome by regulating protein production and protein clearance. Protein production is determined to a large extent by mRNA levels, whereas protein degradation depends mostly upon the proteasome. Dysfunction of the proteasome leads to the accumulation of non-functional proteins that can aggregate, be toxic for the cell, and, in extreme cases, lead to cell death. mRNA levels are controlled by their rates of synthesis and degradation. Recent evidence indicates that these rates have oppositely co-evolved to ensure appropriate mRNA levels. This opposite co-evolution has been correlated with the mutations in the Ccr4-Not complex. Consistently, the deadenylation enzymes responsible for the rate-limiting step in eukaryotic mRNA degradation, Caf1 and Ccr4, are subunits of the Ccr4-Not complex. Another subunit of this complex is a RING E3 ligase, Not4. It is essential for cellular protein solubility and has been proposed to be involved in co-translational quality control. An open question has been whether this role of Not4 resides strictly in the regulation of the deadenylation module of the Ccr4-Not complex. However, Not4 is important for proper assembly of the proteasome, and the Ccr4-Not complex may have multiple functional modules that participate in protein quality control in different ways. In this work we studied how the functions of the Caf1/Ccr4 and Not4 modules are connected. We concluded that Not4 plays a role in protein quality control independently of the Ccr4 deadenylase, and that it is involved in clearance of aberrant proteins at least in part via the proteasome. PMID:24465968

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.

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

Effects of chronic anthropogenic disturbance and rainfall on the specialization of ant-plant mutualistic networks in the Caatinga, a Brazilian dry forest.

PubMed

Câmara, Talita; Leal, Inara R; Blüthgen, Nico; Oliveira, Fernanda M P; Queiroz, Rubens T de; Arnan, Xavier

2018-03-05

Anthropogenic disturbance and climate change might negatively affect the ecosystem services provided by mutualistic networks. However, the effects of such forces remain poorly characterized. They may be especially important in dry forests, which (1) experience chronic anthropogenic disturbances (CADs) as human populations exploit forest resources, and (2) are predicted to face a 22% decline in rainfall under climate change. In this study, we investigated the separate and combined effects of CADs and rainfall levels on the specialization of mutualistic networks in the Caatinga, a seasonally dry tropical forest typical of north-eastern Brazil. More specifically, we examined interactions between plants bearing extrafloral nectaries (EFNs) and ants. We analysed whether differences in network specialization could arise from environmentally mediated variation in the species composition, namely via the replacement of specialist by generalist species. We characterized these ant-plant networks in 15 plots (20 × 20 m) that varied in CAD intensity and mean annual rainfall. We quantified CAD intensity by calculating three indices related to the main sources of disturbance in the Caatinga: livestock grazing (LG), wood extraction (WE) and miscellaneous resource use (MU). We determined the degree of ant-plant network specialization using four metrics: generality, vulnerability, interaction evenness and H 2 '. Our results indicate that CADs differentially influenced network specialization: we observed positive, negative, and neutral responses along LG, MU and WE gradients, respectively. The pattern was most pronounced with LG. Rainfall also shaped network specialization, markedly increasing it. While LG and rainfall were associated with changes in network species composition, this trend was not related to the degree of species specialization. This result suggests that shifts in network specialization might be related to changes in species behaviour, not species composition. Our study highlights the vulnerability of such dry forest ant-plant networks to climate change. Moreover, dry forests experience highly heterogeneous anthropogenic disturbances, creating a geographic mosaic of selective forces that may shape the co-evolution of interactions between ants and EFN-bearing plants. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.

Invasion fitness for gene-culture co-evolution in family-structured populations and an application to cumulative culture under vertical transmission.

PubMed

Mullon, Charles; Lehmann, Laurent

2017-08-01

Human evolution depends on the co-evolution between genetically determined behaviors and socially transmitted information. Although vertical transmission of cultural information from parent to offspring is common in hominins, its effects on cumulative cultural evolution are not fully understood. Here, we investigate gene-culture co-evolution in a family-structured population by studying the invasion fitness of a mutant allele that influences a deterministic level of cultural information (e.g., amount of knowledge or skill) to which diploid carriers of the mutant are exposed in subsequent generations. We show that the selection gradient on such a mutant, and the concomitant level of cultural information it generates, can be evaluated analytically under the assumption that the cultural dynamic has a single attractor point, thereby making gene-culture co-evolution in family-structured populations with multigenerational effects mathematically tractable. We apply our result to study how genetically determined phenotypes of individual and social learning co-evolve with the level of adaptive information they generate under vertical transmission. We find that vertical transmission increases adaptive information due to kin selection effects, but when information is transmitted as efficiently between family members as between unrelated individuals, this increase is moderate in diploids. By contrast, we show that the way resource allocation into learning trades off with allocation into reproduction (the "learning-reproduction trade-off") significantly influences levels of adaptive information. We also show that vertical transmission prevents evolutionary branching and may therefore play a qualitative role in gene-culture co-evolutionary dynamics. More generally, our analysis of selection suggests that vertical transmission can significantly increase levels of adaptive information under the biologically plausible condition that information transmission between relatives is more efficient than between unrelated individuals. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of an ancestral resistance gene cluster involved in the coevolution process between Phaseolus vulgaris and its fungal pathogen Colletotrichum lindemuthianum.

PubMed

Geffroy, V; Sicard, D; de Oliveira, J C; Sévignac, M; Cohen, S; Gepts, P; Neema, C; Langin, T; Dron, M

1999-09-01

The recent cloning of plant resistance (R) genes and the sequencing of resistance gene clusters have shed light on the molecular evolution of R genes. However, up to now, no attempt has been made to correlate this molecular evolution with the host-pathogen coevolution process at the population level. Cross-inoculations were carried out between 26 strains of the fungal pathogen Colletotrichum lindemuthianum and 48 Phaseolus vulgaris plants collected in the three centers of diversity of the host species. A high level of diversity for resistance against the pathogen was revealed. Most of the resistance specificities were overcome in sympatric situations, indicating an adaptation of the pathogen to the local host. In contrast, plants were generally resistant to allopatric strains, suggesting that R genes that were efficient against exotic strains but had been overcome locally were maintained in the plant genome. These results indicated that coevolution processes between the two protagonists led to a differentiation for resistance in the three centers of diversity of the host. To improve our understanding of the molecular evolution of these different specificities, a recombinant inbred (RI) population derived from two representative genotypes of the Andean (JaloEEP558) and Mesoamerican (BAT93) gene pools was used to map anthracnose specificities. A gene cluster comprising both Andean (Co-y; Co-z) and Mesoamerican (Co-9) host resistance specificities was identified, suggesting that this locus existed prior to the separation of the two major gene pools of P. vulgaris. Molecular analysis revealed a high level of complexity at this locus. It harbors 11 restriction fragment length polymorphisms when R gene analog (RGA) clones are used. The relationship between the coevolution process and diversification of resistance specificities at resistance gene clusters is discussed.

Impact of two specialist insect herbivores on reproduction of horse nettle, Solanum carolinense.

PubMed

Wise, Michael J; Sacchi, Christopher F

1996-10-01

The frequency of coevolution as a process of strong mutual interaction between a single plant and herbivore species has been questioned in light of more commonly observed, complex relationships between a plant and a suite of herbivore species. Despite recognition of the possibility of diffuse coevolution, relatively few studies have examined ecological responses of plants to herbivores in complex associations. We studied the impact of two specialist herbivores, the horse nettle beetle, Leptinotarsa juncta, and the eggplant flea beetle, Epitrix fuscula, on reproduction of their host, Solanum carolinense. Our study involved field and controlled-environment experimental tests of the impact on sexual and potential asexual reproduction of attack by individuals of the two herbivore species, individually and in combination. Field tests demonstrated that under normal levels of phytophagous insect attack, horse nettle plants experienced a reduction in fruit production of more than 75% compared with plants from which insects were excluded. In controlled-environment experiments using enclosure-exclosure cages, the horse nettle's two principal herbivores, the flea beetle and the horse nettle beetle, caused decreases in sexual reproduction similar to those observed in the field, and a reduction in potential asexual reproduction, represented by root biomass. Attack by each herbivore reduced the numbers of fruits produced, and root growth, when feeding in isolation. When both species were feeding together, fruit production, but not root growth, was lower than when either beetle species fed alone. Ecological interactions between horse nettle and its two primary herbivores necessary for diffuse coevolution to occur were evident from an overall analysis of the statistical interactions between the two herbivores for combined assessment of fruit and vegetative traits. For either of these traits alone, the interactions necessary to promote diffuse coevolution apparently were lacking.

Insect Immunity to Entomopathogenic Fungi.

PubMed

Lu, H-L; St Leger, R J

2016-01-01

The study of infection and immunity in insects has achieved considerable prominence with the appreciation that their host defense mechanisms share many fundamental characteristics with the innate immune system of vertebrates. Studies on the highly tractable model organism Drosophila in particular have led to a detailed understanding of conserved innate immunity networks, such as Toll. However, most of these studies have used opportunistic human pathogens and may not have revealed specialized immune strategies that have arisen through evolutionary arms races with natural insect pathogens. Fungi are the commonest natural insect pathogens, and in this review, we focus on studies using Metarhizium and Beauveria spp. that have addressed immune system function and pathogen virulence via behavioral avoidance, the use of physical barriers, and the activation of local and systemic immune responses. In particular, we highlight studies on the evolutionary genetics of insect immunity and discuss insect-pathogen coevolution. Copyright © 2016 Elsevier Inc. All rights reserved.

Network-Based Methods for Identifying Key Active Proteins in the Extracellular Electron Transfer Process in Shewanella oneidensis MR-1.

PubMed

Ding, Dewu; Sun, Xiao

2018-01-16

Shewanella oneidensis MR-1 can transfer electrons from the intracellular environment to the extracellular space of the cells to reduce the extracellular insoluble electron acceptors (Extracellular Electron Transfer, EET). Benefiting from this EET capability, Shewanella has been widely used in different areas, such as energy production, wastewater treatment, and bioremediation. Genome-wide proteomics data was used to determine the active proteins involved in activating the EET process. We identified 1012 proteins with decreased expression and 811 proteins with increased expression when the EET process changed from inactivation to activation. We then networked these proteins to construct the active protein networks, and identified the top 20 key active proteins by network centralization analysis, including metabolism- and energy-related proteins, signal and transcriptional regulatory proteins, translation-related proteins, and the EET-related proteins. We also constructed the integrated protein interaction and transcriptional regulatory networks for the active proteins, then found three exclusive active network motifs involved in activating the EET process-Bi-feedforward Loop, Regulatory Cascade with a Feedback, and Feedback with a Protein-Protein Interaction (PPI)-and identified the active proteins involved in these motifs. Both enrichment analysis and comparative analysis to the whole-genome data implicated the multiheme c -type cytochromes and multiple signal processing proteins involved in the process. Furthermore, the interactions of these motif-guided active proteins and the involved functional modules were discussed. Collectively, by using network-based methods, this work reported a proteome-wide search for the key active proteins that potentially activate the EET process.

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 .

Linking the proteins--elucidation of proteome-scale networks using mass spectrometry.

PubMed

Pflieger, Delphine; Gonnet, Florence; de la Fuente van Bentem, Sergio; Hirt, Heribert; de la Fuente, Alberto

2011-01-01

Proteomes are intricate. Typically, thousands of proteins interact through physical association and post-translational modifications (PTMs) to give rise to the emergent functions of cells. Understanding these functions requires one to study proteomes as "systems" rather than collections of individual protein molecules. The abstraction of the interacting proteome to "protein networks" has recently gained much attention, as networks are effective representations, that lose specific molecular details, but provide the ability to see the proteome as a whole. Mostly two aspects of the proteome have been represented by network models: proteome-wide physical protein-protein-binding interactions organized into Protein Interaction Networks (PINs), and proteome-wide PTM relations organized into Protein Signaling Networks (PSNs). Mass spectrometry (MS) techniques have been shown to be essential to reveal both of these aspects on a proteome-wide scale. Techniques such as affinity purification followed by MS have been used to elucidate protein-protein interactions, and MS-based quantitative phosphoproteomics is critical to understand the structure and dynamics of signaling through the proteome. We here review the current state-of-the-art MS-based analytical pipelines for the purpose to characterize proteome-scale networks. Copyright © 2010 Wiley Periodicals, Inc.

Evolution of angiosperm seed disperser mutualisms: the timing of origins and their consequences for coevolutionary interactions between angiosperms and frugivores.

PubMed

Eriksson, Ove

2016-02-01

The origins of interactions between angiosperms and fruit-eating seed dispersers have attracted much attention following a seminal paper on this topic by Tiffney (1984). This review synthesizes evidence pertaining to key events during the evolution of angiosperm-frugivore interactions and suggests some implications of this evidence for interpretations of angiosperm-frugivore coevolution. The most important conclusions are: (i) the diversification of angiosperm seed size and fleshy fruits commenced around 80 million years ago (Mya). The diversity of seed sizes, fruit sizes and fruit types peaked in the Eocene around 55 to 50 Mya. During this first phase of the interaction, angiosperms and animals evolving frugivory expanded into niche space not previously utilized by these groups, as frugivores and previously not existing fruit traits appeared. From the Eocene until the present, angiosperm-frugivore interactions have occurred within a broad frame of existing niche space, as defined by fruit traits and frugivory, motivating a separation of the angiosperm-frugivore interactions into two phases, before and after the peak in the early Eocene. (ii) The extinct multituberculates were probably the most important frugivores during the early radiation phase of angiosperm seeds and fleshy fruits. Primates and rodents are likely to have been important in the latter part of this first phase. (iii) Flying frugivores, birds and bats, evolved during the second phase, mainly during the Oligocene and Miocene, thus exploiting an existing diversity of fleshy fruits. (iv) A drastic climate shift around the Eocene-Oligocene boundary (around 34 Mya) resulted in more semi-open woodland vegetation, creating patchily occurring food resources for frugivores. This promoted evolution of a 'flying frugivore niche' exploited by birds and bats. In particular, passerines became a dominant frugivore group worldwide. (v) Fleshy fruits evolved at numerous occasions in many angiosperm families, and many of the originations of fleshy fruits occurred well after the peak in the early Eocene. (vi) During periods associated with environmental change altering coevolutionary networks and opening of niche space, reciprocal coevolution may result in strong directional selection formative for both fruit and frugivore evolution. Further evidence is needed to test this hypothesis. Based on the abundance of plant lineages with various forms of fleshy fruits, and the diversity of frugivores, it is suggested that periods of rapid coevolution in angiosperms and frugivores occurred numerous times during the 80 million years of angiosperm-frugivore evolution. © 2014 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

Disease gene classification with metagraph representations.

PubMed

Kircali Ata, Sezin; Fang, Yuan; Wu, Min; Li, Xiao-Li; Xiao, Xiaokui

2017-12-01

Protein-protein interaction (PPI) networks play an important role in studying the functional roles of proteins, including their association with diseases. However, protein interaction networks are not sufficient without the support of additional biological knowledge for proteins such as their molecular functions and biological processes. To complement and enrich PPI networks, we propose to exploit biological properties of individual proteins. More specifically, we integrate keywords describing protein properties into the PPI network, and construct a novel PPI-Keywords (PPIK) network consisting of both proteins and keywords as two different types of nodes. As disease proteins tend to have a similar topological characteristics on the PPIK network, we further propose to represent proteins with metagraphs. Different from a traditional network motif or subgraph, a metagraph can capture a particular topological arrangement involving the interactions/associations between both proteins and keywords. Based on the novel metagraph representations for proteins, we further build classifiers for disease protein classification through supervised learning. Our experiments on three different PPI databases demonstrate that the proposed method consistently improves disease protein prediction across various classifiers, by 15.3% in AUC on average. It outperforms the baselines including the diffusion-based methods (e.g., RWR) and the module-based methods by 13.8-32.9% for overall disease protein prediction. For predicting breast cancer genes, it outperforms RWR, PRINCE and the module-based baselines by 6.6-14.2%. Finally, our predictions also turn out to have better correlations with literature findings from PubMed. Copyright © 2017 Elsevier Inc. All rights reserved.

An exploration of alternative visualisations of the basic helix-loop-helix protein interaction network

PubMed Central

Holden, Brian J; Pinney, John W; Lovell, Simon C; Amoutzias, Grigoris D; Robertson, David L

2007-01-01

Background Alternative representations of biochemical networks emphasise different aspects of the data and contribute to the understanding of complex biological systems. In this study we present a variety of automated methods for visualisation of a protein-protein interaction network, using the basic helix-loop-helix (bHLH) family of transcription factors as an example. Results Network representations that arrange nodes (proteins) according to either continuous or discrete information are investigated, revealing the existence of protein sub-families and the retention of interactions following gene duplication events. Methods of network visualisation in conjunction with a phylogenetic tree are presented, highlighting the evolutionary relationships between proteins, and clarifying the context of network hubs and interaction clusters. Finally, an optimisation technique is used to create a three-dimensional layout of the phylogenetic tree upon which the protein-protein interactions may be projected. Conclusion We show that by incorporating secondary genomic, functional or phylogenetic information into network visualisation, it is possible to move beyond simple layout algorithms based on network topology towards more biologically meaningful representations. These new visualisations can give structure to complex networks and will greatly help in interpreting their evolutionary origins and functional implications. Three open source software packages (InterView, TVi and OptiMage) implementing our methods are available. PMID:17683601

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).

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

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.

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.

Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

PubMed Central

Du, Pufeng; Wang, Lusheng

2014-01-01

One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

Coevolution Maintains Diversity in the Stochastic "Kill the Winner" Model

NASA Astrophysics Data System (ADS)

Xue, Chi; Goldenfeld, Nigel

2017-12-01

The "kill the winner" hypothesis is an attempt to address the problem of diversity in biology. It argues that host-specific predators control the population of each prey, preventing a winner from emerging and thus maintaining the coexistence of all species in the system. We develop a stochastic model for the kill the winner paradigm and show that the stable coexistence state of the deterministic kill the winner model is destroyed by demographic stochasticity, through a cascade of extinction events. We formulate an individual-level stochastic model in which predator-prey coevolution promotes the high diversity of the ecosystem by generating a persistent population flux of species.

Biology-Culture Co-evolution in Finite Populations.

PubMed

de Boer, Bart; Thompson, Bill

2018-01-19

Language is the result of two concurrent evolutionary processes: biological and cultural inheritance. An influential evolutionary hypothesis known as the moving target problem implies inherent limitations on the interactions between our two inheritance streams that result from a difference in pace: the speed of cultural evolution is thought to rule out cognitive adaptation to culturally evolving aspects of language. We examine this hypothesis formally by casting it as as a problem of adaptation in time-varying environments. We present a mathematical model of biology-culture co-evolution in finite populations: a generalisation of the Moran process, treating co-evolution as coupled non-independent Markov processes, providing a general formulation of the moving target hypothesis in precise probabilistic terms. Rapidly varying culture decreases the probability of biological adaptation. However, we show that this effect declines with population size and with stronger links between biology and culture: in realistically sized finite populations, stochastic effects can carry cognitive specialisations to fixation in the face of variable culture, especially if the effects of those specialisations are amplified through cultural evolution. These results support the view that language arises from interactions between our two major inheritance streams, rather than from one primary evolutionary process that dominates another.

Sexual conflict over parental care promotes the evolution of sex differences in care and the ability to care

PubMed Central

McNamara, John M.; Wolf, Max

2015-01-01

Strong asymmetries in parental care, with one sex providing more care than the other, are widespread across the animal kingdom. At present, two factors are thought to ultimately cause sex differences in care: certainty of parentage and sexual selection. By contrast, we here show that the coevolution of care and the ability to care can result in strong asymmetries in both the ability to care and the level of care, even in the absence of these factors. While the coevolution of care and the ability to care does not predict which sex evolves to care more than the other, once other factors give rise to even the slightest differences in the cost and benefits of care between the sexes (e.g. differences in certainty in parentage), a clear directionality emerges; the sex with the lower cost or higher benefit of care evolves both to be more able to care and to provide much higher levels of care than the other sex. Our findings suggest that the coevolution of levels of care and the ability to care may be a key factor underlying the evolution of sex differences in care. PMID:25694618

Coevolution in host-parasite systems: behavioural strategies of slave-making ants and their hosts.

PubMed

Foitzik, S; DeHeer, C J; Hunjan, D N; Herbers, J M

2001-06-07

Recently, avian brood parasites and their hosts have emerged as model systems for the study of host-parasite coevolution. However, empirical studies of the highly analogous social parasites, which use the workers of another eusocial species to raise their own young, have never explicitly examined the dynamics of these systems from a coevolutionary perspective. Here, we demonstrate interpopulational variation in behavioural interactions between a socially parasitic slave-maker ant and its host that is consistent with the expectations of host-parasite coevolution. Parasite pressure, as inferred by the size, abundance and raiding frequency of Protomognathus americanus colonies, was highest in a New York population of the host Leptothorax longispinosus and lowest in a West Virginia population. As host-parasite coevolutionary theory would predict, we found that the slave-makers and the hosts from New York were more effective at raiding and defending against raiders, respectively, than were conspecifics from the West Virginia population. Some of these variations in efficacy were brought about by apparently simple shifts in behaviour. These results demonstrate that defence mechanisms against social parasites can evolve, and they give the first indications of the existence of a coevolutionary arms race between a social parasite and its host.

Selection on an antagonistic behavioral trait can drive rapid genital coevolution in the burying beetle, Nicrophorus vespilloides

PubMed Central

Hopwood, Paul E.; Head, Megan L.; Jordan, Eleanor J.; Carter, Mauricio J.; Davey, Emma; Moore, Allen J.; Royle, Nick J.

2016-01-01

Male and female genital morphology varies widely across many taxa, and even among populations. Disentangling potential sources of selection on genital morphology is problematic because each sex is predicted to respond to adaptations in the other due to reproductive conflicts of interest. To test how variation in this sexual conflict trait relates to variation in genital morphology we used our previously developed artificial selection lines for high and low repeated mating rates. We selected for high and low repeated mating rates using monogamous pairings to eliminate contemporaneous female choice and male–male competition. Male and female genital shape responded rapidly to selection on repeated mating rate. High and low mating rate lines diverged from control lines after only 10 generations of selection. We also detected significant patterns of male and female genital shape coevolution among selection regimes. We argue that because our selection lines differ in sexual conflict, these results support the hypothesis that sexually antagonistic coevolution can drive the rapid divergence of genital morphology. The greatest divergence in morphology corresponded with lines in which the resolution of sexual conflict over mating rate was biased in favor of male interests. PMID:27144373

A matching-allele model explains host resistance to parasites.

PubMed

Luijckx, Pepijn; Fienberg, Harris; Duneau, David; Ebert, Dieter

2013-06-17

The maintenance of genetic variation and sex despite its costs has long puzzled biologists. A popular idea, the Red Queen Theory, is that under rapid antagonistic coevolution between hosts and their parasites, the formation of new rare host genotypes through sex can be advantageous as it creates host genotypes to which the prevailing parasite is not adapted. For host-parasite coevolution to lead to an ongoing advantage for rare genotypes, parasites should infect specific host genotypes and hosts should resist specific parasite genotypes. The most prominent genetics capturing such specificity are matching-allele models (MAMs), which have the key feature that resistance for two parasite genotypes can reverse by switching one allele at one host locus. Despite the lack of empirical support, MAMs have played a central role in the theoretical development of antagonistic coevolution, local adaptation, speciation, and sexual selection. Using genetic crosses, we show that resistance of the crustacean Daphnia magna against the parasitic bacterium Pasteuria ramosa follows a MAM. Simulation results show that the observed genetics can explain the maintenance of genetic variation and contribute to the maintenance of sex in the facultatively sexual host as predicted by the Red Queen Theory. Copyright © 2013 Elsevier Ltd. All rights reserved.

Non-parallel coevolution of sender and receiver in the acoustic communication system of treefrogs.

PubMed

Schul, Johannes; Bush, Sarah L

2002-09-07

Advertisement calls of closely related species often differ in quantitative features such as the repetition rate of signal units. These differences are important in species recognition. Current models of signal-receiver coevolution predict two possible patterns in the evolution of the mechanism used by receivers to recognize the call: (i) classical sexual selection models (Fisher process, good genes/indirect benefits, direct benefits models) predict that close relatives use qualitatively similar signal recognition mechanisms tuned to different values of a call parameter; and (ii) receiver bias models (hidden preference, pre-existing bias models) predict that if different signal recognition mechanisms are used by sibling species, evidence of an ancestral mechanism will persist in the derived species, and evidence of a pre-existing bias will be detectable in the ancestral species. We describe qualitatively different call recognition mechanisms in sibling species of treefrogs. Whereas Hyla chrysoscelis uses pulse rate to recognize male calls, Hyla versicolor uses absolute measurements of pulse duration and interval duration. We found no evidence of either hidden preferences or pre-existing biases. The results are compared with similar data from katydids (Tettigonia sp.). In both taxa, the data are not adequately explained by current models of signal-receiver coevolution.

Socio-hydrologic Perspectives of the Co-evolution of Humans and Water in the Tarim River Basin, Western China

NASA Astrophysics Data System (ADS)

Liu, Ye; Tian, Fuqiang; Hu, Heping; Liu, Dengfeng; Sivapalan, Murugesu

2013-04-01

Socio-hydrology studies the co-evolution of coupled human-water systems, which is of great importance for long-term sustainable water resource management in basins suffering from serious eco-environmental degradation. Process socio-hydrology can benefit from the exploring the patterns of historical co-evolution of coupled human-water systems as a way to discovering the organizing principles that may underpin their co-evolution. As a self-organized entity, the human-water system in a river basin would evolve into certain steady states over a sufficiently long time but then could also experience sudden shifts due to internal or external disturbances that exceed system thresholds. In this study, we discuss three steady states (also called stages in the social sciences, including natural, human exploitation and recovery stages) and transitions between these during the past 1500 years in the Tarim River Basin of Western China, which a rich history of civilization including its place in the famous Silk Road that connected China to Europe. Specifically, during the natural stage with a sound environment that existed before the 19th century, shifts in the ecohydrological regime were mainly caused by environmental changes such river channel migration and climate change. During the human exploitation stages in the 5th and again in the 19th-20th centuries, however, humans gradually became the main drivers for system evolution, during which the basin experienced rapid population growth, fast socio-economic development and intense human activities. By the 1970s, after 200 years of colonization, the Tarim River Basin evolved into a new regime with vulnerable ecosystem and water system, and suffered from serious water shortages and desertification. Human society then began to take a critical look into the effects of their activities and reappraise the impact of human development on the ecohydrological system, which eventually led the basin into a treatment and recovery stage. Since then, the basin has shown a reverse trend of regime shift towards healing of the environmental damage that was inflicted in the previous stage of human development. In this paper we analyze the recasting effect of human activities on the water system and provide explanations on how human activities influence the co-evolution of human-water system from a broader perspective.

Synaptic activity induces input-specific rearrangements in a targeted synaptic protein interaction network.

PubMed

Lautz, Jonathan D; Brown, Emily A; VanSchoiack, Alison A Williams; Smith, Stephen E P

2018-05-27

Cells utilize dynamic, network level rearrangements in highly interconnected protein interaction networks to transmit and integrate information from distinct signaling inputs. Despite the importance of protein interaction network dynamics, the organizational logic underlying information flow through these networks is not well understood. Previously, we developed the quantitative multiplex co-immunoprecipitation platform, which allows for the simultaneous and quantitative measurement of the amount of co-association between large numbers of proteins in shared complexes. Here, we adapt quantitative multiplex co-immunoprecipitation to define the activity dependent dynamics of an 18-member protein interaction network in order to better understand the underlying principles governing glutamatergic signal transduction. We first establish that immunoprecipitation detected by flow cytometry can detect activity dependent changes in two known protein-protein interactions (Homer1-mGluR5 and PSD-95-SynGAP). We next demonstrate that neuronal stimulation elicits a coordinated change in our targeted protein interaction network, characterized by the initial dissociation of Homer1 and SynGAP-containing complexes followed by increased associations among glutamate receptors and PSD-95. Finally, we show that stimulation of distinct glutamate receptor types results in different modular sets of protein interaction network rearrangements, and that cells activate both modules in order to integrate complex inputs. This analysis demonstrates that cells respond to distinct types of glutamatergic input by modulating different combinations of protein co-associations among a targeted network of proteins. Our data support a model of synaptic plasticity in which synaptic stimulation elicits dissociation of preexisting multiprotein complexes, opening binding slots in scaffold proteins and allowing for the recruitment of additional glutamatergic receptors. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Protein-Protein Interface and Disease: Perspective from Biomolecular Networks.

PubMed

Hu, Guang; Xiao, Fei; Li, Yuqian; Li, Yuan; Vongsangnak, Wanwipa

Protein-protein interactions are involved in many important biological processes and molecular mechanisms of disease association. Structural studies of interfacial residues in protein complexes provide information on protein-protein interactions. Characterizing protein-protein interfaces, including binding sites and allosteric changes, thus pose an imminent challenge. With special focus on protein complexes, approaches based on network theory are proposed to meet this challenge. In this review we pay attention to protein-protein interfaces from the perspective of biomolecular networks and their roles in disease. We first describe the different roles of protein complexes in disease through several structural aspects of interfaces. We then discuss some recent advances in predicting hot spots and communication pathway analysis in terms of amino acid networks. Finally, we highlight possible future aspects of this area with respect to both methodology development and applications for disease treatment.

A Collaboration Network Model Of Cytokine-Protein Network

NASA Astrophysics Data System (ADS)

Zou, Sheng-Rong; Zhou, Ta; Peng, Yu-Jing; Guo, Zhong-Wei; Gu, Chang-Gui; He, Da-Ren

2008-03-01

Complex networks provide us a new view for investigation of immune systems. We collect data through STRING database and present a network description with cooperation network model. The cytokine-protein network model we consider is constituted by two kinds of nodes, one is immune cytokine types which can be regarded as collaboration acts, the other one is protein type which can be regarded as collaboration actors. From act degree distribution that can be well described by typical SPL (shifted power law) functions [1], we find that HRAS, TNFRSF13C, S100A8, S100A1, MAPK8, S100A7, LIF, CCL4, CXCL13 are highly collaborated with other proteins. It reveals that these mediators are important in cytokine-protein network to regulate immune activity. Dyad in the collaboration networks can be defined as two proteins and they appear in one cytokine collaboration relationship. The dyad act degree distribution can also be well described by typical SPL functions. [1] Assortativity and act degree distribution of some collaboration networks, Hui Chang, Bei-Bei Su, Yue-Ping Zhou, Daren He, Physica A, 383 (2007) 687-702

Universal partitioning of the hierarchical fold network of 50-residue segments in proteins

PubMed Central

Ito, Jun-ichi; Sonobe, Yuki; Ikeda, Kazuyoshi; Tomii, Kentaro; Higo, Junichi

2009-01-01

Background Several studies have demonstrated that protein fold space is structured hierarchically and that power-law statistics are satisfied in relation between the numbers of protein families and protein folds (or superfamilies). We examined the internal structure and statistics in the fold space of 50 amino-acid residue segments taken from various protein folds. We used inter-residue contact patterns to measure the tertiary structural similarity among segments. Using this similarity measure, the segments were classified into a number (Kc) of clusters. We examined various Kc values for the clustering. The special resolution to differentiate the segment tertiary structures increases with increasing Kc. Furthermore, we constructed networks by linking structurally similar clusters. Results The network was partitioned persistently into four regions for Kc ≥ 1000. This main partitioning is consistent with results of earlier studies, where similar partitioning was reported in classifying protein domain structures. Furthermore, the network was partitioned naturally into several dozens of sub-networks (i.e., communities). Therefore, intra-sub-network clusters were mutually connected with numerous links, although inter-sub-network ones were rarely done with few links. For Kc ≥ 1000, the major sub-networks were about 40; the contents of the major sub-networks were conserved. This sub-partitioning is a novel finding, suggesting that the network is structured hierarchically: Segments construct a cluster, clusters form a sub-network, and sub-networks constitute a region. Additionally, the network was characterized by non-power-law statistics, which is also a novel finding. Conclusion Main findings are: (1) The universe of 50 residue segments found here was characterized by non-power-law statistics. Therefore, the universe differs from those ever reported for the protein domains. (2) The 50-residue segments were partitioned persistently and universally into some dozens (ca. 40) of major sub-networks, irrespective of the number of clusters. (3) These major sub-networks encompassed 90% of all segments. Consequently, the protein tertiary structure is constructed using the dozens of elements (sub-networks). PMID:19454039

The BioPlex Network: A Systematic Exploration of the Human Interactome.

PubMed

Huttlin, Edward L; Ting, Lily; Bruckner, Raphael J; Gebreab, Fana; Gygi, Melanie P; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E; De Camilli, Pietro; Paulo, Joao A; Harper, J Wade; Gygi, Steven P

2015-07-16

Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors. Copyright © 2015 Elsevier Inc. All rights reserved.

The BioPlex Network: A Systematic Exploration of the Human Interactome

PubMed Central

Huttlin, Edward L.; Ting, Lily; Bruckner, Raphael J.; Gebreab, Fana; Gygi, Melanie P.; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K.; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A.; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E.; DeCamilli, Pietro; Paulo, Joao A.; Harper, J. Wade; Gygi, Steven P.

2015-01-01

SUMMARY Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally-related proteins. Finally, BioPlex, in combination with other approaches can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial Amyotrophic Lateral Sclerosis perturb a defined community of interactors. PMID:26186194

An upstream open reading frame represses expression of Lc, a member of the R/B family of maize transcriptional activators

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

Damiani, R.D. Jr.; Wessler, S.R.

1993-09-01

The R/B genes of maize encode a family of basic helix-loop-helix proteins that determine where and when the anthocyanin-pigment pathway will be expressed in the plant. Previous studies showed that allelic diversity among family members reflects differences in gene expression, specifically in transcription initiation. The authors present evidence that the R gene Lc is under translational control. They demonstrate that the 235-nt transcript leader of Lc represses expression 25- to 30-fold in an in vivo assay. Repression is mediated by the presence in cis of a 38-codon upstream open reading frame. Furthermore, the coding capacity of the upstream open readingmore » frame influences the magnitude of repression. It is proposed that translational control does not contribute to tissue specificity but prevents overexpression of the Lc protein. The diversity of promoter and 5' untranslated leader sequences among the R/B genes provides an opportunity to study the coevolution of transcriptional and translational mechanisms of gene regulation. 36 refs., 5 figs.« less

Evidence for a novel negative-stranded RNA mycovirus isolated from the plant pathogenic fungus Fusarium graminearum.

PubMed

Wang, Luan; He, Hao; Wang, Shuangchao; Chen, Xiaoguang; Qiu, Dewen; Kondo, Hideki; Guo, Lihua

2018-05-01

Here we describe a novel (-)ssRNA mycovirus, Fusarium graminearum negative-stranded RNA virus 1 (FgNSRV-1), isolated from Fusarium graminearum strain HN1. The genome of FgNSRV-1 is 9072 nucleotides in length, with five discontinuous but linear ORFs (ORF I-V). Phylogenetic analysis based on entire L polymerase sequences indicated that FgNSRV-1 is related to the (-)ssRNA mycovirus Sclerotinia sclerotiorum negative-stranded RNA virus 1 (SsNSRV-1), and other mycoviruses. Our data suggest that FgNSRV-1 can be classified into the family Mymonaviridae, order Mononegavirales. Putative enveloped virion-like structures with filamentous morphology similar to SsNSRV-1 were observed in virion preparation samples. The L proteins of FgNSRV-1, and other fungal mononegaviruses, were found to be related to L protein-like sequences in some fungal genome, supporting the hypothesis that there is coevolution occurring between mycoviruses and fungi. Besides, clearing the virus from the infected host fungus resulted in no discernable phenotypic change. Copyright © 2018 Elsevier Inc. All rights reserved.

microRNA-mediated R gene regulation: molecular scabbards for double-edged swords.

PubMed

Deng, Yingtian; Liu, Minglei; Li, Xiaofei; Li, Feng

2018-02-01

Plant resistance (R) proteins are immune receptors that recognize pathogen effectors and trigger rapid defense responses, namely effector-triggered immunity. R protein-mediated pathogen resistance is usually race specific. During plant-pathogen coevolution, plant genomes accumulated large numbers of R genes. Even though plant R genes provide important natural resources for breeding disease-resistant crops, their presence in the plant genome comes at a cost. Misregulation of R genes leads to developmental defects, such as stunted growth and reduced fertility. In the past decade, many microRNAs (miRNAs) have been identified to target various R genes in plant genomes. miRNAs reduce R gene levels under normal conditions and allow induction of R gene expression under various stresses. For these reasons, we consider R genes to be double-edged "swords" and miRNAs as molecular "scabbards". In the present review, we summarize the contributions and potential problems of these "swords" and discuss the features and production of the "scabbards", as well as the mechanisms used to pull the "sword" from the "scabbard" when needed.

What can ecosystems learn? Expanding evolutionary ecology with learning theory.

PubMed

Power, Daniel A; Watson, Richard A; Szathmáry, Eörs; Mills, Rob; Powers, Simon T; Doncaster, C Patrick; Czapp, Błażej

2015-12-08

The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions.

IML-CZO: Critical Zone Observatory for Intensively Managed Landscapes

NASA Astrophysics Data System (ADS)

Kumar, Praveen; Papanicolaou, Thanos

2014-05-01

Intensively managed landscapes, regions of significant land use change, serve as a cradle for economic prosperity. However, the intensity of change is responsible for unintended deterioration of our land and water environments. By understanding present day dynamics in the context of long-term co-evolution of the Critical Zone comprising of the landscape, soil and biota, IML-CZO aims to support the assessment of short- and long-term resilience of the crucial ecological, hydrological and climatic services provided by the Critical Zone. An observational network of three sites in Illinois, Iowa, and Minnesota that capture the geological diversity of the low relief, glaciated, and tile-drained landscape will drive novel scientific and technological advances. IML-CZO will provide leadership in developing the next generation of scientists and practitioners, and informing management strategies aimed at reducing the vulnerability of the system to present and emerging trends in human activities. IML-CZO, one of the nine observatories funded by the United States National Science Foundation (NSF), consists of two core sites: the 3,690- sq. km. Upper Sangamon River Basin in Illinois and 270-sq. km. Clear Creek Watershed in Iowa, along with the 44,000- sq. km. Minnesota River Basin as third participating site. These sites together are characterized by low-relief landscapes with poorly drained soils and represent a broad range of physiographic variations found throughout the glaciated Midwest, and thereby provide an opportunity to advance understanding of the CZO in this important region. Through novel measurements, analysis and modeling, IML-CZO aims to address the following questions: • How do different time scales of geologic evolution and anthropogenic influence interact to determine the trajectory of CZ structure and function? • How is the co-evolution of biota, consisting of both vegetation and microbes, and soil affected due to intensive management? • How have dynamic patterns of connectivity, which link across transition zones and heterogeneity, changed by anthropogenic impacts? • How do these changes affect residence times and aggregate fluxes of water, carbon, nutrients, and sediment? IML-CZO will use historical data, existing observational networks, new instruments, remote sensing, sampling and laboratory analyses, and novel sensing technologies using open hardware and unmanned vehicles to study a number of variables related to climate and weather, hydrology, geology, geomorphology, soils, water chemistry, biogeochemistry, ecology, and land management. Additional details are available at imlczo.org.

Protein interaction networks from literature mining

NASA Astrophysics Data System (ADS)

Ihara, Sigeo

2005-03-01

The ability to accurately predict and understand physiological changes in the biological network system in response to disease or drug therapeutics is of crucial importance in life science. The extensive amount of gene expression data generated from even a single microarray experiment often proves difficult to fully interpret and comprehend the biological significance. An increasing knowledge of protein interactions stored in the PubMed database, as well as the advancement of natural language processing, however, makes it possible to construct protein interaction networks from the gene expression information that are essential for understanding the biological meaning. From the in house literature mining system we have developed, the protein interaction network for humans was constructed. By analysis based on the graph-theoretical characterization of the total interaction network in literature, we found that the network is scale-free and semantic long-ranged interactions (i.e. inhibit, induce) between proteins dominate in the total interaction network, reducing the degree exponent. Interaction networks generated based on scientific text in which the interaction event is ambiguously described result in disconnected networks. In contrast interaction networks based on text in which the interaction events are clearly stated result in strongly connected networks. The results of protein-protein interaction networks obtained in real applications from microarray experiments are discussed: For example, comparisons of the gene expression data indicative of either a good or a poor prognosis for acute lymphoblastic leukemia with MLL rearrangements, using our system, showed newly discovered signaling cross-talk.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.

PubMed

Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi

2007-10-04

In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Intracellular directed evolution of proteins from combinatorial libraries based on conditional phage replication.

PubMed

Brödel, Andreas K; Jaramillo, Alfonso; Isalan, Mark

2017-09-01

Directed evolution is a powerful tool to improve the characteristics of biomolecules. Here we present a protocol for the intracellular evolution of proteins with distinct differences and advantages in comparison with established techniques. These include the ability to select for a particular function from a library of protein variants inside cells, minimizing undesired coevolution and propagation of nonfunctional library members, as well as allowing positive and negative selection logics using basally active promoters. A typical evolution experiment comprises the following stages: (i) preparation of a combinatorial M13 phagemid (PM) library expressing variants of the gene of interest (GOI) and preparation of the Escherichia coli host cells; (ii) multiple rounds of an intracellular selection process toward a desired activity; and (iii) the characterization of the evolved target proteins. The system has been developed for the selection of new orthogonal transcription factors (TFs) but is capable of evolving any gene-or gene circuit function-that can be linked to conditional M13 phage replication. Here we demonstrate our approach using as an example the directed evolution of the bacteriophage λ cI TF against two synthetic bidirectional promoters. The evolved TF variants enable simultaneous activation and repression against their engineered promoters and do not cross-react with the wild-type promoter, thus ensuring orthogonality. This protocol requires no special equipment, allowing synthetic biologists and general users to evolve improved biomolecules within ∼7 weeks.

Determination of antigenicity-altering patches on the major surface protein of human influenza A/H3N2 viruses

PubMed Central

Kratsch, Christina; Klingen, Thorsten R.; Mümken, Linda; Steinbrück, Lars; McHardy, Alice C.

2016-01-01

Human influenza viruses are rapidly evolving RNA viruses that cause short-term respiratory infections with substantial morbidity and mortality in annual epidemics. Uncovering the general principles of viral coevolution with human hosts is important for pathogen surveillance and vaccine design. Protein regions are an appropriate model for the interactions between two macromolecules, but the currently used epitope definition for the major antigen of influenza viruses, namely hemagglutinin, is very broad. Here, we combined genetic, evolutionary, antigenic, and structural information to determine the most relevant regions of the hemagglutinin of human influenza A/H3N2 viruses for interaction with human immunoglobulins. We estimated the antigenic weights of amino acid changes at individual sites from hemagglutination inhibition data using antigenic tree inference followed by spatial clustering of antigenicity-altering protein sites on the protein structure. This approach determined six relevant areas (patches) for antigenic variation that had a key role in the past antigenic evolution of the viruses. Previous transitions between successive predominating antigenic types of H3N2 viruses always included amino acid changes in either the first or second antigenic patch. Interestingly, there was only partial overlap between the antigenic patches and the patches under strong positive selection. Therefore, besides alterations of antigenicity, other interactions with the host may shape the evolution of human influenza A/H3N2 viruses. PMID:27774294

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.

Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

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

Ba, Qian; Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing; Li, Junyang

2015-03-01

Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong tomore » the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.« less

An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

PubMed

Mallik, Mrinmay Kumar

2018-02-07

Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploration of Panviral Proteome: High-Throughput Cloning and Functional Implications in Virus-host Interactions

PubMed Central

Yu, Xiaobo; Bian, Xiaofang; Throop, Andrea; Song, Lusheng; Moral, Lerys Del; Park, Jin; Seiler, Catherine; Fiacco, Michael; Steel, Jason; Hunter, Preston; Saul, Justin; Wang, Jie; Qiu, Ji; Pipas, James M.; LaBaer, Joshua

2014-01-01

Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies. PMID:24955142

Exploration of panviral proteome: high-throughput cloning and functional implications in virus-host interactions.

PubMed

Yu, Xiaobo; Bian, Xiaofang; Throop, Andrea; Song, Lusheng; Moral, Lerys Del; Park, Jin; Seiler, Catherine; Fiacco, Michael; Steel, Jason; Hunter, Preston; Saul, Justin; Wang, Jie; Qiu, Ji; Pipas, James M; LaBaer, Joshua

2014-01-01

Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies.

Finding Correlation between Protein Protein Interaction Modules Using Semantic Web Techniques

NASA Astrophysics Data System (ADS)

Kargar, Mehdi; Moaven, Shahrouz; Abolhassani, Hassan

Many complex networks such as social networks and computer show modular structures, where edges between nodes are much denser within modules than between modules. It is strongly believed that cellular networks are also modular, reflecting the relative independence and coherence of different functional units in a cell. In this paper we used a human curated dataset. In this paper we consider each module in the PPI network as ontology. Using techniques in ontology alignment, we compare each pair of modules in the network. We want to see that is there a correlation between the structure of each module or they have totally different structures. Our results show that there is no correlation between proteins in a protein protein interaction network.

Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks

DTIC Science & Technology

2012-09-21

Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks Paulo Shakarian1*, J. Kenneth Wickiser2 1 Paulo Shakarian...significantly attacked. Citation: Shakarian P, Wickiser JK (2012) Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks...to 00-00-2012 4. TITLE AND SUBTITLE Similar Pathogen Targets in Arabidopsis thaliana and Homo sapiens Protein Networks 5a. CONTRACT NUMBER 5b

The network organization of protein interactions in the spliceosome is reproduced by the simple rules of food-web models

PubMed Central

Pires, Mathias M.; Cantor, Maurício; Guimarães, Paulo R.; de Aguiar, Marcus A. M.; dos Reis, Sérgio F.; Coltri, Patricia P.

2015-01-01

The network structure of biological systems provides information on the underlying processes shaping their organization and dynamics. Here we examined the structure of the network depicting protein interactions within the spliceosome, the macromolecular complex responsible for splicing in eukaryotic cells. We show the interactions of less connected spliceosome proteins are nested subsets of the connections of the highly connected proteins. At the same time, the network has a modular structure with groups of proteins sharing similar interaction patterns. We then investigated the role of affinity and specificity in shaping the spliceosome network by adapting a probabilistic model originally designed to reproduce food webs. This food-web model was as successful in reproducing the structure of protein interactions as it is in reproducing interactions among species. The good performance of the model suggests affinity and specificity, partially determined by protein size and the timing of association to the complex, may be determining network structure. Moreover, because network models allow building ensembles of realistic networks while encompassing uncertainty they can be useful to examine the dynamics and vulnerability of intracelullar processes. Unraveling the mechanisms organizing the spliceosome interactions is important to characterize the role of individual proteins on splicing catalysis and regulation. PMID:26443080

Network representation of protein interactions: Theory of graph description and analysis.

PubMed

Kurzbach, Dennis

2016-09-01

A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue-resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three-dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin. © 2016 The Protein Society.

Topology association analysis in weighted protein interaction network for gene prioritization

NASA Astrophysics Data System (ADS)

Wu, Shunyao; Shao, Fengjing; Zhang, Qi; Ji, Jun; Xu, Shaojie; Sun, Rencheng; Sun, Gengxin; Du, Xiangjun; Sui, Yi

2016-11-01

Although lots of algorithms for disease gene prediction have been proposed, the weights of edges are rarely taken into account. In this paper, the strengths of topology associations between disease and essential genes are analyzed in weighted protein interaction network. Empirical analysis demonstrates that compared to other genes, disease genes are weakly connected with essential genes in protein interaction network. Based on this finding, a novel global distance measurement for gene prioritization with weighted protein interaction network is proposed in this paper. Positive and negative flow is allocated to disease and essential genes, respectively. Additionally network propagation model is extended for weighted network. Experimental results on 110 diseases verify the effectiveness and potential of the proposed measurement. Moreover, weak links play more important role than strong links for gene prioritization, which is meaningful to deeply understand protein interaction network.

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.

Solvated dissipative electro-elastic network model of hydrated proteins

NASA Astrophysics Data System (ADS)

Martin, Daniel R.; Matyushov, Dmitry V.

2012-10-01

Elastic network models coarse grain proteins into a network of residue beads connected by springs. We add dissipative dynamics to this mechanical system by applying overdamped Langevin equations of motion to normal-mode vibrations of the network. In addition, the network is made heterogeneous and softened at the protein surface by accounting for hydration of the ionized residues. Solvation changes the network Hessian in two ways. Diagonal solvation terms soften the spring constants and off-diagonal dipole-dipole terms correlate displacements of the ionized residues. The model is used to formulate the response functions of the electrostatic potential and electric field appearing in theories of redox reactions and spectroscopy. We also formulate the dielectric response of the protein and find that solvation of the surface ionized residues leads to a slow relaxation peak in the dielectric loss spectrum, about two orders of magnitude slower than the main peak of protein relaxation. Finally, the solvated network is used to formulate the allosteric response of the protein to ion binding. The global thermodynamics of ion binding is not strongly affected by the network solvation, but it dramatically enhances conformational changes in response to placing a charge at the active site of the protein.

Detection and sequence/structure mapping of biophysical constraints to protein variation in saturated mutational libraries and protein sequence alignments with a dedicated server.

PubMed

Abriata, Luciano A; Bovigny, Christophe; Dal Peraro, Matteo

2016-06-17

Protein variability can now be studied by measuring high-resolution tolerance-to-substitution maps and fitness landscapes in saturated mutational libraries. But these rich and expensive datasets are typically interpreted coarsely, restricting detailed analyses to positions of extremely high or low variability or dubbed important beforehand based on existing knowledge about active sites, interaction surfaces, (de)stabilizing mutations, etc. Our new webserver PsychoProt (freely available without registration at http://psychoprot.epfl.ch or at http://lucianoabriata.altervista.org/psychoprot/index.html ) helps to detect, quantify, and sequence/structure map the biophysical and biochemical traits that shape amino acid preferences throughout a protein as determined by deep-sequencing of saturated mutational libraries or from large alignments of naturally occurring variants. We exemplify how PsychoProt helps to (i) unveil protein structure-function relationships from experiments and from alignments that are consistent with structures according to coevolution analysis, (ii) recall global information about structural and functional features and identify hitherto unknown constraints to variation in alignments, and (iii) point at different sources of variation among related experimental datasets or between experimental and alignment-based data. Remarkably, metabolic costs of the amino acids pose strong constraints to variability at protein surfaces in nature but not in the laboratory. This and other differences call for caution when extrapolating results from in vitro experiments to natural scenarios in, for example, studies of protein evolution. We show through examples how PsychoProt can be a useful tool for the broad communities of structural biology and molecular evolution, particularly for studies about protein modeling, evolution and design.

Electrostatically Accelerated Encounter and Folding for Facile Recognition of Intrinsically Disordered Proteins

PubMed Central

Ganguly, Debabani; Zhang, Weihong; Chen, Jianhan

2013-01-01

Achieving facile specific recognition is essential for intrinsically disordered proteins (IDPs) that are involved in cellular signaling and regulation. Consideration of the physical time scales of protein folding and diffusion-limited protein-protein encounter has suggested that the frequent requirement of protein folding for specific IDP recognition could lead to kinetic bottlenecks. How IDPs overcome such potential kinetic bottlenecks to viably function in signaling and regulation in general is poorly understood. Our recent computational and experimental study of cell-cycle regulator p27 (Ganguly et al., J. Mol. Biol. (2012)) demonstrated that long-range electrostatic forces exerted on enriched charges of IDPs could accelerate protein-protein encounter via “electrostatic steering” and at the same time promote “folding-competent” encounter topologies to enhance the efficiency of IDP folding upon encounter. Here, we further investigated the coupled binding and folding mechanisms and the roles of electrostatic forces in the formation of three IDP complexes with more complex folded topologies. The surface electrostatic potentials of these complexes lack prominent features like those observed for the p27/Cdk2/cyclin A complex to directly suggest the ability of electrostatic forces to facilitate folding upon encounter. Nonetheless, similar electrostatically accelerated encounter and folding mechanisms were consistently predicted for all three complexes using topology-based coarse-grained simulations. Together with our previous analysis of charge distributions in known IDP complexes, our results support a prevalent role of electrostatic interactions in promoting efficient coupled binding and folding for facile specific recognition. These results also suggest that there is likely a co-evolution of IDP folded topology, charge characteristics, and coupled binding and folding mechanisms, driven at least partially by the need to achieve fast association kinetics for cellular signaling and regulation. PMID:24278008

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, PCIFI was used to identify protein complexes in real PPI network data and the protein complexes it found were matched against those that were previously known in MIPS. The results show that PCIFI can be an effective technique for the identification of protein complexes. The protein complexes it found can match more known protein complexes with a smaller false-alarm rate and can provide useful insights into the understanding of the functional interdependence relationships between proteins in protein complexes.

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.

Receptor-like kinases in plant innate immunity.

PubMed

Wu, Ying; Zhou, Jian-Min

2013-12-01

Plants employ a highly effective surveillance system to detect potential pathogens, which is critical for the success of land plants in an environment surrounded by numerous microbes. Recent efforts have led to the identification of a number of immune receptors and components of immune receptor complexes. It is now clear that receptor-like kinases (RLKs) and receptor-like proteins (RLPs) are key pattern-recognition receptors (PRRs) for microbe- and plant-derived molecular patterns that are associated with pathogen invasion. RLKs and RLPs involved in immune signaling belong to large gene families in plants and have undergone lineage specific expansion. Molecular evolution and population studies on phytopathogenic molecular signatures and their receptors have provided crucial insight into the co-evolution between plants and pathogens. [Figure: see text] Jian-Min Zhou (Corresponding author). © 2013 Institute of Botany, Chinese Academy of Sciences.

Plant-bacterial pathogen interactions mediated by type III effectors.

PubMed

Feng, Feng; Zhou, Jian-Min

2012-08-01

Effectors secreted by the bacterial type III system play a central role in the interaction between Gram-negative bacterial pathogens and their host plants. Recent advances in the effector studies have helped cementing several key concepts concerning bacterial pathogenesis, plant immunity, and plant-pathogen co-evolution. Type III effectors use a variety of biochemical mechanisms to target specific host proteins or DNA for pathogenesis. The identifications of their host targets led to the identification of novel components of plant innate immune system. Key modules of plant immune signaling pathways such as immune receptor complexes and MAPK cascades have emerged as a major battle ground for host-pathogen adaptation. These modules are attacked by multiple type III effectors, and some components of these modules have evolved to actively sense the effectors and trigger immunity. Copyright © 2012 Elsevier Ltd. All rights reserved.

Co-evolution of insect proteases and plant protease inhibitors.

PubMed

Jongsma, Maarten A; Beekwilder, Jules

2011-08-01

Plants are at the basis of the food chain, but there is no such thing as a "free lunch" for herbivores. To promote reproductive success, plants evolved multi-layered defensive tactics to avoid or discourage herbivory. To the detriment of plants, herbivores, in turn, evolved intricate strategies to find, eat, and successfully digest essential plant parts to raise their own offspring. In this battle the digestive tract is the arena determining final victory or defeat as measured by growth or starvation of the herbivore. Earlier, specific molecular opponents were identified as proteases and inhibitors: digestive proteases of herbivores evolved structural motifs to occlude plant protease inhibitors, or alternatively, the insects evolved proteases capable of specifically degrading the host plant inhibitors. In response plant inhibitors evolved hyper-variable and novel protein folds to remain active against potential herbivores. At the level of protease regulation in herbivorous insects, it was shown that inhibition-insensitive digestive proteases are up-regulated when sensitive proteases are inhibited. The way this regulation operates in mammals is known as negative feedback by gut-luminal factors, so-called 'monitor peptides' that are sensitive to the concentration of active enzymes. We propose that regulation of gut enzymes by endogenous luminal factors has been an open invitation to plants to "hijack" this regulation by evolving receptor antagonists, although yet these plant factors have not been identified. In future research the question of the co-evolution of insect proteases and plant inhibitors should, therefore, be better approached from a systems level keeping in mind that evolution is fundamentally opportunistic and that the plant's fitness is primarily improved by lowering the availability of essential amino acids to an herbivore by any available mechanism.

A protein domain-based interactome network for C. elegans early embryogenesis

PubMed Central

Boxem, Mike; Maliga, Zoltan; Klitgord, Niels; Li, Na; Lemmens, Irma; Mana, Miyeko; de Lichtervelde, Lorenzo; Mul, Joram D.; van de Peut, Diederik; Devos, Maxime; Simonis, Nicolas; Yildirim, Muhammed A.; Cokol, Murat; Kao, Huey-Ling; de Smet, Anne-Sophie; Wang, Haidong; Schlaitz, Anne-Lore; Hao, Tong; Milstein, Stuart; Fan, Changyu; Tipsword, Mike; Drew, Kevin; Galli, Matilde; Rhrissorrakrai, Kahn; Drechsel, David; Koller, Daphne; Roth, Frederick P.; Iakoucheva, Lilia M.; Dunker, A. Keith; Bonneau, Richard; Gunsalus, Kristin C.; Hill, David E.; Piano, Fabio; Tavernier, Jan; van den Heuvel, Sander; Hyman, Anthony A.; Vidal, Marc

2008-01-01

Summary Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or “interactome” networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed new insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms. PMID:18692475

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.

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

PubMed Central

Cocco, Simona; Monasson, Remi; Weigt, Martin

2013-01-01

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant ‘patterns’ of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold. PMID:23990764

Unbiased and targeted mass spectrometry for the HDL proteome.

PubMed

Singh, Sasha A; Aikawa, Masanori

2017-02-01

Mass spectrometry is an ever evolving technology that is equipped with a variety of tools for protein research. Some lipoprotein studies, especially those pertaining to HDL biology, have been exploiting the versatility of mass spectrometry to understand HDL function through its proteome. Despite the role of mass spectrometry in advancing research as a whole, however, the technology remains obscure to those without hands on experience, but still wishing to understand it. In this review, we walk the reader through the coevolution of common mass spectrometry workflows and HDL research, starting from the basic unbiased mass spectrometry methods used to profile the HDL proteome to the most recent targeted methods that have enabled an unprecedented view of HDL metabolism. Unbiased global proteomics have demonstrated that the HDL proteome is organized into subgroups across the HDL size fractions providing further evidence that HDL functional heterogeneity is in part governed by its varying protein constituents. Parallel reaction monitoring, a novel targeted mass spectrometry method, was used to monitor the metabolism of HDL apolipoproteins in humans and revealed that apolipoproteins contained within the same HDL size fraction exhibit diverse metabolic properties. Mass spectrometry provides a variety of tools and strategies to facilitate understanding, through its proteins, the complex biology of HDL.

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.

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

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.

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.

Relationships and Evolution of Double-Stranded RNA Totiviruses of Yeasts Inferred from Analysis of L-A-2 and L-BC Variants in Wine Yeast Strain Populations

PubMed Central

Rodríguez-Cousiño, Nieves

2016-01-01

ABSTRACT Saccharomyces cerevisiae killer strains secrete a protein toxin active on nonkiller strains of the same (or other) yeast species. Different killer toxins, K1, K2, K28, and Klus, have been described. Each toxin is encoded by a medium-size (1.5- to 2.3-kb) M double-stranded RNA (dsRNA) located in the cytoplasm. M dsRNAs require L-A helper virus for maintenance. L-A belongs to the Totiviridae family, and its dsRNA genome of 4.6 kb codes for the major capsid protein Gag and a minor Gag-Pol protein, which form the virions that separately encapsidate L-A or the M satellites. Different L-A variants exist in nature; on average, 24% of their nucleotides are different. Previously, we reported that L-A-lus was specifically associated with Mlus, suggesting coevolution, and proposed a role of the toxin-encoding M dsRNAs in the appearance of new L-A variants. Here we confirm this by analyzing the helper virus in K2 killer wine strains, which we named L-A-2. L-A-2 is required for M2 maintenance, and neither L-A nor L-A-lus shows helper activity for M2 in the same genetic background. This requirement is overcome when coat proteins are provided in large amounts by a vector or in ski mutants. The genome of another totivirus, L-BC, frequently accompanying L-A in the same cells shows a lower degree of variation than does L-A (about 10% of nucleotides are different). Although L-BC has no helper activity for M dsRNAs, distinct L-BC variants are associated with a particular killer strain. The so-called L-BC-lus (in Klus strains) and L-BC-2 (in K2 strains) are analyzed. IMPORTANCE Killer strains of S. cerevisiae secrete protein toxins that kill nonkiller yeasts. The “killer phenomenon” depends on two dsRNA viruses: L-A and M. M encodes the toxin, and L-A, the helper virus, provides the capsids for both viruses. Different killer toxins exist: K1, K2, K28, and Klus, encoded on different M viruses. Our data indicate that each M dsRNA depends on a specific helper virus; these helper viruses have nucleotide sequences that may be as much as 26% different, suggesting coevolution. In wine environments, K2 and Klus strains frequently coexist. We have previously characterized the association of Mlus and L-A-lus. Here we sequence and characterize L-A-2, the helper virus of M2, establishing the helper virus requirements of M2, which had not been completely elucidated. We also report the existence of two specific L-BC totiviruses in Klus and K2 strains with about 10% of their nucleotides different, suggesting different evolutionary histories from those of L-A viruses. PMID:27940540

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

PubMed

Al-Anzi, Bader; Arpp, Patrick; Gerges, Sherif; Ormerod, Christopher; Olsman, Noah; Zinn, Kai

2015-05-01

An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

Social evolution. Oxytocin-gaze positive loop and the coevolution of human-dog bonds.

PubMed

Nagasawa, Miho; Mitsui, Shouhei; En, Shiori; Ohtani, Nobuyo; Ohta, Mitsuaki; Sakuma, Yasuo; Onaka, Tatsushi; Mogi, Kazutaka; Kikusui, Takefumi

2015-04-17

Human-like modes of communication, including mutual gaze, in dogs may have been acquired during domestication with humans. We show that gazing behavior from dogs, but not wolves, increased urinary oxytocin concentrations in owners, which consequently facilitated owners' affiliation and increased oxytocin concentration in dogs. Further, nasally administered oxytocin increased gazing behavior in dogs, which in turn increased urinary oxytocin concentrations in owners. These findings support the existence of an interspecies oxytocin-mediated positive loop facilitated and modulated by gazing, which may have supported the coevolution of human-dog bonding by engaging common modes of communicating social attachment. Copyright © 2015, American Association for the Advancement of Science.

Coevolution of dependency distance, hierarchical structure and word order. Comment on "Dependency distance: a new perspective on syntactic patterns in natural languages" by Haitao Liu et al.

NASA Astrophysics Data System (ADS)

Jing, Yingqi

2017-07-01

Exploring the relationships between structural rules and their linearization constraints have been a central issue in formal syntax and linguistic typology [1]. Liu et al. give a historical overview of the investigation of dependency distance minimization (DDM) in various fields, and specify its potential connections with the graphic patterns of syntactic structure and the linear ordering of words and constituents in real sentences [2]. This comment focuses on discussing the relations between dependency distance (DD), hierarchical structure and word order, and advocates further study on the coevolution of these traits in language histories.

Comparative ribotyping of Staphylococcus intermedius isolated from members of the Canoidea gives possible evidence for host-specificity and co-evolution of bacteria and hosts.

PubMed

Aarestrup, F M

2001-07-01

A total of 41 Staphylococcus intermedius isolates were isolated from skin of healthy members of six phylogenetic groups within the Canoidea (the dog family, skunk subfamily, weasel subfamily, racoon family, red panda and bear family) of different geographical origin and compared by EcoRI ribotyping and cluster analysis. The S. intermedius isolates from the different families and subfamilies clustered together in separate groups, almost completely following the phylogenetic relationship of the animal hosts. These ribotype data indicate host-specificity of different types of S. intermedius and suggest co-evolution between the animal hosts within the Canoidea and S. intermedius.

Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks

NASA Astrophysics Data System (ADS)

White, Forest M.; Wolf-Yadlin, Alejandro

2016-06-01

Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

Uncovering the spatially distant feedback loops of global trade: A network and input-output approach.

PubMed

Prell, Christina; Sun, Laixiang; Feng, Kuishuang; He, Jiaying; Hubacek, Klaus

2017-05-15

Land-use change is increasingly driven by global trade. The term "telecoupling" has been gaining ground as a means to describe how human actions in one part of the world can have spatially distant impacts on land and land-use in another. These interactions can, over time, create both direct and spatially distant feedback loops, in which human activity and land use mutually impact one another over great expanses. In this paper, we develop an analytical framework to clarify spatially distant feedbacks in the case of land use and global trade. We use an innovative mix of multi-regional input-output (MRIO) analysis and stochastic actor-oriented models (SAOMs) for analyzing the co-evolution of changes in trade network patterns with those of land use, as embodied in trade. Our results indicate that the formation of trade ties and changes in embodied land use mutually impact one another, and further, that these changes are linked to disparities in countries' wealth. Through identifying this feedback loop, our results support ongoing discussions about the unequal trade patterns between rich and poor countries that result in uneven distributions of negative environmental impacts. Finally, evidence for this feedback loop is present even when controlling for a number of underlying mechanisms, such as countries' land endowments, their geographical distance from one another, and a number of endogenous network tendencies. Copyright © 2017 Elsevier B.V. All rights reserved.

Advances on plant-pathogen interactions from molecular toward systems biology perspectives.

PubMed

Peyraud, Rémi; Dubiella, Ullrich; Barbacci, Adelin; Genin, Stéphane; Raffaele, Sylvain; Roby, Dominique

2017-05-01

In the past 2 decades, progress in molecular analyses of the plant immune system has revealed key elements of a complex response network. Current paradigms depict the interaction of pathogen-secreted molecules with host target molecules leading to the activation of multiple plant response pathways. Further research will be required to fully understand how these responses are integrated in space and time, and exploit this knowledge in agriculture. In this review, we highlight systems biology as a promising approach to reveal properties of molecular plant-pathogen interactions and predict the outcome of such interactions. We first illustrate a few key concepts in plant immunity with a network and systems biology perspective. Next, we present some basic principles of systems biology and show how they allow integrating multiomics data and predict cell phenotypes. We identify challenges for systems biology of plant-pathogen interactions, including the reconstruction of multiscale mechanistic models and the connection of host and pathogen models. Finally, we outline studies on resistance durability through the robustness of immune system networks, the identification of trade-offs between immunity and growth and in silico plant-pathogen co-evolution as exciting perspectives in the field. We conclude that the development of sophisticated models of plant diseases incorporating plant, pathogen and climate properties represent a major challenge for agriculture in the future. © 2016 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae

PubMed Central

Jarnuczak, Andrew F.; Eyers, Claire E.; Schwartz, Jean‐Marc; Grant, Christopher M.

2015-01-01

Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC‐based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs. PMID:25689132

The N and C Termini of ZO-1 Are Surrounded by Distinct Proteins and Functional Protein Networks*

PubMed Central

Van Itallie, Christina M.; Aponte, Angel; Tietgens, Amber Jean; Gucek, Marjan; Fredriksson, Karin; Anderson, James Melvin

2013-01-01

The proteins and functional protein networks of the tight junction remain incompletely defined. Among the currently known proteins are barrier-forming proteins like occludin and the claudin family; scaffolding proteins like ZO-1; and some cytoskeletal, signaling, and cell polarity proteins. To define a more complete list of proteins and infer their functional implications, we identified the proteins that are within molecular dimensions of ZO-1 by fusing biotin ligase to either its N or C terminus, expressing these fusion proteins in Madin-Darby canine kidney epithelial cells, and purifying and identifying the resulting biotinylated proteins by mass spectrometry. Of a predicted proteome of ∼9000, we identified more than 400 proteins tagged by biotin ligase fused to ZO-1, with both identical and distinct proteins near the N- and C-terminal ends. Those proximal to the N terminus were enriched in transmembrane tight junction proteins, and those proximal to the C terminus were enriched in cytoskeletal proteins. We also identified many unexpected but easily rationalized proteins and verified partial colocalization of three of these proteins with ZO-1 as examples. In addition, functional networks of interacting proteins were tagged, such as the basolateral but not apical polarity network. These results provide a rich inventory of proteins and potential novel insights into functions and protein networks that should catalyze further understanding of tight junction biology. Unexpectedly, the technique demonstrates high spatial resolution, which could be generally applied to defining other subcellular protein compartmentalization. PMID:23553632

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.

Human Dopamine Receptors Interaction Network (DRIN): a systems biology perspective on topology, stability and functionality of the network.

PubMed

Podder, Avijit; Jatana, Nidhi; Latha, N

2014-09-21

Dopamine receptors (DR) are one of the major neurotransmitter receptors present in human brain. Malfunctioning of these receptors is well established to trigger many neurological and psychiatric disorders. Taking into consideration that proteins function collectively in a network for most of the biological processes, the present study is aimed to depict the interactions between all dopamine receptors following a systems biology approach. To capture comprehensive interactions of candidate proteins associated with human dopamine receptors, we performed a protein-protein interaction network (PPIN) analysis of all five receptors and their protein partners by mapping them into human interactome and constructed a human Dopamine Receptors Interaction Network (DRIN). We explored the topology of dopamine receptors as molecular network, revealing their characteristics and the role of central network elements. More to the point, a sub-network analysis was done to determine major functional clusters in human DRIN that govern key neurological pathways. Besides, interacting proteins in a pathway were characterized and prioritized based on their affinity for utmost drug molecules. The vulnerability of different networks to the dysfunction of diverse combination of components was estimated under random and direct attack scenarios. To the best of our knowledge, the current study is unique to put all five dopamine receptors together in a common interaction network and to understand the functionality of interacting proteins collectively. Our study pinpointed distinctive topological and functional properties of human dopamine receptors that have helped in identifying potential therapeutic drug targets in the dopamine interaction network. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

PubMed

Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

2018-05-08

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

A human functional protein interaction network and its application to cancer data analysis

PubMed Central

2010-01-01

Background One challenge facing biologists is to tease out useful information from massive data sets for further analysis. A pathway-based analysis may shed light by projecting candidate genes onto protein functional relationship networks. We are building such a pathway-based analysis system. Results We have constructed a protein functional interaction network by extending curated pathways with non-curated sources of information, including protein-protein interactions, gene coexpression, protein domain interaction, Gene Ontology (GO) annotations and text-mined protein interactions, which cover close to 50% of the human proteome. By applying this network to two glioblastoma multiforme (GBM) data sets and projecting cancer candidate genes onto the network, we found that the majority of GBM candidate genes form a cluster and are closer than expected by chance, and the majority of GBM samples have sequence-altered genes in two network modules, one mainly comprising genes whose products are localized in the cytoplasm and plasma membrane, and another comprising gene products in the nucleus. Both modules are highly enriched in known oncogenes, tumor suppressors and genes involved in signal transduction. Similar network patterns were also found in breast, colorectal and pancreatic cancers. Conclusions We have built a highly reliable functional interaction network upon expert-curated pathways and applied this network to the analysis of two genome-wide GBM and several other cancer data sets. The network patterns revealed from our results suggest common mechanisms in the cancer biology. Our system should provide a foundation for a network or pathway-based analysis platform for cancer and other diseases. PMID:20482850

Optimal network alignment with graphlet degree vectors.

PubMed

Milenković, Tijana; Ng, Weng Leong; Hayes, Wayne; Przulj, Natasa

2010-06-30

Important biological information is encoded in the topology of biological networks. Comparative analyses of biological networks are proving to be valuable, as they can lead to transfer of knowledge between species and give deeper insights into biological function, disease, and evolution. We introduce a new method that uses the Hungarian algorithm to produce optimal global alignment between two networks using any cost function. We design a cost function based solely on network topology and use it in our network alignment. Our method can be applied to any two networks, not just biological ones, since it is based only on network topology. We use our new method to align protein-protein interaction networks of two eukaryotic species and demonstrate that our alignment exposes large and topologically complex regions of network similarity. At the same time, our alignment is biologically valid, since many of the aligned protein pairs perform the same biological function. From the alignment, we predict function of yet unannotated proteins, many of which we validate in the literature. Also, we apply our method to find topological similarities between metabolic networks of different species and build phylogenetic trees based on our network alignment score. The phylogenetic trees obtained in this way bear a striking resemblance to the ones obtained by sequence alignments. Our method detects topologically similar regions in large networks that are statistically significant. It does this independent of protein sequence or any other information external to network topology.

Architecture and dynamics of overlapped RNA regulatory networks.

PubMed

Lapointe, Christopher P; Preston, Melanie A; Wilinski, Daniel; Saunders, Harriet A J; Campbell, Zachary T; Wickens, Marvin

2017-11-01

A single protein can bind and regulate many mRNAs. Multiple proteins with similar specificities often bind and control overlapping sets of mRNAs. Yet little is known about the architecture or dynamics of overlapped networks. We focused on three proteins with similar structures and related RNA-binding specificities-Puf3p, Puf4p, and Puf5p of S. cerevisiae Using RNA Tagging, we identified a "super-network" comprised of four subnetworks: Puf3p, Puf4p, and Puf5p subnetworks, and one controlled by both Puf4p and Puf5p. The architecture of individual subnetworks, and thus the super-network, is determined by competition among particular PUF proteins to bind mRNAs, their affinities for binding elements, and the abundances of the proteins. The super-network responds dramatically: The remaining network can either expand or contract. These strikingly opposite outcomes are determined by an interplay between the relative abundance of the RNAs and proteins, and their affinities for one another. The diverse interplay between overlapping RNA-protein networks provides versatile opportunities for regulation and evolution. © 2017 Lapointe et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

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.

Interplay Between Protein Homeostasis Networks in Protein Aggregation and Proteotoxicity

PubMed Central

Douglas, Peter M.; Cyr, Douglas M.

2010-01-01

The misfolding and aggregation of disease proteins is characteristic of numerous neurodegenerative diseases. Particular neuronal populations are more vulnerable to proteotoxicity while others are more apt to tolerate the misfolding and aggregation of disease proteins. Thus, the cellular environment must play a significant role in determining whether disease proteins are converted into toxic or benign forms. The endomembrane network of eukaryotes divides the cell into different subcellular compartments that possess distinct sets of molecular chaperones and protein interaction networks. Chaperones act as agonists and antagonists of disease protein aggregation to prevent the accumulation of toxic intermediates in the aggregation pathway. Interacting partners can also modulate the conformation and localization of disease proteins and thereby influence proteotoxicity. Thus, interplay between these protein homeostasis network components can modulate the self-association of disease proteins and determine whether they elicit a toxic or benign outcome. PMID:19768782

Fanconi Anemia Core Complex Gene Promoters Harbor Conserved Transcription Regulatory Elements

PubMed Central

Meier, Daniel; Schindler, Detlev

2011-01-01

The Fanconi anemia (FA) gene family is a recent addition to the complex network of proteins that respond to and repair certain types of DNA damage in the human genome. Since little is known about the regulation of this novel group of genes at the DNA level, we characterized the promoters of the eight genes (FANCA, B, C, E, F, G, L and M) that compose the FA core complex. The promoters of these genes show the characteristic attributes of housekeeping genes, such as a high GC content and CpG islands, a lack of TATA boxes and a low conservation. The promoters functioned in a monodirectional way and were, in their most active regions, comparable in strength to the SV40 promoter in our reporter plasmids. They were also marked by a distinctive transcriptional start site (TSS). In the 5′ region of each promoter, we identified a region that was able to negatively regulate the promoter activity in HeLa and HEK 293 cells in isolation. The central and 3′ regions of the promoter sequences harbor binding sites for several common and rare transcription factors, including STAT, SMAD, E2F, AP1 and YY1, which indicates that there may be cross-connections to several established regulatory pathways. Electrophoretic mobility shift assays and siRNA experiments confirmed the shared regulatory responses between the prominent members of the TGF-β and JAK/STAT pathways and members of the FA core complex. Although the promoters are not well conserved, they share region and sequence specific regulatory motifs and transcription factor binding sites (TBFs), and we identified a bi-partite nature to these promoters. These results support a hypothesis based on the co-evolution of the FA core complex genes that was expanded to include their promoters. PMID:21826217

Fanconi anemia core complex gene promoters harbor conserved transcription regulatory elements.

PubMed

Meier, Daniel; Schindler, Detlev

2011-01-01

The Fanconi anemia (FA) gene family is a recent addition to the complex network of proteins that respond to and repair certain types of DNA damage in the human genome. Since little is known about the regulation of this novel group of genes at the DNA level, we characterized the promoters of the eight genes (FANCA, B, C, E, F, G, L and M) that compose the FA core complex. The promoters of these genes show the characteristic attributes of housekeeping genes, such as a high GC content and CpG islands, a lack of TATA boxes and a low conservation. The promoters functioned in a monodirectional way and were, in their most active regions, comparable in strength to the SV40 promoter in our reporter plasmids. They were also marked by a distinctive transcriptional start site (TSS). In the 5' region of each promoter, we identified a region that was able to negatively regulate the promoter activity in HeLa and HEK 293 cells in isolation. The central and 3' regions of the promoter sequences harbor binding sites for several common and rare transcription factors, including STAT, SMAD, E2F, AP1 and YY1, which indicates that there may be cross-connections to several established regulatory pathways. Electrophoretic mobility shift assays and siRNA experiments confirmed the shared regulatory responses between the prominent members of the TGF-β and JAK/STAT pathways and members of the FA core complex. Although the promoters are not well conserved, they share region and sequence specific regulatory motifs and transcription factor binding sites (TBFs), and we identified a bi-partite nature to these promoters. These results support a hypothesis based on the co-evolution of the FA core complex genes that was expanded to include their promoters.

Chimeric exchange of coronavirus nsp5 proteases (3CLpro) identifies common and divergent regulatory determinants of protease activity.

PubMed

Stobart, Christopher C; Sexton, Nicole R; Munjal, Havisha; Lu, Xiaotao; Molland, Katrina L; Tomar, Sakshi; Mesecar, Andrew D; Denison, Mark R

2013-12-01

Human coronaviruses (CoVs) such as severe acute respiratory syndrome CoV (SARS-CoV) and Middle East respiratory syndrome CoV (MERS-CoV) cause epidemics of severe human respiratory disease. A conserved step of CoV replication is the translation and processing of replicase polyproteins containing 16 nonstructural protein domains (nsp's 1 to 16). The CoV nsp5 protease (3CLpro; Mpro) processes nsp's at 11 cleavage sites and is essential for virus replication. CoV nsp5 has a conserved 3-domain structure and catalytic residues. However, the intra- and intermolecular determinants of nsp5 activity and their conservation across divergent CoVs are unknown, in part due to challenges in cultivating many human and zoonotic CoVs. To test for conservation of nsp5 structure-function determinants, we engineered chimeric betacoronavirus murine hepatitis virus (MHV) genomes encoding nsp5 proteases of human and bat alphacoronaviruses and betacoronaviruses. Exchange of nsp5 proteases from HCoV-HKU1 and HCoV-OC43, which share the same genogroup, genogroup 2a, with MHV, allowed for immediate viral recovery with efficient replication albeit with impaired fitness in direct competition with wild-type MHV. Introduction of MHV nsp5 temperature-sensitive mutations into chimeric HKU1 and OC43 nsp5 proteases resulted in clear differences in viability and temperature-sensitive phenotypes compared with MHV nsp5. These data indicate tight genetic linkage and coevolution between nsp5 protease and the genomic background and identify differences in intramolecular networks regulating nsp5 function. Our results also provide evidence that chimeric viruses within coronavirus genogroups can be used to test nsp5 determinants of function and inhibition in common isogenic backgrounds and cell types.

Co-Evolutions of Ecosystems, Societies, and Economy in Dryland Asia

NASA Astrophysics Data System (ADS)

Chen, Jiquan; Ouyang, Zutao; John, Ranjeet; Dong, Gang; Fan, Peilei

2015-04-01

This presentation aims at the interactive changes of the natural system (NS) and the human system (HS) as well as the feedbacks in time and space for dryland Asia where multiple administrative units from several countries experience similar climates, ecosystems, cultures, and traditions but different governments, land uses, economic development, and demographic changes (e.g., ethnical composition). We compiled and examined the changes in major measures for ecosystems (e.g., PAR, LAI, GPP, ET), economy (GDP, export/import, EGS), and human demography (e.g., population, health, education) between 1981 through 2011 (30+ variables) for six Central Asian countries (Afghanistan, Turkmenistan, Tajikistan, Uzbekistan, Kazakhstan, Kyrgyzstan) and two East Asian countries (Mongolia and China). Particular attention was made to understand the co-evolutions of the ratios between the elements of HS and NS, such as: GDP: GPP, PET: FWW, R: PDSI, EGS: GPP, etc., so that feedbacks and interactions can be empirically studied. Spatial and temporal changes of each measure, as well as their ratios, were quantified to highlight the relative contributions of human activities (e.g., policy) and biophysical changes (e.g., climate). We found some tight connections between the HS and NS variables, but the co-evolutions have to be understood in the context of governments, policy, and other major institutional shifts.

Coevolution of antibiotic production and counter-resistance in soil bacteria.

PubMed

Laskaris, Paris; Tolba, Sahar; Calvo-Bado, Leo; Wellington, Elizabeth M; Wellington, Liz

2010-03-01

We present evidence for the coexistence and coevolution of antibiotic resistance and biosynthesis genes in soil bacteria. The distribution of the streptomycin (strA) and viomycin (vph) resistance genes was examined in Streptomyces isolates. strA and vph were found either within a biosynthetic gene cluster or independently. Streptomyces griseus strains possessing the streptomycin cluster formed part of a clonal complex. All S. griseus strains possessing solely strA belonged to two clades; both were closely related to the streptomycin producers. Other more distantly related S. griseus strains did not contain strA. S. griseus strains with only vph also formed two clades, but they were more distantly related to the producers and to one another. The expression of the strA gene was constitutive in a resistance-only strain whereas streptomycin producers showed peak strA expression in late log phase that correlates with the switch on of streptomycin biosynthesis. While there is evidence that antibiotics have diverse roles in nature, our data clearly support the coevolution of resistance in the presence of antibiotic biosynthetic capability within closely related soil dwelling bacteria. This reinforces the view that, for some antibiotics at least, the primary role is one of antibiosis during competition in soil for resources.

Selection on an antagonistic behavioral trait can drive rapid genital coevolution in the burying beetle, Nicrophorus vespilloides.

PubMed

Hopwood, Paul E; Head, Megan L; Jordan, Eleanor J; Carter, Mauricio J; Davey, Emma; Moore, Allen J; Royle, Nick J

2016-06-01

Male and female genital morphology varies widely across many taxa, and even among populations. Disentangling potential sources of selection on genital morphology is problematic because each sex is predicted to respond to adaptations in the other due to reproductive conflicts of interest. To test how variation in this sexual conflict trait relates to variation in genital morphology we used our previously developed artificial selection lines for high and low repeated mating rates. We selected for high and low repeated mating rates using monogamous pairings to eliminate contemporaneous female choice and male-male competition. Male and female genital shape responded rapidly to selection on repeated mating rate. High and low mating rate lines diverged from control lines after only 10 generations of selection. We also detected significant patterns of male and female genital shape coevolution among selection regimes. We argue that because our selection lines differ in sexual conflict, these results support the hypothesis that sexually antagonistic coevolution can drive the rapid divergence of genital morphology. The greatest divergence in morphology corresponded with lines in which the resolution of sexual conflict over mating rate was biased in favor of male interests. © 2016 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Evolution of female multiple mating: A quantitative model of the “sexually selected sperm” hypothesis

PubMed Central

Bocedi, Greta; Reid, Jane M

2015-01-01

Explaining the evolution and maintenance of polyandry remains a key challenge in evolutionary ecology. One appealing explanation is the sexually selected sperm (SSS) hypothesis, which proposes that polyandry evolves due to indirect selection stemming from positive genetic covariance with male fertilization efficiency, and hence with a male's success in postcopulatory competition for paternity. However, the SSS hypothesis relies on verbal analogy with “sexy-son” models explaining coevolution of female preferences for male displays, and explicit models that validate the basic SSS principle are surprisingly lacking. We developed analogous genetically explicit individual-based models describing the SSS and “sexy-son” processes. We show that the analogy between the two is only partly valid, such that the genetic correlation arising between polyandry and fertilization efficiency is generally smaller than that arising between preference and display, resulting in less reliable coevolution. Importantly, indirect selection was too weak to cause polyandry to evolve in the presence of negative direct selection. Negatively biased mutations on fertilization efficiency did not generally rescue runaway evolution of polyandry unless realized fertilization was highly skewed toward a single male, and coevolution was even weaker given random mating order effects on fertilization. Our models suggest that the SSS process is, on its own, unlikely to generally explain the evolution of polyandry. PMID:25330405

Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

PubMed

Dobata, Shigeto

2012-12-01

Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

Collapse of cooperation in evolving games.

PubMed

Stewart, Alexander J; Plotkin, Joshua B

2014-12-09

Game theory provides a quantitative framework for analyzing the behavior of rational agents. The Iterated Prisoner's Dilemma in particular has become a standard model for studying cooperation and cheating, with cooperation often emerging as a robust outcome in evolving populations. Here we extend evolutionary game theory by allowing players' payoffs as well as their strategies to evolve in response to selection on heritable mutations. In nature, many organisms engage in mutually beneficial interactions and individuals may seek to change the ratio of risk to reward for cooperation by altering the resources they commit to cooperative interactions. To study this, we construct a general framework for the coevolution of strategies and payoffs in arbitrary iterated games. We show that, when there is a tradeoff between the benefits and costs of cooperation, coevolution often leads to a dramatic loss of cooperation in the Iterated Prisoner's Dilemma. The collapse of cooperation is so extreme that the average payoff in a population can decline even as the potential reward for mutual cooperation increases. Depending upon the form of tradeoffs, evolution may even move away from the Iterated Prisoner's Dilemma game altogether. Our work offers a new perspective on the Prisoner's Dilemma and its predictions for cooperation in natural populations; and it provides a general framework to understand the coevolution of strategies and payoffs in iterated interactions.

The evolution of floral scent and olfactory preferences in pollinators: coevolution or pre-existing bias?

PubMed

Schiestl, Florian P; Dötterl, Stefan

2012-07-01

Coevolution is thought to be a major factor in shaping plant-pollinator interactions. Alternatively, plants may have evolved traits that fitted pre-existing preferences or morphologies in the pollinators. Here, we test these two scenarios in the plant family of Araceae and scarab beetles (Coleoptera, Scarabaeidae) as pollinators. We focused on floral volatile organic compounds (VOCs) and production/detection of VOCs by scarab beetles. We found phylogenetic structure in the production/detection of methoxylated aromatics in scarabs, but not plants. Within the plants, most of the compounds showed a well-supported pattern of correlated evolution with scarab-beetle pollination. In contrast, the scarabs showed no correlation between VOC production/detection and visitation to Araceae flowers, with the exception of the VOC skatole. Moreover, many VOCs were found in nonpollinating beetle groups (e.g., Melolonthinae) that are ancestors of pollinating scarabs. Importantly, none of the tested VOCs were found to have originated in pollinating taxa. Our analysis indicates a Jurassic origin of VOC production/detection in scarabs, but a Cretaceous/Paleocene origin of floral VOCs in plants. Therefore, we argue against coevolution, instead supporting the scenario of sequential evolution of floral VOCs in Araceae driven by pre-existing bias of pollinators. © 2012 The Author(s).

Coevolution in host-parasite systems: behavioural strategies of slave-making ants and their hosts.

PubMed Central

Foitzik, S.; DeHeer, C. J.; Hunjan, D. N.; Herbers, J. M.

2001-01-01

Recently, avian brood parasites and their hosts have emerged as model systems for the study of host-parasite coevolution. However, empirical studies of the highly analogous social parasites, which use the workers of another eusocial species to raise their own young, have never explicitly examined the dynamics of these systems from a coevolutionary perspective. Here, we demonstrate interpopulational variation in behavioural interactions between a socially parasitic slave-maker ant and its host that is consistent with the expectations of host-parasite coevolution. Parasite pressure, as inferred by the size, abundance and raiding frequency of Protomognathus americanus colonies, was highest in a New York population of the host Leptothorax longispinosus and lowest in a West Virginia population. As host-parasite coevolutionary theory would predict, we found that the slave-makers and the hosts from New York were more effective at raiding and defending against raiders, respectively, than were conspecifics from the West Virginia population. Some of these variations in efficacy were brought about by apparently simple shifts in behaviour. These results demonstrate that defence mechanisms against social parasites can evolve, and they give the first indications of the existence of a coevolutionary arms race between a social parasite and its host. PMID:11375101

Coevolution of coloration and colour vision?

PubMed

Lind, Olle; Henze, Miriam J; Kelber, Almut; Osorio, Daniel

2017-07-05

The evolutionary relationship between signals and animal senses has broad significance, with potential consequences for speciation, and for the efficacy and honesty of biological communication. Here we outline current understanding of the diversity of colour vision in two contrasting groups: the phylogenetically conservative birds, and the more variable butterflies. Evidence for coevolution of colour signals and vision exists in both groups, but is limited to observations of phenotypic differences between visual systems, which might be correlated with coloration. Here, to illustrate how one might interpret the evolutionary significance of such differences, we used colour vision modelling based on an avian eye to evaluate the effects of variation in three key characters: photoreceptor spectral sensitivity, oil droplet pigmentation and the proportions of different photoreceptor types. The models predict that physiologically realistic changes in any one character will have little effect, but complementary shifts in all three can substantially affect discriminability of three types of natural spectra. These observations about the adaptive landscape of colour vision may help to explain the general conservatism of photoreceptor spectral sensitivities in birds. This approach can be extended to other types of eye and spectra to inform future work on coevolution of coloration and colour vision.This article is part of the themed issue 'Animal coloration: production, perception, function and application'. © 2017 The Author(s).

Evolution of spatially structured host-parasite interactions.

PubMed

Lion, S; Gandon, S

2015-01-01

Spatial structure has dramatic effects on the demography and the evolution of species. A large variety of theoretical models have attempted to understand how local dispersal may shape the coevolution of interacting species such as host-parasite interactions. The lack of a unifying framework is a serious impediment for anyone willing to understand current theory. Here, we review previous theoretical studies in the light of a single epidemiological model that allows us to explore the effects of both host and parasite migration rates on the evolution and coevolution of various life-history traits. We discuss the impact of local dispersal on parasite virulence, various host defence strategies and local adaptation. Our analysis shows that evolutionary and coevolutionary outcomes crucially depend on the details of the host-parasite life cycle and on which life-history trait is involved in the interaction. We also discuss experimental studies that support the effects of spatial structure on the evolution of host-parasite interactions. This review highlights major similarities between some theoretical results, but it also reveals an important gap between evolutionary and coevolutionary models. We discuss possible ways to bridge this gap within a more unified framework that would reconcile spatial epidemiology, evolution and coevolution. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Host specificity and coevolution of Flavobacteriaceae endosymbionts within the siphonous green seaweed Bryopsis.

PubMed

Hollants, Joke; Leliaert, Frederik; Verbruggen, Heroen; De Clerck, Olivier; Willems, Anne

2013-06-01

The siphonous green seaweed Bryopsis harbors complex intracellular bacterial communities. Previous studies demonstrated that certain species form close, obligate associations with Flavobacteriaceae. A predominant imprint of host evolutionary history on the presence of these bacteria suggests a highly specialized association. In this study we elaborate on previous results by expanding the taxon sampling and testing for host-symbiont coevolution Therefore, we optimized a PCR protocol to directly and specifically amplify Flavobacteriaceae endosymbiont 16S rRNA gene sequences, which allowed us to screen a large number of algal samples without the need for cultivation or surface sterilization. We analyzed 146 Bryopsis samples, and 92 additional samples belonging to the Bryopsidales and other orders within the class Ulvophyceae. Results indicate that the Flavobacteriaceae endosymbionts are restricted to Bryopsis, and only occur within specific, warm-temperate and tropical clades of the genus. Statistical analyses (AMOVA) demonstrate a significant non-random host-symbiont association. Comparison of bacterial 16S rRNA and Bryopsis rbcL phylogenies, however, reveal complex host-symbiont evolutionary associations, whereby closely related hosts predominantly harbor genetically similar endosymbionts. Bacterial genotypes are rarely confined to a single Bryopsis species and most Bryopsis species harbored several Flavobacteriaceae, obscuring a clear pattern of coevolution. Copyright © 2013 Elsevier Inc. All rights reserved.

Aligning Biomolecular Networks Using Modular Graph Kernels

NASA Astrophysics Data System (ADS)

Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant

Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

Solvated dissipative electro-elastic network model of hydrated proteins

NASA Astrophysics Data System (ADS)

Martin, Daniel

2013-03-01

Elastic network models coarse grain proteins into a network of residue beads connected by springs. We add dissipative dynamics to this mechanical system by applying overdamped Langevin equations of motion to normal-mode vibrations of the network. In addition, the network is made heterogeneous and softened at the protein surface by accounting for hydration of the ionized residues. Solvation changes the network Hessian in two ways. Diagonal solvation terms soften the spring constants and off-diagonal dipole-dipole terms correlate displacements of the ionized residues. The model is used to formulate the response functions of the electrostatic potential and electric field appearing in theories of redox reactions and spectroscopy. We also formulate the dielectric response of the protein and find that solvation of the surface ionized residues leads to a slow relaxation peak in the dielectric loss spectrum, about two orders of magnitude slower than the main peak of protein relaxation. Finally, the solvated network is used to formulate the allosteric response of the protein to ion binding. The global thermodynamics of ion binding is not strongly affected by the network solvation, but it dramatically enhances conformational changes in response to placing a charge at the a the active site.

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

PubMed

Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

2016-07-01

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

Predicting protein complex geometries with a neural network.

PubMed

Chae, Myong-Ho; Krull, Florian; Lorenzen, Stephan; Knapp, Ernst-Walter

2010-03-01

A major challenge of the protein docking problem is to define scoring functions that can distinguish near-native protein complex geometries from a large number of non-native geometries (decoys) generated with noncomplexed protein structures (unbound docking). In this study, we have constructed a neural network that employs the information from atom-pair distance distributions of a large number of decoys to predict protein complex geometries. We found that docking prediction can be significantly improved using two different types of polar hydrogen atoms. To train the neural network, 2000 near-native decoys of even distance distribution were used for each of the 185 considered protein complexes. The neural network normalizes the information from different protein complexes using an additional protein complex identity input neuron for each complex. The parameters of the neural network were determined such that they mimic a scoring funnel in the neighborhood of the native complex structure. The neural network approach avoids the reference state problem, which occurs in deriving knowledge-based energy functions for scoring. We show that a distance-dependent atom pair potential performs much better than a simple atom-pair contact potential. We have compared the performance of our scoring function with other empirical and knowledge-based scoring functions such as ZDOCK 3.0, ZRANK, ITScore-PP, EMPIRE, and RosettaDock. In spite of the simplicity of the method and its functional form, our neural network-based scoring function achieves a reasonable performance in rigid-body unbound docking of proteins. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Evolution of the Max and Mlx networks in animals.

PubMed

McFerrin, Lisa G; Atchley, William R

2011-01-01

Transcription factors (TFs) are essential for the regulation of gene expression and often form emergent complexes to perform vital roles in cellular processes. In this paper, we focus on the parallel Max and Mlx networks of TFs because of their critical involvement in cell cycle regulation, proliferation, growth, metabolism, and apoptosis. A basic-helix-loop-helix-zipper (bHLHZ) domain mediates the competitive protein dimerization and DNA binding among Max and Mlx network members to form a complex system of cell regulation. To understand the importance of these network interactions, we identified the bHLHZ domain of Max and Mlx network proteins across the animal kingdom and carried out several multivariate statistical analyses. The presence and conservation of Max and Mlx network proteins in animal lineages stemming from the divergence of Metazoa indicate that these networks have ancient and essential functions. Phylogenetic analysis of the bHLHZ domain identified clear relationships among protein families with distinct points of radiation and divergence. Multivariate discriminant analysis further isolated specific amino acid changes within the bHLHZ domain that classify proteins, families, and network configurations. These analyses on Max and Mlx network members provide a model for characterizing the evolution of TFs involved in essential networks.

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

Spillover modes in multiplex games: double-edged effects on cooperation and their coevolution.

PubMed

Khoo, Tommy; Fu, Feng; Pauls, Scott

2018-05-02

In recent years, there has been growing interest in studying games on multiplex networks that account for interactions across linked social contexts. However, little is known about how potential cross-context interference, or spillover, of individual behavioural strategy impact overall cooperation. We consider three plausible spillover modes, quantifying and comparing their effects on the evolution of cooperation. In our model, social interactions take place on two network layers: repeated interactions with close neighbours in a lattice, and one-shot interactions with random individuals. Spillover can occur during the learning process with accidental cross-layer strategy transfer, or during social interactions with errors in implementation. Our analytical results, using extended pair approximation, are in good agreement with extensive simulations. We find double-edged effects of spillover: increasing the intensity of spillover can promote cooperation provided cooperation is favoured in one layer, but too much spillover is detrimental. We also discover a bistability phenomenon: spillover hinders or promotes cooperation depending on initial frequencies of cooperation in each layer. Furthermore, comparing strategy combinations emerging in each spillover mode provides good indication of their co-evolutionary dynamics with cooperation. Our results make testable predictions that inspire future research, and sheds light on human cooperation across social domains.

Phylogenetic congruence between subtropical trees and their associated fungi.

PubMed

Liu, Xubing; Liang, Minxia; Etienne, Rampal S; Gilbert, Gregory S; Yu, Shixiao

2016-12-01

Recent studies have detected phylogenetic signals in pathogen-host networks for both soil-borne and leaf-infecting fungi, suggesting that pathogenic fungi may track or coevolve with their preferred hosts. However, a phylogenetically concordant relationship between multiple hosts and multiple fungi in has rarely been investigated. Using next-generation high-throughput DNA sequencing techniques, we analyzed fungal taxa associated with diseased leaves, rotten seeds, and infected seedlings of subtropical trees. We compared the topologies of the phylogenetic trees of the soil and foliar fungi based on the internal transcribed spacer (ITS) region with the phylogeny of host tree species based on matK , rbcL , atpB, and 5.8S genes. We identified 37 foliar and 103 soil pathogenic fungi belonging to the Ascomycota and Basidiomycota phyla and detected significantly nonrandom host-fungus combinations, which clustered on both the fungus phylogeny and the host phylogeny. The explicit evidence of congruent phylogenies between tree hosts and their potential fungal pathogens suggests either diffuse coevolution among the plant-fungal interaction networks or that the distribution of fungal species tracked spatially associated hosts with phylogenetically conserved traits and habitat preferences. Phylogenetic conservatism in plant-fungal interactions within a local community promotes host and parasite specificity, which is integral to the important role of fungi in promoting species coexistence and maintaining biodiversity of forest communities.

Double-dealing behavior potentially promotes cooperation in evolutionary prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Dai, Qionglin; Li, Haihong; Cheng, Hongyan; Li, Yuting; Yang, Junzhong

2010-11-01

We investigate the effects of double-dealing behavior on cooperation in evolutionary games. Each individual in a population has two attributes: character and action. One's action may be consistent with one's character or not. We provide analytical results by a mean-field description of evolutionary prisoner's dilemma games (PDGs). Moreover, we give numerical results on different networks, ranging from square lattices to scale-free networks (SFNs). Two important conclusions have been drawn from the results on SFNs. Firstly, if only non-influential individuals (those with low degrees) have chances of becoming double-dealers, cooperation is certain to deteriorate. Secondly, when influential individuals (those with high degrees) adopt double-dealing behavior moderately, cooperation would be enhanced, which is in opposition to the traditional belief. These results help us to understand better the social phenomenon of the existence of double-dealers. In addition to the PDG, other types of games including the snowdrift game, the stag-hunt game and the harmony game have also been studied on our model. The results for these three games are also presented, which are consistent with the results for the PDG qualitatively. Furthermore, we consider our model under the co-evolution framework, in which the probability of an individual changing into a double-dealer and the individual strategy both could evolve during the evolutionary process.

The Phylogenetic Signature Underlying ATP Synthase c-Ring Compliance

DOE PAGES

Pandini, Alessandro; Kleinjung, Jens; Taylor, Willie R.; ...

2015-09-01

The proton-driven ATP synthase (F OF 1) is comprised of two rotary, stepping motors (F O and F 1) coupled by an elastic power transmission. The elastic compliance resides in the rotor module that includes the membrane-embedded FO c-ring. Proton transport by FO is firmly coupled to the rotation of the c-ring relative to other F O subunits (ab 2). It drives ATP synthesis. We used a computational method to investigate the contribution of the c-ring to the total elastic compliance. We performed principal component analysis of conformational ensembles built using distance constraints from the bovine mitochondrial c-ring x-ray structure.more » Angular rotary twist, the dominant ring motion, was estimated to show that the c-ring accounted in part for the measured compliance. Ring rotation was entrained to rotation of the external helix within each hairpin-shaped c-subunit in the ring. Ensembles of monomer and dimers extracted from complete c-rings showed that the coupling between collective ring and the individual subunit motions was independent of the size of the c-ring, which varies between organisms. Molecular determinants were identified by covariance analysis of residue coevolution and structural-alphabet-based local dynamics correlations. The residue coevolution gave a readout of subunit architecture. The dynamic couplings revealed that the hinge for both ring and subunit helix rotations was constructed from the proton-binding site and the adjacent glycine motif (IB-GGGG) in the midmembrane plane. IB-GGGG motifs were linked by long-range couplings across the ring, while intrasubunit couplings connected the motif to the conserved cytoplasmic loop and adjacent segments. The correlation with principal collective motions shows that the couplings underlie both ring rotary and bending motions. Noncontact couplings between IB-GGGG motifs matched the coevolution signal as well as contact couplings. The residue coevolution reflects the physiological importance of the dynamics that may link proton transfer to ring compliance.« less

Inter-genomic sexual conflict drives antagonistic coevolution in harvester ants

PubMed Central

Herrmann, Michael; Cahan, Sara Helms

2014-01-01

The reproductive interests of males and females are not always aligned, leading to sexual conflict over parental investment, rate of reproduction and mate choice. Traits that increase the genetic interests of one sex often occur at the expense of the other, selecting for counter-adaptations leading to antagonistic coevolution. Reproductive conflict is not limited to intraspecific interactions; interspecific hybridization can produce pronounced sexual conflict between males and females of different species, but it is unclear whether such conflict can drive sexually antagonistic coevolution between reproductively isolated genomes. We tested for hybridization-driven sexually antagonistic adaptations in queens and males of the socially hybridogenetic ‘J’ lineages of Pogonomyrmex harvester ants, whose mating system promotes hybridization in queens but selects against it in males. We conducted no-choice mating assays to compare patterns of mating behaviour and sperm transfer between inter- and intra-lineage pairings. There was no evidence for mate discrimination on the basis of pair type, and the total quantity of sperm transferred did not differ between intra- and inter-lineage pairs; however, further dissection of the sperm transfer process into distinct mechanistic components revealed significant, and opposing, cryptic manipulation of copulatory investment by both sexes. Males of both lineages increased their rate of sperm transfer to high-fitness intra-lineage mates, with a stronger response in the rarer lineage for whom mating mistakes are the most likely. By contrast, the total duration of copulation for intra-lineage mating pairs was significantly shorter than for inter-lineage crosses, suggesting that queens respond to prevent excessive sperm loading by prematurely terminating copulation. These findings demonstrate that sexual conflict can lead to antagonistic coevolution in both intra-genomic and inter-genomic contexts. Indeed, the resolution of sexual conflict may be a key determinant of the long-term evolutionary potential of host-dependent reproductive strategies, counteracting the inherent instabilities arising from such systems. PMID:25355474

The Phylogenetic Signature Underlying ATP Synthase c-Ring Compliance

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

Pandini, Alessandro; Kleinjung, Jens; Taylor, Willie R.

The proton-driven ATP synthase (F OF 1) is comprised of two rotary, stepping motors (F O and F 1) coupled by an elastic power transmission. The elastic compliance resides in the rotor module that includes the membrane-embedded FO c-ring. Proton transport by FO is firmly coupled to the rotation of the c-ring relative to other F O subunits (ab 2). It drives ATP synthesis. We used a computational method to investigate the contribution of the c-ring to the total elastic compliance. We performed principal component analysis of conformational ensembles built using distance constraints from the bovine mitochondrial c-ring x-ray structure.more » Angular rotary twist, the dominant ring motion, was estimated to show that the c-ring accounted in part for the measured compliance. Ring rotation was entrained to rotation of the external helix within each hairpin-shaped c-subunit in the ring. Ensembles of monomer and dimers extracted from complete c-rings showed that the coupling between collective ring and the individual subunit motions was independent of the size of the c-ring, which varies between organisms. Molecular determinants were identified by covariance analysis of residue coevolution and structural-alphabet-based local dynamics correlations. The residue coevolution gave a readout of subunit architecture. The dynamic couplings revealed that the hinge for both ring and subunit helix rotations was constructed from the proton-binding site and the adjacent glycine motif (IB-GGGG) in the midmembrane plane. IB-GGGG motifs were linked by long-range couplings across the ring, while intrasubunit couplings connected the motif to the conserved cytoplasmic loop and adjacent segments. The correlation with principal collective motions shows that the couplings underlie both ring rotary and bending motions. Noncontact couplings between IB-GGGG motifs matched the coevolution signal as well as contact couplings. The residue coevolution reflects the physiological importance of the dynamics that may link proton transfer to ring compliance.« less

Comparative Phylogenetic Studies on Schistosoma japonicum and Its Snail Intermediate Host Oncomelania hupensis: Origins, Dispersal and Coevolution

PubMed Central

Attwood, Stephen W.; Ibaraki, Motomu; Saitoh, Yasuhide; Nihei, Naoko; Janies, Daniel A.

2015-01-01

Background Schistosoma japonicum causes major public health problems in China and the Philippines; this parasite, which is transmitted by freshwater snails of the species Oncomelania hupensis, causes the disease intestinal schistosomiasis in humans and cattle. Researchers working on Schistosoma in Africa have described the relationship between the parasites and their snail intermediate hosts as coevolved or even as an evolutionary arms race. In the present study this hypothesis of coevolution is evaluated for S. japonicum and O. hupensis. The origins and radiation of the snails and the parasite across China, and the taxonomic validity of the sub-species of O. hupensis, are also assessed. Methodology/Principal Findings The findings provide no evidence for coevolution between S. japonicum and O. hupensis, and the phylogeographical analysis suggests a heterochronous radiation of the parasites and snails in response to different palaeogeographical and climatic triggers. The results are consistent with a hypothesis of East to West colonisation of China by Oncomelania with a re-invasion of Japan by O. hupensis from China. The Taiwan population of S. japonicum appears to be recently established in comparison with mainland Chinese populations. Conclusions/Significance The snail and parasite populations of the western mountain region of China (Yunnan and Sichuan) appear to have been isolated from Southeast Asian populations since the Pleistocene; this has implications for road and rail links being constructed in the region, which will breach biogeographical barriers between China and Southeast Asia. The results also have implications for the spread of S. japonicum. In the absence of coevolution, the parasite may more readily colonise new snail populations to which it is not locally adapted, or even new intermediate host species; this can facilitate its dispersal into new areas. Additional work is required to assess further the risk of spread of S. japonicum. PMID:26230619

Topological properties of complex networks in protein structures

NASA Astrophysics Data System (ADS)

Kim, Kyungsik; Jung, Jae-Won; Min, Seungsik

2014-03-01

We study topological properties of networks in structural classification of proteins. We model the native-state protein structure as a network made of its constituent amino-acids and their interactions. We treat four structural classes of proteins composed predominantly of α helices and β sheets and consider several proteins from each of these classes whose sizes range from amino acids of the Protein Data Bank. Particularly, we simulate and analyze the network metrics such as the mean degree, the probability distribution of degree, the clustering coefficient, the characteristic path length, the local efficiency, and the cost. This work was supported by the KMAR and DP under Grant WISE project (153-3100-3133-302-350).

Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations.

PubMed

Suratanee, Apichat; Plaimas, Kitiporn

2017-01-01

The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small. In this study, an analysis framework to infer associations between proteins and diseases was developed based on a large data set of a human protein-protein interaction network integrating an effective network search, namely, the reverse k -nearest neighbor (R k NN) search. The R k NN search was used to identify an impact of a protein on other proteins. Then, associations between proteins and diseases were inferred statistically. The method using the R k NN search yielded a much higher precision than a random selection, standard nearest neighbor search, or when applying the method to a random protein-protein interaction network. All protein-disease pair candidates were verified by a literature search. Supporting evidence for 596 pairs was identified. In addition, cluster analysis of these candidates revealed 10 promising groups of diseases to be further investigated experimentally. This method can be used to identify novel associations to better understand complex relationships between proteins and diseases.

An information-based network approach for protein classification

PubMed Central

Wan, Xiaogeng; Zhao, Xin; Yau, Stephen S. T.

2017-01-01

Protein classification is one of the critical problems in bioinformatics. Early studies used geometric distances and polygenetic-tree to classify proteins. These methods use binary trees to present protein classification. In this paper, we propose a new protein classification method, whereby theories of information and networks are used to classify the multivariate relationships of proteins. In this study, protein universe is modeled as an undirected network, where proteins are classified according to their connections. Our method is unsupervised, multivariate, and alignment-free. It can be applied to the classification of both protein sequences and structures. Nine examples are used to demonstrate the efficiency of our new method. PMID:28350835

deepNF: Deep network fusion for protein function prediction.

PubMed

Gligorijevic, Vladimir; Barot, Meet; Bonneau, Richard

2018-06-01

The prevalence of high-throughput experimental methods has resulted in an abundance of large-scale molecular and functional interaction networks. The connectivity of these networks provides a rich source of information for inferring functional annotations for genes and proteins. An important challenge has been to develop methods for combining these heterogeneous networks to extract useful protein feature representations for function prediction. Most of the existing approaches for network integration use shallow models that encounter difficulty in capturing complex and highly-nonlinear network structures. Thus, we propose deepNF, a network fusion method based on Multimodal Deep Autoencoders to extract high-level features of proteins from multiple heterogeneous interaction networks. We apply this method to combine STRING networks to construct a common low-dimensional representation containing high-level protein features. We use separate layers for different network types in the early stages of the multimodal autoencoder, later connecting all the layers into a single bottleneck layer from which we extract features to predict protein function. We compare the cross-validation and temporal holdout predictive performance of our method with state-of-the-art methods, including the recently proposed method Mashup. Our results show that our method outperforms previous methods for both human and yeast STRING networks. We also show substantial improvement in the performance of our method in predicting GO terms of varying type and specificity. deepNF is freely available at: https://github.com/VGligorijevic/deepNF. vgligorijevic@flatironinstitute.org, rb133@nyu.edu. Supplementary data are available at Bioinformatics online.

Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

PubMed

Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

2010-07-01

The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

Aggregation and network formation in self-assembly of protein (H3.1) by a coarse-grained Monte Carlo simulation.

PubMed

Pandey, R B; Farmer, B L

2014-11-07

Multi-scale aggregation to network formation of interacting proteins (H3.1) are examined by a knowledge-based coarse-grained Monte Carlo simulation as a function of temperature and the number of protein chains, i.e., the concentration of the protein. Self-assembly of corresponding homo-polymers of constitutive residues (Cys, Thr, and Glu) with extreme residue-residue interactions, i.e., attractive (Cys-Cys), neutral (Thr-Thr), and repulsive (Glu-Glu), are also studied for comparison with the native protein. Visual inspections show contrast and similarity in morphological evolutions of protein assembly, aggregation of small aggregates to a ramified network from low to high temperature with the aggregation of a Cys-polymer, and an entangled network of Glu and Thr polymers. Variations in mobility profiles of residues with the concentration of the protein suggest that the segmental characteristic of proteins is altered considerably by the self-assembly from that in its isolated state. The global motion of proteins and Cys polymer chains is enhanced by their interacting network at the low temperature where isolated chains remain quasi-static. Transition from globular to random coil transition, evidenced by the sharp variation in the radius of gyration, of an isolated protein is smeared due to self-assembly of interacting networks of many proteins. Scaling of the structure factor S(q) with the wave vector q provides estimates of effective dimension D of the mass distribution at multiple length scales in self-assembly. Crossover from solid aggregates (D ∼ 3) at low temperature to a ramified fibrous network (D ∼ 2) at high temperature is observed for the protein H3.1 and Cys polymers in contrast to little changes in mass distribution (D ∼ 1.6) of fibrous Glu- and Thr-chain configurations.

Aggregation and network formation in self-assembly of protein (H3.1) by a coarse-grained Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Pandey, R. B.; Farmer, B. L.

2014-11-01

Multi-scale aggregation to network formation of interacting proteins (H3.1) are examined by a knowledge-based coarse-grained Monte Carlo simulation as a function of temperature and the number of protein chains, i.e., the concentration of the protein. Self-assembly of corresponding homo-polymers of constitutive residues (Cys, Thr, and Glu) with extreme residue-residue interactions, i.e., attractive (Cys-Cys), neutral (Thr-Thr), and repulsive (Glu-Glu), are also studied for comparison with the native protein. Visual inspections show contrast and similarity in morphological evolutions of protein assembly, aggregation of small aggregates to a ramified network from low to high temperature with the aggregation of a Cys-polymer, and an entangled network of Glu and Thr polymers. Variations in mobility profiles of residues with the concentration of the protein suggest that the segmental characteristic of proteins is altered considerably by the self-assembly from that in its isolated state. The global motion of proteins and Cys polymer chains is enhanced by their interacting network at the low temperature where isolated chains remain quasi-static. Transition from globular to random coil transition, evidenced by the sharp variation in the radius of gyration, of an isolated protein is smeared due to self-assembly of interacting networks of many proteins. Scaling of the structure factor S(q) with the wave vector q provides estimates of effective dimension D of the mass distribution at multiple length scales in self-assembly. Crossover from solid aggregates (D ˜ 3) at low temperature to a ramified fibrous network (D ˜ 2) at high temperature is observed for the protein H3.1 and Cys polymers in contrast to little changes in mass distribution (D ˜ 1.6) of fibrous Glu- and Thr-chain configurations.

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

Protein complexes and functional modules in molecular networks

NASA Astrophysics Data System (ADS)

Spirin, Victor; Mirny, Leonid A.

2003-10-01

Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.) and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.

Insight into bacterial virulence mechanisms against host immune response via the Yersinia pestis-human protein-protein interaction network.

PubMed

Yang, Huiying; Ke, Yuehua; Wang, Jian; Tan, Yafang; Myeni, Sebenzile K; Li, Dong; Shi, Qinghai; Yan, Yanfeng; Chen, Hui; Guo, Zhaobiao; Yuan, Yanzhi; Yang, Xiaoming; Yang, Ruifu; Du, Zongmin

2011-11-01

A Yersinia pestis-human protein interaction network is reported here to improve our understanding of its pathogenesis. Up to 204 interactions between 66 Y. pestis bait proteins and 109 human proteins were identified by yeast two-hybrid assay and then combined with 23 previously published interactions to construct a protein-protein interaction network. Topological analysis of the interaction network revealed that human proteins targeted by Y. pestis were significantly enriched in the proteins that are central in the human protein-protein interaction network. Analysis of this network showed that signaling pathways important for host immune responses were preferentially targeted by Y. pestis, including the pathways involved in focal adhesion, regulation of cytoskeleton, leukocyte transendoepithelial migration, and Toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling. Cellular pathways targeted by Y. pestis are highly relevant to its pathogenesis. Interactions with host proteins involved in focal adhesion and cytoskeketon regulation pathways could account for resistance of Y. pestis to phagocytosis. Interference with TLR and MAPK signaling pathways by Y. pestis reflects common characteristics of pathogen-host interaction that bacterial pathogens have evolved to evade host innate immune response by interacting with proteins in those signaling pathways. Interestingly, a large portion of human proteins interacting with Y. pestis (16/109) also interacted with viral proteins (Epstein-Barr virus [EBV] and hepatitis C virus [HCV]), suggesting that viral and bacterial pathogens attack common cellular functions to facilitate infections. In addition, we identified vasodilator-stimulated phosphoprotein (VASP) as a novel interaction partner of YpkA and showed that YpkA could inhibit in vitro actin assembly mediated by VASP.

Toward a systems-level view of dynamic phosphorylation networks

PubMed Central

Newman, Robert H.; Zhang, Jin; Zhu, Heng

2014-01-01

To better understand how cells sense and respond to their environment, it is important to understand the organization and regulation of the phosphorylation networks that underlie most cellular signal transduction pathways. These networks, which are composed of protein kinases, protein phosphatases and their respective cellular targets, are highly dynamic. Importantly, to achieve signaling specificity, phosphorylation networks must be regulated at several levels, including at the level of protein expression, substrate recognition, and spatiotemporal modulation of enzymatic activity. Here, we briefly summarize some of the traditional methods used to study the phosphorylation status of cellular proteins before focusing our attention on several recent technological advances, such as protein microarrays, quantitative mass spectrometry, and genetically-targetable fluorescent biosensors, that are offering new insights into the organization and regulation of cellular phosphorylation networks. Together, these approaches promise to lead to a systems-level view of dynamic phosphorylation networks. PMID:25177341

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

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.

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 allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles. PMID:29518071

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 allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles.

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae.

PubMed

Jarnuczak, Andrew F; Eyers, Claire E; Schwartz, Jean-Marc; Grant, Christopher M; Hubbard, Simon J

2015-09-01

Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC-based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs. © 2015 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Generic Information Can Retrieve Known Biological Associations: Implications for Biomedical Knowledge Discovery

PubMed Central

van Haagen, Herman H. H. B. M.; 't Hoen, Peter A. C.; Mons, Barend; Schultes, Erik A.

2013-01-01

Motivation Weighted semantic networks built from text-mined literature can be used to retrieve known protein-protein or gene-disease associations, and have been shown to anticipate associations years before they are explicitly stated in the literature. Our text-mining system recognizes over 640,000 biomedical concepts: some are specific (i.e., names of genes or proteins) others generic (e.g., ‘Homo sapiens’). Generic concepts may play important roles in automated information retrieval, extraction, and inference but may also result in concept overload and confound retrieval and reasoning with low-relevance or even spurious links. Here, we attempted to optimize the retrieval performance for protein-protein interactions (PPI) by filtering generic concepts (node filtering) or links to generic concepts (edge filtering) from a weighted semantic network. First, we defined metrics based on network properties that quantify the specificity of concepts. Then using these metrics, we systematically filtered generic information from the network while monitoring retrieval performance of known protein-protein interactions. We also systematically filtered specific information from the network (inverse filtering), and assessed the retrieval performance of networks composed of generic information alone. Results Filtering generic or specific information induced a two-phase response in retrieval performance: initially the effects of filtering were minimal but beyond a critical threshold network performance suddenly drops. Contrary to expectations, networks composed exclusively of generic information demonstrated retrieval performance comparable to unfiltered networks that also contain specific concepts. Furthermore, an analysis using individual generic concepts demonstrated that they can effectively support the retrieval of known protein-protein interactions. For instance the concept “binding” is indicative for PPI retrieval and the concept “mutation abnormality” is indicative for gene-disease associations. Conclusion Generic concepts are important for information retrieval and cannot be removed from semantic networks without negative impact on retrieval performance. PMID:24260124

PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

PubMed

Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

2017-02-03

The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Correction to: The NMR contribution to protein-protein networking in Fe-S protein maturation.

PubMed

Banci, Lucia; Camponeschi, Francesca; Ciofi-Baffoni, Simone; Piccioli, Mario

2018-05-31

The article "The NMR contribution to protein-protein networking in Fe-S protein maturation", written by Lucia Banci, Francesca Camponeschi, Simone Ciofi‑Baffoni, Mario Piccioli was originally published electronically on the publisher's internet portal (currently SpringerLink) on 22 March, 2018 without open access.

Evolution of SH2 domains and phosphotyrosine signalling networks

PubMed Central

Liu, Bernard A.; Nash, Piers D.

2012-01-01

Src homology 2 (SH2) domains mediate selective protein–protein interactions with tyrosine phosphorylated proteins, and in doing so define specificity of phosphotyrosine (pTyr) signalling networks. SH2 domains and protein-tyrosine phosphatases expand alongside protein-tyrosine kinases (PTKs) to coordinate cellular and organismal complexity in the evolution of the unikont branch of the eukaryotes. Examination of conserved families of PTKs and SH2 domain proteins provides fiduciary marks that trace the evolutionary landscape for the development of complex cellular systems in the proto-metazoan and metazoan lineages. The evolutionary provenance of conserved SH2 and PTK families reveals the mechanisms by which diversity is achieved through adaptations in tissue-specific gene transcription, altered ligand binding, insertions of linear motifs and the gain or loss of domains following gene duplication. We discuss mechanisms by which pTyr-mediated signalling networks evolve through the development of novel and expanded families of SH2 domain proteins and the elaboration of connections between pTyr-signalling proteins. These changes underlie the variety of general and specific signalling networks that give rise to tissue-specific functions and increasingly complex developmental programmes. Examination of SH2 domains from an evolutionary perspective provides insight into the process by which evolutionary expansion and modification of molecular protein interaction domain proteins permits the development of novel protein-interaction networks and accommodates adaptation of signalling networks. PMID:22889907

Semantic integration to identify overlapping functional modules in protein interaction networks

PubMed Central

Cho, Young-Rae; Hwang, Woochang; Ramanathan, Murali; Zhang, Aidong

2007-01-01

Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification. PMID:17650343

Modeling of axonal endoplasmic reticulum network by spastic paraplegia proteins.

PubMed

Yalçın, Belgin; Zhao, Lu; Stofanko, Martin; O'Sullivan, Niamh C; Kang, Zi Han; Roost, Annika; Thomas, Matthew R; Zaessinger, Sophie; Blard, Olivier; Patto, Alex L; Sohail, Anood; Baena, Valentina; Terasaki, Mark; O'Kane, Cahir J

2017-07-25

Axons contain a smooth tubular endoplasmic reticulum (ER) network that is thought to be continuous with ER throughout the neuron; the mechanisms that form this axonal network are unknown. Mutations affecting reticulon or REEP proteins, with intramembrane hairpin domains that model ER membranes, cause an axon degenerative disease, hereditary spastic paraplegia (HSP). We show that Drosophila axons have a dynamic axonal ER network, which these proteins help to model. Loss of HSP hairpin proteins causes ER sheet expansion, partial loss of ER from distal motor axons, and occasional discontinuities in axonal ER. Ultrastructural analysis reveals an extensive ER network in axons, which shows larger and fewer tubules in larvae that lack reticulon and REEP proteins, consistent with loss of membrane curvature. Therefore HSP hairpin-containing proteins are required for shaping and continuity of axonal ER, thus suggesting roles for ER modeling in axon maintenance and function.

Essential protein discovery based on a combination of modularity and conservatism.

PubMed

Zhao, Bihai; Wang, Jianxin; Li, Xueyong; Wu, Fang-Xiang

2016-11-01

Essential proteins are indispensable for the survival of a living organism and play important roles in the emerging field of synthetic biology. Many computational methods have been proposed to identify essential proteins by using the topological features of interactome networks. However, most of these methods ignored intrinsic biological meaning of proteins. Researches show that essentiality is tied not only to the protein or gene itself, but also to the molecular modules to which that protein belongs. The results of this study reveal the modularity of essential proteins. On the other hand, essential proteins are more evolutionarily conserved than nonessential proteins and frequently bind each other. That is to say, conservatism is another important feature of essential proteins. Multiple networks are constructed by integrating protein-protein interaction (PPI) networks, time course gene expression data and protein domain information. Based on these networks, a new essential protein identification method is proposed based on a combination of modularity and conservatism of proteins. Experimental results show that the proposed method outperforms other essential protein identification methods in terms of a number essential protein out of top ranked candidates. Copyright © 2016. Published by Elsevier Inc.

Distinct roles of a tyrosine-associated hydrogen-bond network in fine-tuning the structure and function of heme proteins: two cases designed for myoglobin.

PubMed

Liao, Fei; Yuan, Hong; Du, Ke-Jie; You, Yong; Gao, Shu-Qin; Wen, Ge-Bo; Lin, Ying-Wu; Tan, Xiangshi

2016-10-20

A hydrogen-bond (H-bond) network, specifically a Tyr-associated H-bond network, plays key roles in regulating the structure and function of proteins, as exemplified by abundant heme proteins in nature. To explore an approach for fine-tuning the structure and function of artificial heme proteins, we herein used myoglobin (Mb) as a model protein and introduced a Tyr residue in the secondary sphere of the heme active site at two different positions (107 and 138). We performed X-ray crystallography, UV-Vis spectroscopy, stopped-flow kinetics, and electron paramagnetic resonance (EPR) studies for the two single mutants, I107Y Mb and F138Y Mb, and compared to that of wild-type Mb under the same conditions. The results showed that both Tyr107 and Tyr138 form a distinct H-bond network involving water molecules and neighboring residues, which fine-tunes ligand binding to the heme iron and enhances the protein stability, respectively. Moreover, the Tyr107-associated H-bond network was shown to fine-tune both H2O2 binding and activation. With two cases demonstrated for Mb, this study suggests that the Tyr-associated H-bond network has distinct roles in regulating the protein structure, properties and functions, depending on its location in the protein scaffold. Therefore, it is possible to design a Tyr-associated H-bond network in general to create other artificial heme proteins with improved properties and functions.

MOCASSIN-prot software

USDA-ARS?s Scientific Manuscript database

MOCASSIN-prot is a software, implemented in Perl and Matlab, for constructing protein similarity networks to classify proteins. Both domain composition and quantitative sequence similarity information are utilized in constructing the directed protein similarity networks. For each reference protein i...

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 .

Fluctuations in Mass-Action Equilibrium of Protein Binding Networks

NASA Astrophysics Data System (ADS)

Yan, Koon-Kiu; Walker, Dylan; Maslov, Sergei

2008-12-01

We consider two types of fluctuations in the mass-action equilibrium in protein binding networks. The first type is driven by slow changes in total concentrations of interacting proteins. The second type (spontaneous) is caused by quickly decaying thermodynamic deviations away from equilibrium. We investigate the effects of network connectivity on fluctuations by comparing them to scenarios in which the interacting pair is isolated from the network and analytically derives bounds on fluctuations. Collective effects are shown to sometimes lead to large amplification of spontaneous fluctuations. The strength of both types of fluctuations is positively correlated with the complex connectivity and negatively correlated with complex concentration. Our general findings are illustrated using a curated network of protein interactions and multiprotein complexes in baker’s yeast, with empirical protein concentrations.

On Design Mining: Coevolution and Surrogate Models.

PubMed

Preen, Richard J; Bull, Larry

2017-01-01

Design mining is the use of computational intelligence techniques to iteratively search and model the attribute space of physical objects evaluated directly through rapid prototyping to meet given objectives. It enables the exploitation of novel materials and processes without formal models or complex simulation. In this article, we focus upon the coevolutionary nature of the design process when it is decomposed into concurrent sub-design-threads due to the overall complexity of the task. Using an abstract, tunable model of coevolution, we consider strategies to sample subthread designs for whole-system testing and how best to construct and use surrogate models within the coevolutionary scenario. Drawing on our findings, we then describe the effective design of an array of six heterogeneous vertical-axis wind turbines.

A non-classical phase diagram for virus-bacterial co-evolution mediated by CRISPR

NASA Astrophysics Data System (ADS)

Han, Pu; Deem, Michael

CRISPR is a newly discovered prokaryotic immune system. Bacteria and archaea with this system incorporate genetic material from invading viruses into their genomes, providing protection against future infection by similar viruses. Due to the cost of CRISPR, bacteria can lose the acquired immunity. We will show an intriguing phase diagram of the virus extinction probability, which when the rate of losing the acquired immunity is small, is more complex than that of the classic predator-prey model. As the CRISPR incorporates genetic material, viruses are under pressure to evolve to escape the recognition by CRISPR, and this co-evolution leads to a non-trivial phase structure that cannot be explained by the classical predator-prey model.

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

Differential Occurrence of Interactions and Interaction Domains in Proteins Containing Homopolymeric Amino Acid Repeats

PubMed Central

Pelassa, Ilaria; Fiumara, Ferdinando

2015-01-01

Homopolymeric amino acids repeats (AARs), which are widespread in proteomes, have often been viewed simply as spacers between protein domains, or even as “junk” sequences with no obvious function but with a potential to cause harm upon expansion as in genetic diseases associated with polyglutamine or polyalanine expansions, including Huntington disease and cleidocranial dysplasia. A growing body of evidence indicates however that at least some AARs can form organized, functional protein structures, and can regulate protein function. In particular, certain AARs can mediate protein-protein interactions, either through homotypic AAR-AAR contacts or through heterotypic contacts with other protein domains. It is still unclear however, whether AARs may have a generalized, proteome-wide role in shaping protein-protein interaction networks. Therefore, we have undertaken here a bioinformatics screening of the human proteome and interactome in search of quantitative evidence of such a role. We first identified the sets of proteins that contain repeats of any one of the 20 amino acids, as well as control sets of proteins chosen at random in the proteome. We then analyzed the connectivity between the proteins of the AAR-containing protein sets and we compared it with that observed in the corresponding control networks. We find evidence for different degrees of connectivity in the different AAR-containing protein networks. Indeed, networks of proteins containing polyglutamine, polyglutamate, polyproline, and other AARs show significantly increased levels of connectivity, whereas networks containing polyleucine and other hydrophobic repeats show lower degrees of connectivity. Furthermore, we observed that numerous protein-protein, -nucleic acid, and -lipid interaction domains are significantly enriched in specific AAR protein groups. These findings support the notion of a generalized, combinatorial role of AARs, together with conventional protein interaction domains, in shaping the interaction networks of the human proteome, and define proteome-wide knowledge that may guide the informed biological exploration of the role of AARs in protein interactions. PMID:26734058

A novel progesterone receptor membrane component (PGRMC) in the human and swine parasite Taenia solium: implications to the host-parasite relationship.

PubMed

Aguilar-Díaz, Hugo; Nava-Castro, Karen E; Escobedo, Galileo; Domínguez-Ramírez, Lenin; García-Varela, Martín; Del Río-Araiza, Víctor H; Palacios-Arreola, Margarita I; Morales-Montor, Jorge

2018-03-09

We have previously reported that progesterone (P 4 ) has a direct in vitro effect on the scolex evagination and growth of Taenia solium cysticerci. Here, we explored the hypothesis that the P 4 direct effect on T. solium might be mediated by a novel steroid-binding parasite protein. By way of using immunofluorescent confocal microscopy, flow cytometry analysis, double-dimension electrophoresis analysis, and sequencing the corresponding protein spot, we detected a novel PGRMC in T. solium. Molecular modeling studies accompanied by computer docking using the sequenced protein, together with phylogenetic analysis and sequence alignment clearly demonstrated that T. solium PGRMC is from parasite origin. Our results show that P 4 in vitro increases parasite evagination and scolex size. Using immunofluorescent confocal microscopy, we detected that parasite cells showed expression of a P 4 -binding like protein exclusively located at the cysticercus subtegumental tissue. Presence of the P 4 -binding protein in cyst cells was also confirmed by flow cytometry. Double-dimension electrophoresis analysis, followed by sequencing the corresponding protein spot, revealed a protein that was previously reported in the T. solium genome belonging to a membrane-associated progesterone receptor component (PGRMC). Molecular modeling studies accompanied by computer docking using the sequenced protein showed that PGRMC is potentially able to bind steroid hormones such as progesterone, estradiol, testosterone and dihydrodrotestosterone with different affinities. Phylogenetic analysis and sequence alignment clearly demonstrated that T. solium PGRMC is related to a steroid-binding protein of Echinoccocus granulosus, both of them being nested within a cluster including similar proteins present in platyhelminths such as Schistocephalus solidus and Schistosoma haematobium. Progesterone may directly act upon T. solium cysticerci probably by binding to PGRMC. This research has implications in the field of host-parasite co-evolution as well as the sex-associated susceptibility to this infection. In a more practical matter, present results may contribute to the molecular design of new drugs with anti-parasite actions.

Network-based prediction and knowledge mining of disease genes.

PubMed

Carson, Matthew B; Lu, Hui

2015-01-01

In recent years, high-throughput protein interaction identification methods have generated a large amount of data. When combined with the results from other in vivo and in vitro experiments, a complex set of relationships between biological molecules emerges. The growing popularity of network analysis and data mining has allowed researchers to recognize indirect connections between these molecules. Due to the interdependent nature of network entities, evaluating proteins in this context can reveal relationships that may not otherwise be evident. We examined the human protein interaction network as it relates to human illness using the Disease Ontology. After calculating several topological metrics, we trained an alternating decision tree (ADTree) classifier to identify disease-associated proteins. Using a bootstrapping method, we created a tree to highlight conserved characteristics shared by many of these proteins. Subsequently, we reviewed a set of non-disease-associated proteins that were misclassified by the algorithm with high confidence and searched for evidence of a disease relationship. Our classifier was able to predict disease-related genes with 79% area under the receiver operating characteristic (ROC) curve (AUC), which indicates the tradeoff between sensitivity and specificity and is a good predictor of how a classifier will perform on future data sets. We found that a combination of several network characteristics including degree centrality, disease neighbor ratio, eccentricity, and neighborhood connectivity help to distinguish between disease- and non-disease-related proteins. Furthermore, the ADTree allowed us to understand which combinations of strongly predictive attributes contributed most to protein-disease classification. In our post-processing evaluation, we found several examples of potential novel disease-related proteins and corresponding literature evidence. In addition, we showed that first- and second-order neighbors in the PPI network could be used to identify likely disease associations. We analyzed the human protein interaction network and its relationship to disease and found that both the number of interactions with other proteins and the disease relationship of neighboring proteins helped to determine whether a protein had a relationship to disease. Our classifier predicted many proteins with no annotated disease association to be disease-related, which indicated that these proteins have network characteristics that are similar to disease-related proteins and may therefore have disease associations not previously identified. By performing a post-processing step after the prediction, we were able to identify evidence in literature supporting this possibility. This method could provide a useful filter for experimentalists searching for new candidate protein targets for drug repositioning and could also be extended to include other network and data types in order to refine these predictions.

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.

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

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

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

PubMed

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

PubMed Central

Li, Min; Li, Dongyan; Tang, Yu; Wang, Jianxin

2017-01-01

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster. PMID:28858211

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.

Controlled experiments of hillslope co-evolution at the Biosphere 2 Landscape Evolution Observatory: toward prediction of coupled hydrological, biogeochemical, and ecological change

NASA Astrophysics Data System (ADS)

Volkmann, T. H. M.; Sengupta, A.; Pangle, L.; Abramson, N.; Barron-Gafford, G.; Breshears, D. D.; Bugaj, A.; Chorover, J.; Dontsova, K.; Durcik, M.; Ferre, T. P. A.; Harman, C. J.; Hunt, E.; Huxman, T. E.; Kim, M.; Maier, R. M.; Matos, K.; Alves Meira Neto, A.; Meredith, L. K.; Monson, R. K.; Niu, G. Y.; Pelletier, J. D.; Rasmussen, C.; Ruiz, J.; Saleska, S. R.; Schaap, M. G.; Sibayan, M.; Tuller, M.; Van Haren, J. L. M.; Wang, Y.; Zeng, X.; Troch, P. A.

2017-12-01

Understanding the process interactions and feedbacks among water, microbes, plants, and porous geological media is crucial for improving predictions of the response of Earth's critical zone to future climatic conditions. However, the integrated co-evolution of landscapes under change is notoriously difficult to investigate. Laboratory studies are typically limited in spatial and temporal scale, while field studies lack observational density and control. To bridge the gap between controlled lab and uncontrolled field studies, the University of Arizona - Biosphere 2 built a macrocosm experiment of unprecedented scale: the Landscape Evolution Observatory (LEO). LEO consists of three replicated, 330-m2 hillslope landscapes inside a 5000-m2 environmentally controlled facility. The engineered landscapes contain 1-m depth of basaltic tephra ground to homogenous loamy sand that will undergo physical, chemical, and mineralogical changes over many years. Each landscape contains a dense sensor network capable of resolving water, carbon, and energy cycling processes at sub-meter to whole-landscape scale. Embedded sampling devices allow for quantification of biogeochemical processes, and facilitate the use of chemical tracers applied with the artificial rainfall. LEO is now fully operational and intensive forcing experiments have been launched. While operating the massive infrastructure poses significant challenges, LEO has demonstrated the capacity of tracking multi-scale matter and energy fluxes at a level of detail impossible in field experiments. Initial sensor, sampler, and restricted soil coring data are already providing insights into the tight linkages between water flow, weathering, and (micro-) biological community development during incipient landscape evolution. Over the years to come, these interacting processes are anticipated to drive the model systems to increasingly complex states, potentially perturbed by changes in climatic forcing. By intensively monitoring the evolutionary trajectory, integrating data with models, and fostering community-wide collaborations, we envision that emergent landscape structures and functions can be linked and significant progress can be made toward predicting the coupled hydro-biogeochemical and ecological responses to global change.

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.

Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

PubMed Central

Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

2011-01-01

Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

LINE-1 protein localization and functional dynamics during the cell cycle

PubMed Central

Wudzinska, Aleksandra; Sun, Xiaoji; Andrade, Joshua; Nayak, Shruti; Kahler, David J; Badri, Sana; LaCava, John; Ueberheide, Beatrix; Yun, Chi Y; Fenyö, David

2018-01-01

LINE-1/L1 retrotransposon sequences comprise 17% of the human genome. Among the many classes of mobile genetic elements, L1 is the only autonomous retrotransposon that still drives human genomic plasticity today. Through its co-evolution with the human genome, L1 has intertwined itself with host cell biology. However, a clear understanding of L1’s lifecycle and the processes involved in restricting its insertion and intragenomic spread remains elusive. Here we identify modes of L1 proteins’ entrance into the nucleus, a necessary step for L1 proliferation. Using functional, biochemical, and imaging approaches, we also show a clear cell cycle bias for L1 retrotransposition that peaks during the S phase. Our observations provide a basis for novel interpretations about the nature of nuclear and cytoplasmic L1 ribonucleoproteins (RNPs) and the potential role of DNA replication in L1 retrotransposition. PMID:29309036

A screen for immunity genes evolving under positive selection in Drosophila.

PubMed

Jiggins, F M; Kim, K W

2007-05-01

Genes involved in the immune system tend to have higher rates of adaptive evolution than other genes in the genome, probably because they are coevolving with pathogens. We have screened a sample of Drosophila genes to identify those evolving under positive selection. First, we identified rapidly evolving immunity genes by comparing 140 loci in Drosophila erecta and D. yakuba. Secondly, we resequenced 23 of the fastest evolving genes from the independent species pair D. melanogaster and D. simulans, and identified those under positive selection using a McDonald-Kreitman test. There was strong evidence of adaptive evolution in two serine proteases (persephone and spirit) and a homolog of the Anopheles serpin SRPN6, and weaker evidence in another serine protease and the death domain protein dFADD. These results add to mounting evidence that immune signalling pathway molecules often evolve rapidly, possibly because they are sites of host-parasite coevolution.

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.

Construction of reliable protein-protein interaction networks with a new interaction generality measure.

PubMed

Saito, Rintaro; Suzuki, Harukazu; Hayashizaki, Yoshihide

2003-04-12

Recent screening techniques have made large amounts of protein-protein interaction data available, from which biologically important information such as the function of uncharacterized proteins, the existence of novel protein complexes, and novel signal-transduction pathways can be discovered. However, experimental data on protein interactions contain many false positives, making these discoveries difficult. Therefore computational methods of assessing the reliability of each candidate protein-protein interaction are urgently needed. We developed a new 'interaction generality' measure (IG2) to assess the reliability of protein-protein interactions using only the topological properties of their interaction-network structure. Using yeast protein-protein interaction data, we showed that reliable protein-protein interactions had significantly lower IG2 values than less-reliable interactions, suggesting that IG2 values can be used to evaluate and filter interaction data to enable the construction of reliable protein-protein interaction networks.

Comprehensive search for accessory proteins encoded with archaeal and bacterial type III CRISPR-cas gene cassettes reveals 39 new cas gene families.

PubMed

Shah, Shiraz A; Alkhnbashi, Omer S; Behler, Juliane; Han, Wenyuan; She, Qunxin; Hess, Wolfgang R; Garrett, Roger A; Backofen, Rolf

2018-06-19

A study was undertaken to identify conserved proteins that are encoded adjacent to cas gene cassettes of Type III CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats - CRISPR associated) interference modules. Type III modules have been shown to target and degrade dsDNA, ssDNA and ssRNA and are frequently intertwined with cofunctional accessory genes, including genes encoding CRISPR-associated Rossman Fold (CARF) domains. Using a comparative genomics approach, and defining a Type III association score accounting for coevolution and specificity of flanking genes, we identified and classified 39 new Type III associated gene families. Most archaeal and bacterial Type III modules were seen to be flanked by several accessory genes, around half of which did not encode CARF domains and remain of unknown function. Northern blotting and interference assays in Synechocystis confirmed that one particular non-CARF accessory protein family was involved in crRNA maturation. Non-CARF accessory genes were generally diverse, encoding nuclease, helicase, protease, ATPase, transporter and transmembrane domains with some encoding no known domains. We infer that additional families of non-CARF accessory proteins remain to be found. The method employed is scalable for potential application to metagenomic data once automated pipelines for annotation of CRISPR-Cas systems have been developed. All accessory genes found in this study are presented online in a readily accessible and searchable format for researchers to audit their model organism of choice: http://accessory.crispr.dk .

Molecular dynamics simulations and statistical coupling analysis of GPI12 in L. major: functional co-evolution and conservedness reveals potential drug-target sites.

PubMed

Singh, Shailza; Mandlik, Vineetha; Shinde, Sonali

2015-03-01

GPI12 represents an important enzyme in the GPI biosynthetic pathway of several parasites like 'Leishmania'. GPI activity is generally regulated through either the hindrance in GPI complex assembly formation or the modulation of the lipophosphoglycan (LPG) flux to either reduce or enhance the pathogenicity in an organism. Of the various GPI molecules known, GPI12 is an important enzyme in the GPI biosynthetic pathway which can be exploited as a target due to the substrate specificity difference in parasites and humans. In the present study, the functional importance of the co-evolving residues of the GPI12 protein of Leishmania has been highlighted using the GPI proteins belonging to the GlcNAC-deacetylase family. Exploring the active site of the GPI12 protein and designing inhibitors against the functional residues provide ways and means to change the efficiency of deacetylation activity of the enzyme. The activity of de-N-acetylase is low in the absence of metal ions like zinc. Hence we designed eight small molecules in order to modulate the activity of GPI12. Compound 8 was found to be an appropriate choice to target the agonist (GPI12) active site thereby targeting the residues which were essential in the Zn binding and chelation activity. Inhibition of these sites offered a strong constraint to block the protein activity and in turn GPI biosynthesis.

Evolutionary Conservation and Emerging Functional Diversity of the Cytosolic Hsp70:J Protein Chaperone Network of Arabidopsis thaliana.

PubMed

Verma, Amit K; Diwan, Danish; Raut, Sandeep; Dobriyal, Neha; Brown, Rebecca E; Gowda, Vinita; Hines, Justin K; Sahi, Chandan

2017-06-07

Heat shock proteins of 70 kDa (Hsp70s) partner with structurally diverse Hsp40s (J proteins), generating distinct chaperone networks in various cellular compartments that perform myriad housekeeping and stress-associated functions in all organisms. Plants, being sessile, need to constantly maintain their cellular proteostasis in response to external environmental cues. In these situations, the Hsp70:J protein machines may play an important role in fine-tuning cellular protein quality control. Although ubiquitous, the functional specificity and complexity of the plant Hsp70:J protein network has not been studied. Here, we analyzed the J protein network in the cytosol of Arabidopsis thaliana and, using yeast genetics, show that the functional specificities of most plant J proteins in fundamental chaperone functions are conserved across long evolutionary timescales. Detailed phylogenetic and functional analysis revealed that increased number, regulatory differences, and neofunctionalization in J proteins together contribute to the emerging functional diversity and complexity in the Hsp70:J protein network in higher plants. Based on the data presented, we propose that higher plants have orchestrated their "chaperome," especially their J protein complement, according to their specialized cellular and physiological stipulations. Copyright © 2017 Verma et al.

Interfacing cellular networks of S. cerevisiae and E. coli: Connecting dynamic and genetic information

PubMed Central

2013-01-01

Background In recent years, various types of cellular networks have penetrated biology and are nowadays used omnipresently for studying eukaryote and prokaryote organisms. Still, the relation and the biological overlap among phenomenological and inferential gene networks, e.g., between the protein interaction network and the gene regulatory network inferred from large-scale transcriptomic data, is largely unexplored. Results We provide in this study an in-depth analysis of the structural, functional and chromosomal relationship between a protein-protein network, a transcriptional regulatory network and an inferred gene regulatory network, for S. cerevisiae and E. coli. Further, we study global and local aspects of these networks and their biological information overlap by comparing, e.g., the functional co-occurrence of Gene Ontology terms by exploiting the available interaction structure among the genes. Conclusions Although the individual networks represent different levels of cellular interactions with global structural and functional dissimilarities, we observe crucial functions of their network interfaces for the assembly of protein complexes, proteolysis, transcription, translation, metabolic and regulatory interactions. Overall, our results shed light on the integrability of these networks and their interfacing biological processes. PMID:23663484

Functional modules by relating protein interaction networks and gene expression.

PubMed

Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Functional modules by relating protein interaction networks and gene expression

PubMed Central

Tornow, Sabine; Mewes, H. W.

2003-01-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships. PMID:14576317

Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations

PubMed Central

Beleva Guthrie, Violeta; Masica, David L; Fraser, Andrew; Federico, Joseph; Fan, Yunfan; Camps, Manel; Karchin, Rachel

2018-01-01

Abstract The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure. PMID:29522102