BACKGROUND:A hub protein is one that interacts with many functional partners. The annotation of hub proteins, or more generally the protein-protein interaction "degree" of each gene, requires quality genome-wide data. Data obtained using yeast two-hybrid methods contain many false positive interactions between proteins that rarely encounter each other in living cells, and such data have fallen out of favor.RESULTS:We find that protein "stickiness", measured as network degree in ostensibly low quality yeast two-hybrid data, is a more predictive genomic metric than the number of functional protein-protein interactions, as assessed by supposedly higher quality high throughput affinity capture mass spectrometry data. In the yeast Saccharomyces cerevisiae, a protein's high stickiness, but not its high number of functional interactions, predicts low stochastic noise in gene expression, low plasticity of gene expression across different environments, and high probability of forming a homo-oligomer. Our results are robust to a multiple regression analysis correcting for other known predictors including protein abundance, presence of a TATA box and whether a gene is essential. Once the higher stickiness of homo-oligomers is controlled for, we find that homo-oligomers have noisier and more plastic gene expression than other proteins, consistent with a role for homo-oligomerization in mediating robustness.CONCLUSIONS:Our work validates use of the number of yeast two-hybrid interactions as a metric for protein stickiness. Sticky proteins exhibit low stochastic noise in gene expression, and low plasticity in expression across different environments.

Tradicionalmente, nichos populacionais são descritos como a somatória de todos os recursos utilizados por uma população. Entretanto, diversos estudos mostram que indivíduos dentro de uma população podem usar recursos de forma distinta. Investigamos três maneiras pelas quais indivíduos podem variar quanto ao uso do recurso. Indivíduos podem apresentar a mesma preferência por presas, mas diferir na propensão à adição de novos itens alimentares em sua dieta (Preferências Compartilhadas); indivíduos podem apresentar a mesma presa preferida mas diferirem em suas presas alternativas (Refúgio Competitivo); ou indivíduos podem apresentar presas preferidas distintas (Preferências Distintas). Estudamos os padrões de interação que emergem sob os pressupostos de cada um dos modelos usando redes de interação entre indivíduos e os recursos que eles consomem. Dessa forma, para derivarmos as previsões de cada um dos modelos de uso de recurso, desenvolvemos modelos simples que geram redes de interação segundo regras que seguem os pressupostos dos modelos e confrontamos essas previsões com dados empíricos, comparando a estrutura dessa redes de interação. Encontramos que o modelo que menos se assemelha ao padrão de uso de recurso observado para as populações estudadas foi o modelo de Preferências Compartilhadas. Para as populações estudadas, a variação intrapopulacional na escolha de presas parece estar mais associada a diferenças nas sequências de preferências por presas entre indivíduos e não à propensão desses indivíduos em adicionarem novos recursos às suas dietas. / Traditionally, a population\'s niche is described as the sum of all resources consumed by a population. However, several studies have highlighted that individuals within a population can use resources differently. We investigate three ways in which individuals can vary in their resource use. Individuals can show the same preference for prey, but differ in their likelihood of adding new prey to their diets (Shared Preferences); individuals can share the same top-ranked prey but differ in their alternative prey (Competitive Refuge); or individuals can have different top-ranked prey (Distinct Preferences). We studied the pattern of interaction that emerges under each model\'s assumption using interaction networks between individuals and the resources they consume. In this sense, to derive the predictions associated with each model of resource use, we developed simple models that generates interaction networks according to a set of rules that represent the assumptions of each model and then confronted these predictions with empirical data on interaction networks, by looking at the structure of these interaction networks. We found that the model that least resembles the pattern of resource use observed in the populations studied was the Shared Preferences model. For the studied populations, intrapopulation variation is not associated with individuals sharing the same rank sequence and differing in their willingness to add new resources to their diets. Instead, it seems that differences in the rank sequence of prey choice are more important in structuring the pattern of resource use in these populations.

Redes complexas são utilizadas para representar sistemas complexos, compostos de elementos que interagem uns com os outros. Uma das grandes vantagens de se empregar as redes é a possibilidade de se estudar a topologia presente nos mais diversos sistemas para obtermos informações sobre eles, entendê-los e compará-los. Devido à sua importância para a compreensão de processos intracelulares, desde início do desenvolvimento da área das redes complexas estudou-se a topologia da interação entre proteínas. Entretanto nos últimos anos com o desenvolvimento de novas técnicas de detecção o número de proteínas e interações reportadas cresceu de maneira muito acentuada; além disso, também existem alguns pontos sobre a sua topologia sobre os quais ainda não existe um consenso, como por exemplo qual a distribuição de graus desse tipo de rede. Neste trabalho estudamos as propriedades topológicas de redes de interação entre proteínas, utilizando as informações do banco de dados STRING, com ênfase no comportamento de suas medidas de centralidade e do espectro da matriz Laplaciana normalizada. Tanto a análise das medidas de centralidade e de suas correlações, quanto do espectro da matriz Laplaciana mostram que existem padrões topológicos que são conservados entre as redes dos organismos e que os mesmos também podem ser empregados para sua caracterização. Nossos resultados também mostram que as funções biológicas desempenhadas pelas proteínas podem ser identificadas pelas medidas de centralidade. Especificamente para a centralidade de autovetor, nossas análises indicam que ela está localizada nos maiores K-cores das redes consideradas. Os resultados aqui obtidos ressaltam que muitas informações relevantes podem ser extraídas da topologia das interações entre proteínas, além de indicarem a existência de possíveis estruturas conservadas; entretanto devido a incompletude dessas redes mais estudos precisam ser conduzidos para a avaliação de possíveis mudanças nos resultados aqui apresentados. / Complex networks can be used to model complex systems, composed of main elements that interact with each other. The advantage of using this approach is the possibility to study the topology of a wide range of systems so that we can get more information, understand and compare them. Due to its importance on the understanding of the intracellular biological processes, since the early beginning of the development of the complex networks field protein-protein interaction topologies have been studied. However, new techniques for the detection of proteins and their interactions have been developed recently, which has significantly increased the availability and reliability of the corresponding data over the last few years; moreover, there still are some debate about the topology of protein-protein interaction networks such as the degree distribution of this type of network. Here we will study the topological properties of protein-protein interaction networks created using the information of the STRING database focusing on centrality measures of their nodes, the correlation between them, and the normalized Laplacian matrix spectrum. Our results show the existence of topological patterns conserved between the protein interaction networks of different organisms and that both the correlation of the centrality pairs and the spectrum of the Laplacian matrix can be used for network characterization. Another study indicates that the set of centrality measures of a protein can be used to identify clusters with well defined biological functions. A more detailed look at the eigenvector centrality behavior reveals that this measure is localized on the proteins of the highest k-cores for all networks. These results highlight the importance of the topology on the study of protein-protein interactions and that more studies can lead to a better a more complete understanding of such systems.

Interações ecológicas mutualísticas são aquelas que trazem benefícios para todos os organismos envolvidos. A visitação floral fornece alimento para os animais visitantes, enquanto possibilita a reprodução sexuada em plantas. Enquanto isso, a teoria da síndrome de dispersão supõe que existem certos atributos florais (incluindo recompensas) capazes de atrair certos polinizadores e afastar outros. O declínio de abelhas tem sido reportado em todo o mundo, e encontrar espécies ecologicamente equivalentes é crucial para a preservação da biodiversidade. Vespas possuem funções ecológicas semelhantes às abelhas apesar de não dependerem exclusivamente de pólen e néctar para sobreviver. O objetivo deste projeto de pesquisa foi avaliar as diferenças da visitação floral entre abelhas/plantas e vespas/plantas. O primeiro capítulo possui uma abordagem de redes de interação. O segundo capítulo apresenta uma abordagem multivariada onde avaliamos as diferenças entre as plantas de acordo com os himenópteros visitantes florais. Nós realizamos as coletas em unidades de conservação do município de Porto Alegre. Em cada área de estudo, foram definidas transecções em três ambientes distintos: campo, mata e borda entre estes. As amostragens em cada transecção ocorreram entre horários de 9h e 17h. Durante este período, foram observadas as plantas em floração, entre 20 cm a 4 m de altura, e seus himenópteros visitantes florais coletados com o auxílio de rede entomológica durante 10 minutos em cada planta. As métricas de rede foram calculadas do programa R com o pacote Bipartite. Vespas e abelhas são visitantes florais distintos quanto a seus padrões de redes de interação. Vespas seriam capazes de manter apenas a metade da diversidade vegetal através da polinização após eventos hipotéticos de extinção de abelhas. Através da abordagem multivariada, as plantas visitadas por vespas e por abelhas não formaram grupos distintos. Quanto maior a abertura da corola da flor, menor é a visitação floral de vespas. Concluímos que vespas podem ser polinizadores auxiliares para a manutenção da diversidade vegetal, apesar de serem capazes de manter menor diversidade vegetal em cenários de extinção de abelhas. Além disso, os atributos florais de vespas e abelhas não são diferentes entre si, apontando para o fato de que vespas podem ser polinizadores de um maior número de plantas do que o previsto. / Mutualistic ecological interactions are those that bring benefits to all involved organisms. Floral visitation provides food for visiting animals, while allowing sexual reproduction in plants. Meanwhile, the dispersion syndrome theory assumes that there are certain floral attributes (including rewards) that can attract certain pollinators and drive away others. The decline of bees has been reported worldwide and finding ecologically equivalent species is crucial to the preservation of biodiversity. Wasps have ecological functions like bees although they do not depend exclusively on pollen and nectar to survive. The objective of this research was to evaluate the differences in floral visitation between bees/plants and wasps/plants. The first chapter has an interaction network approach. The second chapter presents a multivariate approach where we evaluate differences between plants according to the floral visiting wasps and bees. We carried out sampling in conservation units of the municipality of Porto Alegre. In each study area, transects were defined in three distinct environments: grassland, forest and edges between them. Sampling at each transection occurred between 9 and 17 h. During this period, flowering plants from 20 cm to 4 m tall were observed, and their floral visiting Hymenoptera collected with the aid of an entomological net for 10 min on each plant. The network metrics were calculated with R software with the Bipartite package. Wasps and bees are distinctive floral visitors given their different patterns of interaction networks. Wasps maintain half of the plant diversity after the hypothetical events of bee extinction. Under a multivariate approach, plants visited by wasps and bees did not form distinct groups. The widder the corolla of the flower, the less is the floral visitation of wasps. We conclude that wasps can be secondary pollinators for the maintenance of plant diversity, although they are able to maintain lower plant diversity in bee’s extinction scenarios. In addition, the floral attributes of wasps and bees are not different from each other, pointing to the fact that wasps may be pollinators of a larger number of plants than predicted.

Protein-protein interactions are important for the prediction of protein functions since two interacting proteins usually have similar functions in a cell. Available protein interaction networks are incomplete / but, they can be used to predict new interactions in a supervised learning framework. However, in the case that the known protein network includes large number of protein pairs, the training time of the machine learning algorithm becomes quite long. In this thesis work, our aim is to predict protein-protein interactions with a known portion of the interaction network. We used Support Vector Machines (SVM) as the machine learning algoritm and used the already known protein pairs in the network. We chose to use phylogenetic profiles of proteins to form the feature vectors required for the learner since the similarity of two proteins in evolution gives a reasonable rating about whether the two proteins interact or not. For large data sets, the training time of SVM becomes quite long, therefore we reduced the data size in a sensible way while we keep approximately the same prediction accuracy. We applied a number of clustering techniques to extract the most representative data and features in a two categorical framework. Knowing that the training data set is a two dimensional matrix, we applied data reduction methods in both dimensions, i.e., both in data size and in feature vector size. We observed that the data clustered by the k-means clustering technique gave superior results in prediction accuracies compared to another data clustering algorithm which was also developed for reducing data size for SVM training. Still the true positive and false positive rates (TPR-FPR) of the training data sets constructed by the two clustering methods did not give satisfying results about which method outperforms the other. On the other hand, we applied feature selection methods on the feature vectors of training data by selecting the most representative features in biological and in statistical meaning. We used phylogenetic tree of organisms to identify the organisms which are evolutionarily significant. Additionally we applied Fisher&sbquo / &Auml / &ocirc / s test method to select the features which are most representative statistically. The accuracy and TPR-FPR values obtained by feature selection methods could not provide to make a certain decision on the performance comparisons. However it can be mentioned that phylogenetic tree method resulted in acceptable prediction values when compared to Fisher&sbquo / &Auml / &ocirc / s test.

Microarray technology enables researchers to measure the expression levels of thousands of genes simultaneously to understand relationships between genes, extract pathways, and in general understand a diverse amount of biological processes such as diseases and cell cycles. While microarrays provide the great opportunity of revealing information about biological processes, it is a challenging task to mine the huge amount of information contained in the microarray datasets. Generally, since an accurate model for the data is missing, first a clustering algorithm is applied and then the resulting clusters are examined manually to find genes that are related with the biological process under inspection. We need automated methods for this analysis which can be used to eliminate unrelated genes from data and mine for biologically important genes. Here, we introduce a general methodology which makes use of traditional clustering algorithms and involves integration of the two main sources of biological information, Gene Ontology and interaction networks, with microarray data for eliminating unrelated information and find a clustering result containing only genes related with a given biological process. We applied our methodology successfully on a number of different cases and on different organisms. We assessed the results with Gene Set Enrichment Analysis method and showed that our final clusters are highly enriched. We also analyzed the results manually and found that most of the genes that are in the final clusters are actually related with the biological process under inspection.

Proteins participate in the majority of cellular processes. To determine the function of a protein it is not sufficient to solely know its sequence, its structure in isolation, or how it works individually. Additionally, we need to know how the protein interacts with other proteins in biological networks. This is because most of the proteins perform their main function through interactions. This thesis sets out to improve the understanding of protein-protein interaction networks (PPINs). For this, we propose three approaches: (1) Studying measures and methods used in social and complex networks. The methods, measures, and properties of social networks allow us to gain an understanding of PPINs via the comparison of different types of network families. We studied models that describe social networks to see which models are useful in describing biological networks. We investigate the similarities and differences in terms of the network community profile and centrality measures. (2) Studying PPINs and their role in evolution. We are interested in the relationship of PPINs and the evolutionary changes between species. We investigate whether the centrality measures are correlated with the variability and similarity in orthologous proteins. (3) Studying protein features that are important to evaluate, classify, and predict interactions. Interactions can be classified according to different characteristics. One characteristic is the energy (that is the attraction or repulsion of the molecules) that occurs in interacting proteins. We identify which type of energy values contributes better to predicting PPIs. We argue that the number of energetic features and their contribution to the interactions can be a key factor in predicting transient and permanent interactions. Contributions of this thesis include: (1) We identified the best community sizes in PPINs. This finding will help to identify important groups of interacting proteins in order to better understand their particular interactions. We furthermore find that the generative model describing biological networks is very different from the model describing social networks A generative model is a model for randomly generating observable data. We showed that the best community size for PPINs is around ten, different from the best community size for social and complex network (around 100). We revealed differences in terms of the network community profile and correlations of centrality measures; (2) We outline a method to test correlation of centrality measures with the percentage of sequence similarity and evolutionary rate for orthologous proteins. We conjecture that a strong correlation exists. While not obtaining positive results for our data. Therefore, (3) we investigate a method to discriminate energetic features of protein interactions that in turn will improve the PPIN data. The use of multiple data sets makes possible to identify the energy values that are useful to classify interactions. For each data set, we performed Random Forest and Support Vector Machine with linear, polynomial, radial, and sigmoid kernels. The accuracy obtained in this analysis reinforces the idea that energetic features in the protein interface help to discriminate between transient and permanent interactions. / Graduate / 0984

Tradicionalmente, nichos populacionais são descritos como a somatória de todos os recursos utilizados por uma população. Entretanto, diversos estudos mostram que indivíduos dentro de uma população podem usar recursos de forma distinta. Investigamos três maneiras pelas quais indivíduos podem variar quanto ao uso do recurso. Indivíduos podem apresentar a mesma preferência por presas, mas diferir na propensão à adição de novos itens alimentares em sua dieta (Preferências Compartilhadas); indivíduos podem apresentar a mesma presa preferida mas diferirem em suas presas alternativas (Refúgio Competitivo); ou indivíduos podem apresentar presas preferidas distintas (Preferências Distintas). Estudamos os padrões de interação que emergem sob os pressupostos de cada um dos modelos usando redes de interação entre indivíduos e os recursos que eles consomem. Dessa forma, para derivarmos as previsões de cada um dos modelos de uso de recurso, desenvolvemos modelos simples que geram redes de interação segundo regras que seguem os pressupostos dos modelos e confrontamos essas previsões com dados empíricos, comparando a estrutura dessa redes de interação. Encontramos que o modelo que menos se assemelha ao padrão de uso de recurso observado para as populações estudadas foi o modelo de Preferências Compartilhadas. Para as populações estudadas, a variação intrapopulacional na escolha de presas parece estar mais associada a diferenças nas sequências de preferências por presas entre indivíduos e não à propensão desses indivíduos em adicionarem novos recursos às suas dietas. / Traditionally, a population\'s niche is described as the sum of all resources consumed by a population. However, several studies have highlighted that individuals within a population can use resources differently. We investigate three ways in which individuals can vary in their resource use. Individuals can show the same preference for prey, but differ in their likelihood of adding new prey to their diets (Shared Preferences); individuals can share the same top-ranked prey but differ in their alternative prey (Competitive Refuge); or individuals can have different top-ranked prey (Distinct Preferences). We studied the pattern of interaction that emerges under each model\'s assumption using interaction networks between individuals and the resources they consume. In this sense, to derive the predictions associated with each model of resource use, we developed simple models that generates interaction networks according to a set of rules that represent the assumptions of each model and then confronted these predictions with empirical data on interaction networks, by looking at the structure of these interaction networks. We found that the model that least resembles the pattern of resource use observed in the populations studied was the Shared Preferences model. For the studied populations, intrapopulation variation is not associated with individuals sharing the same rank sequence and differing in their willingness to add new resources to their diets. Instead, it seems that differences in the rank sequence of prey choice are more important in structuring the pattern of resource use in these populations.

Orientadores: João Vasconcellos Neto, Miguel Francisco de Souza Filho / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-26T15:26:25Z (GMT). No. of bitstreams: 1 Freitas_KelsenFerreira_D.pdf: 2228671 bytes, checksum: 0a1e387d8f6a78f2474f17326ed55b42 (MD5) Previous issue date: 2014 / Resumo: As espécies de plantas disponíveis em uma comunidade, sua estrutura e abundância são elementos cruciais que influenciam nas dinâmicas e interações de populações de insetos herbívoros, uma vez que definem a base de recursos e refletem na interação com outras populações de insetos herbívoros, como predadores e parasitoides. Estudos relacionados às moscas-das-frutas concentram-se em levantamentos de espécies, em especial aquelas consideradas pragas, e abordam principalmente os padrões populacionais. A densidade populacional de tefritídeos e lonqueídeos está intimamente ligada à abundância de plantas hospedeiras e de seus inimigos naturais. Os parasitoides das moscas-das-frutas são micro-himenópteros (Hymenoptera) que atacam e se alimentam das larvas dentro dos frutos. O reconhecimento de padrões de interação das moscas-das-frutas com plantas hospedeiras, em especial nas espécies nativas, e as relações com seus inimigos naturais são importantes para a compreensão da utilização dos recursos disponíveis em uma comunidade e pelo reconhecimento de diferenças na dieta entre as espécies ou populações de uma mesma espécie. O objetivo deste trabalho foi estudar a estrutura da comunidade de moscas-das-frutas e seus parasitoides em diferentes espécies de plantas em uma policultura orgânica entre fragmentos de Mata Atlântica localizada no município de Paraibuna. A utilização de plantas hospedeiras difere entre as espécies de moscas-das-frutas. Apesar de a policultura causar alterações da fisionomia vegetal, foi observado que a estrutura da comunidade de moscas-das-frutas possui características encontradas em comunidades de insetos de florestas tropicais, onde espécies de insetos frugívoros são mais especialistas em família de plantas. A utilização de plantas hospedeiras foi distinta entre as espécies de parasitoides. O fruto foi o fator que mais influenciou o parasitismo das larvas de moscas-das-frutas. As espécies da família Myrtaceae são reservatórios para as espécies de parasitoides da família Braconidae. As interações estabelecidas entre as moscas-das-frutas e as espécies de plantas hospedeiras e entre os parasitoides de moscas e as plantas hospedeiras foram marcadas pela heterogeneidade no número de interações, sendo que um pequeno número de espécies de moscas estabeleceu relações com um grande número de espécies vegetais, enquanto que a maioria delas estabeleceu interações com apenas uma espécie vegetal e vice-versa, apresentando as mesmas propriedades de uma rede de interação aninhada. A interação potencial entre moscas-das-frutas e parasitoides também possuem os padrões de aninhamento. A paisagem natural modificada em policultura apresentou semelhanças com outras comunidades de insetos frugívoros de regiões tropicais / Abstract: The plant species found in a community, their structure and abundance are crucial elements that influence the dynamics and interactions of populations of herbivorous insects since they define the resource base and reflect the interaction with other populations of herbivores, predators and parasitoids. The studies related to fruit flies are concentrated on surveys of species, especially those considered pests, and address the population patterns. Many efforts to understand the patterns of communities of endophagous frugivorous insects and the use of host plants. The population density of tephritids and lonchaeids is closely connected to the abundance of host plants and their natural enemies. The parasitoids of fruit flies are hymenopteran parasitoids that attack and feed on the larvae inside the fruit. The acknowledgment of interaction patterns of fruit flies with host plants, especially the native species, and relationships with their natural enemies are important for understanding the use of available resources in a community and for recognizing the diet differences between species or populations of the same species. The purpose of this work was to study the structure of the community of fruit flies and their parasitoids in different plant species of an organic polyculture between forest fragments located in Paraibuna ¿ SP. The use of host plants was different among species of fruit flies. Although polyculture causes changes in vegetation type, it was observed that the structure of the fruit flies has features found in insect communities in tropical forests, where most species of frugivorous insects are specialists in plant family community. The use of host plants that sheltered the larvae of fruit flies was different among species of parasitoids. The fruit was the factor that most influenced the parasitism of the larvae of fruit flies. The Myrtaceae species are reservoirs to the parasitoid species of braconids. The interactions established between the fruit flies and species of host plants and between parasitoids and host plants that sheltered larvae of fruit flies were marked by heterogeneity in the number of interactions, where a small number of species of flies established relations with a large number of plant species, while most of these interactions established with only one plant species, and vice versa, with the same properties of a nested interaction network. The potential interaction between fruit flies and parasitoids also have patterns of nesting. The modified natural environment in polyculture showed similarities with other communities of frugivorous insects in tropical regions / Doutorado / Biodiversidade Animal / Doutor em Biologia Animal

Butterflies fulfill a unique role among insect pollinators as long-distance flyers. This makes butterflies particularly valuable as vectors of genetic diversity among spatially isolated plant populations. Like many insects, though, butterfly populations have experienced significant declines in recent years. To help inform conservation efforts, and to investigate community and species level dynamics, I studied butterflies and their floral resources as part of a three year pollinator survey across the state of North Dakota. At the community level, I analyzed butterfly-flower interaction networks across space and time. I then examined the specialization of individual species within those networks and their contributions to network structure. I also evaluated spatial and temporal distribution patterns of monarch butterflies, regal fritillaries, and their plant resources. Results revealed dynamic spatiotemporal relationships between butterflies and their plant resources that have important implications for conservation efforts and the study of ecological communities.