Les bactéries magnétotactiques synthétisent des organites spécialisés appelés magnétosomes. Ils sont composés d'un cristal magnétique entouré d'une membrane et de protéines spécifiques. Arrangés en chaîne dans la bactérie, ils orientent la bactérie dans le champ magnétique, ce qui simplifierait sa recherche d’environnements microaérophiles. Dans le génome de toutes les souches magnétotactiques séquencées, l'îlot génomique de magnétotaxie contient les gènes impliqués dans la formation des magnétosomes. Nous avons procédé à l’annotation du génome de la souche magnétotactique marine QH-2 et montré que la région du génome codant les gènes de la magnétotaxie n'est, dans ce cas, pas définie comme un îlot génomique, bien qu’elle ait été acquise par transfert latéral de gènes. Dans le génome de M. magneticum AMB-1, nous avons identifié un nouvel îlot génomique de petite taille que nous avons appelé l'îlet de magnétotaxie portant 7 gènes homologues à des gènes liés à la synthèse des magnétosomes. Pour répondre à la question de la fonction biologique de cet îlet génomique, nous avons examiné le rôle de l'un des sept gènes, mamK-like. MamK-like exprimée dans E. coli forme des filaments, comme observé pour MamK. La polymérisation in vitro des deux protéines est également comparable, mais présente des différences structurales. En outre, nous démontrons que mamK-like est transcrite dans AMB-1 de type sauvage et dans le mutant ΔmamK. Par immuno-marquage, nous montrons la présence d'un filament dans le mutant ΔmamK, probablement dû à MamK-like. Nous émettons l'hypothèse que ce filament contribue à maintenir l’organisation en chaîne des magnétosomes dans la souche mutante. / Magnetotactic bacteria synthesise specialised organelles called magnetosomes. They are composed of a magnetic crystal surrounded by a lipid bilayer and specific proteins. Arranged in chains, they orient magnetotactic bacteria in the geomagnetic field, thereby simplifying their search for their microaerophilic environments. In each sequenced magnetotactic strain, the magnetotaxis genomic island contains the genes involved in magnetosomes formation. Our annotation of the newly sequenced genome of the magnetotactic strain QH-2 shows that the region coding the magnetotaxis genes is not a genomic island, though it has been acquired by lateral genes transfer. In the genome of M. magneticum AMB-1 we identified a new, small genomic island we termed the magnetotaxis islet, encoding 7 genes homologous to genes related to the magnetosomes synthesis. To assess the question of the biological function of this genomic islet, we further investigated the role of one of the seven genes, mamK-like. Filaments were observed in E. coli cells expressing MamK-like-Venus fusion by fluorescence microscopy. In vitro polymerization of both isoforms is comparable, though some differences are present at the structural level. In addition, we demonstrate that mamK-like is transcribed in AMB-1 wild-type and ΔmamK mutant cells. Immunolabelling assay using an anti-MamK antibody reveals the presence of a filament in the ΔmamK mutant. We hypothesise that this filament is due to MamK-like and that it helps maintaining a chain-like organisation of magnetosomes in the mutant strain.

Aeolian dust exerts a notable influence on atmospheric and oceanic conditions and human health, particularly in arid and semi-arid regions like Saudi Arabia. Dust is often characterized by its mineral and chemical composition, but there is a microbiological component of natural aerosols which has received comparatively little attention. Moreover, the amount of materials suspended in the atmosphere is highly variable from day to day. Thus, knowing the loads of dust and suspended microbes and its variability over the year is essential to understand the possible effects of dust on the Red Sea ecosystem. Here, we present the first estimates of dust and microbial loads at a coastal side on the Red Sea over a two-year period supplemented with information from dust samples collected along the Red Sea in offshore water and their variability. Weekly average dust loads ranged from 4.63 to 646.11 μg m-3, while the abundance of airborne prokaryotic cells and viral particles ranged from 31,457 to 608,333 cells m-3 and from 69,615.5 to 3,104,758 particles m-3, respectively. These are the first estimates of airborne microbial abundance that we are aware of in this region. The large number of dust particles and suspended microbes found in the air indicates that airborne microbes may have a large impact on our health and that of the Red Sea ecosystem.

CD16 is a physiologically essential Fc and #947; receptor III as either a single- pass transmembrane protein (CD16A) or as a glycosylated phosphatidylinositol (GPI) anchored protein (CD16B) on the surface of immune cells that have been implicated in many autoimmune and immune complex-mediated diseases. Its functions include binding and clearing antibody (IgG) coated foreign pathogens, receptor-mediated phagocytosis, and triggering antibody dependent cellular cytotoxicity. It is well established that these functions depend on protein-protein interaction between CD16 and the Fc domain of IgG. However, the molecular details of CD16-IgG interactions are less well defined, but are essential to developing therapeutic compounds to treat many autoimmune and IC diseases. Stable mammalian cell lines expressing wild-type CD16 isoforms and site-specific mutants, including extracellular soluble fragments of CD16 have been established. Soluble forms of wild type CD16A and these CD16 mutants were expressed in a bacterial pathway in order to amass sufficient quantities for x-ray crystallographic studies. The soluble portions of wild-type CD16A and several site-specific CD16A and CD16B mutants were constructed by PCR amplification and ligation with a pET vector. The proteins were expressed in a prokaryotic pathway, BL21 AI, for 8-10 hours and lysed to obtain inclusion bodies. A hand-held sonicator was used to wash the inclusion bodies, while a Urea solution separated and dissolved the proteins. The target proteins were then refolded by rapid dilution, concentrated with a stir cell, and purified. Wild type sCD16A and four site specific mutants were constructed with good sequencing, while wild type sCD16A, sCD16A F176V, and sCD16A G147D were expressed and refolded to optimal levels. X-ray crystallographic data has been collected from sCD16A F176V as a result of these studies and crystals are currently being grown from wild type sCD16A and sCD16A G147D.

Thesis (M.S.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains v, 61 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 50-56).

Exonic sequences of eukaryotic genes are interspersed with introns which when accurately removed from the primary transcript (pre-mRNA) results in a functional transcript. These splicing reactions are carried out by the spliceosome, consisting of U1, U2, U4, U5, U6 snRNAs and 150 non-snRNP proteins, which assemble onto the pre-mRNA and catalyzes the two invariant transesterification reactions (Will and Luhrmann, 2006). The flexibility in choice of splice sites allows for alternative splicing which has immensely contributed to eukaryotic genome evolution and in diversifying the metazoan proteome (Nilesen and Graveley, 2010). Dynamic yet ordered interactions between U2, U5 and U6 snRNAs and Prp8, Prp16, Prp17, Prp18, Slu7 and Prp22 splicing factors are required in vitro for second-step of splicing of budding yeast and human model transcripts (Umen and Guthrie, 1995a; Horowitz, 2012). ScSlu7 aids 3’ss selection while its strongly associated partner ScPrp18 stabilises U5 snRNA-exonic interactions (James et al., 2002; Aronova et al., 2007). These factors are dispensable in vitro, for the splicing of introns with short branch nucleotide to 3’ss distances (Brys and Schwer, 1996; Zhang and Schwer, 1997). Nearly 43% of fission yeast genes have short introns, with degenerate splice-signals and unconventional Py(n) tracts (Kuhn and Kaufer, 2003). As these features differ extensively from budding yeast and are interestingly more representative of fungal and other eukaryotic introns, fission yeast is an attractive unicellular model to investigate alternate splice-site recognition and assembly mechanisms. Mechanistic details of the second catalytic step are poorly understood in fission yeast. Strikingly, mutations in 3’ss and Py(n) tract intronic cis elements, known to block second step splicing in budding yeast, cause pre-catalytic arrest with unspliced pre-mRNA accumulation in fission yeast (Romfo and Wise, 1997). Studies in our laboratory focussed on understanding the functions for fission yeast SpPrp18 and SpSlu7 predicted to be second-step factors, revealed remarkable differences as compared to their budding yeast counterparts. Unexpectedly, SpPrp18 and SpSlu7 were found by our lab to be required before catalysis and these proteins do not directly associate with each other. Genome-wide splicing studies in a missense slu7-2 mutant indicated widespread yet intron-specific splicing functions for SpSlu7 (Banerjee et al., 2013). Crucial functions were attributed to helix-5 and conserved region loop of SpPrp18 and in vivo splicing analysis in selected cellular transcripts in a missense mutant (V194R) also revealed intron-specific functions (Thesis, N Vijaykrishna). In this study, we have advanced our understanding of SpPrp18 functions by identifying its global substrates and correlating with its intron-specific roles. Through molecular and genetic approaches, we have probed its role in splicing/spliceosome assembly. We identified intronic features within substrates that increase the propensity for the requirement of SpSlu7 for efficient splicing. Further, using findings from the genome-wide alternative splicing patterns in SpSlu7 and SpPrp18 mutants, we have attempted to understand their role in splice-site choice and thus alternative splicing. Ia. Understanding global splicing functions and spliceosomal interactions of fission yeast splicing factor SpPrp18 Since SpPrp18 is an essential gene, our lab generated the strains (prp18-5int [V194R] and WTint), where the thiamine-repressible promoter allowed conditional expression of wild-type or mutant allele integrated at the heterologous leu1 locus. Splicing efficiency of certain cellular transcripts with differing intron characteristics was assessed by semi-quantitative RT-PCR studies and the data suggested intron-specific SpPrp18 roles (in collaboration with Vijaykrishna N). This prompted us to investigate the global splicing role for SpPrp18 for which we used splicing-sensitive microarrays having custom-designed probes to distinguish unspliced pre-mRNA and spliced mRNA for every individual pombe intron. RNA from prp18-5int (V194R) and WTint cells was used in these experiments. We derived a stringent dataset of 258 introns which were statistically significant and correlated in two biological replicate RNA samples, for various probes. Hierarchical clustering of this dataset showed that the depletion of wild-type SpPrp18 triggered a range of splicing phenotypes like (A) pre-mRNA accumulation with mRNA reduction (B) pre-mRNA accumulation (C) spliced mRNA reduction and (D) unchanged pre-mRNA and mRNA levels. Statistical analysis of cis motifs that may correlate with the substrate-specific SpPrp18 splicing functions was done, but the data showed a lack of a global discriminatory primary sequence feature. However, a subtle intron-specific role for Py(n) tracts located between 5’ss and BrP was deduced for SpPrp18. This lead was validated by examining the in vivo splicing efficiency of minitranscripts with wild-type or an altered Py tract length, carried out for a SpPrp18 dependent and an independent intron. To specifically address if SpPrp18 activity was required for second-step splicing we investigated, using primer extension analyses, for lariat intron-3’exon species, an intermediate formed after step 1. We observed that even in prp18-5int dbr1∆ double mutants (where lariat molecules are not degraded) the cells accumulate only unspliced pre-mRNA and not lariat intermediates, a signature of an early arrest prior to the first transesterification reaction. Strengthening these findings, positive genetic interactions were noted between prp18-5int and ts mutants in two factors (U2AF59 and SpPrp1) involved in precatalytic spliceosome assembly and activation. On the whole, our genome-wide studies indicate intron-specific pre-catalytic functions for SpPrp18 supported by genetic interactions with early acting splicing factors involved in spliceosomal assembly and activation. Ib. Identification of intronic features that determine substrate-specific splicing functions for SpSlu7 In vitro studies with ScSlu7 and hSlu7 show their influence in 3’ss selection when BrP to 3’ss distance is greater than 7 nts and 23 nts respectively; but the global substrates are not known in either species (Brys and Schwer, 1996; Chua and Reed, 1999b). Genome-wide analysis of the splicing efficiency changes in cells with the mis-sense spslu7+ mutant (slu7-2), previously carried out in our lab, revealed a spectrum of splicing defects (Banerjee et al., 2013). To further understand the intron context-specific roles for SpSlu7, we examined intronic cis features that may correlate with SpSlu7 dependence. Statistical analyses of the affected (422 introns) and unaffected categories (90 introns) revealed that intron length, BrP to 3’ss distance and AU content are multiple discriminatory cis features that govern SpSlu7 splicing functions. To assess the contribution of these intronic features we tested whether altering these cis elements changes a transcript’s dependency (or otherwise) on SpSlu7 by RT-PCR analyses. For these studies, we generated plasmid expressed mini-genes containing the respective wild-type intron or intron with altered BrP-3’ss distances. We used nab2+ I2 as a case of an intron spliced independent of SpSlu7 and rhb1+ I1 as a representative for SpSlu7 dependent intron. Experiments testing their in vivo splicing status proved that BrP-3’ss distance is a cis feature that dictates SpSlu7 splicing functions in a context-dependent manner. The intronic AU content particularly between the 5’ss and the BrP was assessed in minigene constructs where a chimeric intron was generated by swapping the low AU containing sequences in the 5’ss to BrP stretch of cdc2+ I2 with AU rich bpb1+ I1 5’ end sequences. The results reaffirmed that low intronic AU content particularly at the 5’ end co-relates with SpSlu7 dependency. Hence, we have deduced novel intronic elements, which perhaps in combination, create a contextual dependence for SpSlu7 to facilitate efficient splicing. II. Alternative splice-site selection in fission yeast and studies on the role of splicing factors SpSlu7 and SpPrp18 Budding yeast second-step splicing factors ScSlu7 and ScPrp18 mediate 3’ss choice in the single intron containing transcripts. Fission yeast genome encodes cis and trans factors that promote alternative splicing similar to higher eukaryotes. In this study, we have devised a data analysis pipeline to identify alternative splice events in multi-intronic transcripts of fission yeast. Further, we utilised this information to interrogate the global role for SpSlu7 and SpPrp18 in alternate splice site selection. We mapped the microarray probe sequences corresponding to all theoretically possible non-consecutive splice junctions of S. pombe transcripts onto two independent experimental next-generation (NGS) transcriptomes from wild-type samples and identified 104 exon skipping events with NGS reads more than 3 (Wilhelm et al., 2008; Rhind et al., 2011). We further generated a stringent list of ten exon skipping events having high sequence reads as well as raw intensity value in our microarray experiments with wild-type cells. Two representative events from this list, an abundant rps13+ exon 2 skipped alternative mRNA and less abundant ats1+ exon 3 skipped alternative mRNA were then taken up for experimental analyses by semi-quantitative RT-PCR assays. We confirmed these events and further noted that SpSlu7 and SpPrp18 were required for the constitutive splicing of ats1+ E2-I2-E3-I3-E4 cassette. On the other hand, SpSlu7, and not SpPrp18, exerted a subtle influence on the skipping of exon 3. In addition to exon 3 skipped mRNA, we detected an intron 3 retained ats1+ alternative mRNA (E2-E3-I3-E4) in wild-type cells. Assessment of this event in cells metabolically depleted of SpSlu7 and SpPrp18 showed a reduced abundance of this species in both instances. This suggests a role for functional SpSlu7 and SpPrp18 in retaining intron 3 in ats1+ transcripts in vivo. Among the ten microarray probes, custom-designed to detect specifically the mRNA isoforms arising from altered use of donor 5’ splice sites, we were able to detect in wild-type cells the utilisation of a downstream alternate 5’ss in intron 1 of D-Tyr-tRNA deacylase. Comparative assessment of this splicing event in prp18-5int and slu7-2 mutant cells revealed that SpPrp18 is preferentially required for the utilisation of its alternative 5’ss and such a role has not yet been attributed to its budding yeast and human homologs. On the other hand, SpSlu7 was required equally for utilisation of canonical and non-canonical 5’ss. Differential requirement for SpSlu7 for the utilisation of an upstream non-canonical 3’ss and the canonical 3’ss in DUF3074 intron 1, was noted. This role of SpSlu7 in 3’ss selection is similar to that known from in vitro studies of its budding yeast and human counterparts. Overall, we identified and experimentally validated novel alternate splice events in fission yeast and we infer an important role for SpSlu7 and SpPrp18 in both 5’ss and 3’ss selection.

The ocean plays essential roles in Earth's biochemistry. Most of the nutrient transformations that fuel trophic webs in the ocean are mediated by microorganisms. The extent of phylogenetic and metabolic diversity of key culture and uncultured marine microbial clades started to be revealed due to progress in sequencing technologies, however we still lack a comprehensive understanding of the evolutionary processes that led to the microbial diversity we see in the ocean today. In this dissertation, I apply phylogenomic and comparative genomic methods to explore the evolutionary genomics of bacterial and archaeal clades that are relevant due to their abundance and biogeochemical activities in the ocean. In Chapter 1, I review relevant literature regarding the evolutionary genomics of marine bacteria and archaea, with emphasis on the origins of marine microbial diversity and the evolution of genome architecture. In Chapter 2, I use a comparative framework to get insights into the evolutionary forces driving genome streamlining in the Ca. Marinimicrobia, a clade widely distributed in the ocean. This project shows that differences in the environmental conditions found along the water column led to contrasting mechanisms of evolution and ultimately genome architectures. In Chapter 3, I assess the phylogenetic signal and congruence of marker genes commonly used for phylogenetic studies of bacteria and archaea and propose a pipeline and a set of genes that provide a robust phylogenetic signal for the reconstruction of multi-domain phylogenies. In Chapter 4, I apply a phylogeny-based statistical approach to evaluate how tightly genome size in bacteria and archaea is linked to evolutionary ii history, including marine clades. I present evidence suggesting that phylogenetic history and environmental complexity are strong drivers of genome size in prokaryotes. Lastly, in Chapter 5, I estimate the emergence time of marine bacterial and archaeal clades in the context of the Prokaryotic Tree of Life and demonstrate that the diversification of these groups is linked to the three main oxygenation periods occurring throughout Earth's history. I also identify the metabolic novelties that likely led to the colonization of marine realms. Here I present methodological frameworks in the fields of comparative genomics and phylogenomics to study the evolution of marine microbial diversity and show evidence suggesting that the main evolutionary processes leading to the extant diversity seen in the ocean today are intimately linked to geological and biological innovations occurring throughout Earth's history. / Doctor of Philosophy / The ocean plays essential roles in the functioning of our planet. Many of the nutrient's transformation happening in marine environments are mediated by microorganisms, whose metabolic activities underpin higher trophic levels. The identity of the most prevalent marine microbial groups has been reveled during the last two decades through sequencing technologies. Despite having a great progress in our understanding of the functions that these microorganisms have in the ocean; we still lack information about the evolutionary processes that allowed their diversification and colonization into marine realms. In this work, I developed and applied computational strategies to disentangle the evolutionary genomics of marine microorganisms. One particularity about most these marine groups is that they have very small genomes. To explore the evolutionary forces driving their genome reduction, I analyzed a broad set of genomes of Marinimicrobia, a bacterial group widely distributed in the ocean. This analysis shows that genome reduction in Marinimicrobia is driven by negative selection, an evolutionary force that allows the deletion of non-essential genes, subsequently leading to genome reduction. Moreover, I developed a benchmarked pipeline for the reconstruction of phylogenetic trees to study the evolutionary relationships of microorganisms. This pipeline allowed me to link the diversification of the main marine groups and the geological periods in which they first emerged. I discovered that the colonization of these groups happened during three different periods, which are coincident with the main oxygenation events occurring across Earth's history. Moreover, the diversification of vi marine microbial groups was associated with the acquisition of genes to exploit the newly created niches that followed the oxygenation of the atmosphere and the ocean. Overall, my work shows that the diversification of the marine microbial clades that are essential for the functioning of the ocean is intimately linked to the redox state of the ocean and the atmosphere throughout Earth's history.

Background: MicrO is an ontology of microbiological terms, including prokaryotic qualities and processes, material entities (such as cell components), chemical entities (such as microbiological culture media and medium ingredients), and assays. The ontology was built to support the ongoing development of a natural language processing algorithm, MicroPIE (or, Microbial Phenomics Information Extractor). During the MicroPIE design process, we realized there was a need for a prokaryotic ontology which would capture the evolutionary diversity of phenotypes and metabolic processes across the tree of life, capture the diversity of synonyms and information contained in the taxonomic literature, and relate microbiological entities and processes to terms in a large number of other ontologies, most particularly the Gene Ontology (GO), the Phenotypic Quality Ontology (PATO), and the Chemical Entities of Biological Interest (ChEBI). We thus constructed MicrO to be rich in logical axioms and synonyms gathered from the taxonomic literature. Results: MicrO currently has similar to 14550 classes (similar to 2550 of which are new, the remainder being microbiologically-relevant classes imported from other ontologies), connected by similar to 24,130 logical axioms (5,446 of which are new), and is available at (http://purl.obolibrary.org/obo/MicrO.owl) and on the project website at https://github.com/carrineblank/MicrO. MicrO has been integrated into the OBO Foundry Library (http://www.obofoundry.org/ontology/micro.html), so that other ontologies can borrow and re-use classes. Term requests and user feedback can be made using MicrO's Issue Tracker in GitHub. We designed MicrO such that it can support the ongoing and future development of algorithms that can leverage the controlled vocabulary and logical inference power provided by the ontology. Conclusions: By connecting microbial classes with large numbers of chemical entities, material entities, biological processes, molecular functions, and qualities using a dense array of logical axioms, we intend MicrO to be a powerful new tool to increase the computing power of bioinformatics tools such as the automated text mining of prokaryotic taxonomic descriptions using natural language processing. We also intend MicrO to support the development of new bioinformatics tools that aim to develop new connections between microbial phenotypes and genotypes (i.e., the gene content in genomes). Future ontology development will include incorporation of pathogenic phenotypes and prokaryotic habitats.

Ce mémoire rapporte deux approches de la synthèse des protéines à l'échelle de la molécule unique. Nous utilisons la microscopie de fluorescence en onde évanescente pour sonder l'activité traductionnelle de deux types de ribosomes. Les premiers, issus d'E. Coli (organisme procaryote), sont mutés afin de les marquer d'un nanocristal semiconducteur (QD). La fin de la traduction, qui correspond au décrochage du ribosome de l'ARNm lorsque celui-ci atteint le codon stop, est alors mise en évidence par la disparition du QD de la surface de l'échantillon. Le deuxième type de ribosome étudié est quant à lui extrait de cellules de lapins (organisme eucaryote) et est dit "sauvage", c'est à dire qu'il n'a pas subi de modification, tandis qu'un oligonucléotide marqué d'un fluorophore est hybridé à l'ARNm. L'activité hélicase du ribosome lui permettant de séparer deux brins complémentaires, l'oligonucléotide et donc le fluorophore disparaissent en même temps que le ribosome parcourt l'ARNm, permettant ainsi de sonder l'activité du ribosome. Nous donnons pour ces deux types de ribosomes une vitesse moyenne de la traduction dans des milieux contenant les facteurs de la traduction issus d'extraits cellulaires.La deuxième approche de la synthèse des protéines porte sur les propriétés de l'ARNm, support de l'information génétique codant pour la séquence des protéines. Nous avons développé un montage de pince optique permettant de manipuler et caractériser les propriétés mécaniques d'oligonucléotides, ainsi qu'une méthode originale de calibration de ce piège optique. La cohérence de nos mesures sur l'étirement d'un double brin d'ADN avec la littérature nous permettra de poursuivre notre étude sur la mesure des forces nécessaires pour ouvrir une structure secondaire de l'ARNm. / We hereby report two approaches of the protein synthesis at the single molecule level. We use total internal reflection fluorescence microscopy to study the translation kinetic of two different types of ribosomes. The first ones, extracted from E. Coli (prokaryotic organism), are mutated in order to label them with a quantum dot (QD). The end of translation, which corresponds to the dissociation of the ribosome from the mRNA when the stop codon has been reached, is highlighted by the disparition of the QD from the surface. The second type of ribosome is extracted from rabbit cells (eukaryotic organism) and has not been modified (wild type), while a labeled oligonucleotide is hybridized on the mRNA. The helicase activity of the ribosome allowing the dissociation of two complementary strands, the oligonucleotide and so the label disappear at the same time while the ribosome moves along the mRNA and thus inform us about its activity. For these two types of ribosomes we measure their average translation speed in cell extracts.The second approach focuses on the properties of the mRNA, carrying the genetic code for the protein sequence. We developped an optical tweezer setup in order to manipulate and characterize the mechanical properties of nucleotides, as well as an original method to calibrate this optical trap. The consistency of our measurements with the litterature on the properties of a double stranded DNA will allow us to study secondary structures of mRNA.

Made available in DSpace on 2015-03-05T13:57:00Z (GMT). No. of bitstreams: 0 Previous issue date: 11 / Nenhuma / A região promotora é uma seqüência de DNA que localiza-se anteriormente a uma determinada região gênica. Ela é responsável pelo início do processo de transcrição de um gene ou conjunto de genes. Assim, ela também atua como um elemento regulador da expressão gênica. O estudo da regulação da expressão gênica é relevante porque é essencial para a compreensão da maquinária vital dos seres vivos, já que a diferença entre duas espécies está mais relacionada em como e quando seus genes estão “ativos” ou “inativos” do que com a estrutura destes em si. Embora exista métodos computacionais para a predição de genes com boa acurácia, o mesmo não é conseguido para os promotores. Esta dificuldade deve-se ao pequeno e pouco conservado padrão das seqüências, gerando assim resultados com alto número de falsos positivos. Além dos motivos consensuais, os promotores possuem características físicas que os diferem de seqüências não-promotoras. No entanto, estas ainda não são amplamente utilizadas no problema de predição in silic / The promoter region is localized few base pairs before the gene region. It is responsible by initiate the gene expression process, thus, it plays a regulatory role. The study about the gene expression regulation is a great area, since it can assist in the comprehension of complex metabolic network presented by several organisms and, because the difference between two different species is how and when your genes are turn off and turn on than your structure. The computational methods to gene prediction have a good accuracy, but this is not achieved in the promoter prediction. This difficulty occurs because the length of promoter and the degenerate pattern presented, thus the results presented a great number of false positives. This work aims employed Neural Networks to promoter prediction and recognition of Escherichia coli by two approaches: whit the orthogonal codification and stability values of the promoter sequence. For characterization, realize the extraction rules of type if … then. The results in this

Made available in DSpace on 2015-03-05T13:57:00Z (GMT). No. of bitstreams: 0 Previous issue date: 28 / Nenhuma / Microarranjos têm sido fortemente usados para monitorar, somultaneamente, o padrão de expressão de milhares de genes. Assim, uma grande quantidade de dados tem sido gerada e o desafio atual é descobrir como extrair informações úteis destes conjuntos de dados. Dados de Microarranjos são fortemente especializados, envolvendo diversas variáveis de forma não linear e temporal, necessitando de modelos recorrentes não lineares, os quais são complexos para formular e analisar. Este trabalho propõe a utilização de Redes Nunes Recorrentes (RNR) como modelo para os dados devido às suas habilidades de aprendizado de sistemas nâo-lineares e complexos. Uma vez obtido um modelo para os dados utilizando uma RNR, é possível extrair regras que representam as características aprendidas. Analisando as regras em conjunto com a base de dados, propõe-se a representação do conhecimento utilizando Cadeias de Markov. Tais Cadeias são facilmente visualizadas, na forma de grafos de estados, apresentando as interações entre os níveis de / Array technologies have made it strainghtforward to simultaneously monitor the expression pattern of thousands of genes. Thus, a lot fot data is being generated and the challenge now is to discover how to extract useful information from these data sets. Microarray data is highly specialized. It involves several variables in a nonlinear and temporal way, demanding nonlinear recurrent free models, which are complex to formulate and to analyse. So, this work proposes the use of Rucurrent Neural Networks(RNN) for data modeling, due to their learning hability of nonlinear and complex systems. Once a model is obtained with a RNN for the data, it is possible to extract rules to represent the knowledge acquired by them. From rule analisys, this work proposes the representation of the knowledge by Markov Chains model, which is easily visualized in the form of a graph of states, which show the interactions among the gene expression levels and their changes in time. In this work, we propose a new approach to microarra