Superexpressão do gene dehidrina de Arachis duranensis em plantas transgênicas de Arabidopsis thaliana

Dissertação (mestrado)—Universidade de Brasília, Departamento de Botânica, Programa de Pós-Graduação em Botânica, 2016.

Cluster-based network model for time-course gene expression data

We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships.

Co-adaptive environments : investigation into computer and network enhanced adaptable, sustainable and participatory environments

This paper presents research in response to environmental concerns we face today. In a search for a better method to manage spaces and building resources consumed excessively through traditional top-down architectural solutions, the research began by speculating that the building spaces and resources can be managed by designing architectural systems that encourage a bottom-up approach. In other words, this research investigates how to design systems that encourage occupants and users of buildings to actively understand, manage and customise their own spaces. Specific attention is paid to the participation of building users because no matter how sophisticated the system is, the building will become as wasteful as conventional buildings if users cannot, or do not want to, utilise the system effectively. The research is still in its early stages. The intension of this paper is to provide a background to the issue, discuss researches and projects relevant to, but not necessarily about, architecture, and introduce a number of hypothesis and investigations to realise adaptable, participatory and sustainable environments for users.

Expression and connection : the integration of the reflective learning process and the writing process into social network sites

A number of instructors have recently adopted social network sites (SNSs) for learning. However, the learning design of SNSs often remains at a preliminary level similar to a personal log book because it does not properly include reflective learning elements such as individual reflection and collaboration. This article looks at the reflective learning process and the public writing process as a way of improving the quality of reflective learning on SNSs. It proposes a reflective learning model on SNSs based on two key pedagogical concepts for social networking: individual expression and collaborative connection. It is expected that the model would be helpful for instructors in designing a reflective learning process on SNSs in an effective and flexible way.

Stimulation of MMP-11 (stromelysin-3) expression in mouse fibroblasts by cytokines, collagen and co-culture with human breast cancer cell lines

Background Matrix metalloproteinases (MMPs) are central to degradation of the extracellular matrix and basement membrane during both normal and carcinogenic tissue remodeling. MT1-MMP (MMP-14) and stromelysin-3 (MMP-11) are two members of the MMP family of proteolytic enzymes that have been specifically implicated in breast cancer progression. Expressed in stromal fibroblasts adjacent to epithelial tumour cells, the mechanism of MT1-MMP and MMP-11 induction remains unknown. Methods To investigate possible mechanisms of induction, we examined the effects of a number of plausible regulatory agents and treatments that may physiologically influence MMP expression during tumour progression. Thus NIH3T3 and primary mouse embryonic fibroblasts (MEFs) were: a) treated with the cytokines IL-1β, IL-2, IL-6, IL-8 and TGF-β for 3, 6, 12, 24, and 48 hours; b) grown on collagens I, IV and V; c) treated with fibronectin, con-A and matrigel; and d) co-cultured with a range of HBC (human breast cancer) cell lines of varied invasive and metastatic potential. Results Competitive quantitative RT-PCR indicated that MMP-11 expression was stimulated to a level greater than 100%, by 48 hour treatments of IL-1β, IL-2, TGF-β, fibronectin and collagen V. No other substantial changes in expression of MMP-11 or MT1-MMP in either tested fibroblast culture, under any treatment conditions, were observed. Conclusion We have demonstrated significant MMP-11 stimulation in mouse fibroblasts using cytokines, matrix constituents and HBC cell lines, and also some inhibition of MT1-MMP. Our data suggest that the regulation of these genes in the complex stromal-epithelial interactions that occur in human breast carcinoma, is influenced by several mechanisms.

Detection of mRNA for nuclear receptor co-activators 1 and 3 in archival breast cancer tissue and surrounding stroma : a tissue expression study

Before the age of 75 years, approximately 10% of women will be diagnosed with breast cancer, one of the most common malignancies and a leading cause of death among women. The objective of this study was to determine if expression of the nuclear receptor coactivators 1 and 3 (NCoA1 and NCoA3) varied in breast cancer grades. RNA was extracted from 25 breast tumours and transcribed into cDNA which underwent semi-quantitative polymerase chain reaction, normalised using 18S. Analysis indicated that an expression change for NCoA1 in cancer grades and estrogen receptor alpha negative tissue (P= 0.028 and 0.001 respectively). NCoA1 expression increased in grade 3 and estrogen receptor alpha negative tumours, compared to controls. NCoA3 showed a similar, but not significant, trend in grade and a non-significant decrease in estrogen receptor alpha negative tissues. Expression of NCoA1 in late stage and estrogen receptor alpha negative breast tumours may have implications to breast cancer treatment, particularly in the area of manipulation of hormone signalling systems in advanced tumours.

Co-movements in commodity prices : a note based on network analysis

This article analyses co-movements in a wide group of commodity prices during the time period 1992–2010. Our methodological approach is based on the correlation matrix and the networks inside. Through this approach we are able to summarize global interaction and interdependence, capturing the existing heterogeneity in the degrees of synchronization between commodity prices. Our results produce two main findings: (a) we do not observe a persistent increase in the degree of co-movement of the commodity prices in our time sample, however from mid-2008 to the end of 2009 co-movements almost doubled when compared with the average correlation; (b) we observe three groups of commodities which have exhibited similar price dynamics (metals, oil and grains, and oilseeds) and which have increased their degree of co-movement during the sampled period.

Quasi-2D XY Magnetic Properties and Slow Relaxation in a Body Centered Metal Organic Network of [Co-4] Clusters

Octahedral Co2+ centers have been connected by mu(3)-OH and mu(2)-OH2 units forming [Co-4] clusters which are linked by pyrazine forming a two-dimensional network. The two-dimensional layers are bridged by oxybisbenzoate (OBA) ligands giving rise to a three-dimensional structure. The [Co-4] clusters bond with the pyrazine and the OBA results in a body-centered arrangement of the clusters, which has been observed for the first time. Magnetic studies reveal a noncollinear frustrated spin structure of the bitriangular cluster, resulting in a net magnetic moment of 1.4 mu B per cluster. For T > 32 K, the correlation length of the cluster moments shows a stretched-exponential temperature dependence typical of a Berezinskii-Kosterlitz-Thouless model, which points to a quasi-2D XY behavior. At lower temperature and down to 14 K, the compound behaves as a soft ferromagnet and a slow relaxation is observed, with an energy barrier of ca. 500 K. Then, on further cooling, a hysteretic behavior takes place with a coercive field that reaches 5 Tat 4 K. The slow relaxation is assigned to the creation/annihilation of vortex-antivortex pairs, which are the elementary excitations of a 2D XY spin system.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

Efficient Regular Expression Pattern Matching for Network Intrusion Detection Systems using Modified Word-based Automata

Network Intrusion Detection Systems (NIDS) intercept the traffic at an organization's network periphery to thwart intrusion attempts. Signature-based NIDS compares the intercepted packets against its database of known vulnerabilities and malware signatures to detect such cyber attacks. These signatures are represented using Regular Expressions (REs) and strings. Regular Expressions, because of their higher expressive power, are preferred over simple strings to write these signatures. We present Cascaded Automata Architecture to perform memory efficient Regular Expression pattern matching using existing string matching solutions. The proposed architecture performs two stage Regular Expression pattern matching. We replace the substring and character class components of the Regular Expression with new symbols. We address the challenges involved in this approach. We augment the Word-based Automata, obtained from the re-written Regular Expressions, with counter-based states and length bound transitions to perform Regular Expression pattern matching. We evaluated our architecture on Regular Expressions taken from Snort rulesets. We were able to reduce the number of automata states between 50% to 85%. Additionally, we could reduce the number of transitions by a factor of 3 leading to further reduction in the memory requirements.

Mycobacterium tuberculosis Response Regulators, DevR and NarL, Interact in Vivo and Co-regulate Gene Expression during Aerobic Nitrate Metabolism

Mycobacterium tuberculosis genes Rv0844c/Rv0845 encoding the NarL response regulator and NarS histidine kinase are hypothesized to constitute a two-component system involved in the regulation of nitrate metabolism. However, there is no experimental evidence to support this. In this study, we established M. tuberculosis NarL/NarS as a functional two-component system and identified His(241) and Asp(61) as conserved phosphorylation sites in NarS and NarL, respectively. Transcriptional profiling between M. tuberculosis H37Rv and Delta narL mutant strain during exponential growth in broth cultures with or without nitrate defined an similar to 30-gene NarL regulon that exhibited significant overlap with DevR-regulated genes, thereby implicating a role for the DevR response regulator in the regulation of nitrate metabolism. Notably, expression analysis of a subset of genes common to NarL and DevR regulons in M. tuberculosis Delta devR, Delta devS Delta dosT, and Delta narL mutant strains revealed that in response to nitrite produced during aerobic nitrate metabolism, the DevRS/DosT regulatory system plays a primary role that is augmented by NarL. Specifically, NarL itself was unable to bind to the narK2, acg, and Rv3130c promoters in phosphorylated or unphosphorylated form; however, its interaction with DevR similar to P resulted in cooperative binding, thereby enabling co-regulation of these genes. These findings support the role of physiologically derived nitrite as a metabolic signal in mycobacteria. We propose NarL-DevR binding, possibly as a heterodimer, as a novel mechanism for co-regulation of gene expression by the DevRS/DosT and NarL/NarS regulatory systems.

Regulation of Acetate Metabolism and Acetyl Co-a Synthetase 1 (ACS1) Expression by Methanol Expression Regulator 1 (Mxr1p) in the Methylotrophic Yeast Pichia pastoris

Methanol expression regulator 1 (Mxr1p) is a zinc finger protein that regulates the expression of genes encoding enzymes of the methanol utilization pathway in the methylotrophic yeast Pichia pastoris by binding to Mxr1p response elements (MXREs) present in their promoters. Here we demonstrate that Mxr1p is a key regulator of acetate metabolism as well. Mxr1p is cytosolic in cells cultured in minimal medium containing a yeast nitrogen base, ammonium sulfate, and acetate (YNBA) but localizes to the nucleus of cells cultured in YNBA supplemented with glutamate or casamino acids as well as nutrient-rich medium containing yeast extract, peptone, and acetate (YPA). Deletion of Mxr1 retards the growth of P. pastoris cultured in YNBA supplemented with casamino acids as well as YPA. Mxr1p is a key regulator of ACS1 encoding acetyl-CoA synthetase in cells cultured in YPA. A truncated Mxr1p comprising 400 N-terminal amino acids activates ACS1 expression and enhances growth, indicating a crucial role for the N-terminal activation domain during acetate metabolism. The serine 215 residue, which is known to regulate the expression of Mxr1p-activated genes in a carbon source-dependent manner, has no role in the Mxr1p-mediated activation of ACS1 expression. The ACS1 promoter contains an Mxr1p response unit (MxRU) comprising two MXREs separated by a 30-bp spacer. Mutations that abrogate MxRU function in vivo abolish Mxr1p binding to MxRU in vitro. Mxr1p-dependent activation of ACS1 expression is most efficient in cells cultured in YPA. The fact that MXREs are conserved in genes outside of the methanol utilization pathway suggests that Mxr1p may be a key regulator of multiple metabolic pathways in P. pastoris.

Co-ordination of pathogenicity island expression by the BipA GTPase in enteropathogenic Escherichia coli (EPEC).

BipA is a novel member of the ribosome binding GTPase superfamily and is widely distributed in bacteria and plants. We report here that it regulates -multiple cell surface- and virulence-associated -components in the enteropathogenic Escherichia coli (EPEC) strain E2348/69. The regulated components include bacterial flagella, the espC pathogenicity island and a type III secretion system specified by the locus of enterocyte effacement (LEE). BipA positively regulated the espC and LEE gene clusters through transcriptional control of the LEE-encoded regulator, Ler. Additionally, it affected the pattern of proteolysis of intimin, a key LEE-encoded adhesin specified by the LEE. BipA control of the LEE operated independently of the previously characterized regulators Per, integration host factor and H-NS. In contrast, it negatively regulated the flagella-mediated motility of EPEC and in a Ler-independent manner. Our results indicate that the BipA GTPase functions high up in diverse regulatory cascades to co-ordinate the expression of key pathogenicity islands and other virulence-associated factors in E. coli.