Análise de propriedades topológicas das redes biológicas integradas da Escherichia coli e da Saccharomyces cerevisiae

Biological processes are complex and possess emergent properties that can not be explained or predict by reductionism methods. To overcome the limitations of reductionism, researchers have been used a group of methods known as systems biology, a new interdisciplinary eld of study aiming to understand the non-linear interactions among components embedded in biological processes. These interactions can be represented by a mathematical object called graph or network, where the elements are represented by nodes and the interactions by edges that link pair of nodes. The networks can be classi- ed according to their topologies: if node degrees follow a Poisson distribution in a given network, i.e. most nodes have approximately the same number of links, this is a random network; if node degrees follow a power-law distribution in a given network, i.e. small number of high-degree nodes and high number of low-degree nodes, this is a scale-free network. Moreover, networks can be classi ed as hierarchical or non-hierarchical. In this study, we analised Escherichia coli and Saccharomyces cerevisiae integrated molecular networks, which have protein-protein interaction, metabolic and transcriptional regulation interactions. By using computational methods, such as MathematicaR , and data collected from public databases, we calculated four topological parameters: the degree distribution P(k), the clustering coe cient C(k), the closeness centrality CC(k) and the betweenness centrality CB(k). P(k) is a function that calculates the total number of nodes with k degree connection and is used to classify the network as random or scale-free. C(k) shows if a network is hierarchical, i.e. if the clusterization coe cient depends on node degree. CC(k) is an indicator of how much a node it is in the lesse way among others some nodes of the network and the CB(k) is a pointer of how a particular node is among several ...(Complete abstract click electronic access below)

Metformin and soybean-derived bioactive molecules attenuate the expansion of stem cell-like epithelial subpopulation and confer apoptotic sensitivity in human colon cancer cells

Colorectal cancer (CRC) is a disease whose genesis may include metabolic dysregulation. Cancer stem cells are attractive targets for therapeutic interventions since their aberrant expansion may underlie tumor initiation, progression, and recurrence. To investigate the actions of metabolic regulators on cancer stem cell-like cells (CSC) in CRC, we determined the effects of soybean-derived bioactive molecules and the anti-diabetes drug metformin (MET), alone and together, on the growth, survival, and frequency of CSC in human HCT116 cells. Effects of MET (60 μM) and soybean components genistein (Gen, 2 μM), lunasin (Lun, 2 μM), β-conglycinin (β-con, 3 μM), and glycinin (Gly, 3 μM) on HCT116 cell proliferation, apoptosis, and mRNA/protein expression and on the frequency of the CSC CD133(+)CD44(+) subpopulation by colonosphere assay and fluorescence-activated cell sorting/flow cytometry were evaluated. MET, Gen, and Lun, individually and together, inhibited HCT116 viability and colonosphere formation and, conversely, enhanced HCT116 apoptosis. Reductions in frequency of the CSC CD133(+)CD44(+) subpopulation with MET, Gen, and Lun were found to be associated with increased PTEN and reduced FASN expression. In cells under a hyperinsulinemic state mimicking metabolic dysregulation and without and with added PTEN-specific inhibitor SF1670, colonosphere formation and frequency of the CD133(+)CD44(+) subpopulation were decreased by MET, Lun and Gen, alone and when combined. Moreover, MET + Lun + Gen co-treatment increased the pro-apoptotic and CD133(+)CD44(+)-inhibitory efficacy of 5-fluorouracil under hyperinsulinemic conditions. Results identify molecular networks shared by MET and bioavailable soy food components, which potentially may be harnessed to increase drug efficacy in diabetic and non-diabetic patients with CRC.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Ion channel macromolecular complexes in cardiomyocytes: roles in sudden cardiac death.

The movement of ions across specific channels embedded on the membrane of individual cardiomyocytes is crucial for the generation and propagation of the cardiac electric impulse. Emerging evidence over the past 20 years strongly suggests that the normal electric function of the heart is the result of dynamic interactions of membrane ion channels working in an orchestrated fashion as part of complex molecular networks. Such networks work together with exquisite temporal precision to generate each action potential and contraction. Macromolecular complexes play crucial roles in transcription, translation, oligomerization, trafficking, membrane retention, glycosylation, post-translational modification, turnover, function, and degradation of all cardiac ion channels known to date. In addition, the accurate timing of each cardiac beat and contraction demands, a comparable precision on the assembly and organizations of sodium, calcium, and potassium channel complexes within specific subcellular microdomains, where physical proximity allows for prompt and efficient interaction. This review article, part of the Compendium on Sudden Cardiac Death, discusses the major issues related to the role of ion channel macromolecular assemblies in normal cardiac electric function and the mechanisms of arrhythmias leading to sudden cardiac death. It provides an idea of how these issues are being addressed in the laboratory and in the clinic, which important questions remain unanswered, and what future research will be needed to improve knowledge and advance therapy.

The Mouse Gene Expression Database (GXD)

The Gene Expression Database (GXD) is a community resource of gene expression information for the laboratory mouse. By combining the different types of expression data, GXD aims to provide increasingly complete information about the expression profiles of genes in different mouse strains and mutants, thus enabling valuable insights into the molecular networks that underlie normal development and disease. GXD is integrated with the Mouse Genome Database (MGD). Extensive interconnections with sequence databases and with databases from other species, and the development and use of shared controlled vocabularies extend GXD’s utility for the analysis of gene expression information. GXD is accessible through the Mouse Genome Informatics web site at http://www.informatic s.jax.org/ or directly at http://www.informatics.jax.org/me nus/expression_menu.shtml.

Neutron-mapping polymer flow: Scattering, flow visualization, and molecular theory

Flows of complex fluids need to be understood at both macroscopic and molecular scales, because it is the macroscopic response that controls the fluid behavior, but the molecular scale that ultimately gives rise to rheological and solid-state properties. Here the flow field of an entangled polymer melt through an extended contraction, typical of many polymer processes, is imaged optically and by small-angle neutron scattering. The dual-probe technique samples both the macroscopic stress field in the flow and the microscopic configuration of the polymer molecules at selected points. The results are compared with a recent tube model molecular theory of entangled melt flow that is able to calculate both the stress and the single-chain structure factor from first principles. The combined action of the three fundamental entangled processes of reptation, contour length fluctuation, and convective constraint release is essential to account quantitatively for the rich rheological behavior. The multiscale approach unearths a new feature: Orientation at the length scale of the entire chain decays considerably more slowly than at the smaller entanglement length.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Mapping the Contemporary Studies on Alliances and Strategic Networks

The competition among the companies depends on the velocity and efficience they can create and commercialize knowledge in a timely and cost-efficient manner. In this context, collaboration emerges as a reaction to the environmental changes. Although strategic alliances and networks have been exploited in the strategic literature for decades, the complexity and continuous usage of these cooperation structures, in a world of growing competition, justify the continuous interest in both themes. This article presents a scanning of the contemporary academic production in strategic alliances and networks, covering the period from January 1997 to august 2007, based on the top five journals accordingly to the journal of Citation Report 2006 in the business and management categories simultaneously. The results point to a retraction in publications about strategic alliances and a significant growth in the area of strategic. networks. The joint view of strategic alliances and networks, cited by some authors a the evolutionary path of study, still did not appear salient. The most cited topics found in the alliance literature are the governance structure, cooperation, knowledge transfer, culture, control, trust, alliance formation,,previous experience, resources, competition and partner selection. The theme network focuses mainly on structure, knowledge transfer and social network, while the joint vision is highly concentrated in: the subjects of alliance formation and the governance choice.

Molecular cloning and chromosomal mapping of the human homologue of MYB binding protein (P160) 1A (MYBBP1A) to 17p13.3

We have previously isolated and characterized murine MYB binding protein (p160) 1a, a protein that specifically interacts with the leucine zipper motif within the negative regulatory domain of the c-Myb proto-oncoprotein, We now describe the molecular cloning of the human MYBBP1A cDNA and chromosomal localization to 17p13.3 by fluorescence in situ hybridization analysis, Given the likely presence of a tumor suppressor gene (or genes) within this region of chromosome 17, the position of MYBBP1A was further mapped by radiation hybrid analysis and was found to lie between markers D17S1828 and D17S938. A P1 artificial chromosome clone containing the 5' region of MYBBP1A was isolated and indicates a physical linkage between MYBBP1A and the 15-lipoxygenase gene (ALOX15), A novel, polymorphic (CA)(25) dinucleotide repeat was also isolated from this PAC and may serve as a useful marker for MYBBP1A and this region of chromosome 17. (C) 1999 Academic Press.

A new clinical and molecular form of Unverricht-Lundborg disease localized by homozygosity mapping

Progressive myoclonus epilepsy (PME) has a number of causes, of which Unverricht-Lundborg disease (ULD) is the most common. ULD has previously been mapped to a locus on chromosome 21 (EPM1). Subsequently, mutations in the cystatin B gene have been found in most cases. In the present work we identified an inbred Arab family with a clinical pattern compatible with ULD, but mutations in the cystatin B gene were absent. We sought to characterize the clinical and molecular features of the disorder. The family was studied by multiple field trips to their town to clarify details of the complex consanguineous relationships and to personally examine the family. DNA was collected for subsequent molecular analyses from 21 individuals. A genome-wide screen was performed using 811 microsatellite markers. Homozygosity mapping was used to identify loci of interest. There were eight affected individuals. Clinical onset was at 7.3 +/- 1.5 years with myoclonic or tonic-clonic seizures. All had myoclonus that progressed in severity over time and seven had tonic-clonic seizures. Ataxia, in addition to myoclonus, occurred in all. Detailed cognitive assessment was not possible, but there was no significant progressive dementia. There was intrafamily variation in severity; three required wheelchairs in adult life; the others could walk unaided. MRI, muscle and skin biopsies on one individual were unremarkable. We mapped the family to a 15-megabase region at the pericentromeric region of chromosome 12 with a maximum lod score of 6.32. Although the phenotype of individual subjects was typical of ULD, the mean age of onset (7.3 years versus 11 years for ULD) was younger. The locus on chromosome 12 does not contain genes for any other form of PME, nor does it have genes known to be related to cystatin B. This represents a new form of PME and we have designated the locus as EPM1B.

HIV-1 drug resistance transmission networks in southwest Switzerland.

To determine viral subtypes and resistance mutations to antiretroviral treatment (ART) in untreated HIV-1 acutely infected subjects from Southwest Switzerland. Clinical samples were obtained from the HIV primary infection cohort from Lausanne. Briefly, pol gene was amplified by nested PCR and sequenced to generate a 1?kb sequence spanning protease and reverse transcriptase key protein regions. Nucleotide sequences were used to assess viral genotype and ART resistance mutations. Blood specimens and medical information were obtained from 30 patients. Main viral subtypes corresponded to clade B, CRF02_AG, and F1. Resistant mutations to PIs consisted of L10V and accessory mutations 16E and 60E present in all F1 clades. The NNRTI major resistant mutation 103N was detected in all F1 viruses and in other 2 clades. Additionally, we identified F1 sequences from other 6 HIV infected and untreated individuals from Southwest Switzerland, harboring nucleotide motifs and resistance mutations to ART as observed in the F1 strains from the cohort. These data reveal a high transmission rate (16.6%) for NNRTI resistant mutation 103N in a cohort of HIV acute infection. Three of the 5 resistant strains were F1 clades closely related to other F1 isolates from HIV-1 infection untreated patients also coming from Southwest Switzerland. Overall, we provide strong evidence towards an HIV-1 resistant transmission network in Southwest Switzerland. These findings have relevant implications for the local molecular mapping of HIV-1 and future ART surveillance studies in the region.

Molecular karyotype analysis and mapping of housekeeping genes to chromosomes of selected species complexes of Leishmania

The molecular karyotypes for 20 reference strais of species complexes of Leishmania were determined by contour-clamped homogeneous eletric field (CHEF) electrosphoresis. Determination of number/position of chromosome-sized bands and chromosomal DNA locations of house-keeping genes were the two criteria used for differentiating and classifying the Leishmania species. We have established two gel running conditions of optimal separation of chromosomes, wich resolved DNA molecules as large as 2,500 kilobase pairs (kb). Chromosomes were polymorphic in number (22-30) and size (200-2,500 kb) of bands among members of five complexes of Leishmania. Although each stock had a distinct karyotype, in general the differences found between strains and/or species within each complex were not clear enough for parasite identification. However, each group showed a specific number of size-concordant DNA molecules, wich allowed distinction among the Leishmania complex parasites. Clear differences between the Old and New world groups of parasites or among some New World Leishmania species were also apparent in relation to the chromosome locations of beta-tubulin genes. Based on these results as well as data from other published studies the potencial of using DNA karyotype for identifying and classifying leishmanial field isolates is discussed.

Gene expression mapping in neuropathic pain : molecular plasticity in nociceptors and superficial dorsal horn

RESUME : La douleur neuropathique est le résultat d'une lésion ou d'un dysfonctionnement du système nerveux. Les symptômes qui suivent la douleur neuropathique sont sévères et leur traitement inefficace. Une meilleure approche thérapeutique peut être proposée en se basant sur les mécanismes pathologiques de la douleur neuropathique. Lors d'une lésion périphérique une douleur neuropathique peut se développer et affecter le territoire des nerfs lésés mais aussi les territoires adjacents des nerfs non-lésés. Une hyperexcitabilité des neurones apparaît au niveau des ganglions spinaux (DRG) et de la corne dorsale (DH) de la moelle épinière. Le but de ce travail consiste à mettre en évidence les modifications moléculaires associées aux nocicepteurs lésés et non-lésés au niveau des DRG et des laminae I et II de la corne dorsale, là où l'information nociceptive est intégrée. Pour étudier les changements moléculaires liés à la douleur neuropathique nous utilisons le modèle animal d'épargne du nerf sural (spared nerve injury model, SNI) une semaine après la lésion. Pour la sélection du tissu d'intérêt nous avons employé la technique de la microdissection au laser, afin de sélectionner une sous-population spécifique de cellules (notamment les nocicepteurs lésés ou non-lésés) mais également de prélever le tissu correspondant dans les laminae superficielles. Ce travail est couplé à l'analyse à large spectre du transcriptome par puce ADN (microarray). Par ailleurs, nous avons étudié les courants électriques et les propriétés biophysiques des canaux sodiques (Na,,ls) dans les neurones lésés et non-lésés des DRG. Aussi bien dans le système nerveux périphérique, entre les neurones lésés et non-lésés, qu'au niveau central avec les aires recevant les projections des nocicepteurs lésés ou non-lésés, l'analyse du transcriptome montre des différences de profil d'expression. En effet, nous avons constaté des changements transcriptionnels importants dans les nocicepteurs lésés (1561 gènes, > 1.5x et pairwise comparaison > 77%) ainsi que dans les laminae correspondantes (618 gènes), alors que ces modifications transcriptionelles sont mineures au niveau des nocicepteurs non-lésés (60 gènes), mais important dans leurs laminae de projection (459 gènes). Au niveau des nocicepteurs, en utilisant la classification par groupes fonctionnels (Gene Ontology), nous avons observé que plusieurs processus biologiques sont modifiés. Ainsi des fonctions telles que la traduction des signaux cellulaires, l'organisation du cytosquelette ainsi que les mécanismes de réponse au stress sont affectés. Par contre dans les neurones non-lésés seuls les processus biologiques liés au métabolisme et au développement sont modifiés. Au niveau de la corne dorsale de la moelle, nous avons observé des modifications importantes des processus immuno-inflammatoires dans l'aire affectée par les nerfs lésés et des changements associés à l'organisation et la transmission synaptique au niveau de l'aire des nerfs non-lésés. L'analyse approfondie des canaux sodiques a démontré plusieurs changements d'expression, principalement dans les neurones lésés. Les analyses fonctionnelles n'indiquent aucune différence entre les densités de courant tétrodotoxine-sensible (TTX-S) dans les neurones lésés et non-lésés même si les niveaux d'expression des ARNm des sous-unités TTX-S sont modifiés dans les neurones lésés. L'inactivation basale dépendante du voltage des canaux tétrodotoxine-insensible (TTX-R) est déplacée vers des potentiels positifs dans les cellules lésées et non-lésées. En revanche la vitesse de récupération des courants TTX-S et TTX-R après inactivation est accélérée dans les neurones lésés. Ces changements pourraient être à l'origine de l'altération de l'activité électrique des neurones sensoriels dans le contexte des douleurs neuropathiques. En résumé, ces résultats suggèrent l'existence de mécanismes différenciés affectant les neurones lésés et les neurones adjacents non-lésés lors de la mise en place la douleur neuropathique. De plus, les changements centraux au niveau de la moelle épinière qui surviennent après lésion sont probablement intégrés différemment selon la perception de signaux des neurones périphériques lésés ou non-lésés. En conclusion, ces modulations complexes et distinctes sont probablement des acteurs essentiels impliqués dans la genèse et la persistance des douleurs neuropathiques. ABSTRACT : Neuropathic pain (NP) results from damage or dysfunction of the peripheral or central nervous system. Symptoms associated with NP are severe and difficult to treat. Targeting NP mechanisms and their translation into symptoms may offer a better therapeutic approach.Hyperexcitability of the peripheral and central nervous system occurs in the dorsal root ganglia (DRG) and the dorsal horn (DH) of the spinal cord. We aimed to identify transcriptional variations in injured and in adjacent non-injured nociceptors as well as in corresponding laminae I and II of DH receiving their inputs.We investigated changes one week after the injury induced by the spared nerve injury model of NP. We employed the laser capture microdissection (LCM) for the procurement of specific cell-types (enrichment in nociceptors of injured/non-injured neurons) and laminae in combination with transcriptional analysis by microarray. In addition, we studied functionál properties and currents of sodium channels (Nav1s) in injured and neighboring non-injured DRG neurons.Microarray analysis at the periphery between injured and non-injured DRG neurons and centrally between the area of central projections from injured and non-injured neurons show significant and differential expression patterns. We reported changes in injured nociceptors (1561 genes, > 1.5 fold, >77% pairwise comparison) and in corresponding DH laminae (618 genes), while less modifications occurred in non-injured nociceptors (60 genes) and in corresponding DH laminae (459 genes). At the periphery, we observed by Gene Ontology the involvement of multiple biological processes in injured neurons such as signal transduction, cytoskeleton organization or stress responses. On contrast, functional overrepresentations in non-injured neurons were noted only in metabolic or developmentally related mechanisms. At the level of superficial laminae of the dorsal horn, we reported changes of immune and inflammatory processes in injured-related DH and changes associated with synaptic organization and transmission in DH corresponding to non-injured neurons. Further transcriptional analysis of Nav1s indicated several changes in injured neurons. Functional analyses of Nav1s have established no difference in tetrodotoxin-sensitive (TTX-S) current densities in both injured and non-injured neurons, despite changes in TTX-S Nav1s subunit mRNA levels. The tetrodotoxin-resistant (TTX-R) voltage dependence of steady state inactivation was shifted to more positive potentials in both injured and non-injured neurons, and the rate of recovery from inactivation of TTX-S and TTX-R currents was accelerated in injured neurons. These changes may lead to alterations in neuronal electrogenesis. Taken together, these findings suggest different mechanisms occurring in the injured neurons and the adjacent non-injured ones. Moreover, central changes after injury are probably driven in a different manner if they receive inputs from injured or non-injured neurons. Together, these distinct and complex modulations may contribute to NP.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.