993 resultados para Metabolic Networks


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The levels of organization that exist in bacteria extend from macromolecules to populations. Evidence that there is also a level of organization intermediate between the macromolecule and the bacterial cell is accumulating. This is the level of hyperstructures. Here, we review a variety of spatially extended structures, complexes, and assemblies that might be termed hyperstructures. These include ribosomal or "nucleolar" hyperstructures; transertion hyperstructures; putative phosphotransferase system and glycolytic hyperstructures; chemosignaling and flagellar hyperstructures; DNA repair hyperstructures; cytoskeletal hyperstructures based on EF-Tu, FtsZ, and MreB; and cell cycle hyperstructures responsible for DNA replication, sequestration of newly replicated origins, segregation, compaction, and division. We propose principles for classifying these hyperstructures and finally illustrate how thinking in terms of hyperstructures may lead to a different vision of the bacterial cell.

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The metabolic network of a cell represents the catabolic and anabolic reactions that interconvert small molecules (metabolites) through the activity of enzymes, transporters and non-catalyzed chemical reactions. Our understanding of individual metabolic networks is increasing as we learn more about the enzymes that are active in particular cells under particular conditions and as technologies advance to allow detailed measurements of the cellular metabolome. Metabolic network databases are of increasing importance in allowing us to contextualise data sets emerging from transcriptomic, proteomic and metabolomic experiments. Here we present a dynamic database, TrypanoCyc (http://www.metexplore.fr/trypanocyc/), which describes the generic and condition-specific metabolic network of Trypanosoma brucei, a parasitic protozoan responsible for human and animal African trypanosomiasis. In addition to enabling navigation through the BioCyc-based TrypanoCyc interface, we have also implemented a network-based representation of the information through MetExplore, yielding a novel environment in which to visualise the metabolism of this important parasite.

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Plant proteolysis is a metabolic process where specific enzymes called peptidases degrade proteins. In plants, this complex process involves broad metabolic networks and different sub-cellular compartments. Several types of peptidases take part in the proteolytic process, mainly cysteine-, serine-, aspartyl- and metallo- peptidases. Among the cysteine-peptidases, the papain-like or C1A peptidases (family C1, clan CA) are extensively present in land plants and are classified into catepsins L-, B-, H- and Flike. The catalytic mechanism of these C1A peptidases is highly conserved and involves the three amino acids Cys, His and Asn in the catalytic triad, and a Gln residue which seems essential for maintaining an active enzyme conformation. These proteins are synthesized as inactive precursors, which comprise an N-terminal signal peptide, a propeptide, and the mature protein. In barley, we have identified 33 cysteine-peptidases from the papain-like family, classifying them into 8 different groups. Five of them corresponded to cathepsins L-like (5 subgroups), 1 cathepsin B-like group, 1 cathepsin F-like group and 1 cathepsin H-like group. Besides, C1A peptidases are the specific targets of the plant proteinaceous inhibitors known as phytocystatins (PhyCys). The cystatin inhibitory mechanism is produced by a tight and reversible interaction with their target enzymes. In barley, the cystatin gene family is comprised by 13 members. In this work we have tried to elucidate the role of the C1A cysteine-peptidases and their specific inhibitors (cystatins) in the germination process of the barley grain. Therefore, we selected a representative member of each group/subgroup of C1A peptidases (1 cathepsin B-like, 1 cathepsin F-like, 1 cathepsin H-like and 5 cathepsins L-like). The molecular characterization of the cysteine-peptidases was done and the peptidase-inhibitor interaction was analyzed in vitro and in vivo. A study in the structural basis for specificity of pro-peptide/enzyme interaction in barley C1A cysteine-peptidases has been also carried out by inhibitory assays and the modeling of the three-dimensional structures. The barley grain maturation produces the accumulation of storage proteins (prolamins) in the endosperm which are mobilized during germination to supply the required nutrients until the photosynthesis is fully established. In this work, we have demonstrated the participation of the cysteine-peptidases and their inhibitors in the degradation of the different storage protein fractions (hordeins, albumins and globulins) present in the barley grain. Besides, transgenic barley plants overexpressing or silencing cysteine-peptidases or cystatins were obtained by Agrobacterium-mediated transformation of barley immature embryos to analyze their physiological function in vivo. Preliminary assays were carried out with the T1 grains of several transgenic lines. Comparing the knock-out and the overexpressing lines with the WT, alterations in the germination process were detected and were correlated with their grain hordein content. These data will be validated with the homozygous grains that are being produced through the double haploid technique by microspore culture. Resumen La proteólisis es un proceso metabólico por el cual se lleva a cabo la degradación de las proteínas de un organismo a través de enzimas específicas llamadas proteasas. En plantas, este complejo proceso comprende un entramado de rutas metabólicas que implican, además, diferentes compartimentos subcelulares. En la proteólisis participan numerosas proteasas, principalmente cisteín-, serín-, aspartil-, y metalo-proteasas. Dentro de las cisteín-proteasas, las proteasas tipo papaína o C1A (familia C1, clan CA) están extensamente representadas en plantas terrestres, y se clasifican en catepsinas tipo L, B, H y F. El mecanismo catalítico de estas proteasas está altamente conservado y la triada catalítica formada por los aminoácidos Cys, His y Asn, y a un aminoácido Gln, que parece esencial para el mantenimiento de la conformación activa de la proteína. Las proteasas C1A se sintetizan como precursores inactivos y comprenden un péptido señal en el extremo N-terminal, un pro-péptido y la proteína madura. En cebada hemos identificado 33 cisteín-proteasas de tipo papaína y las hemos clasificado filogenéticamente en 8 grupos diferentes. Cinco de ellos pertenecen a las catepsinas tipo L (5 subgrupos), un grupo a las catepsinas tipo-B, otro a las catepsinas tipo-F y un último a las catepsinas tipo-H. Las proteasas C1A son además las dianas específicas de los inhibidores protéicos de plantas denominados fitocistatinas. El mecanismo de inhibición de las cistatinas está basado en una fuerte interacción reversible. En cebada, se conoce la familia génica completa de las cistatinas, que está formada por 13 miembros. En el presente trabajo se ha investigado el papel de las cisteín-proteasas de cebada y sus inhibidores específicos en el proceso de la germinación de la semilla. Para ello, se seleccionó una proteasa representante de cada grupo/subgrupo (1 catepsina tipo- B, 1 tipo-F, 1 tipo-H, y 5 tipo-L, una por cada subgrupo). Se ha llevado a cabo su caracterización molecular y se ha analizado la interacción enzima-inhibidor tanto in vivo como in vitro. También se han realizado estudios sobre las bases estructurales que demuestran la especificidad en la interacción enzima/propéptido en las proteasas C1A de cebada, mediante ensayos de inhibición y la predicción de modelos estructurales de la interacción. Finalmente, y dado que durante la maduración de la semilla se almacenan proteínas de reserva (prolaminas) en el endospermo que son movilizadas durante la germinación para suministrar los nutrientes necesarios hasta que la nueva planta pueda realizar la fotosíntesis, en este trabajo se ha demostrado la participación de las cisteínproteasas y sus inhibidores en la degradación de las diferentes tipos de proteínas de reserva (hordeinas, albúmins y globulinas) presentes en el grano de cebada. Además, se han obtenido plantas transgénicas de cebada que sobre-expresan o silencian cistatinas y cisteín-proteasas con el fin de analizar la función fisiológica in vivo. Se han realizado análisis preliminares en las semillas T1 de varias líneas tránsgenicas de cebada y al comparar las líneas knock-out y las líneas de sobre-expresión con las silvestres, se han detectado alteraciones en la germinación que están además correlacionadas con el contenido de hordeinas de las semillas. Estos datos serán validados en las semillas homocigotas que se están generando mediante la técnica de dobles haploides a partir del cultivo de microesporas.

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Senescence-associated proteolysis in plants is a crucial process to relocalize nutrients from leaves to growing or storage tissues. The massive net degradation of proteins involves broad metabolic networks, different subcellular compartments, and several types of proteases and regulators. C1A cysteine proteases, grouped as cathepsin L-, B-, H-, and F-like according to their gene structures and phylogenetic relationships, are the most abundant enzymes responsible for the proteolytic activity during leaf senescence. Besides, cystatins as specific modulators of C1A peptidase activities exert a complex regulatory role in this physiological process. This overview article covers the most recent information on C1A proteases in leaf senescence in different plant species. Particularly, it is focussed on barley, as the unique species where the whole gene family members of C1A cysteine proteases and cystatins have been analysed.

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Glutamine synthetase (GS) is a vital enzyme for the assimilation of ammonia into amino acids in higher plants. In legumes, GS plays a crucial role in the assimilation of the ammonium released by nitrogen-fixing bacteria in root nodules, constituting an important metabolic knob controlling the nitrogen (N) assimilatory pathways. To identify new regulators of nodule metabolism, we profiled the transcriptome of Medicago truncatula nodules impaired in N assimilation by specifically inhibiting GS activity using phosphinothricin (PPT). Global transcript expression of nodules collected before and after PPT addition (4, 8, and 24 h) was assessed using Affymetrix M. truncatula GeneChip arrays. Hundreds of genes were regulated at the three time points, illustrating the dramatic alterations in cell metabolism that are imposed on the nodules upon GS inhibition. The data indicate that GS inhibition triggers a fast plant defense response, induces premature nodule senescence, and promotes loss of root nodule identity. Consecutive metabolic changes were identified at the three time points analyzed. The results point to a fast repression of asparagine synthesis and of the glycolytic pathway and to the synthesis of glutamate via reactions alternative to the GS/GOGAT cycle. Several genes potentially involved in the molecular surveillance for internal organic N availability are identified and a number of transporters potentially important for nodule functioning are pinpointed. The data provided by this study contributes to the mapping of regulatory and metabolic networks involved in root nodule functioning and highlight candidate modulators for functional analysis.

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Evaluating the nature of the earliest, often controversial, traces of life in the geological record (dating to the Palaeoarchaean, up to ~3.5 billion years before the present) is of fundamental relevance for placing constraints on the potential that life emerged on Mars at approximately the same time (the Noachian period). In their earliest histories, the two planets shared many palaeoenvironmental similarities, before the surface of Mars rapidly became inhospitable to life as we know it. Multi-scalar, multi-modal analyses of fossiliferous rocks from the Barberton greenstone belt of South Africa and the East Pilbara terrane of Western Australia are a window onto primitive prokaryotic ecoystems. Complementary petrographic, morphological, (bio)geochemical and nanostructural analyses of chert horizons and the carbonaceous material within using a wide range of techniques – including optical microscopy, SEM-EDS, Raman spectroscopy, PIXE, µCT, laser ablation ICP-MS, high-resolution TEM-based analytical techniques and secondary ion mass spectrometry – can characterise, at scales from macroscopic to nanoscopic, the fossilised biomes of the earliest Earth. These approaches enable the definition of the palaeoenvironments, and potentially metabolic networks, preserved in ancient rocks. Modifying these protocols is necessary for Martian exploration using rovers, since the range and power of space instrumentation is significantly reduced relative to terrestrial laboratories. Understanding the crucial observations possible using highly complementary rover-based payloads is therefore critical in scientific protocols aiming to detect traces of life on Mars.

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In this work, we propose the Networks of Evolutionary Processors (NEP) [2] as a computational model to solve problems related with biological phenomena. In our first approximation, we simulate biological processes related with cellular signaling and their implications in the metabolism, by using an architecture based on NEP (NEP architecture) and their specializations: Networks of Polarized Evolutionary Processors (NPEP) [1] and NEP Transducers (NEPT) [3]. In particular, we use this architecture to simulate the interplay between cellular processes related with the metabolism as the Krebs cycle and the malate-aspartate shuttle pathway (MAS) both being altered by signaling by calcium.

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PhD Thesis in Bioengineering

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The pandemic metabolic syndrome is generally attributed to our lifestyle. The current therapeutic strategies are centered on the behavioral changes and pharmacotherapy. A deeply analysis reveals the importance of the socio-cultural determinants with a "dose-responses effect according to the socio-economic level. The "syndemic" theory, which puts at the same level the socio-cultural environment, the behaviors and biomedecine, suggests a more holistic approach. This theory suggests introducing other partners of care, such cultural-mediators and welfare workers trained in the care, to have finally an approach centered on the roots of the causes. The healthcare networks centered on the management of the costs of health should not forget the socio-cultural dimension, unless wanting to select the good cases.

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Human organism is interpenetrated by the world of microorganisms, from the conception until the death. This interpenetration involves different levels of interactions between the partners including trophic exchanges, bi-directional cell signaling and gene activation, besides genetic and epigenetic phenomena, and tends towards mutual adaptation and coevolution. Since these processes are critical for the survival of individuals and species, they rely on the existence of a complex organization of adaptive systems aiming at two apparently conflicting purposes: the maintenance of the internal coherence of each partner, and a mutually advantageous coexistence and progressive adaptation between them. Humans possess three adaptive systems: the nervous, the endocrine and the immune system, each internally organized into subsystems functionally connected by intraconnections, to maintain the internal coherence of the system. The three adaptive systems aim at the maintenance of the internal coherence of the organism and are functionally linked by interconnections, in such way that what happens to one is immediately sensed by the others. The different communities of infectious agents that live within the organism are also organized into functional networks. The members of each community are linked by intraconnections, represented by the mutual trophic, metabolic and other influences, while the different infectious communities affect each other through interconnections. Furthermore, by means of its adaptive systems, the organism influences and is influenced by the microbial communities through the existence of transconnections. It is proposed that these highly complex and dynamic networks, involving gene exchange and epigenetic phenomena, represent major coevolutionary forces for humans and microorganisms.

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Pós-graduação em Ciências Biológicas (Genética) - IBB

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Neisseria meningitidis, the leading cause of bacterial meningitis, can adapt to different host niches during human infection. Both transcriptional and post-transcriptional regulatory networks have been identified as playing a crucial role for bacterial stress responses and virulence. We investigated the N. meningitidis transcriptional landscape both by microarray and by RNA sequencing (RNAseq). Microarray analysis of N. meningitidis grown in the presence or absence of glucose allowed us to identify genes regulated by carbon source availability. In particular, we identified a glucose-responsive hexR-like transcriptional regulator in N. meningitidis. Deletion analysis showed that the hexR gene is accountable for a subset of the glucose-responsive regulation, and in vitro assays with the purified protein showed that HexR binds to the promoters of the central metabolic operons of meningococcus, by targeting a DNA region overlapping putative regulatory sequences. Our results indicate that HexR coordinates the central metabolism of meningococcus in response to the availability of glucose, and N. meningitidis strains lacking the hexR gene are also deficient in establishing successful bacteremia in a mouse model of infection. In parallel, RNAseq analysis of N. meningitidis cultured under standard or iron-limiting in vitro growth conditions allowed us to identify novel small non-coding RNAs (sRNAs) potentially involved in N. meningitidis regulatory networks. Manual curation of the RNAseq data generated a list of 51 sRNAs, 8 of which were validated by Northern blotting. Deletion of selected sRNAs caused attenuation of N. meningitidis infection in a murine model, leading to the identification of the first sRNAs influencing meningococcal bacteraemia. Furthermore, we describe the identification and initial characterization of a novel sRNA unique to meningococcus, closely associated to genes relevant for the intracellular survival of pathogenic Neisseriae. Taken together, our findings could help unravel the regulation of N. meningitidis adaptation to the host environment and its implications for pathogenesis.

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Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.

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Systems biology techniques are a topic of recent interest within the neurological field. Computational intelligence (CI) addresses this holistic perspective by means of consensus or ensemble techniques ultimately capable of uncovering new and relevant findings. In this paper, we propose the application of a CI approach based on ensemble Bayesian network classifiers and multivariate feature subset selection to induce probabilistic dependences that could match or unveil biological relationships. The research focuses on the analysis of high-throughput Alzheimer's disease (AD) transcript profiling. The analysis is conducted from two perspectives. First, we compare the expression profiles of hippocampus subregion entorhinal cortex (EC) samples of AD patients and controls. Second, we use the ensemble approach to study four types of samples: EC and dentate gyrus (DG) samples from both patients and controls. Results disclose transcript interaction networks with remarkable structures and genes not directly related to AD by previous studies. The ensemble is able to identify a variety of transcripts that play key roles in other neurological pathologies. Classical statistical assessment by means of non-parametric tests confirms the relevance of the majority of the transcripts. The ensemble approach pinpoints key metabolic mechanisms that could lead to new findings in the pathogenesis and development of AD