20 resultados para Genetic Regulatory Networks
em CentAUR: Central Archive University of Reading - UK
Resumo:
The genome of the plant-colonizing bacterium Pseudomonas fluorescens SBW25 harbors a subset of genes that are expressed specifically on plant surfaces. The function of these genes is central to the ecological success of SBW25, but their study poses significant challenges because no phenotype is discernable in vitro. Here, we describe a genetic strategy with general utility that combines suppressor analysis with IVET (SPyVET) and provides a means of identifying regulators of niche-specific genes. Central to this strategy are strains carrying operon fusions between plant environment-induced loci (EIL) and promoterless 'dapB. These strains are prototrophic in the plant environment but auxotrophic on laboratory minimal medium. Regulatory elements were identified by transposon mutagenesis and selection for prototrophs on minimal medium. Approximately 106 mutants were screened for each of 27 strains carrying 'dapB fusions to plant EIL and the insertion point for the transposon determined in approximately 2,000 putative regulator mutants. Regulators were functionally characterized and used to provide insight into EIL phenotypes. For one strain carrying a fusion to the cellulose-encoding wss operon, five different regulators were identified including a diguanylate cyclase, the flagella activator, FleQ, and alginate activator, AmrZ (AlgZ). Further rounds of suppressor analysis, possible by virtue of the SPyVET strategy, revealed an additional two regulators including the activator AlgR, and allowed the regulatory connections to be determined.
Resumo:
Bacteria have evolved complex regulatory networks that enable integration of multiple intracellular and extracellular signals to coordinate responses to environmental changes. However, our knowledge of how regulatory systems function and evolve is still relatively limited. There is often extensive homology between components of different networks, due to past cycles of gene duplication, divergence, and horizontal gene transfer, raising the possibility of cross-talk or redundancy. Consequently, evolutionary resilience is built into gene networks – homology between regulators can potentially allow rapid rescue of lost regulatory function across distant regions of the genome. In our recent study [Taylor, et al. Science (2015), 347(6225)] we find that mutations that facilitate cross-talk between pathways can contribute to gene network evolution, but that such mutations come with severe pleiotropic costs. Arising from this work are a number of questions surrounding how this phenomenon occurs.
Resumo:
Gene expression is a quantitative trait that can be mapped genetically in structured populations to identify expression quantitative trait loci (eQTL). Genes and regulatory networks underlying complex traits can subsequently be inferred. Using a recently released genome sequence, we have defined cis- and trans-eQTL and their environmental response to low phosphorus (P) availability within a complex plant genome and found hotspots of trans-eQTL within the genome. Interval mapping, using P supply as a covariate, revealed 18,876 eQTL. trans-eQTL hotspots occurred on chromosomes A06 and A01 within Brassica rapa; these were enriched with P metabolism-related Gene Ontology terms (A06) as well as chloroplast-and photosynthesis-related terms (A01). We have also attributed heritability components to measures of gene expression across environments, allowing the identification of novel gene expression markers and gene expression changes associated with low P availability. Informative gene expression markers were used to map eQTL and P use efficiency-related QTL. Genes responsive to P supply had large environmental and heritable variance components. Regulatory loci and genes associated with P use efficiency identified through eQTL analysis are potential targets for further characterization and may have potential for crop improvement.
Resumo:
Cholesterol is one of the key constituents for maintaining the cellular membrane and thus the integrity of the cell itself. In contrast high levels of cholesterol in the blood are known to be a major risk factor in the development of cardiovascular disease. We formulate a deterministic nonlinear ordinary differential equation model of the sterol regulatory element binding protein 2 (SREBP-2) cholesterol genetic regulatory pathway in an hepatocyte. The mathematical model includes a description of genetic transcription by SREBP-2 which is subsequently translated to mRNA leading to the formation of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR), a main precursor of cholesterol synthesis. Cholesterol synthesis subsequently leads to the regulation of SREBP-2 via a negative feedback formulation. Parameterised with data from the literature, the model is used to understand how SREBP-2 transcription and regulation affects cellular cholesterol concentration. Model stability analysis shows that the only positive steady-state of the system exhibits purely oscillatory, damped oscillatory or monotic behaviour under certain parameter conditions. In light of our findings we postulate how cholesterol homestasis is maintained within the cell and the advantages of our model formulation are discussed with respect to other models of genetic regulation within the literature.
Resumo:
Preface. Iron is considered to be a minor element employed, in a variety of forms, by nearly all living organisms. In some cases, it is utilised in large quantities, for instance for the formation of magnetosomes within magnetotactic bacteria or during use of iron as a respiratory donor or acceptor by iron oxidising or reducing bacteria. However, in most cases the role of iron is restricted to its use as a cofactor or prosthetic group assisting the biological activity of many different types of protein. The key metabolic processes that are dependent on iron as a cofactor are numerous; they include respiration, light harvesting, nitrogen fixation, the Krebs cycle, redox stress resistance, amino acid synthesis and oxygen transport. Indeed, it is clear that Life in its current form would be impossible in the absence of iron. One of the main reasons for the reliance of Life upon this metal is the ability of iron to exist in multiple redox states, in particular the relatively stable ferrous (Fe2+) and ferric (Fe3+) forms. The availability of these stable oxidation states allows iron to engage in redox reactions over a wide range of midpoint potentials, depending on the coordination environment, making it an extremely adaptable mediator of electron exchange processes. Iron is also one of the most common elements within the Earth’s crust (5% abundance) and thus is considered to have been readily available when Life evolved on our early, anaerobic planet. However, as oxygen accumulated (the ‘Great oxidation event’) within the atmosphere some 2.4 billion years ago, and as the oceans became less acidic, the iron within primordial oceans was converted from its soluble reduced form to its weakly-soluble oxidised ferric form, which precipitated (~1.8 billion years ago) to form the ‘banded iron formations’ (BIFs) observed today in Precambrian sedimentary rocks around the world. These BIFs provide a geological record marking a transition point away from the ancient anaerobic world towards modern aerobic Earth. They also indicate a period over which the bio-availability of iron shifted from abundance to limitation, a condition that extends to the modern day. Thus, it is considered likely that the vast majority of extant organisms face the common problem of securing sufficient iron from their environment – a problem that Life on Earth has had to cope with for some 2 billion years. This struggle for iron is exemplified by the competition for this metal amongst co-habiting microorganisms who resort to stealing (pirating) each others iron supplies! The reliance of micro-organisms upon iron can be disadvantageous to them, and to our innate immune system it represents a chink in the microbial armour, offering an opportunity that can be exploited to ward off pathogenic invaders. In order to infect body tissues and cause disease, pathogens must secure all their iron from the host. To fight such infections, the host specifically withdraws available iron through the action of various iron depleting processes (e.g. the release of lactoferrin and lipocalin-2) – this represents an important strategy in our defence against disease. However, pathogens are frequently able to deploy iron acquisition systems that target host iron sources such as transferrin, lactoferrin and hemoproteins, and thus counteract the iron-withdrawal approaches of the host. Inactivation of such host-targeting iron-uptake systems often attenuates the pathogenicity of the invading microbe, illustrating the importance of ‘the battle for iron’ in the infection process. The role of iron sequestration systems in facilitating microbial infections has been a major driving force in research aimed at unravelling the complexities of microbial iron transport processes. But also, the intricacy of such systems offers a challenge that stimulates the curiosity. One such challenge is to understand how balanced levels of free iron within the cytosol are achieved in a way that avoids toxicity whilst providing sufficient levels for metabolic purposes – this is a requirement that all organisms have to meet. Although the systems involved in achieving this balance can be highly variable amongst different microorganisms, the overall strategy is common. On a coarse level, the homeostatic control of cellular iron is maintained through strict control of the uptake, storage and utilisation of available iron, and is co-ordinated by integrated iron-regulatory networks. However, much yet remains to be discovered concerning the fine details of these different iron regulatory processes. As already indicated, perhaps the most difficult task in maintaining iron homeostasis is simply the procurement of sufficient iron from external sources. The importance of this problem is demonstrated by the plethora of distinct iron transporters often found within a single bacterium, each targeting different forms (complex or redox state) of iron or a different environmental condition. Thus, microbes devote considerable cellular resource to securing iron from their surroundings, reflecting how successful acquisition of iron can be crucial in the competition for survival. The aim of this book is provide the reader with an overview of iron transport processes within a range of microorganisms and to provide an indication of how microbial iron levels are controlled. This aim is promoted through the inclusion of expert reviews on several well studied examples that illustrate the current state of play concerning our comprehension of how iron is translocated into the bacterial (or fungal) cell and how iron homeostasis is controlled within microbes. The first two chapters (1-2) consider the general properties of microbial iron-chelating compounds (known as ‘siderophores’), and the mechanisms used by bacteria to acquire haem and utilise it as an iron source. The following twelve chapters (3-14) focus on specific types of microorganism that are of key interest, covering both an array of pathogens for humans, animals and plants (e.g. species of Bordetella, Shigella, , Erwinia, Vibrio, Aeromonas, Francisella, Campylobacter and Staphylococci, and EHEC) as well as a number of prominent non-pathogens (e.g. the rhizobia, E. coli K-12, Bacteroides spp., cyanobacteria, Bacillus spp. and yeasts). The chapters relay the common themes in microbial iron uptake approaches (e.g. the use of siderophores, TonB-dependent transporters, and ABC transport systems), but also highlight many distinctions (such as use of different types iron regulator and the impact of the presence/absence of a cell wall) in the strategies employed. We hope that those both within and outside the field will find this book useful, stimulating and interesting. We intend that it will provide a source for reference that will assist relevant researchers and provide an entry point for those initiating their studies within this subject. Finally, it is important that we acknowledge and thank wholeheartedly the many contributors who have provided the 14 excellent chapters from which this book is composed. Without their considerable efforts, this book, and the understanding that it relays, would not have been possible. Simon C Andrews and Pierre Cornelis
Resumo:
Acquisition and maintenance of cell fate and potential are dependent on the complex interplay of extracellular signaling, gene regulatory networks and epigenetic states. During embryonic development, embryonic stem cells become progressively more restricted along specific lineages, ultimately giving rise to the diversity of cell types in the adult mammalian organism. Recent years have seen major advances in our understanding of the mechanisms that regulate the underlying transcriptional programmes during development. In particular, there has been a significant increase in our knowledge of how epigenetic marks on chromatin can regulate transcription by generating more or less permissive chromatin conformations. This article focuses on how a single transcription factor, repressor element-1 silencing transcription factor, can function as both a transcriptional and epigenetic regulator, controlling diverse aspects of development. We will discuss how the elucidation of repressor element-1 silencing transcription factor function in both normal and disease conditions has provided valuable insights into how the epigenome and transcriptional regulators might cooperatively orchestrate correct development.
Resumo:
A central process in evolution is the recruitment of genes to regulatory networks. We engineered immotile strains of the bacterium Pseudomonas fluorescens that lack flagella due to deletion of the regulatory gene fleQ. Under strong selection for motility, these bacteria consistently regained flagella within 96 hours via a two-step evolutionary pathway. Step 1 mutations increase intracellular levels of phosphorylated NtrC, a distant homologue of FleQ, which begins to commandeer control of the fleQ regulon at the cost of disrupting nitrogen uptake and assimilation. Step 2 is a switch-of-function mutation that redirects NtrC away from nitrogen uptake and towards its novel function as a flagellar regulator. Our results demonstrate that natural selection can rapidly rewire regulatory networks in very few, repeatable mutational steps.
Resumo:
This paper presents a parallel genetic algorithm to the Steiner Problem in Networks. Several previous papers have proposed the adoption of GAs and others metaheuristics to solve the SPN demonstrating the validity of their approaches. This work differs from them for two main reasons: the dimension and the characteristics of the networks adopted in the experiments and the aim from which it has been originated. The reason that aimed this work was namely to build a comparison term for validating deterministic and computationally inexpensive algorithms which can be used in practical engineering applications, such as the multicast transmission in the Internet. On the other hand, the large dimensions of our sample networks require the adoption of a parallel implementation of the Steiner GA, which is able to deal with such large problem instances.
Resumo:
The genetic analysis workshop 15 (GAW15) problem 1 contained baseline expression levels of 8793 genes in immortalised B cells from 194 individuals in 14 Centre d’Etude du Polymorphisme Humane (CEPH) Utah pedigrees. Previous analysis of the data showed linkage and association and evidence of substantial individual variations. In particular, correlation was examined on expression levels of 31 genes and 25 target genes corresponding to two master regulatory regions. In this analysis, we apply Bayesian network analysis to gain further insight into these findings. We identify strong dependences and therefore provide additional insight into the underlying relationships between the genes involved. More generally, the approach is expected to be applicable for integrated analysis of genes on biological pathways.
Resumo:
Glucokinase Regulatory Protein (GCKR) plays a central role regulating both hepatic triglyceride and glucose metabolism. Fatty acids are key metabolic regulators, which interact with genetic factors and influence glucose metabolism and other metabolic traits. Omega-3 polyunsaturated fatty acids (n-3 PUFA) have been of considerable interest, due to their potential to reduce metabolic syndrome (MetS) risk. Objective To examine whether genetic variability at the GCKR gene locus was associated with the degree of insulin resistance, plasma concentrations of C-reactive protein (CRP) and n-3 PUFA in MetS subjects. Design Homeostasis model assessment of insulin resistance (HOMA-IR), HOMA-B, plasma concentrations of C-peptide, CRP, fatty acid composition and the GCKR rs1260326-P446L polymorphism, were determined in a cross-sectional analysis of 379 subjects with MetS participating in the LIPGENE dietary cohort. Results Among subjects with n-3 PUFA levels below the population median, carriers of the common C/C genotype had higher plasma concentrations of fasting insulin (P = 0.019), C-peptide (P = 0.004), HOMA-IR (P = 0.008) and CRP (P = 0.032) as compared with subjects carrying the minor T-allele (Leu446). In contrast, homozygous C/C carriers with n-3 PUFA levels above the median showed lower plasma concentrations of fasting insulin, peptide C, HOMA-IR and CRP, as compared with individuals with the T-allele. Conclusions We have demonstrated a significant interaction between the GCKR rs1260326-P446L polymorphism and plasma n-3 PUFA levels modulating insulin resistance and inflammatory markers in MetS subjects. Further studies are needed to confirm this gene-diet interaction in the general population and whether targeted dietary recommendations can prevent MetS in genetically susceptible individuals.
Resumo:
Self-organizing neural networks have been implemented in a wide range of application areas such as speech processing, image processing, optimization and robotics. Recent variations to the basic model proposed by the authors enable it to order state space using a subset of the input vector and to apply a local adaptation procedure that does not rely on a predefined test duration limit. Both these variations have been incorporated into a new feature map architecture that forms an integral part of an Hybrid Learning System (HLS) based on a genetic-based classifier system. Problems are represented within HLS as objects characterized by environmental features. Objects controlled by the system have preset targets set against a subset of their features. The system's objective is to achieve these targets by evolving a behavioural repertoire that efficiently explores and exploits the problem environment. Feature maps encode two types of knowledge within HLS — long-term memory traces of useful regularities within the environment and the classifier performance data calibrated against an object's feature states and targets. Self-organization of these networks constitutes non-genetic-based (experience-driven) learning within HLS. This paper presents a description of the HLS architecture and an analysis of the modified feature map implementing associative memory. Initial results are presented that demonstrate the behaviour of the system on a simple control task.
Resumo:
The authors describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive online diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.
Resumo:
Proteomics approaches have made important contributions to the characterisation of platelet regulatory mechanisms. A common problem encountered with this method, however, is the masking of low-abundance (e.g. signalling) proteins in complex mixtures by highly abundant proteins. In this study, subcellular fractionation of washed human platelets either inactivated or stimulated with the glycoprotein (GP) VI collagen receptor agonist, collagen-related peptide, reduced the complexity of the platelet proteome. The majority of proteins identified by tandem mass spectrometry are involved in signalling. The effect of GPVI stimulation on levels of specific proteins in subcellular compartments was compared and analysed using in silico quantification, and protein associations were predicted using STRING (the search tool for recurring instances of neighbouring genes/proteins). Interestingly, we observed that some proteins that were previously unidentified in platelets including teneurin-1 and Van Gogh-like protein 1, translocated to the membrane upon GPVI stimulation. Newly identified proteins may be involved in GPVI signalling nodes of importance for haemostasis and thrombosis.
Resumo:
Platelets in the circulation are triggered by vascular damage to activate, aggregate and form a thrombus that prevents excessive blood loss. Platelet activation is stringently regulated by intracellular signalling cascades, which when activated inappropriately lead to myocardial infarction and stroke. Strategies to address platelet dysfunction have included proteomics approaches which have lead to the discovery of a number of novel regulatory proteins of potential therapeutic value. Global analysis of platelet proteomes may enhance the outcome of these studies by arranging this information in a contextual manner that recapitulates established signalling complexes and predicts novel regulatory processes. Platelet signalling networks have already begun to be exploited with interrogation of protein datasets using in silico methodologies that locate functionally feasible protein clusters for subsequent biochemical validation. Characterization of these biological systems through analysis of spatial and temporal organization of component proteins is developing alongside advances in the proteomics field. This focused review highlights advances in platelet proteomics data mining approaches that complement the emerging systems biology field. We have also highlighted nucleated cell types as key examples that can inform platelet research. Therapeutic translation of these modern approaches to understanding platelet regulatory mechanisms will enable the development of novel anti-thrombotic strategies.