796 research outputs found
Impact of limited solvent capacity on metabolic rate, enzyme activities, and metabolite concentrations of S. cerevisiae glycolysis
The cell's cytoplasm is crowded by its various molecular components, resulting in a limited solvent capacity for the allocation of new proteins, thus constraining various cellular processes such as metabolism. Here we study the impact of the limited solvent capacity constraint on the metabolic rate, enzyme activities, and metabolite concentrations using a computational model of Saccharomyces cerevisiae glycolysis as a case study. We show that given the limited solvent capacity constraint, the optimal enzyme activities and the metabolite concentrations necessary to achieve a maximum rate of glycolysis are in agreement with their experimentally measured values. Furthermore, the predicted maximum glycolytic rate determined by the solvent capacity constraint is close to that measured in vivo. These results indicate that the limited solvent capacity is a relevant constraint acting on S. cerevisiae at physiological growth conditions, and that a full kinetic model together with the limited solvent capacity constraint can be used to predict both metabolite concentrations and enzyme activities in vivo. © 2008 Vazquez et al
Identification of capacity development indicators for faculty development programs: A nominal group technique study.
HiNO: An Approach for Inferring Hierarchical Organization from Regulatory Networks
BACKGROUND: Gene expression as governed by the interplay of the components of regulatory networks is indeed one of the most complex fundamental processes in biological systems. Although several methods have been published to unravel the hierarchical structure of regulatory networks, weaknesses such as the incorrect or inconsistent assignment of elements to their hierarchical levels, the incapability to cope with cyclic dependencies within the networks or the need for a manual curation to retrieve non-overlapping levels remain unsolved. METHODOLOGY/RESULTS: We developed HiNO as a significant improvement of the so-called breadth-first-search (BFS) method. While BFS is capable of determining the overall hierarchical structures from gene regulatory networks, it especially has problems solving feed-forward type of loops leading to conflicts within the level assignments. We resolved these problems by adding a recursive correction approach consisting of two steps. First each vertex is placed on the lowest level that this vertex and its regulating vertices are assigned to (downgrade procedure). Second, vertices are assigned to the next higher level (upgrade procedure) if they have successors with the same level assignment and have themselves no regulators. We evaluated HiNO by comparing it with the BFS method by applying them to the regulatory networks from Saccharomyces cerevisiae and Escherichia coli, respectively. The comparison shows clearly how conflicts in level assignment are resolved in HiNO in order to produce correct hierarchical structures even on the local levels in an automated fashion. CONCLUSIONS: We showed that the resolution of conflicting assignments clearly improves the BFS-method. While we restricted our analysis to gene regulatory networks, our approach is suitable to deal with any directed hierarchical networks structure such as the interaction of microRNAs or the action of non-coding RNAs in general. Furthermore we provide a user-friendly web-interface for HiNO that enables the extraction of the hierarchical structure of any directed regulatory network. AVAILABILITY: HiNO is freely accessible at http://mips.helmholtz-muenchen.de/hino/
Seasonal variations in carbon, nitrogen and phosphorus concentrations and C:N:P stoichiometry in different organs of a Larix principis-rupprechtii Mayr. plantation in the Qinling Mountains, China
Understanding how concentrations of elements and their stoichiometry change with plant growth and age is critical for predicting plant community responses to environmental change. Weusedlong-term field experiments to explore how the leaf, stem and root carbon (C), nitrogen (N) and phosphorous (P) concentrations and their stoichiometry changed with growth and stand age in a L.principis-rupprechtii Mayr. plantation from 2012–2015 in the Qinling Mountains, China. Our results showed that the C, N and P concentrations and stoichiometric ratios in different tissues of larch stands were affected by stand age, organ type andsampling month and displayed multiple correlations with increased stand age in different growing seasons. Generally, leaf C and N concentrations were greatest in the fast-growing season, but leaf P concentrations were greatest in the early growing season. However, no clear seasonal tendencies in the stem and root C, N and P concentrations were observed with growth. In contrast to N and P, few differences were found in organ-specific C concentrations. Leaf N:P was greatest in the fast-growing season, while C:N and C:P were greatest in the late-growing season. No clear variations were observed in stem and root C:N, C:P andN:Pthroughout the entire growing season, but leaf N:P was less than 14, suggesting that the growth of larch stands was limited by N in our study region. Compared to global plant element concentrations and stoichiometry, the leaves of larch stands had higher C, P, C:NandC:PbutlowerNandN:P,andtherootshadgreater PandC:NbutlowerN,C:Pand N:P. Our study provides baseline information for describing the changes in nutritional elements with plant growth, which will facilitates plantation forest management and restoration, and makes avaluable contribution to the global data pool on leaf nutrition and stoichiometry
Information transmission in oscillatory neural activity
Periodic neural activity not locked to the stimulus or to motor responses is
usually ignored. Here, we present new tools for modeling and quantifying the
information transmission based on periodic neural activity that occurs with
quasi-random phase relative to the stimulus. We propose a model to reproduce
characteristic features of oscillatory spike trains, such as histograms of
inter-spike intervals and phase locking of spikes to an oscillatory influence.
The proposed model is based on an inhomogeneous Gamma process governed by a
density function that is a product of the usual stimulus-dependent rate and a
quasi-periodic function. Further, we present an analysis method generalizing
the direct method (Rieke et al, 1999; Brenner et al, 2000) to assess the
information content in such data. We demonstrate these tools on recordings from
relay cells in the lateral geniculate nucleus of the cat.Comment: 18 pages, 8 figures, to appear in Biological Cybernetic
Exploring the Free Energy Landscape: From Dynamics to Networks and Back
The knowledge of the Free Energy Landscape topology is the essential key to
understand many biochemical processes. The determination of the conformers of a
protein and their basins of attraction takes a central role for studying
molecular isomerization reactions. In this work, we present a novel framework
to unveil the features of a Free Energy Landscape answering questions such as
how many meta-stable conformers are, how the hierarchical relationship among
them is, or what the structure and kinetics of the transition paths are.
Exploring the landscape by molecular dynamics simulations, the microscopic data
of the trajectory are encoded into a Conformational Markov Network. The
structure of this graph reveals the regions of the conformational space
corresponding to the basins of attraction. In addition, handling the
Conformational Markov Network, relevant kinetic magnitudes as dwell times or
rate constants, and the hierarchical relationship among basins, complete the
global picture of the landscape. We show the power of the analysis studying a
toy model of a funnel-like potential and computing efficiently the conformers
of a short peptide, the dialanine, paving the way to a systematic study of the
Free Energy Landscape in large peptides.Comment: PLoS Computational Biology (in press
Vascular endothelial growth factor (VEGF) upregulates BCL-2 and inhibits apoptosis in human and murine mammary adenocarcinoma cells
Tumour progression is regulated by the balance of proliferation and apoptosis in the tumour cell population. To date, the role of vascular endothelial growth factor (VEGF) in tumour growth has been attributed to the induction of angiogenesis. VEGF has been shown to be a survival factor for endothelial cells, preventing apoptosis by inducing Bcl-2 expression. In both murine (4T1) and human (MDA-MB-231) metastatic mammary carcinoma cell lines, we found that VEGF upregulated Bcl-2 expression and anti-VEGF antibodies reduced Bcl-2 expression. These alterations in Bcl-2 expression were reflected by the levels of tumour cell apoptosis. VEGF resulted in reduced tumour cell apoptosis, whereas its inhibition with anti-VEGF neutralizing antibodies induced apoptosis directly in tumour cells. Therefore, in addition to its role in angiogenesis and vessel permeability, VEGF acts as a survival factor for tumour cells, inducing Bcl-2 expression and inhibiting tumour cell apoptosis. © 2001 Cancer Research Campaign http://www.bjcancer.co
Small RNA analysis in Sindbis virus infected human HEK293 cells
In contrast to the defence mechanism of RNA interference (RNAi) in plants and invertebrates, its role in the innate response to virus infection of mammals is a matter of debate. Since RNAi has a well-established role in controlling infection of the alphavirus Sindbis virus (SINV) in insects, we have used this virus to investigate the role of RNAi in SINV infection of human cells
Targeting of highly conserved Dengue virus sequences with anti-Dengue virus trans-splicing group I introns
<p>Abstract</p> <p>Background</p> <p>Dengue viruses (DENV) are one of the most important viral diseases in the world with approximately 100 million infections and 200,000 deaths each year. The current lack of an approved tetravalent vaccine and ineffective insecticide control measures warrant a search for alternatives to effectively combat DENV. The <it>trans</it>-splicing variant of the <it>Tetrahymena thermophila </it>group I intron catalytic RNA, or ribozyme, is a powerful tool for post-transcriptional RNA modification. The nature of the ribozyme and the predictability with which it can be directed makes it a powerful tool for modifying RNA in nearly any cell type without the need for genome-altering gene therapy techniques or dependence on native cofactors.</p> <p>Results</p> <p>Several anti-DENV Group I <it>trans</it>-splicing introns (αDENV-GrpIs) were designed and tested for their ability to target DENV-2 NGC genomes <it>in situ</it>. We have successfully targeted two different uracil bases on the positive sense genomic strand within the highly conserved 5'-3' cyclization sequence (CS) region common to all serotypes of DENV with our αDENV-GrpIs. Our ribozymes have demonstrated ability to specifically <it>trans</it>-splice a new RNA sequence downstream of the targeted site <it>in vitro </it>and in transfected insect cells as analyzed by firefly luciferase and RT-PCR assays. The effectiveness of these αDENV-GrpIs to target infecting DENV genomes is also validated in transfected or transformed Aedes mosquito cell lines upon infection with unattenuated DENV-2 NGC.</p> <p>Conclusions</p> <p>Analysis shows that our αDENV-GrpIs have the ability to effectively <it>trans</it>-splice the DENV genome <it>in situ</it>. Notably, these results show that the αDENV-GrpI 9v1, designed to be active against all forms of Dengue virus, effectively targeted the DENV-2 NGC genome in a sequence specific manner. These novel αDENV-GrpI introns provide a striking alternative to other RNA based approaches for the transgenic suppression of DENV in transformed mosquito cells and tissues.</p
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