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Find video protocols related to scientific articles indexed in Pubmed.
Stochastic simulations of mixed-lipid compartments: from self-assembling vesicles to self-producing protocells.
Adv. Exp. Med. Biol.
PUBLISHED: 03-25-2011
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The computational platform ENVIRONMENT, developed to simulate stochastically reaction systems in varying compartmentalized conditions [Mavelli and Ruiz-Mirazo: Philos Trans R Soc Lond B Biol Sci 362:1789-1802, 2007; Physical Biology 7(3): 036002, 2010], is here applied to study the dynamic properties and stability of model protocells that start producing their own lipid molecules (e.g., phospholipids), which get inserted in previously self-assembled vesicles, made of precursor amphiphiles (e.g., fatty acids). Attention is mainly focused on the changes that this may provoke in the permeability of the compartment, as well as in its eventual osmotic robustness.
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A simple self-maintaining metabolic system: robustness, autocatalysis, bistability.
PLoS Comput. Biol.
PUBLISHED: 02-26-2010
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A living organism must not only organize itself from within; it must also maintain its organization in the face of changes in its environment and degradation of its components. We show here that a simple (M,R)-system consisting of three interlocking catalytic cycles, with every catalyst produced by the system itself, can both establish a non-trivial steady state and maintain this despite continuous loss of the catalysts by irreversible degradation. As long as at least one catalyst is present at a sufficient concentration in the initial state, the others can be produced and maintained. The system shows bistability, because if the amount of catalyst in the initial state is insufficient to reach the non-trivial steady state the system collapses to a trivial steady state in which all fluxes are zero. It is also robust, because if one catalyst is catastrophically lost when the system is in steady state it can recreate the same state. There are three elementary flux modes, but none of them is an enzyme-maintaining mode, the entire network being necessary to maintain the two catalysts.
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Allele-specific gene expression is widespread across the genome and biological processes.
PLoS ONE
PUBLISHED: 01-07-2009
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Allelic specific gene expression (ASGE) appears to be an important factor in human phenotypic variability and as a consequence, for the development of complex traits and diseases. In order to study ASGE across the human genome, we have performed a study in which genotyping was coupled with an analysis of ASGE by screening 11,500 SNPs using the Mapping 10 K Array to identify differential allelic expression. We found that from the 5,133 SNPs that were suitable for analysis (heterozygous in our sample and expressed in peripheral blood mononuclear cells), 2,934 (57%) SNPs had differential allelic expression. Such SNPs were equally distributed along human chromosomes and biological processes. We validated the presence or absence of ASGE in 18 out 20 SNPs (90%) randomly selected by real time PCR in 48 human subjects. In addition, we observed that SNPs close to -but not included in- segmental duplications had increased levels of ASGE. Finally, we found that transcripts of unknown function or non-coding RNAs, also display ASGE: from a total of 2,308 intronic SNPs, 1510 (65%) SNPs underwent differential allelic expression. In summary, ASGE is a widespread mechanism in the human genome whose regulation seems to be far more complex than expected.
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Size matters: influence of stochasticity on the self-maintenance of a simple model of metabolic closure.
J. Theor. Biol.
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A fundamental landmark in the emergence and maintenance of the first proto-biological systems must have been the formation of a "closed" metabolic organization, and this paper describes a stochastic analysis of a simple model of a system that is closed to efficient causation. Although it shows an absorbing barrier corresponding to the trivial solution that implies collapse and extinction, for certain values of the kinetic parameters it can also show a "coexistence state" in which there are non-null populations of its intermediates, which corresponds approximately to a non-trivial deterministic stable steady state. Depending on the initial conditions, fluctuations can drive the system either to the self-maintaining regime or to extinction, with different probabilities. Different lines of equal probability have been obtained and compared with the deterministic results, and the average time for reaching these states (characteristic time) has been estimated. The system shows strong dependence on volume size, and there is a critical volume below which it collapses very rapidly. The characteristic time is also affected by the volume, with faster responses for lower system volumes. All these results are discussed in the context of the origin of living organization.
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Viability conditions for a compartmentalized protometabolic system: a semi-empirical approach.
PLoS ONE
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In this work we attempt to find out the extent to which realistic prebiotic compartments, such as fatty acid vesicles, would constrain the chemical network dynamics that could have sustained a minimal form of metabolism. We combine experimental and simulation results to establish the conditions under which a reaction network with a catalytically closed organization (more specifically, an (M,R-system) would overcome the potential problem of self-suffocation that arises from the limited accessibility of nutrients to its internal reaction domain. The relationship between the permeability of the membrane, the lifetime of the key catalysts and their efficiency (reaction rate enhancement) turns out to be critical. In particular, we show how permeability values constrain the characteristic time scale of the bounded protometabolic processes. From this concrete and illustrative example we finally extend the discussion to a wider evolutionary context.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.