458 research outputs found
Coding limits on the number of transcription factors
Transcription factor proteins bind specific DNA sequences to control the
expression of genes. They contain DNA binding domains which belong to several
super-families, each with a specific mechanism of DNA binding. The total number
of transcription factors encoded in a genome increases with the number of genes
in the genome. Here, we examined the number of transcription factors from each
super-family in diverse organisms.
We find that the number of transcription factors from most super-families
appears to be bounded. For example, the number of winged helix factors does not
generally exceed 300, even in very large genomes. The magnitude of the maximal
number of transcription factors from each super-family seems to correlate with
the number of DNA bases effectively recognized by the binding mechanism of that
super-family. Coding theory predicts that such upper bounds on the number of
transcription factors should exist, in order to minimize cross-binding errors
between transcription factors. This theory further predicts that factors with
similar binding sequences should tend to have similar biological effect, so
that errors based on mis-recognition are minimal. We present evidence that
transcription factors with similar binding sequences tend to regulate genes
with similar biological functions, supporting this prediction.
The present study suggests limits on the transcription factor repertoire of
cells, and suggests coding constraints that might apply more generally to the
mapping between binding sites and biological function.Comment: http://www.weizmann.ac.il/complex/tlusty/papers/BMCGenomics2006.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1590034/
http://www.biomedcentral.com/1471-2164/7/23
Entrainment of noise-induced and limit cycle oscillators under weak noise
Theoretical models that describe oscillations in biological systems are often
either a limit cycle oscillator, where the deterministic nonlinear dynamics
gives sustained periodic oscillations, or a noise-induced oscillator, where a
fixed point is linearly stable with complex eigenvalues and addition of noise
gives oscillations around the fixed point with fluctuating amplitude. We
investigate how each class of model behaves under the external periodic
forcing, taking the well-studied van der Pol equation as an example. We find
that, when the forcing is additive, the noise-induced oscillator can show only
one-to-one entrainment to the external frequency, in contrast to the limit
cycle oscillator which is known to entrain to any ratio. When the external
forcing is multiplicative, on the other hand, the noise-induced oscillator can
show entrainment to a few ratios other than one-to-one, while the limit cycle
oscillator shows entrain to any ratio. The noise blurs the entrainment in
general, but clear entrainment regions for limit cycles can be identified as
long as the noise is not too strong.Comment: 27 pages in preprint style, 12 figues, 2 tabl
Understanding Hydrogen-Bond Patterns in Proteins using a Novel Statistical Model
Proteins are built from basic structural elements and their systematic characterization is of interest. Searching for recurring patterns in protein contact maps, we found several network motifs, patterns that occur more frequently in experimentally determined protein contact maps than in randomized contact maps with the same properties. Some of these network motifs correspond to sub-structures of alpha helices, including topologies not previously recognized in this context. Other motifs characterize beta-sheets, again some of which appear to be novel. This topological characterization of patterns serves as a tool to characterize proteins, and to reveal a high detailed differences map for comparing protein structures solved by X-ray crystallography, NMR and molecular dynamics (MD) simulations. Both NMR and MD show small but consistent differences from the crystal structures of the same proteins, possibly due to the pair-wise energy functions used. Network motifs analysis can serve as a base for many-body energy statistical energy potential, and suggests a dictionary of basic elements of which protein secondary structure is made
Accurate prediction of gene feedback circuit behavior from component properties
A basic assumption underlying synthetic biology is that analysis of genetic circuit elements, such as regulatory proteins and promoters, can be used to understand and predict the behavior of circuits containing those elements. To test this assumption, we used time‐lapse fluorescence microscopy to quantitatively analyze two autoregulatory negative feedback circuits. By measuring the gene regulation functions of the corresponding repressor–promoter interactions, we accurately predicted the expression level of the autoregulatory feedback loops, in molecular units. This demonstration that quantitative characterization of regulatory elements can predict the behavior of genetic circuits supports a fundamental requirement of synthetic biology
Environmental variability and modularity of bacterial metabolic networks
<p>Abstract</p> <p>Background</p> <p>Biological systems are often modular: they can be decomposed into nearly-independent structural units that perform specific functions. The evolutionary origin of modularity is a subject of much current interest. Recent theory suggests that modularity can be enhanced when the environment changes over time. However, this theory has not yet been tested using biological data.</p> <p>Results</p> <p>To address this, we studied the relation between environmental variability and modularity in a natural and well-studied system, the metabolic networks of bacteria. We classified 117 bacterial species according to the degree of variability in their natural habitat. We find that metabolic networks of organisms in variable environments are significantly more modular than networks of organisms that evolved under more constant conditions.</p> <p>Conclusion</p> <p>This study supports the view that variability in the natural habitat of an organism promotes modularity in its metabolic network and perhaps in other biological systems.</p
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