41 research outputs found
RNA-based regulation: dynamics and response to perturbations of competing RNAs
The observation that, through a titration mechanism, microRNAs (miRNAs) can
act as mediators of effective interactions among their common targets
(competing endogenous RNAs or ceRNAs) has brought forward the idea ('ceRNA
hypothesis') that RNAs can regulate each other in extended 'cross-talk'
networks. Such an ability might play a major role in post-transcriptional
regulation (PTR) in shaping a cell's protein repertoire. Recent work focusing
on the emergent properties of the cross-talk networks has emphasized the high
flexibility and selectivity that may be achieved at stationarity. On the other
hand, dynamical aspects, possibly crucial on the relevant time scales, are far
less clear. We have carried out a dynamical study of the ceRNA hypothesis on a
model of PTR. Sensitivity analysis shows that ceRNA cross-talk is dynamically
extended, i.e. it may take place on time scales shorter than those required to
achieve stationairity even in cases where no cross-talk occurs in the steady
state, and is possibly amplified. Besides, in case of large, transfection-like
perturbations the system may develop strongly non-linear, threshold response.
Finally, we show that the ceRNA effect provides a very efficient way for a cell
to achieve fast positive shifts in the level of a ceRNA when necessary. These
results indicate that competition for miRNAs may indeed provide an elementary
mechanism to achieve system-level regulatory effects on the transcriptome over
physiologically relevant time scales.Comment: Main text: 10 pages, 13 figures. Supporting Text: 3 pages, 6 figure
MicroRNAs as a selective channel of communication between competing RNAs: a steady-state theory
It has recently been suggested that the competition for a finite pool of
microRNAs (miRNA) gives rise to effective interactions among their common
targets (competing endogenous RNAs or ceRNAs) that could prove to be crucial
for post-transcriptional regulation (PTR). We have studied a minimal model of
PTR where the emergence and the nature of such interactions can be
characterized in detail at steady state. Sensitivity analysis shows that
binding free energies and repression mechanisms are the key ingredients for the
cross-talk between ceRNAs to arise. Interactions emerge in specific ranges of
repression values, can be symmetrical (one ceRNA influences another and
vice-versa) or asymmetrical (one ceRNA influences another but not the reverse)
and may be highly selective, while possibly limited by noise. In addition, we
show that non-trivial correlations among ceRNAs can emerge in experimental
readouts due to transcriptional fluctuations even in absence of miRNA-mediated
cross-talk.Comment: 15 pages, 10 figures, to appear in Biophys
Probing the limits to microRNA-mediated control of gene expression
According to the `ceRNA hypothesis', microRNAs (miRNAs) may act as mediators
of an effective positive interaction between long coding or non-coding RNA
molecules, carrying significant potential implications for a variety of
biological processes. Here, inspired by recent work providing a quantitative
description of small regulatory elements as information-conveying channels, we
characterize the effectiveness of miRNA-mediated regulation in terms of the
optimal information flow achievable between modulator (transcription factors)
and target nodes (long RNAs). Our findings show that, while a sufficiently
large degree of target derepression is needed to activate miRNA-mediated
transmission, (a) in case of differential mechanisms of complex processing
and/or transcriptional capabilities, regulation by a post-transcriptional
miRNA-channel can outperform that achieved through direct transcriptional
control; moreover, (b) in the presence of large populations of weakly
interacting miRNA molecules the extra noise coming from titration disappears,
allowing the miRNA-channel to process information as effectively as the direct
channel. These observations establish the limits of miRNA-mediated
post-transcriptional cross-talk and suggest that, besides providing a degree of
noise buffering, this type of control may be effectively employed in cells both
as a failsafe mechanism and as a preferential fine tuner of gene expression,
pointing to the specific situations in which each of these functionalities is
maximized.Comment: 16 page
Inverse Statistical Physics of Protein Sequences: A Key Issues Review
In the course of evolution, proteins undergo important changes in their amino
acid sequences, while their three-dimensional folded structure and their
biological function remain remarkably conserved. Thanks to modern sequencing
techniques, sequence data accumulate at unprecedented pace. This provides large
sets of so-called homologous, i.e.~evolutionarily related protein sequences, to
which methods of inverse statistical physics can be applied. Using sequence
data as the basis for the inference of Boltzmann distributions from samples of
microscopic configurations or observables, it is possible to extract
information about evolutionary constraints and thus protein function and
structure. Here we give an overview over some biologically important questions,
and how statistical-mechanics inspired modeling approaches can help to answer
them. Finally, we discuss some open questions, which we expect to be addressed
over the next years.Comment: 18 pages, 7 figure
A scalable algorithm to explore the Gibbs energy landscape of genome-scale metabolic networks
The integration of various types of genomic data into predictive models of
biological networks is one of the main challenges currently faced by
computational biology. Constraint-based models in particular play a key role in
the attempt to obtain a quantitative understanding of cellular metabolism at
genome scale. In essence, their goal is to frame the metabolic capabilities of
an organism based on minimal assumptions that describe the steady states of the
underlying reaction network via suitable stoichiometric constraints,
specifically mass balance and energy balance (i.e. thermodynamic feasibility).
The implementation of these requirements to generate viable configurations of
reaction fluxes and/or to test given flux profiles for thermodynamic
feasibility can however prove to be computationally intensive. We propose here
a fast and scalable stoichiometry-based method to explore the Gibbs energy
landscape of a biochemical network at steady state. The method is applied to
the problem of reconstructing the Gibbs energy landscape underlying metabolic
activity in the human red blood cell, and to that of identifying and removing
thermodynamically infeasible reaction cycles in the Escherichia coli metabolic
network (iAF1260). In the former case, we produce consistent predictions for
chemical potentials (or log-concentrations) of intracellular metabolites; in
the latter, we identify a restricted set of loops (23 in total) in the
periplasmic and cytoplasmic core as the origin of thermodynamic infeasibility
in a large sample () of flux configurations generated randomly and
compatibly with the prior information available on reaction reversibility.Comment: 11 pages, 6 figures, 1 table; for associated supporting material see
http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.100256
RNA-Based Regulation: Dynamics and Response to Perturbations of Competing RNAs.
The observation that, through a titration mechanism, microRNAs (miRNAs) can act as mediators of effective interactions among their common targets (competing endogenous RNAs or ceRNAs) has brought forward the idea (i.e., the ceRNA hypothesis) that RNAs can regulate each other in extended cross-talk networks. Such an ability might play a major role in posttranscriptional regulation to shape a cell's protein repertoire. Recent work focusing on the emergent properties of the cross-talk networks has emphasized the high flexibility and selectivity that may be achieved at stationarity. On the other hand, dynamical aspects, possibly crucial on the relevant timescales, are far less clear. We have carried out a dynamical study of the ceRNA hypothesis on a model of posttranscriptional regulation. Sensitivity analysis shows that ceRNA cross-talk is dynamically extended, i.e., it may take place on timescales shorter than those required to achieve stationarity even in cases where no cross-talk occurs in the steady state, and is possibly amplified. In addition, in the case of large, transfection-like perturbations, the system may develop a strongly nonlinear, threshold response. Finally, we show that the ceRNA effect provides a very efficient way for a cell to achieve fast positive shifts in the level of a ceRNA when necessary. These results indicate that competition for miRNAs may indeed provide an elementary mechanism to achieve system-level regulatory effects on the transcriptome over physiologically relevant timescales. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved
Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1
International audienceThe quantitative characterization of mutational landscapes is a task of outstanding importance in evolutionary and medical biology: It is, for example, of central importance for our understanding of the phenotypic effect of mutations related to disease and antibiotic drug resistance. Here we develop a novel inference scheme for mutational landscapes, which is based on the statistical analysis of large alignments of homologs of the protein of interest. Our method is able to capture epistatic couplings between residues, and therefore to assess the dependence of mutational effects on the sequence context where they appear. Compared with recent large-scale mutagenesis data of the beta-lactamase TEM-1, a protein providing resistance against beta-lactam antibiotics, our method leads to an increase of about 40% in explicative power as compared with approaches neglecting epistasis. We find that the informative sequence context extends to residues at native distances of about 20 Ă
from the mutated site, reaching thus far beyond residues in direct physical contact
Inverse statistical physics of protein sequences: a key issues review
No abstract availabl
Effect of the 3D Artificial Nichoid on the Morphology and Mechanobiological Response of Mesenchymal Stem Cells Cultured In Vitro
Stem cell fate and behavior are affected by the bidirectional communication of cells and their local microenvironment (the stem cell niche), which includes biochemical cues, as well as physical and mechanical factors. Stem cells are normally cultured in conventional two-dimensional monolayer, with a mechanical environment very different from the physiological one. Here, we compare culture of rat mesenchymal stem cells on flat culture supports and in the “Nichoid”, an innovative three-dimensional substrate micro-engineered to recapitulate the architecture of the physiological niche in vitro. Two versions of the culture substrates Nichoid (single-layered or “2D Nichoid” and multi-layered or “3D Nichoid”) were fabricated via two-photon laser polymerization in a biocompatible hybrid organic-inorganic photoresist (SZ2080). Mesenchymal stem cells, isolated from rat bone marrow, were seeded on flat substrates and on 2D and 3D Nichoid substrates and maintained in culture up to 2 weeks. During cell culture, we evaluated cell morphology, proliferation, cell motility and the expression of a panel of 89 mesenchymal stem cells’ specific genes, as well as intracellular structures organization. Our results show that mesenchymal stem cells adhered and grew in the 3D Nichoid with a comparable proliferation rate as compared to flat substrates. After seeding on flat substrates, cells displayed large and spread nucleus and cytoplasm, while cells cultured in the 3D Nichoid were spatially organized in three dimensions, with smaller and spherical nuclei. Gene expression analysis revealed the upregulation of genes related to stemness and to mesenchymal stem cells’ features in Nichoid-cultured cells, as compared to flat substrates. The observed changes in cytoskeletal organization of cells cultured on 3D Nichoids were also responsible for a different localization of the mechanotransducer transcription factor YAP, with an increase of the cytoplasmic retention in cells cultured in the 3D Nichoid. This difference could be explained by alterations in the import of transcription factors inside the nucleus due to the observed decrease of mean nuclear pore diameter, by transmission electron microscopy. Our data show that 3D distribution of cell volume has a profound effect on mesenchymal stem cells structure and on their mechanobiological response, and highlight the potential use of the 3D Nichoid substrate to strengthen the potential effects of MSC in vitro and in vivo