118,426 research outputs found
Genetic noise control via protein oligomerization
Gene expression in a cell entails random reaction events occurring over
disparate time scales. Thus, molecular noise that often results in phenotypic
and population-dynamic consequences sets a fundamental limit to biochemical
signaling. While there have been numerous studies correlating the architecture
of cellular reaction networks with noise tolerance, only a limited effort has
been made to understand the dynamic role of protein-protein interactions. Here
we have developed a fully stochastic model for the positive feedback control of
a single gene, as well as a pair of genes (toggle switch), integrating
quantitative results from previous in vivo and in vitro studies. We find that
the overall noise-level is reduced and the frequency content of the noise is
dramatically shifted to the physiologically irrelevant high-frequency regime in
the presence of protein dimerization. This is independent of the choice of
monomer or dimer as transcription factor and persists throughout the multiple
model topologies considered. For the toggle switch, we additionally find that
the presence of a protein dimer, either homodimer or heterodimer, may
significantly reduce its random switching rate. Hence, the dimer promotes the
robust function of bistable switches by preventing the uninduced (induced)
state from randomly being induced (uninduced). The specific binding between
regulatory proteins provides a buffer that may prevent the propagation of
fluctuations in genetic activity. The capacity of the buffer is a non-monotonic
function of association-dissociation rates. Since the protein oligomerization
per se does not require extra protein components to be expressed, it provides a
basis for the rapid control of intrinsic or extrinsic noise
Gene autoregulation via intronic microRNAs and its functions
Background: MicroRNAs, post-transcriptional repressors of gene expression,
play a pivotal role in gene regulatory networks. They are involved in core
cellular processes and their dysregulation is associated to a broad range of
human diseases. This paper focus on a minimal microRNA-mediated regulatory
circuit, in which a protein-coding gene (host gene) is targeted by a microRNA
located inside one of its introns. Results: Autoregulation via intronic
microRNAs is widespread in the human regulatory network, as confirmed by our
bioinformatic analysis, and can perform several regulatory tasks despite its
simple topology. Our analysis, based on analytical calculations and
simulations, indicates that this circuitry alters the dynamics of the host gene
expression, can induce complex responses implementing adaptation and Weber's
law, and efficiently filters fluctuations propagating from the upstream network
to the host gene. A fine-tuning of the circuit parameters can optimize each of
these functions. Interestingly, they are all related to gene expression
homeostasis, in agreement with the increasing evidence suggesting a role of
microRNA regulation in conferring robustness to biological processes. In
addition to model analysis, we present a list of bioinformatically predicted
candidate circuits in human for future experimental tests. Conclusions: The
results presented here suggest a potentially relevant functional role for
negative self-regulation via intronic microRNAs, in particular as a homeostatic
control mechanism of gene expression. Moreover, the map of circuit functions in
terms of experimentally measurable parameters, resulting from our analysis, can
be a useful guideline for possible applications in synthetic biology.Comment: 29 pages and 7 figures in the main text, 18 pages of Supporting
Informatio
Transcriptional delay stabilizes bistable gene networks
Transcriptional delay can significantly impact the dynamics of gene networks.
Here we examine how such delay affects bistable systems. We investigate several
stochastic models of bistable gene networks and find that increasing delay
dramatically increases the mean residence times near stable states. To explain
this, we introduce a non-Markovian, analytically tractable reduced model. The
model shows that stabilization is the consequence of an increased number of
failed transitions between stable states. Each of the bistable systems that we
simulate behaves in this manner
Doxorubicin Selectively Inhibits Brain versus Atrial Natriuretic Peptide Gene Expression in Cultured Neonatal Rat Myocytes
Doxorubicin is an antineoplastic agent with significant cardiotoxicity. We examined the effects of this agent on the expression of the natriuretic peptide (NP) genes in cultured neonatal rat atrial myocytes. Doxorubicin suppressed NP secretion, steady-state NP mRNA levels, and NP gene promoter activity. In each instance, brain NP (BNP) proved to be more sensitive than atrial NP (ANP) to the inhibitory effects of the drug. ICRF-187 and probucol reversed the inhibition by doxorubicin of ANP mRNA accumulation and ANP gene promoter activity while exerting no effect on BNP mRNA levels or promoter activity. This represents the first identification of the NP genes as targets of doxorubicin toxicity in the myocardial cell. This inhibition operates predominantly at a transcriptional locus and has more potent effects on BNP versus ANP secretion/gene expression. Measurement of BNP secretion/gene expression may provide a sensitive marker of early doxorubicin cardiotoxicity
The Role of Regulated mRNA Stability in Establishing Bicoid Morphogen Gradient in Drosophila Embryonic Development
The Bicoid morphogen is amongst the earliest triggers of differential spatial pattern of gene expression and subsequent cell fate determination in the embryonic development of Drosophila. This maternally deposited morphogen is thought to diffuse in the embryo, establishing a concentration gradient which is sensed by downstream genes. In most model based analyses of this process, the translation of the bicoid mRNA is thought to take place at a fixed rate from the anterior pole of the embryo and a supply of the resulting protein at a constant rate is assumed. Is this process of morphogen generation a passive one as assumed in the modelling literature so far, or would available data support an alternate hypothesis that the stability of the mRNA is regulated by active processes? We introduce a model in which the stability of the maternal mRNA is regulated by being held constant for a length of time, followed by rapid degradation. With this more realistic model of the source, we have analysed three computational models of spatial morphogen propagation along the anterior-posterior axis: (a) passive diffusion modelled as a deterministic differential equation, (b) diffusion enhanced by a cytoplasmic flow term; and (c) diffusion modelled by stochastic simulation of the corresponding chemical reactions. Parameter estimation on these models by matching to publicly available data on spatio-temporal Bicoid profiles suggests strong support for regulated stability over either a constant supply rate or one where the maternal mRNA is permitted to degrade in a passive manner
A combination of transcriptional and microRNA regulation improves the stability of the relative concentrations of target genes
It is well known that, under suitable conditions, microRNAs are able to fine
tune the relative concentration of their targets to any desired value. We show
that this function is particularly effective when one of the targets is a
Transcription Factor (TF) which regulates the other targets. This combination
defines a new class of feed-forward loops (FFLs) in which the microRNA plays
the role of master regulator. Using both deterministic and stochastic equations
we show that these FFLs are indeed able not only to fine-tune the TF/target
ratio to any desired value as a function of the miRNA concentration but also,
thanks to the peculiar topology of the circuit, to ensures the stability of
this ratio against stochastic fluctuations. These two effects are due to the
interplay between the direct transcriptional regulation and the indirect
TF/Target interaction due to competition of TF and target for miRNA binding
(the so called "sponge effect"). We then perform a genome wide search of these
FFLs in the human regulatory network and show that they are characterizedby a
very peculiar enrichment pattern. In particular they are strongly enriched in
all the situations in which the TF and its target have to be precisely kept at
the same concentration notwithstanding the environmental noise. As an example
we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and
miR-17 family as master regulator. These FFLs ensure a tight control of the
E2F/RB ratio which in turns ensures the stability of the transition from the
G0/G1 to the S phase in quiescent cells.Comment: 23 pages, 10 figure
Nonlinear Protein Degradation and the Function of Genetic Circuits
The functions of most genetic circuits require sufficient degrees of
cooperativity in the circuit components. While mechanisms of cooperativity have
been studied most extensively in the context of transcriptional initiation
control, cooperativity from other processes involved in the operation of the
circuits can also play important roles. In this study, we examine a simple
kinetic source of cooperativity stemming from the nonlinear degradation of
multimeric proteins. Ample experimental evidence suggests that protein subunits
can degrade less rapidly when associated in multimeric complexes, an effect we
refer to as cooperative stability. For dimeric transcription factors, this
effect leads to a concentration-dependence in the degradation rate because
monomers, which are predominant at low concentrations, will be more rapidly
degraded. Thus cooperative stability can effectively widen the accessible range
of protein levels in vivo. Through theoretical analysis of two exemplary
genetic circuits in bacteria, we show that such an increased range is important
for the robust operation of genetic circuits as well as their evolvability. Our
calculations demonstrate that a few-fold difference between the degradation
rate of monomers and dimers can already enhance the function of these circuits
substantially. These results suggest that cooperative stability needs to be
considered explicitly and characterized quantitatively in any systematic
experimental or theoretical study of gene circuits.Comment: 42 pages, 10 figure
Complex coordination of cell plasticity by a PGC-1α-controlled transcriptional network in skeletal muscle
Skeletal muscle cells exhibit an enormous plastic capacity in order to adapt to external stimuli. Even though our overall understanding of the molecular mechanisms that underlie phenotypic changes in skeletal muscle cells remains poor, several factors involved in the regulation and coordination of relevant transcriptional programs have been identified in recent years. For example, the peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) is a central regulatory nexus in the adaptation of muscle to endurance training. Intriguingly, PGC-1α integrates numerous signaling pathways and translates their activity into various transcriptional programs. This selectivity is in part controlled by differential expression of PGC-1α variants and post-translational modifications of the PGC-1α protein. PGC-1α-controlled activation of transcriptional networks subsequently enables a spatio-temporal specification and hence allows a complex coordination of changes in metabolic and contractile properties, protein synthesis and degradation rates and other features of trained muscle. In this review, we discuss recent advances in our understanding of PGC-1α-regulated skeletal muscle cell plasticity in health and disease
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