66 research outputs found
Ribosome traffic on mRNAs maps to gene ontology : genome-wide quantification of translation initiation rates and polysome size regulation
Peer reviewedPublisher PD
Gene length as a regulator for ribosome recruitment and protein synthesis : theoretical insights
The authors would like to acknowledge the funding provided by the European Union Seventh Framework Programme [FP7/2007–2013] (NICHE; grant agreement 289384) (LDF). LDF also acknowledges the funding provided by the São Paulo Research Foundation (FAPESP - grant #2015/26989-4). AM was partially funded by the UK Biotechnology and Biological Research Council (BBSRC), through grant BB/N015711/1. LC would like to acknowledge Maria Carmen Romano, Jean Hausser, Marco Cosentino Lagomarsino, Jean-Charles Walter and Norbert Kern for early discussions on this work, and the CNRS for having granted him a “demi-délégation” (2017–18). We would like to dedicate this work in memory of Maxime Clusel and Vladimir Lorman.Peer reviewedPublisher PDFPublisher PD
Motor proteins traffic regulation by supply-demand balance of resources
In cells and in vitro assays the number of motor proteins involved in
biological transport processes is far from being unlimited. The cytoskeletal
binding sites are in contact with the same finite reservoir of motors (either
the cytosol or the flow chamber) and hence compete for recruiting the available
motors, potentially depleting the reservoir and affecting cytoskeletal
transport. In this work we provide a theoretical framework to study,
analytically and numerically, how motor density profiles and crowding along
cytoskeletal filaments depend on the competition of motors for their binding
sites. We propose two models in which finite processive motor proteins actively
advance along cytoskeletal filaments and are continuously exchanged with the
motor pool. We first look at homogeneous reservoirs and then examine the
effects of free motor diffusion in the surrounding medium. We consider as a
reference situation recent in vitro experimental setups of kinesin-8 motors
binding and moving along microtubule filaments in a flow chamber. We
investigate how the crowding of linear motor proteins moving on a filament can
be regulated by the balance between supply (concentration of motor proteins in
the flow chamber) and demand (total number of polymerised tubulin
heterodimers). We present analytical results for the density profiles of bound
motors, the reservoir depletion, and propose novel phase diagrams that present
the formation of jams of motor proteins on the filament as a function of two
tuneable experimental parameters: the motor protein concentration and the
concentration of tubulins polymerized into cytoskeletal filaments. Extensive
numerical simulations corroborate the analytical results for parameters in the
experimental range and also address the effects of diffusion of motor proteins
in the reservoir.Comment: 31 pages, 10 figure
Identification of the mRNA targets of tRNA-specific regulation using genome-wide simulation of translation
FUNDING Biotechnology and Biological Sciences Research Council (BBSRC) [BB/I020926/1 to I.S.]; BBSRC PhD studentship award [C103817D to I.S. and M.C.R.]; Scottish Universities Life Science Alliance PhD studentship award (to M.C.R. and I.S.]. Funding for open access charge: BBSRC. Conflict of interest statement. None declared.Peer reviewedPublisher PD
Stepping and crowding of molecular motors: statistical kinetics from an exclusion process perspective
Motor enzymes are remarkable molecular machines that use the energy derived
from the hydrolysis of a nucleoside triphosphate to generate mechanical
movement, achieved through different steps that constitute their kinetic cycle.
These macromolecules, nowadays investigated with advanced experimental
techniques to unveil their molecular mechanisms and the properties of their
kinetic cycles, are implicated in many biological processes, ranging from
biopolymerisation (e.g. RNA polymerases and ribosomes) to intracellular
transport (motor proteins such as kinesins or dyneins). Although the kinetics
of individual motors is well studied on both theoretical and experimental
grounds, the repercussions of their stepping cycle on the collective dynamics
still remains unclear. Advances in this direction will improve our
comprehension of transport process in the natural intracellular medium, where
processive motor enzymes might operate in crowded conditions. In this work, we
therefore extend the current statistical kinetic analysis to study collective
transport phenomena of motors in terms of lattice gas models belonging to the
exclusion process class. Via numerical simulations, we show how to interpret
and use the randomness calculated from single particle trajectories in crowded
conditions. Importantly, we also show that time fluctuations and non-Poissonian
behavior are intrinsically related to spatial correlations and the emergence of
large, but finite, clusters of co-moving motors. The properties unveiled by our
analysis have important biological implications on the collective transport
characteristics of processive motor enzymes in crowded conditions.Comment: 9 pages, 6 figures, 2 supplementary figure
TASEPy: a Python-based package to iteratively solve the inhomogeneous exclusion process
The totally asymmetric simple exclusion process (TASEP) is a paradigmatic
lattice model for one-dimensional particle transport subject to excluded-volume
interactions. Solving the inhomogeneous TASEP in which particles' hopping rates
vary across the lattice is a long-standing problem. In recent years, a power
series approximation (PSA) has been developed to tackle this problem, however
no computer algorithm currently exists that implements this approximation. This
paper addresses this issue by providing a Python-based package TASEPy that
finds the steady state solution of the inhomogeneous TASEP for any set of
hopping rates using the PSA truncated at a user-defined order.Comment: 20 pages, 6 figures, submission to SciPos
Power series solution of the inhomogeneous exclusion process
We develop a power series method for the nonequilibrium steady state of the
inhomogeneous one-dimensional totally asymmetric simple exclusion process
(TASEP) in contact with two particle reservoirs and with site-dependent hopping
rates in the bulk. The power series is performed in the entrance or exit rates
governing particle exchange with the reservoirs, and the corresponding particle
current is computed analytically up to the cubic term in the entry or exit
rate, respectively. We also show how to compute higher-order terms using
combinatorial objects known as Young tableaux. Our results address the long
outstanding problem of finding the exact nonequilibrium steady state of the
inhomogeneous TASEP. The findings are particularly relevant to the modelling of
mRNA translation in which the rate of translation initiation, corresponding to
the entrance rate in the TASEP, is typically small.Comment: 14 pages, 6 figures, mean-field solution include
An equilibrium model for ribosome competition
The number of ribosomes in a cell is considered as limiting, and gene
expression is thus largely determined by their cellular concentration. In this
work we develop a toy model to study the trade-off between the ribosomal supply
and the demand of the translation machinery, dictated by the composition of the
transcript pool. Our equilibrium framework is useful to highlight qualitative
behaviours and new means of gene expression regulation determined by the fine
balance of this trade-off. We also speculate on the possible impact of these
mechanisms on cellular physiology
Deciphering mRNA Sequence Determinants of Protein Production Rate
5 pages, 3 figures, Supplemental Material (3 pages)One of the greatest challenges in biophysical models of translation is to identify coding sequences features that affect the rate of translation and therefore the overall protein production in the cell. We propose an analytic method to solve a translation model based on the inhomogeneous totally asymmetric simple exclusion process, which allow us to unveil simple design principles of nucleotide sequences determining protein production rates. Our solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, together with the value of the initiation rate, are the main determinants of protein production rate. Finally, we interpret the obtained analytic results based on the evolutionary role of codons' choice for regulating translation rates and ribosome densities
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