Biology subjects

Michael Stumpf

Publications and source records attributed to Michael Stumpf.

3 recordsLinked to original sources

bioRxiv2016

Control mechanisms for stochastic biochemical systems via computation of reachable sets

Controlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently non-linear. We present an approach to studying the impact of control measures on motifs of molecular interactions, that addresses the problems faced in biological systems: stochasticity, parameter uncertainty, and non-linearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters.

Systems Biology↗

bioRxiv2015

Information Processing by Simple Molecular Motifs and Susceptibility to Noise

Biological organisms rely on their ability to sense and respond appropriately to their environment. The molecular mechanisms that facilitate these essential processes are however subject to a range of random effects and stochastic processes, which jointly affect the reliability of information transmission between receptors and e.g. the physiological downstream response. Information is mathematically defined in terms of the entropy; and the extent of information flowing across an information channel or signalling system is typically measured by the \"mutual information\", or the reduction in the uncertainty about the output once the input signal is known. Here we quantify how extrinsic and intrinsic noise affect the transmission of simple signals along simple motifs of molecular interaction networks. Even for very simple systems the effects of the different sources of variability alone and in combination can give rise to bewildering complexity. In particular extrinsic variability is apt to generate \"apparent\" information that can in extreme cases mask the actual information that for a single system would flow between the different molecular components making up cellular signalling pathways. We show how this artificial inflation in apparent information arises and how the effects of different types of noise alone and in combination can be understood.

Systems Biology↗

bioRxiv2015

Origins of cell-to-cell variability, kinetic proof-reading and the robustness of MAPK signal transduction

Cellular signalling processes can exhibit pronounced cell-to-cell variability in genetically identical cells. This affects how individual cells respond differentially to the same environmental stimulus. However, the origins of cell-to-cell variability in cellular signalling systems remain poorly understood. Here we measure the temporal evolution of phosphorylated MEK and ERK dynamics across populations of cells and quantify the levels of population heterogeneity over time using high-throughput image cytometry. We use a statistical modelling framework to show that upstream noise is the dominant factor causing cell-to-cell variability in ERK phosphorylation, rather than stochasticity in the phosphorylation/dephosphorylation of ERK. In particular, the cell-to-cell variability during sustained phosphorylation stems from random fluctuations in the background upstream signalling processes, while during transient phosphorylation, the heterogeneity is primarily due to noise in the intensity of the upstream signal(s). We show that the core MEK/ERK system uses kinetic proof-reading to faithfully and robustly transmits these variable inputs. The MAPK cascade thus propagates cell-to-cell variability at the population level, rather than attenuating or increasing it.

Systems Biology↗