Biology subjects

de Cesare, I.

Publications and source records attributed to de Cesare, I..

3 recordsLinked to original sources

bioRxiv2020

ChipSeg: an automatic tool to segment bacteria and mammalian cells cultured in microfluidic devices

Extracting quantitative measurements from time-lapse images is necessary in external feedback control applications, where segmentation results are used to inform control algorithms. While such image segmentation applications have been previously reported, there is in the literature a lack of open-source and documented code for the community. We describe ChipSeg, a computational tool to segment bacterial and mammalian cells cultured in microfluidic devices and imaged by time-lapse microscopy. The method is based on thresholding and uses the same core functions for both cell types. It allows to segment individual cells in high cell-density microfluidic devices, to quantify fluorescence protein expression over a time-lapse experiment and to track individual cells. ChipSeg enables robust segmentation in external feedback control experiments and can be easily customised for other experimental settings and research aims.

synthetic biology↗

bioRxiv2020

Cheetah: a computational toolkit for cybergenetic control

Advances in microscopy, microfluidics and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups that hinder reproducibility. To address this, we introduce Cheetah - a flexible computational toolkit that simplifies the integration of real-time microscopy analysis with algorithms for cellular control. Central to the platform is an image segmentation system based on the versatile U-Net convolutional neural network. This is supplemented with functionality to robustly count, characterise and control cells over time. We demonstrate Cheetahs core capabilities by analysing long-term bacterial and mammalian cell growth and by dynamically controlling protein expression in mammalian cells. In all cases, Cheetahs segmentation accuracy exceeds that of a commonly used thresholding-based method, allowing for more accurate control signals to be generated. Availability of this easy-to-use platform will make control engineering techniques more accessible and offer new ways to probe and manipulate living cells.

synthetic biology↗

bioRxiv2019

Exploring the Dynamics of Nonlinear Biochemical Systems using Control-Based Continuation

AO_SCPLOWBSTRACTC_SCPLOWMathematical modelling is routinely used in Systems Biology to understand the mechanisms causing nonlinear phenomena in gene expression, such as switch-like behaviours and temporal oscillations. The reliability of model predictions and bifurcation analysis depend on modelling assumptions and specific choices of model parameters; however, the identification of models is highly challenging due to the complexity of biochemical interactions and noise in experimental data. This paper numerically investigates the use of control-based continuation (CBC) for tracking dynamical features of biochemical systems and, in particular, the bistable dynamics of a gene regulating pluripotency in embryonic stem cells. CBC is a method that exploits feedback control and path following algorithms to explore the dynamic features of a nonlinear physical system directly during experimental tests. CBC applications have so far been limited to non-living (i.e. electro-mechanical) systems. Our numerical simulations show that, in principle, CBC could also be applied to biological experiments to characterise the switch-like dynamics of genes that are important for cell decision making.

systems biology↗