Biology subjects

Sechkar, K.

Publications and source records attributed to Sechkar, K..

4 recordsLinked to original sources

bioRxiv2024

Model-guided gene circuit design for engineering genetically stable cell populations in diverse applications

Maintaining engineered cell populations genetic stability is a key challenge in synthetic biology. Synthetic genetic constructs compete with a host cells native genes for expression resources, burdening the cell and impairing its growth. This creates a selective pressure favouring mutations which alleviate this growth defect by removing synthetic gene expression. Non-functional mutants thus spread in cell populations, eventually making them lose engineered functions. Past work has attempted to limit mutation spread by coupling synthetic gene expression to survival. However, these approaches are highly context-dependent and must be tailor-made for each particular synthetic gene circuit to be retained. In contrast, we develop and analyse a biomolecular controller which depresses mutant cell growth independently of the mutated synthetic genes identity. Modelling shows how our design can be deployed alongside various synthetic circuits without any re-engineering of its genetic components, outperforming extant gene-specific mutation spread mitigation strategies. Our controllers performance is evaluated using a novel simulation approach which leverages resource-aware cell modelling to directly link a circuits design parameters to its population-level behaviour. Our designs adaptability promises to mitigate mutation spread in an expanded range of applications, whilst our analyses provide a blueprint for using resource-aware cell models in circuit design.

synthetic biology↗

bioRxiv2024

Combining positive and negative regulation for modular and robust biomolecular control architectures

Engineered biotechnologies are powered by synthetic gene regulation and control systems, known as genetic circuits, which must be modular and robust to disturbances if they are to perform reliably. An emerging family of regulatory mechanisms is mediated by clustered interspaced palindromic repeats (CRISPR) that can both interfere with (downregulate) or activate (upregulate) a given genes expression. However, all CRSIPR regulation relies on a shared resource pool of dCas9 proteins. Hence, a circuits components can indirectly affect one another via resource competition - even without any intended interactions between them - which compromises the modularity of synthetic biological designs. Using a resourceaware model of CRISPR regulation, we find that circuit modules which simultaneously subject a gene to CRISPR interference and activation are rendered robust to resource competition crosstalk. Evaluating this architectures simulated performance, we identify the scenarios where it can be advantageous over the extant resource competition mitigation strategies. We then consider different feedback architectures to demonstrate that combining opposite regulatory interactions overcomes the trade-off in robustness to perturbations of different nature. The motif of combined positive and negative regulation may therefore give rise to more robust and modular biomolecular controllers, as well as hint at the characteristics of natural systems that possess it.

synthetic biology↗

bioRxiv2023

A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits

Synthetic genes compete among themselves and with the host cells genes for expression machinery, exhibiting resource couplings that affect the dynamics of cellular processes. The modeling of such couplings can be facilitated by simplifying the kinetics of resource-substrate binding. Model-guided design allows to counter unwanted indirect interactions by using biomolecular controllers or tuning the biocircuits parameters. However, resource-aware biocircuit design in bacteria is complicated by the interdependence of resource availability and cell growth rate, which significantly affects biocircuit performance. This phenomenon can be captured by coarse-grained models of the whole bacterial cell. The level of detail in these models must balance accurate representation of metabolic regulation against model simplicity and interpretability. We propose a coarse-grained E. coli cell model that combines the ease of simplified resource coupling analysis with the appreciation of bacterial growth regulation mechanisms. Reliably capturing known growth phenomena, it enables numerical prototyping of biocircuits and derivation of analytical relations which can guide the design process. By reproducing several distinct empirical laws observed in prior studies, our model provides a unifying framework for previously disjoint experimental observations. Finally, we propose a novel biomolecular controller that achieves near-perfect adaptation of cell-wide ribosome availability to changes in synthetic gene expression. Showcasing our models usefulness, we use it to determine the controllers setpoint and operation range from its constituent genes parameters.

synthetic biology↗

bioRxiv2021

A linear programming-based strategy to save pipette tips in automated DNA assembly

Laboratory automation and mathematical optimisation are key to improving the efficiency of synthetic biology research. While there are algorithms optimising the construct designs and synthesis strategies for DNA assembly, the optimisation of how DNA assembly reaction mixes are prepared remains largely unexplored. Here, we focus on reducing the pipette tip consumption of a liquid-handling robot as it delivers DNA parts across a multi-well plate where several constructs are being assembled in parallel. We propose a linear programming formulation of this problem based on the capacitated vehicle routing problem, along with an algorithm which applies a linear programming solver to our formulation, hence providing a strategy to prepare a given set of DNA assembly mixes using fewer pipette tips. The algorithm performed well in randomly generated and real-life scenarios concerning several modular DNA assembly standards, proving capable of reducing the pipette tip consumption by up to 61% in large-scale cases. Combining automatic process optimisation and robotic liquid-handling, our strategy promises to greatly improve the efficiency of DNA assembly, either used alone or in combination with other algorithmic methods.

synthetic biology↗