Dataset Information

Multi-compartment encapsulation of communicating droplets and droplet networks in hydrogel as a model for artificial cells.

ABSTRACT: Constructing a cell mimic is a major challenge posed by synthetic biologists. Efforts to this end have been primarily focused on lipid- and polymer-encapsulated containers, liposomes and polymersomes, respectively. Here, we introduce a multi-compartment, nested system comprising aqueous droplets stabilized in an oil/lipid mixture, all encapsulated in hydrogel. Functional capabilities (electrical and chemical communication) were imparted by protein nanopores spanning the lipid bilayer formed at the interface of the encapsulated aqueous droplets and the encasing hydrogel. Crucially, the compartmentalization enabled the formation of two adjoining lipid bilayers in a controlled manner, a requirement for the realization of a functional protocell or prototissue.

SUBMITTER: Bayoumi M

PROVIDER: S-EPMC5377250 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Publications

Multi-compartment encapsulation of communicating droplets and droplet networks in hydrogel as a model for artificial cells.

Bayoumi Mariam M Bayley Hagan H Maglia Giovanni G Sapra K Tanuj KT

Scientific reports 20170403

Constructing a cell mimic is a major challenge posed by synthetic biologists. Efforts to this end have been primarily focused on lipid- and polymer-encapsulated containers, liposomes and polymersomes, respectively. Here, we introduce a multi-compartment, nested system comprising aqueous droplets stabilized in an oil/lipid mixture, all encapsulated in hydrogel. Functional capabilities (electrical and chemical communication) were imparted by protein nanopores spanning the lipid bilayer formed at t ...[more]

PMID: 28367984

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Project description:BACKGROUND: Constructing predictive dynamic models of interacting signalling networks remains one of the great challenges facing systems biology. While detailed dynamical data exists about individual pathways, the task of combining such data without further lengthy experimentation is highly nontrivial. The communicating links between pathways, implicitly assumed to be unimportant and thus excluded, are precisely what become important in the larger system and must be reinstated. To maintain the delicate phase relationships between signals, signalling networks demand accurate dynamical parameters, but parameters optimised in isolation and under varying conditions are unlikely to remain optimal when combined. The computational burden of estimating parameters increases exponentially with increasing system size, so it is crucial to find precise and efficient ways of measuring the behaviour of systems, in order to re-use existing work. RESULTS: Motivated by the above, we present a new frequency domain-based systematic analysis technique that attempts to address the challenge of network assembly by defining a rigorous means to quantify the behaviour of stochastic systems. As our focus we construct a novel coupled oscillatory model of p53, NF-kB and the mammalian cell cycle, based on recent experimentally verified mathematical models. Informed by online databases of protein networks and interactions, we distilled their key elements into simplified models containing the most significant parts. Having coupled these systems, we constructed stochastic models for use in our frequency domain analysis. We used our new technique to investigate the crosstalk between the components of our model and measure the efficacy of certain network-based heuristic measures. CONCLUSIONS: We find that the interactions between the networks we study are highly complex and not intuitive: (i) points of maximum perturbation do not necessarily correspond to points of maximum proximity to influence; (ii) increased coupling strength does not necessarily increase perturbation; (iii) different perturbations do not necessarily sum and (iv) overall, susceptibility to perturbation is amplitude and frequency dependent and cannot easily be predicted by heuristic measures.Our methodology is particularly relevant for oscillatory systems, though not limited to these, and is most revealing when applied to the results of stochastic simulation. The technique is able to characterise precisely the distance in behaviour between different models, different systems and different parts within the same system. It can also measure the difference between different simulation algorithms used on the same system and can be used to inform the choice of dynamic parameters. By measuring crosstalk between subsystems it can also indicate mechanisms by which such systems may be controlled in experiments and therapeutics. We have thus found our technique of frequency domain analysis to be a valuable benchmark systems-biological tool.

Dataset Information

Multi-compartment encapsulation of communicating droplets and droplet networks in hydrogel as a model for artificial cells.

Publications

Multi-compartment encapsulation of communicating droplets and droplet networks in hydrogel as a model for artificial cells.

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