ROADBLOCK: Towards Programmable Defensive Bacterial Coatings & Skins

Lead Research Organisation: University of Nottingham
Department Name: School of Computer Science

Abstract

This project fits the EPSRC Synthetic Biology Signpost.This application-driven research project will seek to integrate the creation of new computational algorithms, tools and theories for synthetic biology (SB) with well-established wet lab techniques to develop an integrated and validated software suite (i.e. an in silico workbench) for SB. This project will focus on synthetic biology (SB) routes for creating engineered coatings, based on modified bacteria, that will act as bio-programmable shields against colonisation. The target application in this proposal is healthcare, using SB to develop biological based tools to tackle infection, however it is envisaged that ROADBLOCK constructs could be applicable in other medical, environmental or industrial applications in which bacterial colonisation or biofilm formation should be avoided. It will also consider the major social and ethical issues raised by this technology. The new computational tools will permit rapid bio-model prototyping and specification, simulation, verification, analysis and optimisation. Moreover, it will create ROADBLOCK biological parts, devices and systems. Previous SB projects had mainly mathematical (e.g. control theory, bifurcation analysis, differential equations, etc) components as auxiliary tools. In this project, Computer Science (CS) takes centre stage as we look to push its boundaries in the context of ROADBLOCK bio-devices. To the best of our knowledge, this is the first wet SB project that will directly drive the development of cutting-edge computer science (CS) activities.

Planned Impact

This application is at the crossroad of executable biology, an emergent computational approach to biological problems, and synthetic biology, a growing discipline in its own right. A successful outcome to this project will impart momentum to the computational sciences behind synthetic biology and would, for the first time, demonstrate conclusively that executable biology/algorithmic systems biology are not mere academic curiosities applicable to small and well know biological systems but rather practical and useful tools for designing, analyzing and verifying large and complex biological systems. From the biological applications viewpoint, ROADBLOCK could extend its scope beyond clinical settings into different industrial sectors. In industry (e.g. drinking water distribution systems, dental water unit lines, food processing), distribution pipes get colonised by pathogenic bacteria that form biofilms, which may have health implications if not treated appropriately. Those pipes could be coated or treated with the bacterial skins reducing the use of environmentally unfriendly chemicals. In agriculture bacterial spy bullets could be used to spray plant and protect them against bacterial diseases. The public at large (see impact statement )will also benefit from a very intensive activity of engagement whereby they will not only have the opportunity to learn about synthetic biology and its potential impacts (health, environment, etc) but also inform the workings of this consortium. Thus, we believe, this proposal to be highly relevant, timely and may well have a wide impact (for more details please see impact statement).

Related Projects

Project Reference Relationship Related To Start End Award Value
EP/I031642/1 01/02/2012 31/12/2013 £791,388
EP/I031642/2 Transfer EP/I031642/1 01/01/2014 31/07/2016 £536,933
 
Description Synthetic Biology aspires to design, compose and engineer biological systems that implement specified behaviour. When designing such systems, hypothesis testing via computational modelling and simulation is vital in order to reduce the need of costly wet lab experiments. As a case study, we worked on computational modelling and stochastic simulation for engineered genetic circuits that realised engineered biofilms. We present performance analysis results for different state-of-the-art stochastic simulation algorithms and analyse the dynamic behaviour of the proposed biofillms. Stochastic simulations verify the desired functioning of the proposed biofilms designs.
Stochastic simulation algorithms (SSAs) were developped to trace realistic trajectories of biochemical systems at low species concentrations. As the complexity of modeled biosystems increases, it is important to select the best performing SSA. Numerous improvements to SSAs have been introduced but they each only tend to apply to a certain class of models. This makes it difficult for a systems or synthetic biologist to decide which algorithm to employ when confronted with a new model that requires simulation. In this project, we demonstrated that it is possible to determine which algorithm is best suited to simulate a particular model and that this can be predicted a priori to algorithm execution. We present a Web based tool ssapredict that allows scientists to upload a biochemical model and obtain a prediction of the best performing SSA. Furthermore, ssapredict gives the user the option to download our high performance simulator ngss preconfigured to perform the simulation of the queried biochemical model with the predicted fastest algorithm as the simulation engine. The ssapredict Web application is available at http://ssapredict.ico2s.org. It is free software and its source code is distributed under the terms of the GNU Affero General Public License.
Moreover, we utilised, data mining and knowledge discovery techniques to process laboratory data. Our data analytics techniques are now able to handle larger and larger datasets, process heterogeneous information, integrate complex metadata, and extract and visualize new knowledge. Often these advances were driven by new challenges arising from real-world domains, with biology and biotechnology a prime source of diverse and hard (e.g., high volume, high throughput, high variety, and high noise) data analytics problems.
Exploitation Route Our computational design strategy for synthetic biology mixed consortia biofilms might be taken forward to engineer antimicrobial surfaces for example.
Sectors Agriculture, Food and Drink,Chemicals,Digital/Communication/Information Technologies (including Software),Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology

URL https://roadblock.ico2s.org/HomePage
 
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Description The webserver presented here provides solutions of near-minimal stages and thanks to almost instantaneous planning of DNA libraries it can be used as a metric of ?manufacturability? to guide DNA library design. Rapid planning remains applicable even for DNA library sizes vastly exceeding today's biochemical assembly methods, future-proofing our method. 
Type Of Technology Webtool/Application 
Year Produced 2014 
Impact -- 
URL http://www.dnald.org/planner/index.html
 
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Description De novo DNA synthesis is in need of new ideas for increasing production rate and reducing cost. DNA reuse in combinatorial library construction is one such idea. Here, we describe an algorithm for planning multistage assembly of DNA libraries with shared intermediates that greedily attempts to maximize DNA reuse, and show both theoretically and empirically that it runs in linear time. We compare solution quality and algorithmic performance to the best results reported for computing DNA assembly graphs, finding that our algorithm achieves solutions of equivalent quality but with dramatically shorter running times and substantially improved scalability. We also show that the related computational problem bounded-depth min-cost string production (BDMSP), which captures DNA library assembly operations with a simplified cost model, is NP-hard and APX-hard by reduction from vertex cover. The algorithm presented here provides solutions of near-minimal stages and thanks to almost instantaneous planning of DNA libraries it can be used as a metric of ?manufacturability? to guide DNA library design. Rapid planning remains applicable even for DNA library sizes vastly exceeding today's biochemical assembly methods, future-proofing our method. 
Type Of Technology Software 
Year Produced 2014 
Open Source License? Yes  
Impact -- 
URL http://www.dnald.org/planner/ACS_sb-2013-00161v_SI.zip
 
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Year Produced 2012 
Open Source License? Yes  
Impact -- 
URL http://ico2s.org/software/infobiotics.html