Field-programmable biological circuits and configurable (bio)logic blocks for distributed biological computing.

Biological wires Configurable (bio)logic blocks Distributed computation Field-programmable biological circuits Memory Multiplexer

Journal

Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250

Informations de publication

Date de publication:
01 2021
Historique:
received: 31 08 2020
revised: 28 10 2020
accepted: 05 11 2020
pubmed: 23 11 2020
medline: 22 6 2021
entrez: 22 11 2020
Statut: ppublish

Résumé

Synthetic biology applications often require engineered computing structures, which can be programmed to process the information in a given way. However, programming of these structures usually requires significant amount of trial-and-error genetic engineering. This process is to some degree analogous to the design of application-specific integrated circuits (ASIC) in the domain of digital electronic circuits, which often require complex and time-consuming workflows to obtain a desired response. We describe a design of programmable biological circuits that can be configured without additional genetic engineering. Their configuration can be changed in vivo, i.e. during the execution of their biological program, simply with an introduction of programming inputs. These, e.g., increase the degradation rates of selected proteins that store the current configuration of the circuit. Programming can be thus performed in the field as in the case of field-programmable gate array (FPGA) circuits, which present an attractive alternative of ASICs in digital electronics. We describe a basic programmable unit, which we denote configurable (bio)logical block (CBLB) inspired by the architecture of configurable logic blocks (CLBs), basic functional units within the FPGA circuits. The design of a CBLB is based on distributed cellular computing modules, which makes its biological implementation easier to achieve. We establish a computational model of a CBLB and analyse its response with a given set of biologically feasible parameter values. Furthermore, we show that the proposed CBLB design exhibits correct behaviour for a vast range of kinetic parameter values, different population ratios, and as well preserves this response in stochastic simulations.

Identifiants

pubmed: 33221638
pii: S0010-4825(20)30440-6
doi: 10.1016/j.compbiomed.2020.104109
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

104109

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Auteurs

Miha Moškon (M)

Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia. Electronic address: miha.moskon@fri.uni-lj.si.

Žiga Pušnik (Ž)

Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.

Nikolaj Zimic (N)

Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.

Miha Mraz (M)

Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.

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Classifications MeSH