Multiplexing and demultiplexing logic functions for computing signal processing tasks in synthetic biology

Lorenzo Pasotti, Mattia Quattrocelli, Daniela Galli, Maria Gabriella Cusella De Angelis, Paolo Magni*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


Building biological devices to perform computational and signal processing tasks is one of the main research issues in synthetic biology. Herein, two modular biological systems that could mimic multiplexing and demultiplexing logic functions are proposed and discussed. These devices, called multiplexer (mux) and demultiplexer (demux), respectively, have a remarkable importance in electronic, telecommunication, and signal processing systems and, similarly, they could play a crucial role if implemented in a living organism, such as Escherichia coli. BioBrick standard parts were used to design mux and demux and to construct two genetic circuits that could carry out the desired tasks. A modular approach, mimicking basic logic gates (AND, OR, and NOT) with protein/autoinducer or protein/DNA interactions and interconnecting them to create the final circuits, was adopted. A mathematical model of the designed gene networks was been defined and simulations performed to validate the expected behavior of the systems. In addition, circuit subparts were tested in vivo and the results used to determine some of the parameters of the mathematical model. According to both the experimental and simulated results, guidelines for future finalization of mux and demux are provided.

Original languageEnglish (US)
Pages (from-to)784-795
Number of pages12
JournalBiotechnology Journal
Issue number7
StatePublished - Jul 2011


  • BioBricks
  • In vivo signal processing
  • Mathematical modeling of gene networks
  • Multiplexing
  • Quorum sensing

ASJC Scopus subject areas

  • Applied Microbiology and Biotechnology
  • Molecular Medicine


Dive into the research topics of 'Multiplexing and demultiplexing logic functions for computing signal processing tasks in synthetic biology'. Together they form a unique fingerprint.

Cite this