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A multiplexed, electrochemical interface for gene-circuit-based sensors

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Peivand Sadat Mousavi at University of Toronto
Peivand Sadat Mousavi
Sarah J. Smith
Sarah J. Smith
Sarah J. Smith
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Jenise Chen at GenMark Diagnostics
Jenise Chen
Margot Karlikow at University of Toronto
Margot Karlikow
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Abstract and Figures

The field of synthetic biology has used the engineered assembly of synthetic gene networks to create a wide range of functions in biological systems. To date, gene-circuit-based sensors have primarily used optical proteins (for example, fluorescent, colorimetric) as reporter outputs, which has limited the potential to measure multiple distinct signals. Here we present an electrochemical interface that permits expanded multiplexed reporting for cell-free gene-circuit-based sensors. We have engineered a scalable system of reporter enzymes that cleave specific DNA sequences in solution, which results in an electrochemical signal when these newly liberated strands are captured at the surface of a nanostructured microelectrode. We describe the development of this interface and show its utility using a ligand-inducible gene circuit and toehold switch-based sensors by demonstrating the detection of multiple antibiotic resistance genes in parallel. This technology has the potential to expand the field of synthetic biology by providing an interface for materials, hardware and software. Gene-circuit-based sensors have, to date, largely relied on optical proteins (such as green fluorescent protein) to report the output, which limits the signalling bandwidth. Now, an electrochemical output has been developed and integrated with cell-free gene circuits. This approach enables multiplexing of sensors and introduces the possibility of electronic-based logic, memory and response elements to synthetic biology.
A gene-circuit/electrode interface for cell-free synthetic gene networks By combining cell-free transcription and translation systems with engineered gene circuits on nanostructured microelectrodes, distinct and multiplexed output signals can be tracked in parallel. This approach uses toehold switch-based RNA sensors, which, in the presence of trigger RNA, express one of ten restriction-enzyme-based reporters. Upon sensor activation, expressed restriction enzymes cleave annealed reporter DNA, which is free floating in cell-free reactions, releasing reporter DNA labelled with the redox reporter (blue circle). Nanostructured microelectrodes with conjugated capture DNA then recruit the redox-active reporter DNA to their surface, generating an electrochemical signal. Each toehold switch is engineered to produce a unique restriction-enzyme-based reporter that is coupled to a distinct reporter DNA and capture DNA pair for multiplexed signalling.
A gene-circuit/electrode interface for cell-free synthetic gene networks By combining cell-free transcription and translation systems with engineered gene circuits on nanostructured microelectrodes, distinct and multiplexed output signals can be tracked in parallel. This approach uses toehold switch-based RNA sensors, which, in the presence of trigger RNA, express one of ten restriction-enzyme-based reporters. Upon sensor activation, expressed restriction enzymes cleave annealed reporter DNA, which is free floating in cell-free reactions, releasing reporter DNA labelled with the redox reporter (blue circle). Nanostructured microelectrodes with conjugated capture DNA then recruit the redox-active reporter DNA to their surface, generating an electrochemical signal. Each toehold switch is engineered to produce a unique restriction-enzyme-based reporter that is coupled to a distinct reporter DNA and capture DNA pair for multiplexed signalling.
… 
Development of orthogonal, restriction-enzyme-based reporters a, Candidate restriction enzymes were evaluated through a four-step screening pipeline designed to find enzymes with high rates of expression and processivity in the cell-free expression system (CFS). Step 1: 37 of 66 commercially available enzymes demonstrated activity in the cell-free (CF) buffer system that replicates the pH, buffer and salt composition found in the complete transcription and translation system. Step 2: 26 of the 37 above restriction enzymes were successfully expressed de novo in the cell-free system (Supplementary Fig. 1). Step 3: 14 of these 26 cell-free expressed enzymes showed high levels of cleavage activity (Supplementary Fig. 2). Step 4: 10 of the 14 enzymes demonstrated high rates of enzyme-mediated cleavage from de novo cell-free expression. b, A summary of the performance of the screened restriction enzymes with the colours matching the categories described in a. c, Representative data of three candidate restriction-enzyme-based reporters in molecular beacon cleavage assays. The data are presented as a percentage of maximum fluorescence for each molecular beacon. Error bars represent the standard error (sample number, N = 3, Supplementary Fig. 3). d, Heat map of the specific enzyme activity. All combinations of restriction enzymes and molecular beacons were tested. The values are the average of three replicates at 180 min.
Development of orthogonal, restriction-enzyme-based reporters a, Candidate restriction enzymes were evaluated through a four-step screening pipeline designed to find enzymes with high rates of expression and processivity in the cell-free expression system (CFS). Step 1: 37 of 66 commercially available enzymes demonstrated activity in the cell-free (CF) buffer system that replicates the pH, buffer and salt composition found in the complete transcription and translation system. Step 2: 26 of the 37 above restriction enzymes were successfully expressed de novo in the cell-free system (Supplementary Fig. 1). Step 3: 14 of these 26 cell-free expressed enzymes showed high levels of cleavage activity (Supplementary Fig. 2). Step 4: 10 of the 14 enzymes demonstrated high rates of enzyme-mediated cleavage from de novo cell-free expression. b, A summary of the performance of the screened restriction enzymes with the colours matching the categories described in a. c, Representative data of three candidate restriction-enzyme-based reporters in molecular beacon cleavage assays. The data are presented as a percentage of maximum fluorescence for each molecular beacon. Error bars represent the standard error (sample number, N = 3, Supplementary Fig. 3). d, Heat map of the specific enzyme activity. All combinations of restriction enzymes and molecular beacons were tested. The values are the average of three replicates at 180 min.
… 
Electrochemical detection of restriction-enzyme reporters a, A schematic of the electrochemical detection chip designed to detect (in triplicate) the reporter DNA generated by five restriction-enzyme-based reporters in parallel. b, Scanning electron microscopy images of the nanostructured microelectrodes. Scale bars, 50 μm. c, In solution, restriction enzymes cleave a reporter–inhibitor DNA duplex. The reporter DNA strand carrying methylene blue (blue circle) is then recruited to the surface of the electrode through duplex formation with conjugated capture DNA, bringing the electrochemical reporter molecule to the electrode surface. d, Representative square-wave voltammetry curves showing the measured current with (black) and without (grey) restriction-enzyme expression. e, On-chip square-wave voltammetry measurements in real time as the restriction enzyme AciI is expressed (Supplementary Fig. 8). For the negative control reactions, DNA coding for the restriction enzyme was not added to the cell-free reaction. f, Fold turn-on of the measured peak current in the presence of restriction enzymes for each of the ten respective reporter-DNA–capture-DNA systems. The data are normalized to the measured current in the absence of DNA encoding each restriction enzyme, represented as a dotted line (Supplementary Fig. 9). g, Electrochemical reporter-DNA–capture-DNA systems were tested to evaluate cross-reactivity between the respective restriction-enzyme reporters. The values on the heat map represent the average current of three replicates at 30 min. h, Using methylated DNA, fold turn-on from the co-expression of five restriction-enzyme reporters in a single solution and measured on a single chip. The data are normalized to the measured current in the absence of DNA encoding each restriction enzyme, represented as a dotted line (Supplementary Fig. 10). The data represent the mean ± s.e.m. of three replicates. All electrochemical measurements were performed with square-wave voltammetry and the peak current was used to calculate the fold turn-on.
Electrochemical detection of restriction-enzyme reporters a, A schematic of the electrochemical detection chip designed to detect (in triplicate) the reporter DNA generated by five restriction-enzyme-based reporters in parallel. b, Scanning electron microscopy images of the nanostructured microelectrodes. Scale bars, 50 μm. c, In solution, restriction enzymes cleave a reporter–inhibitor DNA duplex. The reporter DNA strand carrying methylene blue (blue circle) is then recruited to the surface of the electrode through duplex formation with conjugated capture DNA, bringing the electrochemical reporter molecule to the electrode surface. d, Representative square-wave voltammetry curves showing the measured current with (black) and without (grey) restriction-enzyme expression. e, On-chip square-wave voltammetry measurements in real time as the restriction enzyme AciI is expressed (Supplementary Fig. 8). For the negative control reactions, DNA coding for the restriction enzyme was not added to the cell-free reaction. f, Fold turn-on of the measured peak current in the presence of restriction enzymes for each of the ten respective reporter-DNA–capture-DNA systems. The data are normalized to the measured current in the absence of DNA encoding each restriction enzyme, represented as a dotted line (Supplementary Fig. 9). g, Electrochemical reporter-DNA–capture-DNA systems were tested to evaluate cross-reactivity between the respective restriction-enzyme reporters. The values on the heat map represent the average current of three replicates at 30 min. h, Using methylated DNA, fold turn-on from the co-expression of five restriction-enzyme reporters in a single solution and measured on a single chip. The data are normalized to the measured current in the absence of DNA encoding each restriction enzyme, represented as a dotted line (Supplementary Fig. 10). The data represent the mean ± s.e.m. of three replicates. All electrochemical measurements were performed with square-wave voltammetry and the peak current was used to calculate the fold turn-on.
… 
Application of the gene-circuit/electrochemical interface for small-molecule- and RNA-actuated electrochemical signalling a, Anhydrotetracycline (ATc)-mediated de-repression of TetR-regulated TetO expression of the restriction-enzyme-based reporter AciI (left). ATc-dependent induction (40 µM) of electrochemical signalling on-chip (right). The data represent the mean ± s.e.m. of three replicates. b, Toehold switches (S1–6) specific to synthetic RNA sequences (T1–6) were designed to control the expression of six different restriction-enzyme-based reporters. RNA-dependent activation of toehold switches induces electrochemical signalling. The dotted line indicates negative controls containing only the switch. All electrochemical measurements were performed with square-wave voltammetry and the peak current was used to calculate the fold turn-on. The data represent the mean ± s.e.m. of three replicates.
Application of the gene-circuit/electrochemical interface for small-molecule- and RNA-actuated electrochemical signalling a, Anhydrotetracycline (ATc)-mediated de-repression of TetR-regulated TetO expression of the restriction-enzyme-based reporter AciI (left). ATc-dependent induction (40 µM) of electrochemical signalling on-chip (right). The data represent the mean ± s.e.m. of three replicates. b, Toehold switches (S1–6) specific to synthetic RNA sequences (T1–6) were designed to control the expression of six different restriction-enzyme-based reporters. RNA-dependent activation of toehold switches induces electrochemical signalling. The dotted line indicates negative controls containing only the switch. All electrochemical measurements were performed with square-wave voltammetry and the peak current was used to calculate the fold turn-on. The data represent the mean ± s.e.m. of three replicates.
… 
Detection of mcr genes a, Toehold switch-based RNA sensors were designed and screened for the detection of four mcr genes. Five separate electrochemical experiments were performed in the presence of all components except the corresponding mcr-specific trigger RNA(s). The first four experiments (samples A–D) tested the detection of single mcr-related RNAs (1 nM) based on the electrochemical response (sample A: mcr-3 RNA trigger, sample B: mcr-1 RNA trigger, sample C: mcr-4 trigger, sample D: mcr-2 trigger). Sample E tested the co-detection of mcr-3 and mcr-4 RNA triggers (1 nM each) in parallel (for standard error data, see Supplementary Fig. 16). The data are normalized to the measured current in the absence of trigger RNA (5 μM). The graphs represent the peak current for methylene blue measured using square-wave voltammetry. The data represent the mean ± s.e.m. of three replicates. b, Workflow for the detection of mcr-4 RNA from a complex sample. c, On-chip electrochemical signalling from the activation of mcr-4_ClaI in the presence of mcr-4 RNA from complex whole-cell RNA samples isolated from E. coli. Tested with a combination of inputs, the real-time signal was only detected in the presence of mcr-4 RNA and isothermal amplification. Cellular RNA was isolated from DH5α E. coli cells in the presence or absence of a plasmid expressing mcr-4. All electrochemical measurements were performed with square-wave voltammetry and the peak current was used to calculate the fold turn-on. Switch: mcr-4_ClaI; Amp: NASBA with (+) or without (−) primers. The data represent the mean ± s.e.m. of three replicates.
Detection of mcr genes a, Toehold switch-based RNA sensors were designed and screened for the detection of four mcr genes. Five separate electrochemical experiments were performed in the presence of all components except the corresponding mcr-specific trigger RNA(s). The first four experiments (samples A–D) tested the detection of single mcr-related RNAs (1 nM) based on the electrochemical response (sample A: mcr-3 RNA trigger, sample B: mcr-1 RNA trigger, sample C: mcr-4 trigger, sample D: mcr-2 trigger). Sample E tested the co-detection of mcr-3 and mcr-4 RNA triggers (1 nM each) in parallel (for standard error data, see Supplementary Fig. 16). The data are normalized to the measured current in the absence of trigger RNA (5 μM). The graphs represent the peak current for methylene blue measured using square-wave voltammetry. The data represent the mean ± s.e.m. of three replicates. b, Workflow for the detection of mcr-4 RNA from a complex sample. c, On-chip electrochemical signalling from the activation of mcr-4_ClaI in the presence of mcr-4 RNA from complex whole-cell RNA samples isolated from E. coli. Tested with a combination of inputs, the real-time signal was only detected in the presence of mcr-4 RNA and isothermal amplification. Cellular RNA was isolated from DH5α E. coli cells in the presence or absence of a plasmid expressing mcr-4. All electrochemical measurements were performed with square-wave voltammetry and the peak current was used to calculate the fold turn-on. Switch: mcr-4_ClaI; Amp: NASBA with (+) or without (−) primers. The data represent the mean ± s.e.m. of three replicates.
… 
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Articles
https://doi.org/10.1038/s41557-019-0366-y
1Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada. 2Department of Chemistry, Bucknell University, Lewisburg, PA, USA.
3Department of Chemistry, University of Toronto, Toronto, Ontario, Canada. 4Institute of Biomaterials and Biomedical Engineering, University of Toronto,
Toronto, Ontario, Canada. 5Biodesign Center for Molecular Design and Biomimetics, The Biodesign Institute and the School of Molecular Sciences,
Arizona State University, Tempe, AZ, USA. 6These authors contributed equally: Peivand Sadat Mousavi, Sarah J. Smith, Jenise B. Chen.
*e-mail: shana.kelley@utoronto.ca; keith.pardee@utoronto.ca
The field of synthetic biology uses genetically encoded tools to
create biological systems with new functions1,2. Work to date
has generated organisms with engineered metabolic path-
ways for bioproduction3,4, embedded synthetic logic and memory5–7
and the capacity to sense and respond8,9. Despite being poised to
revolutionize many aspects of modern life, this cell-based approach
requires that all processes be laboriously encoded within a living
organism10 and introduces significant complexity into the appli-
cation of synthetic biology, including limits to the distribution of
these tools over concerns for biosafety. Recent efforts have aimed
to tackle this long-standing challenge by creating cell-free synthetic
biology applications that use the enzymes of transcription and trans-
lation11–13 to provide a biosafe format for applications ranging from
point-of-care diagnostics to biomanufacturing to classroom edu-
cation14–20. Cell-free systems are particularly advantageous as they
can be freeze-dried for distribution without refrigeration, and so
the central motivation for many of these projects has been to pro-
vide portable diagnostics or sensors for global health, agriculture,
national security and other applications that would benefit from
sensing outside of laboratory settings. Sensors used in these and con-
ventional synthetic biology studies have relied on the expression of
optical reporter proteins (for example, colourimetric, fluorescence),
which, although successful, generally provide the capacity for one,
or at most two or three, reporter signals from a single reaction.
Here we describe a direct gene-circuit/electrode interface that
allows for the output from engineered, cell-free gene circuits to be
transformed into a signal that can be detected electrochemically.
Electrochemical methods have previously been developed to detect
nucleic acids21–25, small molecules26–29 and proteins30,31 with high
sensitivity and specificity. However, by amalgamating program-
mable gene-circuit-based sensors with electrochemical detection,
we have created a biohybrid system that is adaptive, broadly capable
and has the potential to allow 5–10 multiplexed sensors to oper-
ate with parallel but distinct signals. Importantly, this approach can
be adapted to retrofit other gene-circuit-based sensors by simply
swapping the respective reporter proteins. We envision that elec-
trochemical interfaces will enable multiplexed gene-circuit-based
portable diagnostics and, more broadly, will foster greater interac-
tion between synthetic biology and electronic device development.
Using DNA-functionalized nanostructured microelectrodes
as electrochemical detectors26,32, the activation of gene circuits is
linked to specifically paired electrodes through the expression of
orthogonal reporters (Fig. 1). Sequence-specific and scalable, this
approach uses the production of restriction-enzyme-based report-
ers to catalyse the release of reporter DNA (single-stranded DNA,
ssDNA, labelled with methylene blue), which in turn interacts with
capture DNA (complementary ssDNA) conjugated to the electrode
surface. Upon hybridization of reporter DNA with capture DNA,
methylene blue, a redox reporter molecule, is brought in close
proximity to the electrode surface, leading to a large increase in
the measured current at that electrode22,27. It is this conversion of
gene-circuit-based sensor activation into sequence-specific DNA
interactions that enables distinct and multiplexed signals to oper-
ate without crosstalk. Here we demonstrate the power of this new
electrochemical interface by detecting the activation of rationally
designed toehold switch-based RNA sensors, a small-molecule
actuated synthetic gene network, and demonstrate the multiplexed
detection of colistin antibiotic resistance genes.
Results and discussion
Screening for high-performing restriction-enzyme-based reporters.
The creation of this electrochemical approach to gene-circuit-based
A multiplexed, electrochemical interface for
gene-circuit-based sensors
Peivand Sadat Mousavi 1,6, Sarah J. Smith 1,2,6, Jenise B. Chen3,6, Margot Karlikow1, Aidan Tinafar1,
Clare Robinson1, Wenhan Liu4, Duo Ma5, Alexander A. Green 5, Shana O. Kelley 1,3,4* and
Keith Pardee 1*
The field of synthetic biology has used the engineered assembly of synthetic gene networks to create a wide range of functions
in biological systems. To date, gene-circuit-based sensors have primarily used optical proteins (for example, fluorescent, colo-
rimetric) as reporter outputs, which has limited the potential to measure multiple distinct signals. Here we present an electro-
chemical interface that permits expanded multiplexed reporting for cell-free gene-circuit-based sensors. We have engineered
a scalable system of reporter enzymes that cleave specific DNA sequences in solution, which results in an electrochemical
signal when these newly liberated strands are captured at the surface of a nanostructured microelectrode. We describe the
development of this interface and show its utility using a ligand-inducible gene circuit and toehold switch-based sensors by
demonstrating the detection of multiple antibiotic resistance genes in parallel. This technology has the potential to expand the
field of synthetic biology by providing an interface for materials, hardware and software.
NATURE CHEMISTRY | VOL 12 | JANUARY 2020 | 48–55 | www.nature.com/naturechemistry
48
Content courtesy of Springer Nature, terms of use apply. Rights reserved
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Microbiota-modulating interventions are an emerging strategy to promote gastrointestinal homeostasis. Yet, their use in the detection, prevention, and treatment of acute infections remains underexplored. We report the basis of a probiotic-based strategy to promote colonization resistance and point-of-need diagnosis of cholera, an acute diarrheal disease caused by the pathogen Vibrio cholerae Oral administration of Lactococcus lactis, a common dietary fermentative bacterium, reduced intestinal V. cholerae burden and improved survival in infected infant mice through the production of lactic acid. Furthermore, we engineered an L. lactis strain that specifically detects quorum-sensing signals of V. cholerae in the gut and triggers expression of an enzymatic reporter that is readily detected in fecal samples. We postulate that preventive dietary interventions with fermented foods containing natural and engineered L. lactis strains may hinder cholera progression and improve disease surveillance in populations at risk of cholera outbreaks.
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Molecular detection of colistin resistance genes (mcr-1, mcr-2 and mcr-3) in nasal/oropharyngeal and anal/cloacal swabs from pigs and poultry
Article
Full-text available
  • Feb 2018
Antimicrobial resistance against colistin has emerged worldwide and is threatening the efficacy of colistin treatment of multi-resistant Gram-negative bacteria. In this study, PCRs were used to detect mcr genes (mcr-1, mcr-2, mcr-3) in 213 anal and 1,339 nasal swabs from pigs (n = 1,454) in nine provinces of China, and 1,696 cloacal and 1,647 oropharyngeal samples from poultry (n = 1,836) at live-bird markets in 24 provinces. The mcr-1 prevalences in pigs (79.2%) and geese (71.7%) were significantly higher than in chickens (31.8%), ducks (34.6%) and pigeons (13.1%). The mcr-2 prevalence in pigs was 56.3%, significantly higher than in chickens (5.5%), ducks (2.3%), geese (5.5%) and pigeons (0%). The mcr-3 prevalences in pigs (18.7%), ducks (13.8%) and geese (11.9%) were significantly higher than in chickens (5.2%) and pigeons (5.1%). In total, 173 pigs and three chickens were positive for all three mcr genes. The prevalences of the mcr were significantly higher in nasal/oropharyngeal swabs than in the anal /cloacal swabs. Phylogenetic studies identified 33 new mcr-2 variants and 12 new mcr-3 variants. This study demonstrates high prevalences of mcr in pigs and poultry in China, and indicates there is need for more thorough surveillance and control programs to prevent further selection of colistin resistance.
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A Cell-Free Biosensor for Detecting Quorum Sensing Molecules in P. aeruginosa -Infected Respiratory Samples
Article
Full-text available
  • Oct 2017
Synthetic biology designed cell-free biosensors are a promising new tool for the detection of clinically relevant biomarkers in infectious diseases. Here, we report that a modular DNA-encoded biosensor in cell-free protein expression systems can be used to measure a bacterial biomarker of Pseudomonas aeruginosa infection from human sputum samples. By optimizing the cell-free system and sample extraction, we demonstrate that the quorum sensing molecule 3-oxo-C12-HSL in sputum samples from cystic fibrosis lungs can be quantitatively measured at nanomolar levels using our cell-free biosensor system, and is comparable to LC–MS measurements of the same samples. This study further illustrates the potential of modular cell-free biosensors as rapid, low-cost detection assays that can inform clinical practice.
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Co-occurrence of mcr-1, mcr-4 and mcr-5 genes in multidrug-resistant ST10 Enterotoxigenic and Shiga toxin-producing Escherichia coli in Spain (2006-2017)
Article
  • Apr 2018
  • INT J ANTIMICROB AG
Colistin is an antimicrobial polypeptide commonly employed for controlling and treating neonatal and post-weaning diarrhoea (PWD) diseases caused by Enterotoxigenic and Shiga toxin-producing Escherichia coli (ETEC and STEC). Plasmid-mediated colistin resistance gene, mcr-1, was described in late 2015, and since then multiple studies have reported its global distribution. In addition, five different mcr genes were identified. The aim of this study was to characterize the colistin-resistant E. coli clonal groups implicated in PWD in farms of intensive pig production. Of 186 ETEC and STEC isolated in Spain (2006-2017), 76.9% showed resistance to colistin. From those, 102 were mcr-4 carriers, 37 mcr-1 and 5 mcr-5, with co-occurrence of mcr-1/mcr-4, mcr-1/mcr-5 and mcr-4/mcr-5 in five isolates. Three different mcr-4 variants were detected, including the new mcr-4.4 and mcr-4.5 described here. Interestingly, the clonal group ST10-A (CH11-24) shows to be primarily responsible for the spreading of mcr-4. In summary, our results show that the pig industry is an important reservoir of colistin-resistant E. coli, carriers of other additional risk genes such as blaESBL. These food-production animals might be spreading a cocktail of multiple resistances, posing a worrisome threat to the human health.
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Programming gene and engineered-cell therapies with synthetic biology
Article
  • Feb 2018
Toward programmed therapeutics Advances in synthetic biology are enabling the development of new gene and cell therapies. Kitada et al. review recent successes in areas such as cancer immunotherapy and stem cell therapy, point out the limitations of current approaches, and describe prospects for using synthetic biology to overcome these challenges. Broader adoption of these therapies requires precise, context-specific control over cellular behavior. Gene circuits can be built to give sophisticated control over cellular behaviors so that therapeutic functions can, for example, be programmed to activate in response to disease biomarkers. Science , this issue p. eaad1067
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Scaling Computation and Memory in Living Cells
Article
  • Oct 2017
The semiconductor revolution that began in the 20th century has transformed society. Key to this revolution has been the integrated circuit, which enabled exponential scaling of computing devices using silicon-based transistors over many decades. Analogously, decreasing costs in DNA sequencing and synthesis, along with the development of robust genetic circuits, are enabling a “biocomputing revolution”. First-generation gene circuits largely relied on assembling various transcriptional regulatory elements to execute digital and analog computing functions in living cells. Basic design rules and computational tools have since been derived so that such circuits can be scaled in order to implement complex computations. In the past five years, great strides have been made in expanding the biological programming toolkit to include recombinase- and CRISPR–based gene circuits that execute complex cellular logic and memory. Recent advances have enabled increasingly dense computing and memory circuits to function in living cells while expanding the application of these circuits from bacteria to eukaryotes, including human cells, for a wide range of uses.
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Complex cellular logic computation using ribocomputing devices
Article
  • Jul 2017
Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedback, and logic capabilities. However, it remains challenging to scale up these circuits owing to the limited number of designable, orthogonal, high-performance parts, the empirical and often tedious composition rules, and the requirements for substantial resources for encoding and operation. Here, we report a strategy for constructing RNA-only nanodevices to evaluate complex logic in living cells. Our 'ribocomputing' systems are composed of de-novo-designed parts and operate through predictable and designable base-pairing rules, allowing the effective in silico design of computing devices with prescribed configurations and functions in complex cellular environments. These devices operate at the post-transcriptional level and use an extended RNA transcript to co-localize all circuit sensing, computation, signal transduction, and output elements in the same self-assembled molecular complex, which reduces diffusion-mediated signal losses, lowers metabolic cost, and improves circuit reliability. We demonstrate that ribocomputing devices in Escherichia coli can evaluate two-input logic with a dynamic range up to 900-fold and scale them to four-input AND, six-input OR, and a complex 12-input expression (A1 AND A2 AND NOT A1*) OR (B1 AND B2 AND NOT B2*) OR (C1 AND C2) OR (D1 AND D2) OR (E1 AND E2). Successful operation of ribocomputing devices based on programmable RNA interactions suggests that systems employing the same design principles could be implemented in other host organisms or in extracellular settings.
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