Abstract
Real-time chemical sensing is crucial for applications in environmental and health monitoring1. Biosensors can detect a variety of molecules through genetic circuits that use these chemicals to trigger the synthesis of a coloured protein, thereby producing an optical signal2,3,4. However, the process of protein expression limits the speed of this sensing to approximately half an hour, and optical signals are often difficult to detect in situ5,6,7,8. Here we combine synthetic biology and materials engineering to develop biosensors that produce electrical readouts and have detection times of minutes. We programmed Escherichia coli to produce an electrical current in response to specific chemicals using a modular, eight-component, synthetic electron transport chain. As designed, this strain produced current following exposure to thiosulfate, an anion that causes microbial blooms, within 2 min. This amperometric sensor was then modified to detect an endocrine disruptor. The incorporation of a protein switch into the synthetic pathway and encapsulation of the bacteria with conductive nanomaterials enabled the detection of the endocrine disruptor in urban waterway samples within 3 min. Our results provide design rules to sense various chemicals with mass-transport-limited detection times and a new platform for miniature, low-power bioelectronic sensors that safeguard ecological and human health.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 51 print issues and online access
$199.00 per year
only $3.90 per issue
Rent or buy this article
Get just this article for as long as you need it
$39.95
Prices may be subject to local taxes which are calculated during checkout
Data availability
All data generated or analysed during this study are included in this published article and its Supplementary Information. Source data are provided with this paper.
References
Schwarzenbach, R. P. et al. The challenge of micropollutants in aquatic systems. Science 313, 1072–1077 (2006).
Jung, J. K. et al. Cell-free biosensors for rapid detection of water contaminants. Nat. Biotechnol. 38, 1451–1459 (2020).
Bereza-Malcolm, L. T., Mann, G. & Franks, A. E. Environmental sensing of heavy metals through whole cell microbial biosensors: a synthetic biology approach. ACS Synth. Biol. 4, 535–546 (2015).
Del Valle, I. et al. Translating new synthetic biology advances for biosensing into the earth and environmental sciences. Front. Microbiol. 11, 618373 (2020).
Golitsch, F., Bücking, C. & Gescher, J. Proof of principle for an engineered microbial biosensor based on Shewanella oneidensis outer membrane protein complexes. Biosens. Bioelectron. 47, 285–291 (2013).
Webster, D. P. et al. An arsenic-specific biosensor with genetically engineered Shewanella oneidensis in a bioelectrochemical system. Biosens. Bioelectron. 62, 320–324 (2014).
Ueki, T., Nevin, K. P., Woodard, T. L. & Lovley, D. R. Genetic switches and related tools for controlling gene expression and electrical outputs of Geobacter sulfurreducens. J. Ind. Microbiol. Biotechnol. 43, 1561–1575 (2016).
West, E. A., Jain, A. & Gralnick, J. A. Engineering a native inducible expression system in Shewanella oneidensis to control extracellular electron transfer. ACS Synth. Biol. 6, 1627–1634 (2017).
Ryon, M. G., Stewart, A. J., Kszos, L. A. & Phipps, T. L. Impacts on streams from the use of sulfur-based compounds for dechlorinating industrial effluents. Water Air Soil Pollut. 136, 255–268 (2002).
Kidd, K. A. et al. Collapse of a fish population after exposure to a synthetic estrogen. Proc. Natl Acad. Sci. USA 104, 8897–8901 (2007).
Rice, J. & Westerhoff, P. High levels of endocrine pollutants in US streams during low flow due to insufficient wastewater dilution. Nat. Geosci. 10, 587–591 (2017).
Zhou, A. Y., Baruch, M., Ajo-Franklin, C. M. & Maharbiz, M. M. A portable bioelectronic sensing system (BESSY) for environmental deployment incorporating differential microbial sensing in miniaturized reactors. PLoS ONE 12, e0184994 (2017).
Brooks, S. M. & Alper, H. S. Applications, challenges, and needs for employing synthetic biology beyond the lab. Nat. Commun. 12, 1390 (2021).
Kabessa, Y. et al. Standoff detection of explosives and buried landmines using fluorescent bacterial sensor cells. Biosens. Bioelectron. 79, 784–788 (2016).
Tang, T.-C. et al. Hydrogel-based biocontainment of bacteria for continuous sensing and computation. Nat. Chem. Biol. 17, 724–731 (2021).
Zhao, S. et al. A new design for living cell-based biosensors: microgels with a selectively permeable shell that can harbor bacterial species. Sens. Actuators B Chem. 334, 129648 (2021).
Liu, X. et al. Stretchable living materials and devices with hydrogel-elastomer hybrids hosting programmed cells. Proc. Natl Acad. Sci. USA 114, 2200–2205 (2017).
Bretschger, O. et al. Current production and metal oxide reduction by Shewanella oneidensis MR-1 wild type and mutants. Appl. Environ. Microbiol. 73, 7003–7012 (2007).
Jensen, H. M., TerAvest, M. A., Kokish, M. G. & Ajo-Franklin, C. M. CymA and exogenous flavins improve extracellular electron transfer and couple it to cell growth in Mtr-expressing Escherichia coli. ACS Synth. Biol. 5, 679–688 (2016).
Goldbeck, C. P. et al. Tuning promoter strengths for improved synthesis and function of electron conduits in Escherichia coli. ACS Synth. Biol. 2, 150–159 (2013).
Atkinson, J. T. et al. Metalloprotein switches that display chemical-dependent electron transfer in cells. Nat. Chem. Biol. 15, 189–195 (2019).
Barstow, B. et al. A synthetic system links FeFe-hydrogenases to essential E. coli sulfur metabolism. J. Biol. Eng. 5, 7 (2011).
Yuan, S.-J. et al. A photometric high-throughput method for identification of electrochemically active bacteria using a WO3 nanocluster probe. Sci. Rep. 3, 1315 (2013).
Su, L. et al. Modifying cytochrome c maturation can increase the bioelectronic performance of engineered Escherichia coli. ACS Synth. Biol. 9, 115–124 (2020).
Shibata, H. & Kobayashi, S. Sulfide oxidation in gram-negative bacteria by expression of the sulfide-quinone reductase gene of Rhodobacter capsulatus and by electron transport to ubiquinone. Can. J. Microbiol. 47, 855–860 (2001).
Shibata, H., Suzuki, K. & Kobayashi, S. Menaquinone reduction by an HMT2-like sulfide dehydrogenase from Bacillus stearothermophilus. Can. J. Microbiol. 53, 1091–1100 (2007).
Liu, H. et al. Synthetic gene circuits enable Escherichia coli to use endogenous H2S as a signaling molecule for quorum sensing. ACS Synth. Biol. 8, 2113–2120 (2019).
Cosnefroy, A. et al. A stable fish reporter cell line to study estrogen receptor transactivation by environmental (xeno)estrogens. Toxicol. in Vitro 23, 1450–1454 (2009).
Wu, B., Atkinson, J. T., Kahanda, D., Bennett, G. N. & Silberg, J. J. Combinatorial design of chemical‐dependent protein switches for controlling intracellular electron transfer. AIChE J. 66, e16796 (2020).
Mimee, M. et al. An ingestible bacterial–electronic system to monitor gastrointestinal health. Science 360, 915–918 (2018).
VanArsdale, E. et al. Redox-based synthetic biology enables electrochemical detection of the herbicides dicamba and Roundup via rewired Escherichia coli. ACS Sens. 4, 1180–1184 (2019).
VanArsdale, E. et al. A coculture based tyrosine-tyrosinase electrochemical gene circuit for connecting cellular communication with electronic networks. ACS Synth. Biol. 9, 1117–1128 (2020).
Su, L., Yin, T., Du, H., Zhang, W. & Fu, D. Synergistic improvement of Shewanella loihica PV-4 extracellular electron transfer using a TiO2@TiN nanocomposite. Bioelectrochemistry 134, 107519 (2020).
Terrell, J. L. et al. Bioelectronic control of a microbial community using surface-assembled electrogenetic cells to route signals. Nat. Nanotechnol. 16, 688–697 (2021).
Gordley, R. M. et al. Engineering dynamical control of cell fate switching using synthetic phospho-regulons. Proc. Natl Acad. Sci. USA 113, 13528–13533 (2016).
Gao, X. J., Chong, L. S., Kim, M. S. & Elowitz, M. B. Programmable protein circuits in living cells. Science 361, 1252–1258 (2018).
Smith, D. A., Sessions, A. L., Dawson, K. S., Dalleska, N. & Orphan, V. J. Rapid quantification and isotopic analysis of dissolved sulfur species. Rapid Commun. Mass Spectrom. 31, 791–803 (2017).
Bobin-Dubigeon, C. et al. New UPLC–MS/MS assay for the determination of tamoxifen and its metabolites in human plasma, application to patients. Future Sci. OA 5, FSO374 (2019).
Monteiro, T. & Almeida, M. G. Electrochemical enzyme biosensors revisited: old solutions for new problems. Crit. Rev. Anal. Chem. 49, 44–66 (2019).
Reimers, C. E., Tender, L. M., Fertig, S. & Wang, W. Harvesting energy from the marine sediment−water interface. Environ. Sci. Technol. 35, 192–195 (2001).
Esri. Community Map https://www.arcgis.com/home/item.html?id=e64f06e8d912465a96f9ea9bfdb72676 (accessed 21 April 2021).
Pinske, C., Bönn, M., Krüger, S., Lindenstrauss, U. & Sawers, R. G. Metabolic deficiences revealed in the biotechnologically important model bacterium Escherichia coli BL21(DE3). PLoS ONE 6, e22830 (2011).
Spiro, S. & Guest, J. R. Adaptive responses to oxygen limitation in Escherichia coli. Trends Biochem. Sci. 16, 310–314 (1991).
Monk, J. M. et al. Multi-omics quantification of species variation of Escherichia coli links molecular features with strain phenotypes. Cell Syst. 3, 238–251.e12 (2016).
Kim, H., Kim, S. & Yoon, S. H. Metabolic network reconstruction and phenome analysis of the industrial microbe, Escherichia coli BL21(DE3). PLoS ONE 13, e0204375 (2018).
Sauer, U., Canonaco, F., Heri, S., Perrenoud, A. & Fischer, E. The soluble and membrane-bound transhydrogenases UdhA and PntAB have divergent functions in NADPH metabolism of Escherichia coli. J. Biol. Chem. 279, 6613–6619 (2004).
Fan, J. et al. Quantitative flux analysis reveals folate-dependent NADPH production. Nature 510, 298–302 (2014).
Engler, C., Kandzia, R. & Marillonnet, S. A one pot, one step, precision cloning method with high throughput capability. PLoS ONE 3, e3647 (2008).
Gibson, D. G. et al. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat. Methods 6, 343–345 (2009).
Torella, J. P. et al. Unique nucleotide sequence-guided assembly of repetitive DNA parts for synthetic biology applications. Nat. Protoc. 9, 2075–2089 (2014).
Bassalo, M. C. et al. Rapid and efficient one-step metabolic pathway integration in E. coli. ACS Synth. Biol. 5, 561–568 (2016).
Datta, S., Costantino, N. & Court, D. L. A set of recombineering plasmids for gram-negative bacteria. Gene 379, 109–115 (2006).
Zhang, Y. & Weiner, J. H. A simple semi-quantitative in vivo method using H2S detection to monitor sulfide metabolizing enzymes. Biotechniques 57, 208–210 (2014).
Fatin-Rouge, N., Starchev, K. & Buffle, J. Size effects on diffusion processes within agarose gels. Biophys. J. 86, 2710–2719 (2004).
Acknowledgements
E. coli EW11 and the genes encoding FNR and SIR were a gift from P. Silver (Harvard University). pSIM19 was a gift from D. Court (NIH-National Cancer Institute). pSS9 (Addgene, plasmid 71655), pSS9-RNA (Addgene, plasmid 71656) and pX2-Cas9 (Addgene, plasmid 8581) were gifts from R. Gill (University of Colorado). We thank S. Li (Rice University) for help with water sampling; X. Chen and C. Masiello (Rice University) with help with TOC measurements; H. Du and D. Fu (Southeast University) with help with TiO2@TiN nanocomposite synthesis; J. Soman (Rice University) for internal reviewing and providing writing suggestions; and M. Baruch (Rice University) for helping to conceptualize the project. Funding was from the Office of Science, Office of Basic Energy Sciences of the US Department of Energy grants DE-SC0014462 (to J.J.S. and G.N.B.); Office of Naval Research grants 0001418IP00037 (to C.M.A.-F.), N00014-17-1-2639 (to J.J.S.) and N00014-20-1-2274 (to C.M.A.-F. and J.J.S.); Cancer Prevention and Research Institute of Texas RR190063 (to C.M.A.-F.); National Science Foundation grant 1843556 (to J.J.S. and G.N.B.); Department of Energy Office of Science Graduate Student Research (SCGSR) Program Fellowship DE‐SC0014664 (to J.T.A.); Loideska Stockbridge Vaughn Fellowship (to J.T.A.); and China Scholarship Council Fellowship CSC-201606090098 (to L.S.). Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the US Department of Energy under contract number DE-AC02-05CH11231.
Author information
Authors and Affiliations
Contributions
J.T.A., L.S., C.M.A.-F. and J.J.S. conceptualized the project. J.T.A. performed all molecular biology and genome engineering. J.T.A. and L.S. performed assays to verify the functions of the modules. L.S. and X.Z. developed the cell encapsulation protocol, performed the bioelectrochemical analysis of thiosulfate and 4-HT sensing, and performed water sampling. L.S. synthesized the WO3 and TiO2@TiN nanomaterials. X.Z. and C.M.A.-F. performed diffusion modelling. J.T.A., L.S. and X.Z. analysed and visualized all the data and made the schematic diagrams. J.T.A., L.S., X.Z., J.J.S. and C.M.A.-F. wrote the manuscript. All authors reviewed and edited the manuscript.
Corresponding authors
Ethics declarations
Competing interests
J.J.S., J.T.A. and G.N.B. have submitted a patent application (number 16/186,226) covering the use of fragmented proteins as chemical-dependent electron carriers, entitled ‘Regulating electron flow using fragmented proteins’. L.S., X.Z. and C.M.A.-F. declare no competing interests.
Peer review
Peer review information
Nature thanks Luying Xun and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Extended Data Fig. 1 Impact of sulfur source on sulfide evolution from E. coli EW11.
(A) A schematic of sulfur metabolism and regulation in E. coli (yellow) and the redox coupling of the Input module (blue) with this pathway. (B) PbS accumulation and (C) optical density of the I+C−O− strain containing a vector for expressing Fd after 24 h in M9sa medium containing 2 mM of sulfate, sulfite, or thiosulfate and varying amounts of aTc to control Fd expression. The optical density in sulfate and sulfite containing media were significantly lower than thiosulfate containing media when < 7.81 nM aTc was added (p = 8.47 × 10−5 for 3.91 nM aTc with sulfate, p = 6.98 x 10−8 for 0 nM aTc with sulfate, p = 1.70 × 10−4 for for 3.91 nM aTc with sulfite, p = 7.16 x 10−8) for 0 nM aTc with sulfite. (D) PbS accumulation and (E) optical density after 24 h in M9sa medium containing varying amounts of thiosulfate and varying amounts of aTc to control Fd expression. In media with ≥ 0.25 mM thiosulfate, optical densities were not significantly different in the presence of aTc (p > 0.01 for all concentrations). For panels B-E, symbols and error bars represent the mean and standard deviation, respectively (n = 3 biologically independent samples). P-values were obtained using two-tailed, independent t-tests.
Extended Data Fig. 2 Effect of Output module expression on cytochrome levels.
(A) Red color intensity values of IC42AC−O+ (circle) or IC42AC−O− (square) cell pellets following aerobic growth in 2xYT medium containing varying amounts of IPTG, which induces expression of CymA-MtrCAB. (B) Blue color intensity values of IC42AC−O+ (circle) or IC42AC−O− (square) in minimal media containing lactate and electrochromic WO3 nanoparticles that change from white to blue when reduced by microbes that present EET. (C) Cell density (OD600) of IC42AC−O+ (circle) or IC42AC−O− (square) grown in M9 minimal medium containing varying amounts of IPTG. Growth of IC42AC−O+ was significantly decreased at > 10 µM IPTG (p = 6.55 × 10−3 for 12.5 µM, p = 7.30 × 10−6 for 25 µM, p = 3.87 × 10−4 for 50 µM, p = 4.65 × 10−6 for 100 µM, p = 5.89 × 10−5 for 200 µM). Data represents the mean values with error bars representing one standard deviation (n = 3 biologically independent samples). P-values were obtained using two-tailed, independent t-tests.
Extended Data Fig. 3 Sulfane sulfur accumulation in SQR expressing cells.
Relative fluorescence of cells treated with the sulfane sulfur probe SSP4. The fluorescence from cells expressing Gs-SQR and Rc-SQR was significantly higher than cells transformed with an empty vector (EV) (p = 4.89 × 10−3 and p = 3.14 × 10−3, respectively). Fluorescence from cells expressing Gs-SQR and Rc-SQR were not significantly different. Error bars represent one standard deviation (n = 3 biologically independent samples) with individual samples shown as white circles and bars heights representing the mean. P-values were obtained using two-tailed, independent t-tests.
Extended Data Fig. 4 Planktonic cells present a small, noisy current response to thiosulfate.
(A) The chronoamperometric response of planktonic I+C+O+ and IC42AC+O+ cells in a bioelectrochemical reactor. Arrows indicate the addition of thiosulfate to varying concentrations. Data represents the mean values with error bars representing one standard deviation (n = 3 biologically independent samples). The working electrodes were poised at +0.42 VSHE. (B) The signal-to-noise ratio (SNR) was calculated as dividing the average current generated from bacteria by the standard deviation (n = 3) of the current. The average SNR across the 150 to 400 min was calculated to reflect the SNR changes between planktonic (-gel) and encapsulated (+gel) strains, as 140.00 for +gel, I+C+O+, 4.35 for -gel, I+C+O+, 12.27 for +gel, IC42AC+O+ and 2.88 for -gel, IC42AC+O+.
Extended Data Fig. 5 Linear fit for the thiosulfate sensing with different ranges.
5 min (A) and 30 min (B) sensing time, linear range from 0.1 mM to 20 mM; 5 min (C) and 30 min (D) sensing time, linear range from 0.1 mM to 10 mM.
Extended Data Fig. 6
Amperometric response and calculated signal intensity of ISC+O+ and IC42AC+O+ upon addition of DMSO (A, B, C) or 4-HT (D, E, F) in each 2-EWE configured BES with working electrodes poised at +0.42 VSHE. Time zero indicates the start of the chronoamperometric measurements.
Extended Data Fig. 7 Response of I+C+O+ and IC42AC+O+ to thiosulfate in complex urban waterway samples.
Percent increase in the amperometric response of I+C+O+ relative to IC42AC+O+ immediately before and 6.54 min (p = 0.045) after addition of 10 mM thiosulfate in the waterway samples from Brays Bayou (red), Buffalo Bayou (blue), and Galveston Beach (green). Each point represents a single waterway replicate, the center line represents the mean of the response in the three waterway samples with error bars representing one standard deviation.
Extended Data Fig. 8 Cyclic voltammetry analysis of environmental samples.
(A) Each environmental sample shows multiple pairs of redox peaks, indicating abundant redox active chemicals exist which might interfere with 4-HT sensing. (B) Environmental samples supplemented with 0.2% glucose show no changes to their voltammograms. All CVs were measured at a scan rate of 10 mV/s.
Extended Data Fig. 9 Addition of TiO2@TiN nanoparticles enables more current collection.
(A) Chronoamperometry and (B) current of I+C+O+ strain encapsulated in an alginate-agarose hydrogel with and without TiO2@TiN nanoparticles upon addition of 1 mM thiosulfate (arrow). The strains encapsulated with nanoparticles respond to thiosulfate more rapidly and with a higher steady-state level. Data represents two biologically independent measurements.
Extended Data Fig. 10 Simplified 1D geometry for calculation of diffusion timescales for the response of the living bioelectronic sensor.
Schematic of analyte diffusion from bulk solution through the agarose layer to cells embedded in the hydrogel on the electrode surface.
Supplementary information
Supplementary Information
This file contains Supplementary Text detailing the evaluation of sulfur source on assimilation and H2S evolution, Supplementary Tables 1–4 and Supplementary References.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Atkinson, J.T., Su, L., Zhang, X. et al. Real-time bioelectronic sensing of environmental contaminants. Nature 611, 548–553 (2022). https://doi.org/10.1038/s41586-022-05356-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41586-022-05356-y
Comments
By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.
