A Bacterial Consortium-based Sensing System for Detecting

Subscriber access provided by AUB Libraries

Article

A Bacterial Consortium-based Sensing System for Detecting Organophosphorus Pesticides Mst Afroza Khatun, Md Anarul Hoque, Yong Zhang, Ting Lu, Li Cui, Ning-Yi Zhou, and Yan Feng Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b02709 • Publication Date (Web): 31 Jul 2018 Downloaded from http://pubs.acs.org on July 31, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Analytical Chemistry

A Bacterial Consortium-based Sensing System for Detecting Organophosphorus Pesticides

Mst Afroza Khatun1,2, Md Anarul Hoque1,2, Yong Zhang1,2, Ting Lu3-6, Li Cui1,2, Ning-Yi Zhou1,2, and Yan Feng1,2,*

1

State Key Laboratory of Microbial Metabolism, 2School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China

3

Department of Bioengineering, 4Department of Physics, 5Center for Biophysics and Quantitative Biology, and 6Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA

Corresponding author: Yan Feng, Email: [email protected]

1

ACS Paragon Plus Environment

Analytical Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ABSTRACT Engineered bacteria with synthetic gene circuits are attractive tools to detect environmental contaminants. However, their applications in realistic settings are hindered by its relatively low sensitivity, long response time and limited portability. Here, we present a synthetic bacterial consortium-based system for detecting organophosphorus pesticides (OPs). The system consists of two Escherichia coli strains with divided tasks, including one for hydrolyzing OPs to p-nitrophenol (PNP) and the other for converting the PNP signal into β-galactosidase production for colorimetric detection. Upon optimization, the system was able to detect ethyl-paraoxon at the concentration of 1×10-9 M within 3.5 h of induction at 28°C, which is approximately 200-fold more sensitive than single-cell based whole-cell sensing. In addition, it was capable of detecting several OPs, commonly used in agriculture. Furthermore, the system showed the promise for on-site detection through the demonstration of a paper-based setting and real apple and soil samples. This study provides a rapid, sensitive and portable biosensing platform for contaminant detection, and also demonstrates the utility of engineered microbial ecosystems for novel environmental applications.

2


Page 2 of 32

Page 3 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


OPs are widely used for insect control, accounting for about 38% of the global pesticides use.1–4 As potent inhibitors of nervous system acetylcholine esterase, they can also cause acute neurotoxic poisoning to human and animals.5–7 Thus, despite their considerable agricultural benefits, the mass application of OPs has raised serious public concerns regarding health, environment and food safety.8,9 Developing methods for rapid, sensitive and portable OPs detection are hence urgently needed. Many analytical methods, such as liquid or gas chromatography and mass spectrometry, have been developed for OPs detection. However, they are often expensive and require substantial logistics.10 Recently, biosensors have received increasing attentions due to their ease of operation, rapid response time and cost-efficiency.10,11 For the case of OPs, the organophosphate hydrolase (OPH), a highly efficient enzyme for OPs conversion,4,12 has been immobilized on the surface of electroanalytical detectors, providing an alternative method for the detection of OP compounds.13,14 However, this type of sensors often suffers from interferences by other oxidizable substances (e.g., glucose, sucrose and phenol) in real samples.15,16 One promising approach to address the limitations of existing methods is whole-cell biosensing, which harnesses the diverse regulatory elements of microorganisms for the detection of environmental signals.17 Whole-cell biosensors usually consist of a transcriptional regulator, which binds to its target analyte, and a reporter gene that converts the regulator-target interaction into a measurable output.18 For OP detection, Chong et al. constructed a novel whole-cell E. coli biosensor by sensing and reporting PNP, one product from OPs hydrolysis, with a dimethyl 3



phenol regulatory protein (DmpR).19 Notably, as DmpR is not the native regulator responsive to PNP, the researchers adopted a systematic engineering approach to optimize DmpR, resulting in a detection sensitivity of 1~5×10-5 M. However, the sensitivity is still two to three orders of magnitude lower than those electrochemical and chromatographic methods.13,20 Additionally, it costs a long response time (more than 6 h). As part of the PNP degradation pathway from Pseudomonas sp. strain WBC-3, the LysR-type transcriptional regulator, LTTR (denoted PnpR) has been shown to activate three operons (pnpA, pnpB, and pnpCDEFG) in response to PNP.21 Therefore, harnessing this native PNP responsive regulator could serve as a promising solution to develop an ultra-sensitive OP biosensor. In addition to the catalytic efficiency of OPH, PNP sensing highly depends on the physical accessibility of OPH for OPs.19,22 Studies have shown that the diffusion of OPs into the cytoplasm, where OPH locates, is a limiting step for PNP sensing.23 Indeed, when OPH anchoring on the outer membrane, its activity was improved for seven folds.24 One issue associated with the surface display was prolonged incubation required for proper translocation of target protein,25,26 which could result in delayed and nonlinear signal accumulations.17,27 Recently, synthetic microbial consortia have become an effective route for the programming of cellular functionalities. A set of artificial ecosystems have been successfully created to overproduce chemicals and biomolecules as well as to generate defined population dynamics.28–30 Compared to single engineered strain, these rationally design ecosystems possess several compelling advantages, including enhanced performance, stability and programmability of cellular functions, through the division of labor among species within ecosystems.31–33 4


Page 4 of 32

Page 5 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Leveraging the concept of division of labors, here we designed a compartmentalized, consortium-based system for rapid and sensitive detection of OPs. As shown in Figure 1, the system is composed of two E. coli strains that carry distinct gene circuit modules, namely the OPH module and the signal generator module. The OPH module contains a tac promoter that drives the expression of OPH displayed on the cell surface, which enables the OP-to-PNP conversion. In contrast, the signal generator module consists of the transcriptional regulator gene pnpR and its cognate promoter PpnpC that drives the lacZ gene, which allows a colorimetric detection of the PNP signal. With this design, exposure to OPs induces the OPH module to produce PNP which, in turn, triggers the LacZ expression in the reporter module and subsequently produces a visual signal in the presence of X-gal. A series of experiments in 96-wells microtiter plates was performed to collectively demonstrate the consortium-based sensing system as a rapid and sensitive OP detection method. Additionally, to enable real-world utilization, a mandatory requirement for the detection of environmental contaminants is the ability to be portable and easy-to-implement for on-site testing. To this end, experiments using paper strips and with real soil and apple samples were performed to illustrate the feasibility of our consortium-based biosensing in realistic settings.

EXPERIMENTAL SECTION Bacterial Strains, Media, and Chemicals E. coli XL1-Blue and E. coli DH5α were used for all cloning and protein expression procedures. The bacteria were grown in 2YT media (16 g/L tryptone, 10 g/L yeast extract, and 5 g/L sodium chloride). PNP and OPs such as ethyl-paraoxon, methyl-paraoxon, ethyl-parathion, methyl-parathion, fenitrothion, and ethyl p-nitrophenylphosphorothioate (EPN) were dissolved in

5



Page 6 of 32

acetonitrile to prepare stock solutions at a concentration of 1×10-1 M. All tested chemicals were purchased from Sigma-Aldrich. Whatman general-purpose filter paper (medium speed, creped, diameter = 9.0 cm), peptone from animal tissue, beef extract, gelatin, sodium L-ascorbate, D-(+)-raffinosepentahydrate, L-glutamic acid monosodium salt monohydrate, ampicillin, kanamycin, tetracycline and anhydrous N,N-dimethylformamide (DMF) were purchased from Promega (Madison, WI, USA). HPLC-grade acetonitrile, sodium chloride, potassium chloride, magnesium chloride, sodium phosphate monohydrate, and disodium phosphate heptahydrate were purchased from Fisher Scientific (Pittsburgh, PA, USA). The chromogenic substrate X-gal (5-bromo-4-chloro-3-indolyl-D-galactopyranoside) was purchased from Gold Biotechnology (St. Louis, MO, USA). The Beta-Glo Assay reagent was obtained from Promega (Madison, WI, USA).

The

Alpha

2-4

lyophilizer

was

purchased

from

Martin

Christ

GefriertrocknungsanlagenGmbH (Osterode, Germany). The polymerase chain reaction (PCR) was performed using Q5 High-Fidelity DNA polymerase or Taq DNA polymerase (New England Biolabs, Ipswich, MA, USA), and PCR products were gel extracted with a QIAquick Gel Extraction Kit (Qiagen, Valencia, CA, USA). Restriction enzymes and T4 DNA ligase were purchased from New England Biolabs (Ipswich, MA, USA), and recombinant plasmids were recovered using a QIA prep Spin Miniprep Kit (Qiagen, Valencia, CA, USA).

Plasmid Construction and Culture Conditions The pPNCO33 plasmid was a kind gift from Prof. Ping Xu.4 The pPNCO33 plasmid was transformed into E. coli XL1-Blue to form the OPH module. E. coli bearing the plasmid was grown in 2YT medium supplemented with kanamycin (50µg/mL) and shaken at 250 rpm and 37 °C. Once the OD600 of the E. coli culture reached 0.6, 0.3 mM IPTG was added to induce 6


Page 7 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


protein expression for 24 h at 28 °C. The LysR-type transcriptional regulator gene pnpR-containing plasmid (pBBR1-tacpnpR) and pnpC promoter containing pCMgfp-spClacZ plasmid were kind gifts from Prof. Ning-Yi-Zhou.21 Both pCMgfp-spClacZ and pBBR1-tacpnpR were co-transformed into a single E. coli DH5α cell to form the signal generator module. The transformed E. coli was grown with shaking at 250 rpm and 37 °C in 2YT medium supplemented with kanamycin (50µg/mL) and tetracycline (100µg/mL). Once the E. coli culture reached an OD600 of 0.6, 0.5 mM IPTG was added to express the PnpR protein. Wild-type pnpR and the promoter of the PNP catabolic operon PpnpC were amplified from the pBBR1-tacpnpR and pCMgfp-spClacZ plasmids respectively, and used to construct a single plasmid for signal generation (the primer list is shown in Table S1). These two fragments were fused by overlap extension PCR (OEP). The fused pnpR-pnpC fragment was cloned into HindIII-BsaAI digested pSV-β-galactosidase vector (Promega, Madison, WI, USA) to yield the pSVRCL plasmid. To terminate the activity of the SV40 promoter at the desired location, a long T7 terminal region (48 bp) from the pET-28a (+) plasmid was inserted between pnpR and pnpC to yield the pSVRTCL plasmid. The recombinant plasmid was transformed into E. coli DH5α. All strains and plasmids used in this study are listed in Table S2.

Whole-cell OPH Activity The whole-cell OPH activity was measured using ethyl-paraoxon as the substrate. The recombinant OPH-expressing E. coli cells were harvested after 6, 12, 18 and 24 h of IPTG 7



induction, washed twice with 100 mM phosphate buffer (pH 7.4) and then resuspended to an OD600 of 1 in the same buffer. The hydrolysis of ethyl-paraoxon was measured spectrophotometrically by monitoring the formation of PNP at 405 nm (ε405=16,600 M-1 cm-1). The OPH activity assay was performed at 28 °C in 100 mM phosphate buffer (pH 7.4) supplemented with 1×10-4 M substrate and 100 µL of cells (OD600=1.0). The activities are expressed in units (1 unit equals1 µmol of substrate hydrolyzed per minute) per OD600 of whole cells.

Response of Signal Generator E. coli to PNP The signal generator E. coli DH5α cells harboring pCMgfp-spClacZ and pBBR1-tacpnpR were grown in a 100-mL culture flask to an OD600 of 1, and 90 µL of the culture was then aliquoted into each well of a 96-well microtiter plate. After various concentrations of PNP were added, 10 µL of 10 mg/mL X-gal solution was added to each well, and the culture plates were incubated at 28 °C with orbital shaking at 220 rpm. The absorbance at 650 nm was measured every 30 min until 3.5 h using a SpectraMax○R M5 microplate reader.

Dose Response of Consortium Biosensor to OPs Commercially available OPs, such as ethyl-paraoxon, methyl-paraoxon, ethyl-parathion, methyl-parathion, EPN and fenitrothion, were dissolved in acetonitrile to obtain stock solutions with a concentration of 1×10-1 M. OPH E. coli cells that had been cultured for 24 h were collected by centrifugation and diluted with fresh media to reach an OD600 of 1. Signal generator E. coli cells were grown in 100-mL culture flasks until an OD600 of 1. The ratio of OPH E. coli and signal generator E. coli cells was 1:1 that was used for 96-well microtiter plate based OPs

8


Page 8 of 32

Page 9 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


detection. 20 µL of the different OP compounds obtained from dissolved stock solutions were used to obtain final concentrations in the range of 1×10-4 to 1×10-10 M. 10 µL of a 10 mg/mL X-gal solution were added to each well, and the culture plates were then incubated in an orbital plate shaker at 220 rpm and 28 °C. The aliquots induced with the OPs were incubated for a maximum of 5 h, and the absorbance at 650 nm of both the induced and uninduced cultures was measured at 30 min intervals using a SpectraMax○R M5 microplate reader.

Time-course Study of Consortium OP Biosensor OPH-expressing cells at an OD600 of 1 were added to each well of a 96-welll microtiter plate. Cells with the pSVRTCL plasmid were cultured at 37 °C to an OD600 of 1, and 90 µL of the cell culture was then added to each well of the 96-well microtiter plate containing the OPH-expressing cells to analyze the effect of time on the biosensor system.

Finally, 20 µL of

OP compounds at concentrations ranging from 1×10- 3 to 1×10- 9 M and 10 µL of X-gal solution (10 mg/mL) were added to each well. The absorbance response at 650 nm was monitored every 30 min of interval from 0 to 5 h.

β-Galactosidase Activity Test Using a Chemiluminescence Assay Fresh single-cell colonies were picked from culture plates and cultured in 5 mL of 2YT medium in culture tubes. After 6 h of growth, 1 mL of grown culture was poured into a 100-mL culture flask that contained 2YT medium. When the cultures reached an OD600 of 1, 90 µL of the pSVRTCL cell cultures was placed in each well of a 96-well plate containing 90 µL of the cell cultures (OD600=1) that had expressed OPH for 24 h. Finally, 20 µL of OPs at various concentrations was added to each well, and the microtiter plate was placed in a shaker at 28 °C at

9



Page 10 of 32

220 rpm. After 3.5 h, the cell culture was centrifuged, and the cells were resuspended in 200 µL of fresh 2YT medium to remove the OP compounds. Finally, cells at an OD600 of 0.30 were collected and placed in a black 96-well plate for a β-galactosidase assay. The amount of the reporter protein (β-galactosidase) expressed was determined using the chemiluminescence-based Beta-Glo

assay

system

following

the

manufacturer’s

instructions.

The

induced

chemiluminescence was measured (1 s/well).

Preparation of Filter Paper-based Sensing Strips Paper sensing strips were prepared as reported previously.34 Briefly, the two cell types at a 1:1 ratio were suspended in sterile drying protectant solution preheated at 37 °C. A volume of 5 µL of cell suspension was spotted on Whatman filter paper strips (0.6 × 4 cm), and these paper strips were then dried for 10 min in a laminar air flow cabinet and subsequently dried in vacuum at 20 °C in a lyophilizer. The filter paper sensing strips were then stored at 4 °C until use.

Dose-response OP Curve on Filter Paper Strips Ethyl-paraoxon (at concentrations from 1×10-3 to 1×10-9 M) was diluted with 50 mM HEPES buffer (pH 7.0) that contained 50 mM each of sodium chloride, potassium chloride, and magnesium chloride. 100 µL of each of these standard solutions were added to culture tubes containing 900 µL of 2YT media and the prepared filter strips. The culture tubes were then incubated at 28 °C without shaking for 2 h. The strips were then removed from the culture tubes and maintained between layers of plastic wrap to prevent drying. Subsequently, 10 µL of X-gal substrate solution (50 mg/mL) in DMF was added carefully to the spot where the sensing cells had been deposited, and color development was allowed to proceed for 90 min. In addition to 10


Page 11 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


visual observation of the developed blue color, the color intensities were measured using ImageJ software (NIH, Bethesda, MD, USA) (http://rsbweb.nih.gov/ij/).

Real Sample Test In this assay, approximately 1 g of soil was collected and dissolved in 900 µl of water. Collected apples were cut into pieces and smashed and 1 g of smashed apple was dissolved in 900 µl of water. Both sample solutions were then centrifuged at 37 °C and 8000 rpm for 10 min, and the supernatant was filtered through a well-defined 0.22-µm PVDF filter and diluted 2 times with DI water. Subsequently, the supernatant was spiked with ethyl-paraoxon solutions to yield concentrations of 1×10-5 and 1×10-6 M. Finally, the developed biosensor was employed to detect the spiked OP concentration, and the absorption at 650 nm was measured using Spectramax○R M5 plate reader.

RESULTS AND DISCUSSIONS Construction of the OPH Module in E. coli XL1-Blue The OPH module contains an inpnc-opd fragment (encoded INPNC-OPH fusion protein) under the control of an IPTG-inducible tac promoter. It was placed in pPNCO33, a pVLT33-based vector (Figure 2A).4 The opd part was used to encode the hydrolase that converts OPs to PNP. The inpnc of the inpnc-opd fragment encodes a truncated version of the INP that contains only its N- and C-terminal domains, which has been widely used as a surface anchoring motif.35 Such a fusion design allows OPH to be displayed on the cell surface for an enhanced rate of OP-to-PNP conversion. Because overexpression of the active OPH on cell surface is highly 11



host-specific and was shown to exhibit a higher rate of OP degradation in XL1-Blue strain,25 the pPNCO33 plasmid was transformed into E. coli XL1-Blue. The resulting cells were cultured and induced with 0.3 mM IPTG, and the OPH expression levels were measured by monitoring the whole-cell OPH activity. As shown in Figure 2B, the OPH catalytic activity appeared in the exponential phase and increased as the cells reached the stationary phase of growth. Notably, this time course informed the time required for full translocation of the INPNC-OPH fusion to the cell surface. Therefore, cells at the late stationary phase (24 h) were used for OP degradation, because these cells can efficiently breakdown the contaminants and generate the maximal amount of PNP for the signal generator module.

Construction of the Signal Generator Module in E. coli DH5α The signal generator module was constructed in E. coli DH5α using the reporter gene lacZ as well as the components of the PNP catabolic pathway from Pseudomonas sp. WBC-3, specifically the transcriptional regulator gene pnpR and its cognate promoter, PpnpC. According to a previous study, PNP exposure substantially increases the gene expression level of all three promoters in the PNP catabolic operons pnpA, pnpB, and pnpCDEFG.21 However, the pnpCDEFG promoter fragment, 119 bp in length (from -94 to +25), showed no detectable basal expression of the downstream gene in the absence of PNP. Therefore, we used two plasmids pBBR1-tacpnpR, which contains the pnpR gene under the regulation of IPTG-inducible tac promoter, and pCMgfp-spClacZ within which the lacZ gene was placed downstream of the pnpC promoter (Figure 3A). The two plasmids were co-transformed into E. coli DH5α. To test the function of the developed module, the resulting strain was cultured until an OD600 of ~1.0 and 12


Page 12 of 32

Page 13 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


subsequently supplemented with 10µL of 10 mg/mL X-gal and different concentrations of PNP. The system response to PNP was then determined by quantifying the blue color generated by the reporter protein β-galactosidase after X-gal consumption, which can be implemented by measuring the absorbance at 650 nm. Indeed, the data clearly showed that the absorbance of blue color at 650 nm positively correlates with the PNP concentration (Figure 3B).

Validation of the Consortium-based Biosensing System for Ethyl-paraoxon Detection To assess the feasibility of the consortium sensing system, suspension culture of the OPH cell and the signal generator cell was co-incubated at 28 °C in 2YT liquid media supplemented with X-gal and ethyl-paraoxon. By varying the relative abundance of the OPH cell and the signal generator cell (in the ratio of 10:1, 3:1, 1:1, 1:3, and 1:10) while keeping their total density the same (OD600=1.0), we found that the output of the consortium, color absorbance, follows a bell-like shape with the highest occurring around 1:1 and 1:3 ratios (Figure S1). This result confirmed three folds of information. First, the consortium-based system is able to successfully detect ethyl-paraoxon. Second, the detection requires the both strains to implement the tasks, namely OPH conversion and signal generation. Third, the performance of the detection is subject to the relative abundance of the two strains. Using the 1:1 ratio, we next examined the detection limit of the biosensing system by co-incubating the suspension culture of the two strains in 2YT liquid media supplemented with varied concentrations of ethyl-paraoxon (from 1×10-10 to 1×10-4 M). As shown in Figure 4C (Row I), we observed that the responding color intensity increases with the concentration of ethyl-paraoxon, indicating a positive correlation between the color intensity and the concentration of ethyl-paraoxon. Notably, the system response limit was found to be 1×10-6 M of 13



ethyl-paraoxon. From the assay, we also found that coupling the fully active surface-expressed OPH, which readily generates the threshold amount of PNP, with the signal-generating cells at their exponential stage of growth, resulted in a response time (3.5 h) that is significantly shorter than the previous report (around 6 h).19

Enhancing the Sensitivity by Optimizing the Signal Generator Module A key character that defines a sensor is its detection sensitivity. Inspired by the study showing that increased intracellular abundance of a regulatory protein can enhance the sensitivity of a gene expressed system controlled by the regulator,36 we speculated that boosting the intracellular concentration of the transcriptional regulatory protein, PnpR, can enhance the sensitivity of the biosensing system. Thus, we targeted to move the pnpR gene from the medium copy number plasmid pBBR1-tacpnpR to the high copy number plasmid pSV-β-galactosidase. To create such a construct, pnpR gene and the promoter PpnpC fragment were cloned respectively from the pBBR1-tacpnpR and pCMgfp-spClacZ plasmids, joined together through overlap extension polymerase chain reaction and inserted into the vector pSV-β-galactosidase, generating the plasmid pSVRCL (Figure S2A). Here, the pnpC promoter drives the lacZ gene while the SV40 promoter, in the presence of an enhancer, drives the expression of the regulator gene pnpR. For the new signal generator, a microtiter plate assay was then performed to test the response of this system. Unexpectedly, the system lost its dosage-dependent response as apparent blue color appeared after 2 h of incubation with or without paraoxon (Figure S3). One possible reason is that transcription initiated from the constitutive SV40 promoter continued through both the receptor gene pnpR and the reporter gene lacZ. Hence, we placed a T7 terminator (T7 ter) between pnpR gene and pnpC promoter to insulate positional effect caused by the SV40

14


Page 14 of 32

Page 15 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


promoter (Figure 4A and Figure S2B). Indeed, introduction of the T7 terminator restored the previously observed concentration dependence response. A major concern associated with abundant protein production is the reduction of cell growth caused by increased metabolic load or toxicity.37 To test whether the increase in the amount of regulatory protein inhibits cell growth, we compared the growth kinetics of cells carrying pSVRTCL with those harboring pBBR1-tacpnpR. We found that, in our system, increased PnpR production does not lead to obvious growth inhibition (Figure S4). Using the new signal generator module in conjugation the OPH module, we tested the sensitivity of the optimized biosensing system responding to ethyl-paraoxon. The schemes and blue color absorbance obtained from the optimized and original versions of the sensing system are shown in Figures 4A and 4B. We found that detectable level of color was observed at concentrations as low as 1×10-9 M ethyl-paraoxon (Figure 4C, Row II). The result suggested that the sensitivity of the optimized system was successfully increased by three orders of magnitude from the starting system (cells harboring both pBBR1-tacpnpR and pCMgfp-spClacZ plasmids) (Figure 4A, Row I; Figure 4B, circles; and Figure 4C, Row I).

Time-course Study of the Consortium-based OP Biosensing To analyze temporal response dynamics of the biosensing system, we monitored the absorbance response at 650 nm every 30 min for 5 h after the exposure of the consortium culture to ethyl-paraoxon. As shown in Figure 5, the absorbance value increased with increasing induction (or exposure) time, as reflected by the positive slope of the graph. We also found that within 3.5 h of incubation at 28 °C, the cultures with ethyl-paraoxon concentrations as low as 1×10-9 M showed significant increases in color when compared to controls. In contrast, at

15



concentrations higher than 1×10-6 M, a detectable signal was found within 2 h of exposure to ethyl-paraoxon.

Applications of the Biosensing System to Detect Pesticides beyond Ethyl-paraoxon To examine the versatility of the biosensing system, we applied it to detect a series of pesticides beyond ethyl-paraoxon, including methyl-paraoxon, ethyl-parathion, methyl-parathion, EPN, and fenitrothion (Figure 6A). We found that, similar to the signal response observed in ethyl-paraoxon detection, the colors of the co-culture media gradually changed from light yellow to deep blue with increasing concentrations for all tested pesticides (Figure 6B). For the tested OPs, we also performed chemiluminescence-based assay by measuring the extent of enzymatic reactions (Figure S5A). As shown in Figure S5B, the system exhibited a predictable and dose-dependent manner that is consistent with the results from visual inspection. By comparing the detection profiles, we found that, for different pesticides, the sensitivity of the consortium-based system varied from 1×10-9 M to 1×10-5 M. For common OP compounds, the system had the sensitivity that is 2-400 fold more sensitive than single cell-based colorimetric approach.19,38 We also noticed that, for fenitrothion, the sensitivity is 1×10-5 M, which is possibly due to the catalytic inefficiency of OPH for this substrate or the production of 2-methyl-4-nitrophenol instead of p-nitrophenol.4,19 Additionally, the sensitivity of our OP detection system is 1-2 orders of magnitude lower than the chromatographic techniques but comparable to electrochemical sensor.14,20 However, the simplicity and cost-effectiveness of consortium-based sensor make it more suitable for onsite, portable detection as detailed in the next section. Moreover, this PNP dependent signal production of the present biosensor provides a better selectivity than electrochemical OPs biosensors which are easily influenced by other

16


Page 16 of 32

Page 17 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


oxidizable substances present in real samples.14,15

Paper-based Test of the Consortium-based Biosensing System Motivated by the fact that portability is a critical measure for sensing in field,39 we tested the OP detection system on filter papers using a previously reported method.34 Specifically, the both types of cells were suspended in a drying protectant solution and dropped on a filter paper strip under sterile condition. Because cell viability is an issue during the process of freeze-drying, the samples were vacuum-dried from suspension to the solid state to enhance cell survival. The paper strip containing the consortium system was then exploited for the detection of ethyl-paraoxon dissolved in 2YT liquid media. After 2 h incubation of the strip at 28 °C, X-gal was added to the zone of lyophilized cells. As shown in Figure 7A, the strip’s cell retention zone shifted from colorless to blue as the concentration of ethyl-paraoxon increased. Additionally, ImageJ software analysis confirmed the results obtained through visual estimation of the paper strip (Figure 7B), suggesting a linear relationship between the measured color intensity and the logarithm of the ethyl-paraoxon concentration. The result also showed that in this setting the sensing system can clearly detect ethyl-paraoxon at the concentration of 1×10-7 M within 1.5 h. Together, these results demonstrate the feasibility of using the paper-based consortium biosensor for reliable detection of OPs, which is particularly useful in developing countries and remote societies.

Using the Biosensing System to Analyze Real Samples To further evaluate the feasibility of our biosensing system in field applications, we tested it with real samples. Specifically, ethyl-paraoxon-spiked apple and soil samples were prepared and

17



measured. For comparison, standard solutions of ethyl-paraoxon (1×10-5 or 1×10-6 M) were also tested. As shown in Figure 8, the response values obtained for the apple and soil samples showed similar patterns as the standard solutions. In addition, the recoveries of the spiked ethyl-paraoxon in the apple and soil samples were in the range of 89.40 ± 5.1 to 94.80 ± 6.9% (Table S3), indicating that this new sensing platform can be suitable for assaying OPs in real samples.

CONCLUSION In this study, we developed an engineered E. coli consortium system for sensing and responding to OPs. The system possesses following unique advantages when compared to other detection methods including single-cell based biosensing. First, it is highly sensitive, with its lower detection limit at nanomolar concentrations. Notably, the sensitivity of the consortium system is over two orders of magnitude higher than previously reported single-cell based methods. It is due to the enhanced OP-to-PNP rate by displaying the hydrolysis enzyme on cell surface in the OPH module, augmented PNP responsiveness upon the introduction of the regulator PnpR in the signal generator module, and facilitated modulation of the two modules with easily adjustable relative abundance of the two populations. Second, its rapid colorimetric response to OPs eliminates the need for sophisticated instrumentation, which offers a feasible analytical test in low-resource settings. Third, this system works in both liquid and freeze-dried states, enabling a wide range of applicability. Fourth, the detection of spiked ethyl-paraoxon in apples and soils with excellent recovery rates showed that the sensor is suitable for OP detection in real samples. Together, these unique advantages make the consortium-based biosensing

18


Page 18 of 32

Page 19 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


system a highly promising solution to OP detection. Notably, although the biosensing system was designed to detect PNP converted from OP, in principle, it can be applied for detecting PNP from other sources.40 Therefore, the system can be adopted as a stand-alone subsystem for other PNP-related applications. ACKNOWLEDGMENTS The authors wish to thank Dr. Guangyu Yang, and Dr. Qian Liu for their valuable suggestions. The authors also wish to thank Chong Yuesheng for laboratory technical assistance. This work is supported by the grants from Science and Technology Commission of Shanghai Municipality (15JC1400402, 14JC1403500). Ting Lu was supported by the National Science Foundation (1553649, 1227034), the Office of Naval Research (N000141612525) and the Center for Advanced Study at the University of Illinois at Urbana-Champaign.

19



REFERENCES 1.

Qian, S.; Lin, H. Anal. Chem. 2015, 87, 5395-5400.

2.

Yan, F.; He, Y.; Ding, L.; Su, B. Anal. Chem. 2015, 87, 4436-4441.

3.

Liu, W.; Gan, J.; Schlenk, D.; Jury, W.A. Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 701-706.

4.

Liu, R.; Yang, C.; Xu, Y.; Xu, P.; Jiang, H.; Qiao, C. J. Agric. Food. Chem. 2013, 61, 7810-7816.

5.

Chen, J.C.; Shih, J.L.; Liu, C.H.; Kuo, M.Y.; Zen, J.M. Anal. Chem. 2006, 78, 3752-3757.

6.

Rauh, V.A.; Perera, F.P.; Horton, M.K.; Whyatt, R.M.; Bansal, R.; Hao, X.; Liu, J.; Barr, D.B.; Slotkin, T.A.; Peterson, B.S. Proc.Natl. Acad. Sci. U. S. A. 2012, 109, 7871-7876.

7.

Pang, Z.; Hu, C. M.; Fang, R. H.; Luk, B. T.; Gao, W.; Wang, F.; Chuluun, E.; Angsantikul, P.; Thamphiwatana, S.; Lu, W.; Jiang, X.; Zhang, L. ACS Nano 2015, 9, 6450–6458.

8.

Bao, J.; Hou, C.; Chen, M.; Li, J.; Huo, D.; Yang, M.; Luo, X.; Lei, Y. J. Agric. Food Chem. 2015, 63, 10319–10326.

9.

Gupta, R.D.; Goldsmith, M.; Ashani, Y.; Simo, Y.; Mullokandov, G.; Bar, H.; Ben-David, M.; Leader, H.; Margalit, R.; Silman, I. Nat. Chem. Biol. 2011, 7, 120-125.

10.

Febbraio, F.; Merone, L.; Cetrangolo, G.P.; Rossi, M.; Nucci, R.; Manco, G. Anal.Chem. 2011, 83, 1530-1536.

11.

Rogers, J.K.; Church, G.M. Proc. Natl. Acad Sci. U. S. A. 2016, 113, 2388-2393.

12.

Hoque, M.A.; Zhang, Y.; Chen, L.; Yang, G.; Khatun, M.A.; Chen, H.; Hao, L.; Feng, Y. 20


Page 20 of 32

Page 21 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


ACS Chem. Biol. 2017, 12, 1188-1193. 13.

Tang, X.; Zhang, T.; Liang, B.; Han, D.; Zeng, L.; Zheng, C.; Li, T.; Wei, M.; Liu, A. Biosens. Bioelectron. 2014, 60, 137-142.

14.

Lei, Y.; Mulchandani, P.; Chen, W.; Mulchandani, A.

J. Agric. Food. Chem. 2005, 53,

524-527. 15.

Funari, R.; Della Ventura, B.; Schiavo, L.; Esposito, R.; Altucci, C.; Velotta, R. Anal. Chem. 2013, 85, 6392-6397.

16.

Mulchandani, P.; Chen, W.; Mulchandani, A.

Anal. Chim. Acta 2006, 568, 217-221.

17.

Bereza-Malcolm, L.T.; Mann, G.; Franks, A.E. ACS Synth. Biol. 2015, 4, 535-546.

18.

Rebets, Y.; Schmelz, S.; Gromyko, O.; Tistechok, S.; Petzke, L.; Scrima, A.; Luzhetskyy, A. Metab. Eng. 2018, doi: 10.1016/j.ymben.

19.

Chong, H.; Ching, C.B.

ACS Synth. Biol. 2016, 5, 1290-1298.

20.

LeDoux, M. J .Chromatogr. A 2011, 1218, 1021-1036.

21.

Zhang, W.M.; Zhang, J.J.; Jiang, X.; Chao, H.; Zhou, N.Y. Appl. Environ. Microbiol. 2015, 81, 220-230.

22.

Jha, R.K.; Kern, T.L.; Kim, Y.; Tesar, C.; Jedrzejczak, R.; Joachimiak, A.; Strauss, C.E. Nucleic Acids Res. 2016, 44, 8490-8500.

23.

Kang, D.G.; Lim, G.B.; Cha, H.J. J. Biotechnol. 2005, 118, 379-385.

24.

Richins, R.D.; Kaneva, I.; Mulchandani, A.; Chen, W. Nat. Biotechnol. 1997, 15, 984-987.

25.

Kaneva, I.; Mulchandani, A.; Chen, W. Biotechnol. Prog. 1998, 14, 275-278. 21



Page 22 of 32

26.

Li, L.; Gyun Kang, D.; Joon Cha, H. Biotechnol. Bioeng. 2004, 85, 214-221.

27.

Branco, R.; Cristovao, A.; Morais, P.V. PLoS One 2013, 8, e54005.

28.

Zhou, K.; Qiao, K.; Edgar, S.; Stephanopoulos, G. Nat. Biotechnol. 2015, 33, 377-383.

29.

Minty, J.J.; Singer, M.E.; Scholz, S.A.; Bae, C.H.; Ahn, J.H.; Foster, C.E.; Liao, J.C.; Lin, X.N. Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 14592-14597.

30.

Liu, H.; Lu, T. Metab. Eng. 2015, 29, 135-141.

31.

Brenner, K.; You, L.; Arnold, F.H. Trends Biotechnol. 2008, 26, 483-489.

32.

Großkopf, T.; Soyer, O.S. Curr. Opin. Microbiol. 2014, 18, 72-77.

33.

Kong, W.; Meldgin, D. R.; Collins, J. J.; Lu, T. Nat. Chem. Biol. 2018, 14, 821–829.

34.

Struss, A.; Pasini, P.; Ensor, C.M.; Raut, N.; Daunert, S.Anal. Chem. 2010, 82, 4457-4463.

35.

Lee, J.-S.; Shin, K.-S.; Pan, J.-G.; Kim, C.-J. Nat. Biotechnol. 2000, 18, 645-648.

36.

Wang, B.; Barahona, M.; Buck, M. Nucleic Acids Res. 2015, 43, 1955-1964.

37.

Rugbjerg, P.; Sarup-Lytzen, K.; Nagy, M.; Sommer, M.O.A. Proc. Natl. Acad. Sci. U. S. A. 2018, 115, 2347-2352.

38.

Tang, X.; Liang, B.; Yi, T.; Manco, G.; Liu, A. Enzyme Microb. Technol. 2014, 55, 107-112.

39.

Pardee, K.; Green, A.A.; Ferrante, T.; Cameron, D.E.; DaleyKeyser, A.; Yin, P.; Collins, J.J. Cell 2014, 159, 940-954.

40.

Chen, Z.; Niu, Y.; Zhao, S.; Khan, A.; Ling, Z.; Chen, Y.; Liu, P.; Li, X. Bioelectron. 2016, 85, 860-868. 22


Biosens.

Page 23 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


LIST of FIGURES

Figure 1. Schematic of the consortium-based biosensing system for OP detection.

23



Figure 2. Design and characterization of the OPH module. (A) Map of the pPNCO33 plasmid. The plasmid contains the inpnc-opd gene, which encodes the INPNC-OPH fusion protein under the control of the tac promoter. (B) Time course of whole-cell OPH activity. Cells harboring pPNCO33 were incubated at 28 °C for 24 h after induction with 0.3 mM IPTG. Samples were withdrawn at regular time intervals, and OPH activity was measured by using 1×10-4 M ethyl-paraoxon as the substrate. The data are reported as the mean values ± standard deviations from three replicates.

24


Page 24 of 32

Page 25 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 3. Design and characterization of the signal generator module. (A) Maps of the plasmid pBBR1-tacpnpR, which contains the pnpR gene under the regulation of the tac promoter, and the plasmid pCMgfp-spClacZ which contains the lacZ gene driven by the pnpC promoter. (B) Dose response of the signal generator module to PNP concentrations ranging from 5×10-6 to 1×10-4 M. Error bar represents the standard deviation of three replicates.

25



Figure 4. Testing of the consortium-based biosensing system with ethyl-paraoxon. (A) Schematic of the OPH module with two versions of the signal generator module: (Row I) the pnpR gene regulated by the inducible tac promoter and the lacZ gene driven by the pnpC promoter, (Row II) the pnpR gene regulated by a constitutive promoter SV40, a T7 terminator that insulates gene expression, and the lacZ gene driven by the pnpC promoter. (B) The absorbance at 650 nm was monitored in the suspension of culture in presence of various ethyl-paraoxon concentrations. The absorbance values were calculated by subtracting the absorbance responses from the ethyl-paraxon induced wells by the average absorbance responses from the corresponding uninduced control wells. (C) Images of the colorimetric tests of the two different systems under various concentrations of ethyl-paraoxon (from 1×10-10 to 1×10-4 M). These are the images of the data in Figure 4B. Error bar represents the standard deviation of three replicates.

26


Page 26 of 32

Page 27 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 5. The absorbance of biosensor samples as a function of time at different incubation concentrations of ethyl-paraoxon. Error bar represents the standard deviation of three replicates.

27



Figure 6. Utilization of the consortium-based system for detecting different OPs. (A) Structure of the OPs used in the study. (B) Microtiter plate-based colorimetric responses of the consortium system for the OPs shown in panel A.

28


Page 28 of 32

Page 29 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 7. Filter paper-based test of the consortium sensing system for ethyl-paraoxon detection. (A) Image of colorimetric results obtained with a digital camera. The assay was performed in the presence of ethyl-paraoxon at the concentration ranging from 1×10-10 to 1×10-4 M (N=3). The incubation of the strip with ethyl-paraoxon and the color development steps were conducted at 28 °C. (B) Color intensity of the results in panel a (measured using the software ImageJ) as a function of the ethyl-paraoxon concentration. Inset: the linear response at different concentrations of ethyl-paraoxon.

29



Figure 8. Colorimetric test of the consortium sensing system using real samples. The standard solution, apple sample and soil sample contains 1×10-5 M (crosshatched) and 1×10-6 M (white) of ethyl-paraoxon. Error bar represents the standard deviation of three replicates.

30


Page 30 of 32

Page 31 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


SUPPORTING INFORMATION Figure S1. Optimization of OPH module and signal generator module's ratios for consortium Biosensor Figure S2. Plasmid maps of pSVRCL and pSVRTCL Figure S3.The scheme of consortium system contains signal generator cell harboring pSVRCL plasmid and its colorimetric response towards ethyl-paraoxon at various concentrations. Figure S4. Time courses of the growth of E. coli carrying pSVRTCL and pBBR1-tacpnpR Figure S5. Monitoring of β-galactosidase expression using a chemiluminescence assay. Table S1. Primers used in this study Table S2. Escherichia coli strains and plasmids used in this study Table S3. Recovery of spiked ethyl-paraoxon in apples and soils

31



'for TOC only'

32


Page 32 of 32

A Bacterial Consortium-based Sensing System for Detecting

Recommend Documents