A novel Genetically Engineered Microbial (GEM) biosensor for specific detection of Cd 2+ , Zn 2+ and Pb 2+ heavy metals; calibration and validation aspects

doi:10.21203/rs.3.rs-2455659/v1

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Research Article

A novel Genetically Engineered Microbial (GEM) biosensor for specific detection of Cd 2+ , Zn 2+ and Pb 2+ heavy metals; calibration and validation aspects

https://doi.org/10.21203/rs.3.rs-2455659/v1

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Journal Publication

published 08 Dec, 2023

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Background

In this study, we designed a novel genetic circuit sensitive to Cd²⁺, Zn²⁺ and Pb²⁺ by mimicking the CadA/CadR operon system mediated heavy metal homeostasis mechanism of Pseudomonas aeruginosa. The regular DNA motifs on natural operon were reconfigured and coupled with the enhanced Green Fluorescent Protein (eGFP) reporter to develop a novel basic NOT type logic gate CadA/CadR-eGFP to respond metal ions mentioned above. A Genetically Engineered Microbial (GEM)-based biosensor (E.coli-BL21:pJET1.2-CadA/CadR-eGFP) was developed by cloning the chemically synthesised CadA/CadR-eGFP gene circuit into pJET1.2-plasmid and transforming into Escherichia coli (E. coli)-BL21 bacterial cells.

Results

The GEM-based biosensor cells indicated the reporter gene expression in the presence of Cd²⁺, Zn²⁺ and Pb²⁺ either singly or in combination. Further, the same biosensor cells calibrated for fluorescent intensity against heavy metal concentration generated linear graphs for Cd²⁺, Zn²⁺ and Pb²⁺ with the R² values of 0.9809, 0.9761 and 0.9758, respectively as compared to non-specific metals, Fe³⁺ (0.0373), AsO₄³⁻ (0.3825) and Ni²⁺ (0.8498) making our biosensor suitable for the detection of low concentration of the former metal ions in the range of 1–6 ppb. Furthermore, the GEM based biosensor cells were growing naturally within the concentration range of heavy metals, at 37 ^oC and optimum pH = 7.0 in the medium, resembling the characteristics of wildtype E.coli.

Conclusion

Finally, the novel GEM based biosensor cells developed in this study can be applied for detection of targeted heavy metals in low concentration ranges (1–6 ppb) at normal bacterial physiological conditions.

Microbial biosensors

Cadmium

Lead

Zinc

Genetic circuits

Heavy metal detection

Heavy metals naturally exist in the environment and are generally defined as metallic chemical elements with relatively high density and toxic or poisonous at low concentrations [1]. Their extensive industrial, medical, agricultural and domestic applications have led to wide dispersion in the environment [2]. Heavy metals that are released into water reservoirs tend to bioaccumulate along food chains and eventually cause heavy metal poisoning in higher vertebrates [3, 4]. Arsenic (As), Lead (Pb) and Mercury (Hg) are systemic toxins that can either affect multiple organs or different cell types, even in minor quantities [4]. The International Agency for Research on Cancer (IARC) further categorizes Cadmium (Cd), Chromium (Cr), Nickel (Ni) and Arsenic (As) in the group of “the number one carcinogen” due to their potent cancer-causing ability [5].

The environmental risk caused by heavy metal pollution is traditionally determined by the quantification of total metals via conventional analytical methods after digestion with strong acids [6]. The common chemical techniques used in heavy metal detection are; chemical precipitation, ion exchange, chelation, membrane separation, cold vapor atomic absorption spectrometry, inductively coupled plasma mass spectrometry, UV visible spectrometry and X-ray absorption spectroscopy [7–9]. The major drawbacks of the above techniques are their inability to be applied in the field due to complexity, and significant time required to run the analysis. In spite of this, nowadays there is a great interest in developing rapid and portable techniques to detect heavy metals in contaminated water samples [10].

Biosensors are typically defined as analytical devices that consist of bio components in conjunction with transducers to convert biological signals into electrical signals and represent synergetic effects of biotechnology and microelectronics and are ideal candidates for real-time environmental monitoring [11]. Based on the nature of the biological components in use, heavy metal detecting biosensors are classified into two main groups; protein-based (enzyme, metal-binding protein and antibody) and whole-cell-based (natural and genetically engineered microorganism) [11]. The main advantages of biosensors to detect environmental contaminants are their specificity, low cost, ease of use, portability and the ability to provide continuous real time signals [11, 12]. One of the preeminent features shared among all of these biosensors is their ability to detect “bioavailable” levels of heavy metals, which in turn can be accountable for environmental risks and toxicity [13].

Overall biosensors are ideal alternatives to detect heavy metal contaminations in environmental samples. On the other hand, one of their disadvantages is their non-specific responses to various environmental pollutants [14]. In order to overcome this drawback, biosensors can be genetically improved, incorporating specific molecular mechanisms with constructed genetic circuits. The most promising approach to construct gene circuits to detect heavy metals is to architect the mechanism inside a live microorganism. The molecular mechanisms are often enhanced in microbial cells due to the optimal environment provided by the cells [15, 16]. This category of biosensors is widely known as Genetically Engineered Microorganism (GEM) based sensors and typically rely on the analysis of gene expression by creating transcriptional fusions between a promoter of interest and the reporter gene expression. This serves as a measurement for the availability of specific pollutants in complex environments [17]. There have been numerous attempts to design GEM sensors for heavy metal detection by encoding protein components that are naturally occurring in bacteria to resist from heavy metals adapting metal sequestration and efflux mechanisms [18, 19].

More recently, genetically engineered bacterial cells were shown to be specifically responsive towards heavy metal bioavailability in contaminated sediments and soils showing promising real-world application [20]. By utilizing the naturally occurring mercury resistant mechanism of Escherichia coli (E.coli), a specific mercury detecting biosensor was developed and its sensitivity has been compared with eight different reporter systems: Fluorescent reporter genes gfp (gfpmut3), deGFP, mCherry, and mScarlet-I, luciferase genes NanoLuc and lux operons from Aliivibrio fischeri and Photorhabdus luminescens, and colorimetric output gene lacZ [21]. In red fluorescent proteins, mCherry and mScarlet-I, the higher fold of induction and lowest detection limit was shown by the mScarlet-I. Similarly, out of GFP and deGFP, the GFP reporter gene has shown the best performances. Comparatively, the induction fold and the lowest detection limit which were given by the lacZ and NanoLuc were lower than the other reporter genes used. Further to detect Cd, Pb and antimony (Sb), a recombinant Cad promoter/CadC gene construct has been transformed into E. coli DH5α (pVLCD1) strain to obtain precise GFP signals [6].

Despite the high demand on GEMs, the gap between laboratory and the onsite analysis of heavy metals based on microbial biosensors seems to be lacking. Therefore, in the present study we designed a novel genetic circuit by rearranging the natural CadA/CadR gene operon of Pseudomonas aeruginosa in order to specifically sense Cd²⁺, Pb²⁺ and Zn²⁺ metal (loid)s. The enhanced Green Fluorescent Protein (eGFP) gene coding sequence was incorporated as the reporter gene. The plasmid containing DNA construct was transformed into Escherichia coli (E.coli)-BL21 bacterial strain. We tested the engineered microbial strain towards Cd²⁺, Zn²⁺ and Pb²⁺ sensitivity or specificity via fluorescent microscopy and digital image processing with individual metal ion treatments and combinational metal treatments. The modified cells were further assessed for optimal growth conditions, pH and temperature in order to record ideal incubation conditions for the novel sensor in this study. Here, we demonstrate a quantitative single cell digital tool to specifically detect Cd²⁺, Zn²⁺ and Pb²⁺ and we believe that this will contribute to the lacking knowledge of developing novel real-time onsite heavy metal analysis systems in future.

2.1. Construction of gene circuit

An enhanced novel artificial genetic circuit to efficiently sense targeted heavy metals (Cd²⁺, Zn²⁺ and Pb²⁺) was constructed by shuffling the key DNA motifs of Pseudomonas aeruginosa’s CadA/ CadR operon, which exists naturally for the detoxification of cadmium ions [22]. To computationally draft the DNA architecture of the gene circuit, the main DNA sequences were retrieved from Pseudomonas genome database (https://www.pseudomonas.com/). The DNA motifs on the genetic circuit were coordinated to theoretically function as a NOT molecular logic gate as described by Chia-Hua Chuang [23] and the T7 protein produced by E.coli-BL21 genome was interlined with the circuit to trigger the transcription initiation of the molecular mechanism. In brief, the T7 promoter coupled coding sequence of CadR gene (CP000744.1/PSPA7_1449) (WP_003154109) was placed in clockwise direction. A Ribosomal Binding Site (RBS) was embedded in between the CadR and T7 promoter sequence as the transcription initiation recognition signal. The coding sequence of eGFP (DQ399412.1) coupled with CadA promoter (CP000744.1/PSPA7_1448) was incorporated in anti-clockwise direction. Both CadR gene and eGFP gene expression were terminated by two T7 terminator sequences. The DNA architecture of the genetic circuit was visualized by SnapGene viewer software (http://www.snapgene.com). Eventually, the genetic circuit was chemically synthesized at Genscript, USA (https://www.genscript.com/) and was cloned into pJET1.2-plasmid (https://www.snapgene.com/resources/plasmidfiles/?set=basic_cloning_vectors&plasmid=pJET1.2). The cloned plasmid was designated as pJET1.2-CadA/CadR.

2.2. Microbial strains, culture conditions and production of biosensing cells

E.coli-BL21(DE3) (CP001509) bacterial strain was used as the host microorganism to provide the optimal physiological conditions for biosensor activity and to encapsulate the pJET1.2-CadA/CadR. The chemically competent cells of E.coli-BL21 were prepared by using the chemical competent cell preparation method [24]. The plasmid containing genetic circuit was transformed into E.coli-BL21 chemically competent bacterial cells using the heat shock method [25]. E.coli cells used in this study were grown on Luria-Bertani (LB) broth (10 g/L bacto-tryptone, 5 g/L bacto-yeast extract, and 5 g/l NaCl) supplemented with antibiotic (ampicillin, 100 mg/L) at 37°C under vigorous shaking [26]. Cultured cells were stored at 4°C for short-term use and − 20°C for long term use. The plates containing E.coli-BL21-pJET1.2-CadA/CadR cells were sub-cultured every two weeks and stored in 4 ^oC cold room. The glycerol stocks containing E.coli-BL21-pJET1.2-CadA/CadR cells were stored in -70°C freezers. The E.coli-BL21-pJET1.2-CadA/CadR cells were freshly cultured and sourced for each heavy metal treatment. Briefly, A single colony of E.coli-BL21 containing the pJET1.2-CadA/CadR plasmid was grown overnight at 37°C. The overnight culture was diluted 10-fold in minimal (M9) medium supplemented with 100 µg/mL ampicillin and incubated at 37°C in an orbital shaker at 200 rpm until the optical density at 600 nm was 0.6 Au (OD₆₀₀ ~ 0.6). Immediately after absorbance had reached 0.6 Au, cells were seeded into 96 well plates for heavy metal treatments [27].

2.3. Heavy metal solutions for treatments

The 100 ppm stock solutions of Cd²⁺, Pb²⁺, Zn²⁺, Ni²⁺, Fe³⁺ and AsO₄³⁻ ions were prepared by using CdCl₂, Pb(NO₃)₂, Zn(CH₃COO)₂, Ni(NO₃)₂.6H₂O, FeCl₃·6H₂O and Na₂HAsO₄ (Sigma-Aldrich) respectively and dissolving them in ddH₂O. The concentrations of each stock solution were confirmed initially by measuring the concentrations with Microwave Plasma-Atomic Emission Spectrometry (MP-AES) (Agilent 4210) [28]. Heavy metal standards of 0.1 ppm, 0.5 ppm, 1.0 ppm, 2.0 ppm, 3.0 ppm, 4.0 ppm and 5.0 ppm prepared from each metal by following a serial dilution method [29] and stored at room temperature for subsequent treatments. All the storage, handling, treatments, discarding of heavy metal contaminated samples and environmental releasing regulation were carried out by strictly following the standard Material Safety Data Sheet (MSDS) protocols as described by Sigma-Aldrich.

2.4. Confirmation of biosensing activity

2.4.1. Polymerase Chain Reaction (PCR) and quantitative Polymerase Chain Reaction (qPCR)

The successful transformation of pJET1.2-CadA/CadR plasmids into E.coli-BL21 cells were confirmed by carrying out a colony PCR reaction with transformed bacterial cells [30]. Briefly, an isolated E.coli-BL21 transformed colony was picked with a sterilized tool and transferred into a PCR tube. The PCR reaction was performed in a 50 µL volume of PCR mixture by adding 5 µL of 10× Ex Taq Buffer (with Mg²⁺), 4 µL of 2.5 mM dNTPs, 40 pmol of each primer, 50 ng of cDNA, and 5 U of Ex Taq polymerase (TaKaRa). PCR conditions were set as follows: initial denaturation at 94°C for 3 min, there after 35 cycles of amplification at 94°C for 30 s, 59°C for 30 s, and 72°C for 1.5 min, with a final extension at 72°C for 5 min. Subsequently, the resulting PCR product was resolved on an agarose gel. Primer sequences are; CadA/CadR–F = 5′-ATGAAGATCGGTGAACTGGCGA-3′, CadA/CadR–R = 5′-GCCAACCCTCCTCCAAT-3′ and amplicon size is 652 bp. The chemically synthesized CadA/CadR genetic circuit was used as the positive. The PCR buffer was used as the negative control.

To monitor the production of eGFP mRNA upon the activation of gene circuit, a quantitative Polymerase Chain Reaction (qPCR) was performed, and are reported in accordance with the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) [31]. Primers specific to the eGFP coding sequence were designed by using PrimerQuest Tool (Integrated DNA Technologies, USA) based on gene sequence provided by http://www.ncbi.nlm.nih.gov for eGFP gene sequence. Primer specificity was confirmed using primer-BLAST (https://www.ncbi.nlm.nih.gov/tools/primer-blast/). Primer sequences are eGFP-F = 5′- GCTACCCCGACCACATGAA- 3′ and eGFP-R = 5′-GACGTTGTGGCTGTTGTAGT − 3′. The freshly cultured E.coli-BL21 cells were sourced for treatments as described in section 2.2. Subsequently, cells were treated with Cd²⁺, Pb²⁺, Zn²⁺ and Ni²⁺ as a series of concentrations from 1.0 ppb to 6.0 ppb. The heavy metal treated cells were incubated for 2 hours at 37°C and subjected to RNA extraction using QIAprep Spin Miniprep Kit by following manufacturer’s protocol. The cDNA was prepared using iScript™ cDNA Synthesis Kit by following manufacturer’s protocol and aliquoted to prepare the qPCR reaction mixture of HOT FIREPol EvaGreen qPCR Mix Plus (ROX), 10.0 µL and cDNA template, 5.0 µL and reaction conditions were set to initial denaturation, 95 ⁰C for 15 mins; denaturation, 95°C for 15 seconds; annealing. 59°C for 20 seconds; extension, 72°C for 20 seconds; for 40 thermal cycles (Biorad CFX96 Touch Real-Time PCR Detection System). The housekeeping gene of 18S ribosomal RNA (18SrRNA) was used as the reference gene.

2.4.2. Fluorescent microscopy and Fluorimetry

To visually image the green fluorescent signals, E.coli-BL21-pJET1.2-CadA/CadR cells exposed to 2 ppb of Cd²⁺ and 2 ppb of Pb²⁺ for 2 hours were harvested after centrifugation at 3500 x g for 5 min. at 4°C and they were then washed with phosphate buffered saline solution (PBS) and resuspended in PBS solution supplemented with 0.3% as described by Ravikumar [26]. Microscopic slides were prepared in order to obtain a single layer of isolated cells [32]. Cells were observed under fluorescent microscope (Olympus BX53; magnification; 600X, Excitation wavelength range = 460–490 nm; filter; FITC) and the fluorescence images were captured and exported as JPG images. A 2 ppb of Fe³⁺ treated E.coli-BL21-pJET1.2-CadA/CadR, 2 ppb of Ni²⁺ treated E.coli-BL21-pJET1.2-CadA/CadR, heavy metal untreated E.coli-BL21-pJET1.2-CadA/CadR and heavy metal untreated wild type E.coli-BL21 cells were used as control experiments separately.

To investigate the correlation between heavy metal concentrations and eGFP signal intensities, fluorimetry was used. The E.coli-BL21-pJET1.2-CadA/CadR cells were treated with Cd²⁺, Zn²⁺, Pb²⁺ and Ni²⁺ solutions at the concentration points of 1, 2, 3, 4, 5 and 6 ppb. Subsequently, the heavy metal treated cells were incubated for 2 hours before subjecting to fluorometric readings. The fluorometric readings were recorded using Hitachi Fluorescent Spectrophotometer FL-7000 with a 96-well microplate reader accessory. The instrument parameters were set to excitation wavelength at 488 nm and the emission wavelengths in the range of 450– 550 nm. Triplicate measurements were obtained for each sample and the mean values were taken. The obtained relative fluorescence intensity (RFU) values were plotted against the metal ion concentrations in a line graph [33].

2.5. Digital image processing based fluorescent signal calibration

The fluorescent intensities of microscopic images were analysed using image processing software, ImageJ2 bundled with 64-bit Java 1.8.0_112 [34]. Briefly, three isolated single cells were selected from each image, and cell boundaries were marked with the freedom selection tool and then retrieved the Area, Mean Gray Value, Minimum/Maximum Gray Values, and Integrated Density. The Gray values were measured simultaneously for the immediate background of each cell. The calculated mean intensity values were then converted into Corrected Total Cell Fluorescent (CTCF) values by applying the equation described elsewhere [35]. The average CTCF values of all biological replicates were tabulated corresponding to the calibration graphs.

2.5.1. Concentration dependent signals

The freshly cultured E.coli-BL21-pJET1.2-CadA/CadR cells were sourced as described in the section 2.2. The cells were mixed with 1, 2, 3, 4, 5 and 6 ppb concentrations of Cd²⁺, Pb²⁺, Zn²⁺, Ni²⁺, Fe³⁺, AsO₄³⁻ and 1:1 ratio 0.5, 1, 2, 3, 4, 5 and 6 ppb concentration combinations of [Cd²⁺ + Pb²⁺], [Cd²⁺ + Zn²⁺] and [Pb²⁺ + Zn²⁺] and incubated for 2 hours at 37°C without shaking. These cells were subjected to fluorescent microscopy and images generated were exported and processed as described in the sections 2.4.2 and 2.5, respectively to measure biosensing signals. Triplicate measurements were obtained for each sample and the mean value was taken. Data were plotted on Corrected Total Cell Fluorescent (CTCF) Vs Heavy metal concentration [ppb] graphs to evaluate correlations of fluorescent signals.

2.5.2. Time dependent induction

The effect of heavy metal incubation time on the intensity of fluorescent signals were monitored by conducting Cd²⁺, Pb²⁺ and Zn²⁺ treatments at different time points of 0, 1, 2, 3, 4, 5, 6 and 7 hours with the concentration gradient of 1, 2, 3, 4, 5 and 6 ppb. The fluorescent intensity data converted into CTCF values from each time point were plotted on 3 dimensional plots with the Z-axis representing fluorescent intensities in CTCF, the Y-axis representing heavy metal concentration in ppb and the X- axis representing Time (hours). In generating the plots, the multiple experimental data was saved in the table format in three separate .csv files dedicated for Cd²⁺, Pb²⁺ and Zn²⁺. To visualize the data in 3-Dimentions (3D), Jupyter Notebook IDE v6.1.1 (https://jupyter.org/) was used. The code was implemented in Python v3.7.7 (https://www.python.org/downloads/release/python-377/). Initially, .csv files (Comma Separated Values) containing data were loaded into data frames (https://pandas.pydata.org/pandas-docs/stable/reference/frame.html) for visualization using Pandas library v1.1.0 (https://pandas.pydata.org/). Subsequently, using Plotly library v4.9.0 (https://plotly.com/), data in data frames was visualized in 3D Surface Plots.

2.6. Validation of physiological conditions

2.6.1. Growth

The typical sigmoid shaped bacterial growth curve was reconstructed upon the presence of heavy metals in the medium with a modified protocol [27] to evaluate the toxicity effect of heavy metals on bacterial cells. Initially, a single colony of bacterial cells was inoculated in freshly prepared 15 mL of LB broth and the inoculated culture was incubated overnight at 37 ⁰C. This culture was used as the starting culture and added 1 mL for 50 mL fresh LB broths treated to achieve effective concentrations of 1 ppb, 2 ppb, 3 ppb, 4 ppb, 5 ppb, 6 ppb and 1 ppm Cd²⁺ in the medium. Absorbance readings at 600 nm were measured at 0, 1, 2, 3, 4, 5, 6, 7 and 8 hour time points. An untreated, inoculated LB broth was used as the control experiment. A line graph was plotted between OD_{600 nm} Vs. time (hours) for each treatment separately.

2.6.2. pH

The optimum pH conditions for biosensing activity were assessed by plotting the graph between pH values (2–12 pH) vs CTCF values. A single colony of E. coli-BL21 harbouring pJET1.2-CadA/CadR plasmid was grown overnight at 37°C. The overnight culture was diluted 10-fold in minimal (M9) medium supplemented with 100 µg/mL ampicillin and incubated with 2.0 ppb concentration of Cd²⁺ in the medium in an orbital shaker at 200 rpm with a pH gradient from 2–12 pH for 2 hours optimal incubation time. The cells were subjected to fluorescent microscopy and image processing to quantify the temperature dependent biosensing signals. Triplicate measurements were obtained for each sample and the mean value was taken.

2.6.3. Temperature

The optimum incubation temperature in the medium on biosensing activity was examined by plotting the graph between temperature of the medium (0–60°C) vs CTCF values. A single colony of E. coli-BL21 harbouring pJET1.2-CadA/CadR plasmid was grown overnight at 37°C. The overnight culture was diluted 10-fold in minimal (M9) medium supplemented with 100 µg/mL ampicillin and incubated with 10.0 ppb concentrations of Cd²⁺, Pb²⁺ and Ni²⁺ in the medium in an orbital shaker at 200 rpm with a temperature gradient of 0, 25, 37, 45 and 60°C with 2 hours of optimal incubation time. The cells were subjected to fluorescent microscopy and image processing to quantify the temperature dependent biosensing signals. Triplicate measurements were obtained for each sample and the mean values were taken.

2.7. Statistical Analysis

The One-way (analysis of variance) ANOVA statistical analysis was performed by assigning the expression as the dependent data and heavy metal ion concentration and type as independent data using IBM SPSS v21. In order to find the metal ions which significantly gives higher expression than others the least significant difference (LSD) post-hoc test was performed at 95% confidence interval (CI). P < 0.05 was considered as the significant level of difference.

3.1. The genetic circuit and heavy metal sensing mechanism

The key DNA motifs incorporated into the genetic circuit of this study were CadR gene coding sequence of P. aeruginosa, CadA gene promoter sequence of P. aeruginosa, the coding sequence of eGFP protein and the DNA sequence corresponding to T7 promoter. In lengths, CadR is 470 bp long, CadA is 114 bp long, eGFP is 720 bp long and T7 is 19 bp long. The full length of complete DNA sequence is 1460 bp. The genetic architecture of the gene construct is as shown in Fig. 1. Functionally, the genetic circuit in this study operates as a NOT molecular logic gate to detect Cd²⁺, Pb²⁺ and Zn²⁺. The NOT molecular logic gates are simple ON-OFF type switches which trigger the expression of reporter gene upon the presence of effector molecules and the expression is terminated when the effector molecules are absent [36]. The heavy metal sensing molecular mechanism is diagrammatically illustrated in Fig. 2. In this circuit, the molecular mechanism of heavy metal sensing is distributed between both the plasmid DNA and E.coli-BL21 genomic elements. On the E.coli-BL21 genome, T7 RNA polymerase is available under the control of the lacUVS promoter. T7 RNA polymerase proteins produced through E.coli-BL21 genome subsequently function as an efficient polymerase enzyme in the initial gene transcription process of the gene circuit. The modified pJET1.2 plasmid vector consists of key genetic components corresponding to the metal sensing as the CadR gene sequence is placed under the regulation of the T7 promoter and regulates the expression of CadR gene. The T7 promoter ensures the efficient transcription of the CadR gene, and its translated protein specifically interacts with Cd²⁺, Pb²⁺ and Zn²⁺ in order to induce conformational changes in the CadR protein structure. Subsequently, the conformationally changed CadR proteins are directed towards the eGFP gene segment, which has been coupled with the CadA promoter and will trigger the expression of fluorescent signal corresponding to heavy metal dose.

The biosensors based on genetically engineered microorganisms have arguably received considerable attention over the conventional analytical techniques due to the feasibility of their application on site during environmental toxicity assessment [37–39]. Specific genes for selective heavy metal sensing can be retrieved by screening up or down regulated genes in transcriptional profiles of heavy metal treated bacterial cells [6, 40, 41, 42]. The CadA/CadR operon of Pseudomonas aeruginosa (P. aeruginosa) is one of the well annotated natural gene systems in bacteria for metal tolerance and homeostasis mechanisms [43, 44]. An in-silico promoter analysis study has also demonstrated its specific responses for Cd²⁺ [45]. Further, its Metal Responsive Elements (MREs) located in the promoter overlapping regions have been shown to be specific for Cd²⁺ Pb²⁺ and Zn²⁺ [46]. A previous biosensor developed on Cad/CadC promoter system in another bacterial strain (Staphylococcus aureus) has been sensitive to detect Cd²⁺, Pb^2+, and Sb³⁺ with low detection limits of 0.1 nmol/L, 10 nmol/L, and 0.1 nmol/L respectively [6]. Thus, based on collective evidence, we chose the CadA and CadR genes of P. aeruginosa to develop Cd²⁺, Pb²⁺ and Zn²⁺ sensing DNA construct in current study.

3.2. Molecular and functional confirmation of biosensing activity

3.2.1. PCR and qPCR

The pJET1.2-CadA/CadR plasmids in transformed bacterial cells were confirmed by the presence of a 652 bp long PCR product on agarose gel. No bands were detected in the wells corresponding to non-transformant E.coli-BL21(DE3) cells and negative control PCR products (Supp. Figure 1). This confirms the efficient transformation of pJET1.2-CadA/CadR plasmids into E.coli -BL21(DE3) cells. The successfully transformed E.coli-BL21(DE3)-pJET1.2-CadA/CadR cells were tested for the expression of eGFP mRNA by qPCR. The eGFP mRNA loads were plotted in a graph of relative gene expression against heavy metal ion concentrations. Interestingly, mRNA levels were elevated significantly in Cd²⁺, Zn²⁺ and Pb²⁺ treatments while no significant mRNA expression was associated with Ni²⁺ treatment. As per the significant test of LSD, Cd²⁺, Zn²⁺ and Pb²⁺ showed P values of 0.019, 0.026 and 0.082 respectively deviating significantly from Ni²⁺. Along the plots, expressional difference between concentration points (3, 4, 5 and 6 ppb) were significantly different for all three Cd²⁺, Zn²⁺ and Pb²⁺ plots (Fig. 3). Accordingly, the gene expression outcomes have indicated the capability of modified E.coli biosensor cells to potently produce eGFP mRNA upon the treatment of heavy metals that are specific to genetic circuit. As per our knowledge, this is the first insight into the assessment of reporter mRNA loads of a genetically engineered bacterial biosensor for heavy metal analysis and overall result reflects that the mRNA quantity produced due to the exposure of specific heavy metals was significantly risen compared to the exposure of non-specific metal ions. Genes can be utilized as biomarkers and the expression of genes can be integrated in biosensing applications in order to sense various substances [47]. Even though the direct assessment of gene expression via analysing mRNA loads has not been recorded with microbial biosensors, mRNA quantification can also be considered in microbe based biosensing applications in future.

3.2.2. Fluorescent microscopy and Fluorometry

The bacterial cells harbouring pJET1.2-CadA/CadR construct treated with 2 ppb of Cd²⁺ and 2 ppb of Pb²⁺ ions exhibited distinguished green colour signals under fluorescent microscope with eGFP filter (Fig. 4). The control cells; Wildtype E.coli-BL21 (heavy metals untreated), genetically modified E.coli-BL21-CadA/CadR-eGFP (treated with 2 ppb of Ni²⁺), Wildtype E.coli-BL21 (treated with 2 ppb of Cd²⁺), Wildtype E.coli-BL21 (treated with 2 ppb of Pb²⁺) and genetically modified E.coli-BL21-CadA/CadR-eGFP (heavy metals untreated) did not show any detectable signals in the fluorescent microscopic imaging. The Genetically modified E.coli-BL21-CadR/CadA-eGFP cells (treated with 2 ppb of Fe³⁺) did not show any signals visible under microscope similar to controls. The microscopic imaging result confirmed that the genetically modified biosensing cells have expressed the eGFP proteins due to the exposure of heavy metals that are specific to our genetic circuit. Similarly, a Green Fluorescent Protein reporter based bacterial biosensor developed in a previous study to detect bioavailability of Cd, Pb and Sb has shown intensified fluorescent signals under the fluorescent microscope coupled with a cooled charged device (CCD) camera with x1000 magnification [6]. Moreover, another recent study conducted by Ravikumar [26] has demonstrated dual colour overlays and single colour microscopic images with intense fluorescence signals at the exposure for 0.1 mM Zn²⁺, Cu²⁺ and combination exposure. As exposed to the heavy metal mixture, The GFP and Red Fluorescent Protein (RFP) reporters simultaneously responded for two different heavy metal ions and detected under the Olympus reflected fluorescence microscope equipped with a Peltier-cooled CCD camera.

The intensities of green fluorescent signals due to the production of eGFP protein in E.coli cells were quantitatively analyzed by fluorometry. The fluorescent intensities of all three specific metals, Cd²⁺, Zn²⁺ and Pb²⁺ were significantly deviated from non-specific Ni²⁺ treatment with the P value of 0.000. The correlation between fluorescent intensity in RFU and heavy metal concentration in ppb were observed to be linear for all three specific metal ions with the R² values of 0.9637, 0.9703, 0.9023 respectively for Cd²⁺, Zn²⁺ and Pb²⁺. Comparatively, Cd²⁺ showed the highest intensity values for fluorescent signals while Zn²⁺ being the second highest and Pb²⁺ with the lowest values of fluorescent intensity. Even though the mean intensity values were slightly different for these three metal ions, they were not significantly different from each other (Fig. 5). As observed in the fluorometric experiment, the E.coli-BL21-pJET2.1-CadA/CadR-eGFP cells have been able to fluoresce specific fluorescent signals towards Cd²⁺, Zn²⁺ and Pb²⁺ and have been significantly deviated from non-specific Ni²⁺ treatment. Similarly, the recent study conducted by Ravikumar’s research group [26] has also illustrated the capacity of a GFP and RFP dual reporter system to be linearly and significantly responsive against Ni²⁺ and Zn²⁺ in a genetically modified bacterial strain.

3.3. Calibration of biosensor

3.3.1. Concentration dependent responses

To calibrate the fluorescent signals due to individual heavy metal treatments, fluorescent signals converted in CTCF values were plotted against heavy metal concentrations in ppb at the contractions of 1, 2, 3, 4, 5 and 6 ppb (Fig. 6). Interestingly, Cd²⁺, Zn²⁺ and Pb²⁺ exhibited linear correlations with the R² values of 0.9809, 0.9761 and 0.9758 respectively. The lowest levels of fluorescent expressions were observed for AsO₄³⁻ at a negligible level. The highest expressional level was observed for Cd²⁺. The plots of Cd²⁺, Zn²⁺ and Pb²⁺ were deviated significantly from AsO₄³⁻, with the P value of 0.000. The mean expressions of Cd²⁺ and Zn²⁺were not significantly deviated from each other with the p value of 0.090 but significant from Pb²⁺ with the p value of 0.000 for Cd²⁺ to Pb²⁺ and p value of 0.000 for Zn²⁺ to Pb²⁺. Taken together, individual heavy metal treatment outcomes have shown the capacity of E.coli-BL21-pJET2.1-CadA/CadR-eGFP cells to produce accurate biosensing signals towards Cd²⁺, Zn²⁺ and Pb²⁺ while distinguishing them from other non-specific heavy metals Fe³⁺, Ni²⁺ and AsO₄³⁻. The higher specificity of Cd²⁺ and Zn²⁺ compared to Pb²⁺ can corelate to the different chemical properties of the metals and the variations of their binding capacities to the promoter region of the pJET1.2-CadA/CadR gene construct [48].

The tendency of Cd²⁺, Zn²⁺ and Pb²⁺ to cause synergetic interactions with CadA/CadR-eGFP genetic circuit was examined by combining above heavy metals as mixtures for subsequent treatments. Upon mixing, Cd²⁺+Zn²⁺ mixture showed significantly high CTCF signals when compared to Cd²⁺+Pb²⁺ and Pb²⁺+Zn²⁺ treatments at each combinatorial total heavy metal concentrations (Fig. 7). In general, the treatments with heavy metal mixtures showed the ability of these metals to competitively interact with the gene circuit due to similarities and dissimilarities of chemical properties. These synergetic interactions of multiple metal ions with a single gene circuit are disadvantageous when performing biosensing operations with the samples which contain heavy metal mixtures. However, mathematical approaches can be implemented to determine the metal ion concentrations separately in a mixture by using a single reporter gene. The use of dual reporter molecules with separate promoters also reduces this combined effect when analysing mixtures. Ravikumar has proven the reduced disadvantage due to combination effect by using two separate reporter genes and promoters [26]. In this study, the reporter genes were given two different wavelengths of fluorescence signals which can be identified separately or as a color overlay.

3.3.2. Time dependency of fluorescent signals

To activate heavy metal sensing mechanism of modified bacterial cells, exogenous metal ions are required to cross cell membranes to interact and trigger the expression of genetic circuit in modified cells. This process of metal absorbance takes a predetermined period of time and is represented by cell incubation time of the sample of interest. To examine this aspect of E.coli-BL21-pJET2.1-CadA/CadR-eGFP cells, the fluorescent signals in CTCF were plotted against heavy metal concentrations and the incubation time on a same graph assigning X axis for concentration, Y axis for incubation time and Z axis for fluorescent intensity in CTCF (Fig. 8). As observed, Cd²⁺, Zn²⁺ and Pb²⁺ exhibited their highest fluorescent intensity values when incubation time was the longest. Accordingly, Cd²⁺ at 7 hours incubation and 6 ppb concentration showed CTCF = 87.144K (Fig. 8A) of intensity while Zn²⁺ and Pb²⁺ showed CTCF = 73.935K (Fig. 8B) and CTCF = 55.514K (Fig. 8C) respectively. Moreover, CTCF signals were gradually increasing when the incubation time was increased for all three metal ions. This observation has been universal throughout other microbial biosensors as well. In the previous studies, similar trends have been observed in the Arsarnate/Arsanite detecting bacterial biosensor developed by Stocker [49] and the GFP based biosensor developed by Liao [6] to detect heavy metal bioavailability in soil.

3.4. Validation of growth conditions for biosensing bacterial cells

As compared to heavy metal untreated E.coli-BL21-pJET2.1-CadA/CadR-eGFP growth curve, any of the growth curves of Cd²⁺ treated bacterial cells with the concentrations of 1, 2, 3, 4, 5 and 6 ppb was not significantly deviated and tended to follow the typical sigmoid shape of bacterial growth. Meantime, the growth of 1 ppm treatment was insignificant and did not exhibited any growth at every time point observed within 1–8 hours. (Fig. 9) This observation indicates that the growth of E.coli-BL21-pJET2.1-CadA/CadR-eGFP cells have not been affected by the low heavy metal concentrations within ppb range but it has been severely affected at the high concentration of 1 ppm. Heavy metals can cause toxicity effects on biological cells including microorganisms [50]. As our microbial biosensor has been designed to detect heavy metals in contaminated samples, adverse effects of corresponding heavy metals on bacterial cell growth were initially examined by reconstructing the typical sigmoid curve of bacterial cell growth upon the presence of Cd²⁺ in the medium.

To understand the most suitable pH range to utilize E.coli-BL21-pJET2.1-CadA/CadR-eGFP cells for biosensing operations, the fluorescent signals of Cd²⁺, Zn²⁺, Pb²⁺ and Ni²⁺ 2 ppb treated cells were observed at different pH levels of 2, 4, 6, 8, 10 and 12. As observed in the graph plotted between CTCF values and pH, all three plots indicated the highest intensities in CTCF expression within the pH range of 6–8 with the peak expression at 7 (Fig. 10). Ideally, wildtype bacterial cells exhibit their optimal physiological activities under specific pH levels of the growth medium. For E.coli cells, the optimal growth pH condition is shown to be 5.5-7.0 [51]. Therefore, biosensing cells in our study were chosen to be applied for application at the constant pH value of 7.0 in the medium.

The effect of temperature variations on biosensing signals were assessed observing intensity of fluorescent signals of the cells grown in between 0–60°C and treated with 2 ppb of Cd²⁺, Pb²⁺, Zn²⁺ and Ni²⁺ for 2 hrs. The normalized CTCF values were considerably lowered in the temperatures which are lower than the room temperature (28°C) and temperatures higher than the 45°C. The calculated CTCF values in the range of 28–45°C were not shown any significant increment or decrement. When considering the Ni²⁺, the calculated CTCF values within 0–60°C were not shown any significant variations (Fig. 11). The temperature variations are directly affected by the several biological processes inside the cells such as protein folding and enzyme activations [52]. Based on this observation, optimum temperature of 37 ⁰C was selected as the most suitable temperature to conduct subsequent biosensing applications.

Bacterial cells as microorganisms are sensitive to various environmental conditions including temperature, pH and nutritional levels in the medium [53]. To utilize bacterial cells as the host organism for biosensing applications, modified bacterial cells require validation information for its applicational range describing its optimal temperature, pH of growth medium, nutritional supply and tolerance to toxic substances. To ensure all the essential supplements required for bacterial cell growth, LB broth and LB agar were used as mediums for the purposes of growing the cells throughout the experiments [54] in this study in addition to optimum pH and incubation temperature.

In summary, for detecting heavy metal contaminations in water samples, GEM biosensors developed with bacteria have shown to provide specific measurements with less labour work. A handful of bacterial biosensors have been developed to detect various combinations of heavy metals based on gene circuits sensitive to specific heavy metal combinations and a variety of reporter molecules but still lacking intensive calibration and validation detail before applying them in on-sight applications. In this study, we have demonstrated the construction of an E.coli-BL21 bacterial biosensor based on a natural bacterial CadA/CadR gene operon system coupled with eGFP reporter gene to specifically sense for Cd²⁺, Pb²⁺ and Zn²⁺. The activity of biosensing cells have been confirmed with a combination of molecular and fluorometric techniques. The fluorescent responses of biosensing cells were calibrated towards Cd²⁺, Zn²⁺ and Pb²⁺ separately with digital image processing techniques to make it feasible to integrate in future potential digital platforms like wide-field fluorescence microscopy on a cell phone as described by Zhu [55] and highly sensitive fluorescence detection model using smartphone camera described in Cao Z. [56]. The calibration data has been shown to be promising in utilizing these cells to detect all three Cd²⁺, Zn²⁺ and Pb²⁺ in comparatively low concentration range of 1–6 ppb with optimum incubation time of cells for 2 hours with the metal sample. Further, our genetically modified cells have exhibited its application parameters resembling the typical growth scales of wildtype bacteria. These features validate our bacterial biosensor as a potential candidate in future on-sight Cd²⁺, Zn²⁺ and Pb²⁺detection applications.

Ethical approval and consent to participate: Not required.

Consent for Publications: Not Applicable

Availability of data and materials:

The standard data sets analysed during the current study were included in the manuscript. Additional data or materials can be obtained from the corresponding author upon request.

Competing interests:
Authors do not have any competing interests.

Funding:

National Research Council of Sri Lanka [NRC TO -16-18]

Authors' contributions:

H. M. L. P. B. Herath– Conceptualization, Data curation, Writing- Reviewing and Editing, Statistics. W.R.M. de Silva- Methodology, Data curation, Writing – original draft preparation. R.S. Dassanayake- Supervision, Data curation, Writing- Reviewing and Editing. Y.I.N.S. Gunawardene- . Methodology, Data curation, Writing – original draft preparation, Supervision. J. R. P. Jayasingha- Methodology, Data curation, Writing – original draft preparation. M. K. Gayashan- Methodology, Data curation, Writing – original draft preparation. L.O.B. Afonso- Methodology, Data curation, Writing – original draft preparation, Methodology, Data curation, Writing – original draft preparationK.M.N. de Silva- Methodology, Data curation, Writing – original draft preparation, Supervision.

Acknowledgements

This study was financially supported by the National Research Council of Sri Lanka [NRC TO -16-18]

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A novel Genetically Engineered Microbial (GEM) biosensor for specific detection of Cd 2+ , Zn 2+ and Pb 2+ heavy metals; calibration and validation aspects

Status:

Journal Publication

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Abstract

Background

Results

Conclusion

Figures

1. Introduction

2. Material And Methods

2.1. Construction of gene circuit

2.2. Microbial strains, culture conditions and production of biosensing cells

2.3. Heavy metal solutions for treatments

2.4. Confirmation of biosensing activity

2.4.1. Polymerase Chain Reaction (PCR) and quantitative Polymerase Chain Reaction (qPCR)

2.4.2. Fluorescent microscopy and Fluorimetry

2.5. Digital image processing based fluorescent signal calibration

2.5.1. Concentration dependent signals

2.5.2. Time dependent induction

2.6. Validation of physiological conditions

2.6.1. Growth

2.6.2. pH

2.6.3. Temperature

2.7. Statistical Analysis

3. Results And Discussion

3.1. The genetic circuit and heavy metal sensing mechanism

3.2. Molecular and functional confirmation of biosensing activity

3.2.1. PCR and qPCR

3.2.2. Fluorescent microscopy and Fluorometry

3.3. Calibration of biosensor

3.3.1. Concentration dependent responses

3.3.2. Time dependency of fluorescent signals

3.4. Validation of growth conditions for biosensing bacterial cells

4. Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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