Arsenic (As) is an extremely toxic metalloid that has attracted considerable attention worldwide due to its harmful effects on humans, animals and plants. It is estimated that millions of people around the world at risk of being affected by As contamination (Rahman et al., 2017). As species mainly enters the soil through different routes, including surface runoff of industrial As-containing wastewater, the application of pesticides containing As, chemical fertilizers, organic fertilizers and other human activities (Boulanger et al., 2019). In addition, natural factors such as volcanic movement, flooding, chemical weathering also contribute to excessive As levels in the soil (Huq et al., 2020). The As that enter the soil can accumulate in crops and enter the human body through the food chain, leading to the development of diseases including skin, lung and bladder cancer (Palansooriya et al., 2020; Palma-Lara et al., 2020).
As in the environment can be found in both inorganic and organic forms, while the inorganic forms, including arsenate, As(V) and arsenite, As(III), are the predominant forms in soils, and studies have found that As(III) has greater mobility and greater toxicity than As(V) (Gao et al., 2022; Gorny et al., 2015; Lee et al., 2019). Changes in the form and valence of As in soil directly affect its bioavailability and toxicity, and thus its environmental risk. Therefore, it is important to conduct environmental risk assessment of As in soil to safeguard soil health. Two commonly used approaches of environmental risk assessment include the ground accumulation index method and potential ecological risk assessment method. However, they all based on the detection of concentrations of As by traditional analytical methods such as inductively coupled plasma emission spectrometry (ICP-OES) (Henry and Thorpe, 1980) and atomic absorption spectrometry (AAS) (Aggett and Aspell, 1976). These methods usually require expensive instruments and specialized personnel to pre-treat and analyze the samples. In addition, they are unable to reflect the bioavailability of As (Bereza-Malcolm et al., 2015). Therefore, streamlining this risk assessment process is essential for the rapid identification of environmental risks of As in soil.
In recent years, whole-cell bioreporter (WCB) technology has been used for the assessment of the bioavailability of heavy metals in the environment and consequently to evaluate their environmental risks (Huang et al., 2024). WCB is a living genetically engineered bacterial, which can sense target chemicals and generate electrochemical or optical signals that can be detected, and determine the bioavailability or toxicity of pollutants (Dhyani et al., 2022). In addition, it has been reported that WCB can both assess the bioavailability of As in the environment and differentiate the different forms of As (Yoon et al., 2016b). The application of WCB technology, as reviewed herein, represents a progressive shift toward more sensitive, cost-effective, and ecologically relevant environmental risk assessment.
2 Construction principles of WCB for detecting As bioavailabilityWCB technology, by harnessing the biological responses of microbial systems, offers a direct measure of As bioavailability and its potential risks. Generally, As-WCBs were constructed based on sensing element from As-resistance operon ars and reporter genes (Kaur et al., 2015). Bacteria such as E. coli, Pseudomonas, and Staphylococcus aureus are often selected as host strains of As-WCB because they carry genes with specific resistance mechanisms to As, exhibiting As resistance (Bereza-Malcolm et al., 2018). ars operon has been found in above-mentioned bacteria and known as the optimal microbial As detoxification system (Ordóñez et al., 2005). Hedges and Baumberg (1973) and Mobley et al. (1983) found that the plasmid R773 in Escherichia coli (E. coli) can help strains acquire As resistance, and further research on the R773 plasmid revealed the existence of a gene cluster, the ars operon, conferring As resistance. ars operon contains five co-transcribed genes (arsRDABC), arsR is identified as As regulatory gene, and the encodes regulatory protein ArsR which controls the basal expression level ensuring that the expression level of As resistance operon in different environments is within a certain range (Arik et al., 2023). Since it plays an important role in regulation of intracellular As levels, ArsR regulatory protein from bacterial origin has been often deployed in WCB technology for determination of environmental As contamination. When the sample does not contain As(III), ArsR binds to the binding site (ABS) of the promoter of ars operon (ParsR), inhibiting its expression (Valenzuela-García et al., 2023). Reversely, in the presence of As(III), As(III) binds to ArsR and changes its conformation, relieving ArsR inhibition of ParsR, which is shown in Figure 1 (Yoon et al., 2016b). The ArsRBC proteins in the ars operon regulated by the ArsR protein cooperate to form a regulatory mechanism for As transport and maintain the balance of As in the cell. Although ArsR only responds to As(III), As-WCB can also respond to As(V) because sensing strains containing chromosome-encoded arsRBC operons produce moderate resistance to As and arsenate is reduced to arsenite in bacterial cells (Elcin and Öktem, 2019). Apart from ArsR, ArsC reduces As(V) to As(III), ArsB excretes As(III) from cells using the potential drive on the cell membrane, and the structural gene arsA, which codes for the As ATPase subunit ArsA, and the regulatory gene arsD, which codes for the arsenite chaperone that transports As(III) to the ArsAB transporter complex (Irvine et al., 2017; Yang et al., 2011; Yu et al., 2021).
Figure 1. Schematic diagram of whole-cell bioreporter for As detection.
In addition to the ars operon, As-WCB developed using the nikA promoter of the nik operon in E. coli also specifically detects As. Similar to the mechanism of action of the ars operon, As(III) interacts with residues (His79 and His92) on NikR, and the conformational change in NikR may lead to its release from the promoter region of the nik operon, which would increase the transcription of the reporter gene for the detection of As(III) in soil (Yoon et al., 2016a).
Since most of the As sensing WCB are based on bacterial cells, the type, culture, and number of host bacteria, as well as the growth status of bacteria, may affect the detection performance of WCB. For example, Wu et al. (2023) discovered that the optimal assay stability was attained when WCB was incubated at 30°C until the exponential growth period and that selecting a sample volume of 200 μl produced the highest luminescence or fluorescence output. Therefore, on the basis of extensive research on As-WCB construction, optimizing the detection environment and promoting its practical applications will be the main research target in this field.
3 Application of WCBs in assessing As bioavailabilityCai and DuBow (1997) constructed the first WCB based on the fusion of an As resistance operon and luciferase gene in E. coli for the detection of chromate arsenate, which provided a good research direction for the detection of As toxicity by WCB. Over the next two decades, to enhance the sensitivity, specificity and stability of As detection, researchers have developed the As-WCB using different sensing and reporter elements. A novel As-WCB constructed by fusing the nikA gene from nik operon in E. coli and the green fluorescent protein encoding gene which selective only for As among eight metals has been used for the determination of As in soil (Yoon et al., 2016a). Pola-López et al. (2018) amplified the As input signal by adding a T7 RNAP gene amplifier module within the strain, significantly enhanced the sensitivity performance of the WCB and successfully detected arsenate in the range of 5–140 μg/L with a response time as little as an hour. Chen et al. (2022) combined an As-WCB based on the optimized ParsOC2 promoter with a smartphone color recognition application to analyze As in groundwater samples with a detection limit as low as 0.24 μg/L.
It is worth noting that As in the natural environment usually exists in the form of As(III) or As(V), which are different in toxicity [As(III) possesses a toxicity 60 times greater than As(V)]. They can be easily transformed into each other when there is a change in the redox potential, pH, and oxygen-enriched state, which poses a great challenge to accurate assess the environmental risk of As in different valence states (Pena et al., 2005). In a recent study, Elcin and Öktem (2019) constructed As-WCB on the basis of arsR regulatory gene of E. coli plasmid R773 and a green fluorescent reporter protein using E. coli MG1655 host strain. The WCB can specifically assess both As(III) and As(V) in phosphate-restricted medium and to differentiate between the two on the basis of the response time at 10 ppb level.
However, no matter how sophisticated genetic engineering techniques are used, they can only be applied in the field outside the laboratory if the WCBs are secured into a suitable platform and become portable sensing devices. For this purpose, immobilization methods that have been developed for WCB include lyophilization (Bilal and Iqbal, 2019), agar (Huang et al., 2024) and calcium alginate entrapment (Tohfegar and Habibi, 2023), and embedded fiber-optics (Zhu et al., 2022). Elcin and Öktem (2020) immobilized the As-WCB cells into agar hydrogels and alginate beads for a first-step field application and reported that under optimal incubation conditions, it could detect 10 μg/L and 200 μg/L of As(III) and As(V) within 5 hour and 2 hour, respectively. In addition, it was found in the experiment that adjusting the cell density of OD600 to 0.4 significantly improved the sensitivity of WCB. Arik et al. (2023) used polycaprolactone (PCL) electrostatically spun fibers as a support material to immobilize WCB, and found that the system was able to be used in natural waters and sensitive only to As which can rapidly detect As(III) in the range of 10–100 μg/L.
In addition, the coupling of WCB with other chemical methods provides new ideas for the field application of WCB. Buffi et al. (2011) attempted to immobilize WCB in agarose beads and integrate them into a microfluidic chip for on-site monitoring of As. Their study showed that the strain maintained performance for up to 1 month when stored in the microfluidic chip at −20°C and was able to respond to arsenate within a concentration bracket of 10–50 μg/L. In a recent study, Sánchez et al. (2021) combined As-WCB with electrochemical measurements, strains produced electrochemically detectable 4-aminophenol in the presence of As(III). The system provides higher accuracy and signal strength than traditional WCB detection methods and has garnered regulatory clearance for field use in both Canada and the United States. Soil systems are more complex than water environment, research on As-WCB for soil on-site measurement is relatively immature. Due to the attenuation of the WCB signal by soil particles, the transmission of the optical signal from the WCB is reduced, thus affecting the accuracy of the results. It has been reported that many studies have neglected the weakening of the WCB signal by soil, which can lead to orders of magnitude errors in the results (Zhang et al., 2022). To date, there is no standard to unify the method, which has brought some challenges for the application of As-WCB in soil. However, in view of the intensity of As contamination in soil, we believe that the development of portable, low-cost, and highly sensitive in situ WCB for detecting As bioavailability in soil will be a future direction.
4 ConclusionsThe environmental contamination of As is highly complex and its toxicity varies according to the different forms present in the soil, making it particularly important to accurately assess and differentiate the bioavailability of these forms of As. WCB reflects the bioavailability of the As and has the potential to discriminate between different forms of As. As yet, WCB has not yet become a standard method for environmental risk assessment of As contamination, and only a small number of WCB has been commercialized. We believe that with continuous and in-depth development, WCB is expected to become an effective environmental risk assessment method for As contamination in soil. As we advance, it becomes crucial to not only understand but also anticipate the ecological impacts of contaminants. WCB technology emerges as a critical tool in this regard, facilitating a more proactive approach to environmental management.
Author contributionsXZhang: Funding acquisition, Project administration, Supervision, Writing – review & editing, Writing – original draft. XZhao: Writing – original draft, Writing – review & editing. CG: Visualization, Writing – review & editing. ZH: Visualization, Writing – review & editing. TG: Writing – review & editing. BL: Writing – review & editing. EE: Writing – review & editing. LH: Writing – review & editing.
FundingThe author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by projects from the National Natural Science Foundation of China (42107245 and 42477518).
Conflict of interestThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's noteAll claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
ReferencesArik, N., Elcin, E., Tezcaner, A., and Oktem, H. A. (2023). Biosensing of arsenic by whole-cell bacterial bioreporter immobilized on polycaprolactone (PCL) electrospun fiber. Environ. Technol. 45, 4874–4886. doi: 10.1080/09593330.2023.2283405
PubMed Abstract | Crossref Full Text | Google Scholar
Bereza-Malcolm, L., Aracic, S., Mann, G., and Franks, A. E. (2018). The development and analyses of several Gram-negative arsenic biosensors using a synthetic biology approach. Sensor. Actuat. B–Chem. 256, 117–125. doi: 10.1016/j.snb.2017.10.068
Crossref Full Text | Google Scholar
Bereza-Malcolm, L. T., Mann, G., and Franks, A. E. (2015). Environmental sensing of heavy metals through whole cell microbial biosensors: a synthetic biology approach. ACS Synth. Biol. 4, 535–546. doi: 10.1021/sb500286r
PubMed Abstract | Crossref Full Text | Google Scholar
Bilal, M., and Iqbal, H. M. (2019). Microbial-derived biosensors for monitoring environmental contaminants: Recent advances and future outlook. Process Saf. Environ. 124, 8–17. doi: 10.1016/j.psep.2019.01.032
Crossref Full Text | Google Scholar
Boulanger, M., Tual, S., Pons, R., Busson, A., Delafosse, P., Guizard, A. V., et al. (2019). Use of arsenical pesticides and risk of lung cancer among french farmers. Occup. Environ. Med. 76:A53. doi: 10.1136/OEM-2019-EPI.142
Crossref Full Text | Google Scholar
Buffi, N., Merulla, D., Beutier, J., Barbaud, F., Beggah, S., van Lintel, H., et al. (2011). Miniaturized bacterial biosensor system for arsenic detection holds great promise for making integrated measurement device. Bioengineered Bugs 2, 296–298. doi: 10.4161/bbug.2.5.17236
PubMed Abstract | Crossref Full Text | Google Scholar
Cai, J., and DuBow, M. S. (1997). Use of a luminescent bacterial biosensor for biomonitoring and characterization of arsenic toxicity of chromated copper arsenate (CCA). Biodegradation 8, 105–111. doi: 10.1023/A:1008281028594
PubMed Abstract | Crossref Full Text | Google Scholar
Chen, S. Y., Zhang, Y., Li, R., Wang, B., and Ye, B. C. (2022). De novo design of the ArsR regulated Pars promoter enables a highly sensitive whole-cell biosensor for arsenic contamination. Anal. Chem. 94, 7210–7218. doi: 10.1021/acs.analchem.2c00055
PubMed Abstract | Crossref Full Text | Google Scholar
Dhyani, R., Jain, S., Bhatt, A., Kumar, P., and Navani, N. K. (2022). Genetic regulatory element based whole-cell biosensors for the detection of metabolic disorders. Biosens. Bioelectron. 199:113869. doi: 10.1016/j.bios.2021.113869
PubMed Abstract | Crossref Full Text | Google Scholar
Elcin, E., and Öktem, H.A. (2019). Whole-cell fluorescent bacterial bioreporter for arsenic detection in water. Int. J. Environ. Sci. Technol. 16, 5489–5500. doi: 10.1007/s13762-018-2077-0
Crossref Full Text | Google Scholar
Elcin, E., and Öktem, H.A. (2020). Immobilization of fluorescent bacterial bioreporter for arsenic detection. J. Environ. Health Sci. Engineer. 18, 137–148. doi: 10.1007/s40201-020-00447-2
PubMed Abstract | Crossref Full Text | Google Scholar
Gao, M., Su, Y., Gao, J., Zhong, X., Li, H., Wang, H., et al. (2022). Arsenic speciation transformation in soils with high geological background: New insights from the governing role of Fe. Chemosphere 302:134860. doi: 10.1016/j.chemosphere.2022.134860
PubMed Abstract | Crossref Full Text | Google Scholar
Gorny, J., Billon, G., Lesven, L., Dumoulin, D., Mad,é, B., and Noiriel, C. (2015). Arsenic behavior in river sediments under redox gradient: a review. Sci. Total Environ. 505, 423–434. doi: 10.1016/j.scitotenv.2014.10.011
PubMed Abstract | Crossref Full Text | Google Scholar
Hedges, R., and Baumberg, S. (1973). Resistance to arsenic compounds conferred by a plasmid transmissible between strains of Escherichia coli. J. Bacteriol. 115, 459–460. doi: 10.1128/jb.115.1.459-460.1973
PubMed Abstract | Crossref Full Text | Google Scholar
Henry, F., and Thorpe, T. (1980). Determination of arsenic (III), arsenic (V), monomethylarsonate, and dimethylarsinate by differential pulse polarography after separation by ion exchange chromatography. Anal. Chem. 52, 80–83. doi: 10.1021/AC50051A020
Crossref Full Text | Google Scholar
Huang, Z., Gustave, W., Bai, S., Li, Y., Li, B., Elçin, E., et al. (2024). Challenges and opportunities in commercializing whole-cell bioreporters in environmental application. Environ. Res. 262:119801. doi: 10.1016/j.envres.2024.119801
PubMed Abstract | Crossref Full Text | Google Scholar
Huq, M. E., Fahad, S., Shao, Z., Sarven, M. S., Khan, I. A., Alam, M., et al. (2020). Arsenic in a groundwater environment in Bangladesh: Occurrence and mobilization. J. Environ. Manage. 262:110318. doi: 10.1016/j.jenvman.2020.110318
PubMed Abstract | Crossref Full Text | Google Scholar
Irvine, G. W., Tan, S. N., and Stillman, M. J. (2017). A simple metallothionein-based biosensor for enhanced detection of arsenic and mercury. Biosensors 7:14. doi: 10.3390/bios7010014
PubMed Abstract | Crossref Full Text | Google Scholar
Kaur, H., Kumar, R., Babu, J. N., and Mittal, S. (2015). Advances in arsenic biosensor development–a comprehensive review. Biosens. Bioelectron. 63, 533–545. doi: 10.1016/j.bios.2014.08.003
PubMed Abstract | Crossref Full Text | Google Scholar
Lee, S., Roh, Y., and Koh, D. C. (2019). Oxidation and reduction of redox-sensitive elements in the presence of humic substances in subsurface environments: a review. Chemosphere 220, 86–97. doi: 10.1016/j.chemosphere.2018.11.143
PubMed Abstract | Crossref Full Text | Google Scholar
Mobley, H. L., Chen, C. M., Silver, S., and Rosen, B. P. (1983). Cloning and expression of R-factor mediated arsenate resistance in Escherichia coli. Molec. Gen. Genet. 191, 421–426. doi: 10.1007/BF00425757
PubMed Abstract | Crossref Full Text | Google Scholar
Ordóñez, E. N., Letek, M., Valbuena, N., Gil, J. A., and Mateos, L. M. (2005). Analysis of genes involved in arsenic resistance in Corynebacterium glutamicum ATCC 13032. Appl. Environ. Microb. 71, 6206–6215. doi: 10.1128/AEM.71.10.6206-6215.2005
PubMed Abstract | Crossref Full Text | Google Scholar
Palansooriya, K. N., Shaheen, S. M., Chen, S. S., Tsang, D. C., Hashimoto, Y., Hou, D., et al. (2020). Soil amendments for immobilization of potentially toxic elements in contaminated soils: a critical review. Environ. Int. 134:105046. doi: 10.1016/j.envint.2019.105046
PubMed Abstract | Crossref Full Text | Google Scholar
Palma-Lara, I., Martínez-Castillo, M., Quintana-Pérez, J. C., Arellano-Mendoza, M. G., Tamay-Cach, F., Valenzuela-Limón, O. L., et al. (2020). Arsenic exposure: a public health problem leading to several cancers. Regul. Toxicol. Pharm. 110:104539. doi: 10.1016/j.yrtph.2019.104539
PubMed Abstract | Crossref Full Text | Google Scholar
Pena, M. E., Korfiatis, G. P., Patel, M., Lippincott, L., and Meng, X. (2005). Adsorption of As(V) and As(III) by nanocrystalline titanium dioxide. Water Res. 39, 2327–2337. doi: 10.1016/j.watres.2005.04.006
PubMed Abstract | Crossref Full Text | Google Scholar
Pola-López, L., Camas-Anzueto, J., Martínez-Antonio, A., Luján-Hidalgo, M., Anzueto-Sánchez, G., Ruíz-Valdiviezo, V., et al. (2018). Novel arsenic biosensor “POLA” obtained by a genetically modified E. coli bioreporter cell. Sensor. Actuat. B: Chem. 254, 1061–1068. doi: 10.1016/j.snb.2017.08.006
Crossref Full Text | Google Scholar
Rahman, M., Reichelt-Brushet, A., Clark, M. W., Farzana, T., and Yee, L. H. (2017). Arsenic bio-accessibility and bioaccumulation in aged pesticide contaminated soils: a multiline investigation to understand environmental risk. Sci. Total Environ. 581, 782–793. doi: 10.1016/j.scitotenv.2017.01.009
PubMed Abstract | Crossref Full Text | Google Scholar
Sánchez, S., McDonald, M., Silver, D. M., de Bonnault, S., Chen, C., LeBlanc, K., et al. (2021). The integration of whole-cell biosensors for the field-ready electrochemical detection of arsenic. J. Electrochem. Soc. 168:067508. doi: 10.1149/1945-7111/ac049e
Crossref Full Text | Google Scholar
Tohfegar, E., and Habibi, A. (2023). Immobilization of Candida catenulata cells by surface-loading of an amino-functionalized Fe3O4 nanoparticles and its application as the sustainable whole-cell biocatalyst for enzymatic biodiesel production. Energ. Convers. Manage. 293:117503. doi: 10.1016/j.enconman.2023.117503
Crossref Full Text | Google Scholar
Valenzuela-García, L. I., Alarcón-Herrera, M. T., Ayala-García, V. M., Barraza-Salas, M., Salas-Pacheco, J. M., Díaz-Valles, J. F., et al. (2023). Design of a whole-cell biosensor based on Bacillus subtilis spores and the green fluorescent protein to monitor arsenic. Microbiol. Spect. 11, e00432–e00423. doi: 10.1128/spectrum.00432-23
PubMed Abstract | Crossref Full Text | Google Scholar
Wu, S., Zheng, H., Wang, Y., Wang, L., and Chen, W. (2023). Cyanobacterial bioreporter of nitrate bioavailability in aquatic ecosystems. Water Res. 247:120749. doi: 10.1016/j.watres.2023.120749
PubMed Abstract | Crossref Full Text | Google Scholar
Yang, J., Abdul Salam, A. A., and Rosen, B. P. (2011). Genetic mapping of the interface between the ArsD metallochaperone and the ArsA ATPase. Mol. Microbiol. 79, 872–881. doi: 10.1111/j.1365-2958.2010.07494.x
PubMed Abstract | Crossref Full Text | Google Scholar
Yoon, Y., Kang, Y., Chae, Y., Kim, S., Lee, Y., Jeong, S. W., et al. (2016a). Arsenic bioavailability in soils before and after soil washing: the use of Escherichia coli whole-cell bioreporters. Environ. Sci. Pollut. Res. 23, 2353–2361. doi: 10.1007/s11356-015-5457-8
PubMed Abstract | Crossref Full Text | Google Scholar
Yoon, Y., Kim, S., Chae, Y., Jeong, S. W., and An, Y. J. (2016b). Evaluation of bioavailable arsenic and remediation performance using a whole-cell bioreporter. Sci. Total Environ. 547, 125–131. doi: 10.1016/j.scitotenv.2015.12.141
PubMed Abstract | Crossref Full Text | Google Scholar
Yu, Y., Chen, J., Li, Y., Liang, J., Xie, Z., Feng, R., et al. (2021). Identification of a MarR subfamily that regulates arsenic resistance genes. Appl. Environ. Microbiol. 87, e01588–e01521. doi: 10.1128/AEM.01588-21
PubMed Abstract | Crossref Full Text | Google Scholar
Zhang, X. K., Li, B. L., Schillereff, D. N., Chiverrell, R. C., Tefsen, B., and Wells, M. (2022). Whole-cell biosensors for determination of bioavailable pollutants in soils and sediments: Theory and practice. Sci. Total Eeviron. 811:152178. doi: 10.1016/j.scitotenv.2021.152178
PubMed Abstract | Crossref Full Text | Google Scholar
Zhu, Y., Elcin, E., Jiang, M., Li, B., Wang, H., Zhang, X., et al. (2022). Use of whole-cell bioreporters to assess bioavailability of contaminants in aquatic systems. Front. Chem. 10:1018124. doi: 10.3389/fchem.2022.1018124
留言 (0)