Dual-mode fluorescence and colorimetric detection of pesticides realized by integrating stimulus-responsive luminescence with oxidase-mimetic activity into cerium-based coordination polymer nanoparticles

Highlights

• CPNs(Ⅳ) with both stimulus-responsive luminescence and oxidase-mimetic activity.

• The ACP+AAP system promotes the luminescence but reduces the nanozyme activity.

• Pesticides inhibit ACP, suppressing the luminescence and recovering the activity.

• Dual-mode fluorescence and colorimetric detection of pesticides.

Abstract

The great threat of pesticide residues to the environment and human health has drawn widespread interest to explore approaches for pesticide monitoring. Compared to commonly developed single-signal pesticide assays, multi-mode detection with inherent self-validation and self-correction is expected to offer more reliable and anti-interference results. However, how to realize multi-mode analysis of pesticides still remains challenging. Herein, we propose a dual-mode fluorescence and colorimetric method for pesticide determination by integrating stimulus-responsive luminescence with oxidase-mimetic activity into cerium-based coordination polymer nanoparticles (CPNs(Ⅳ)). The CPNs(Ⅳ) exhibit good oxidase-like activity of catalyzing the colorless 3,3′,5,5′-tetramethylbenzidine (TMB) oxidation to its blue oxide, offering a visible color signal; by employing acid phosphatase (ACP) to hydrolyze ascorbic acid 2-phosphate (AAP), the generated ascorbic acid (AA) can chemically reduce the CPNs(Ⅳ) to CPNs(Ⅲ), which exhibit a remarkable fluorescence signal but lose the oxidase-mimicking ability to trigger the TMB chromogenic reaction; when pesticides exist, the enzymatic activity of ACP is restrained and the hydrolysis of AAP to AA is blocked, leading to the recovery of the catalytic TMB chromogenic reaction but the suppression of the fluorescence signal of CPNs(Ⅲ). According to this principle, by taking malathion as a pesticide model, dual-mode ‘off-on-off’ fluorescence and ‘on-off-on’ colorimetric detection of the pesticide with good sensitivity was realized. Excellent interference-tolerance and reliability were verified by applying it to analyze the target in real sample matrices. With good performance and practicability, the proposed dual-mode approach shows great potential in the facile and reliable monitoring of pesticide residues.

Introduction

As a crucial means to improve product quality and increase crop yield, pesticides are universally applied to protect crops from pests. In spite of huge benefits brought by the use of pesticides, most of them are hard to degrade and remain in agricultural products or further transfer to other food chains and ecosystems, causing severe threats to the environment and human health. Consumption of agricultural and sideline products containing pesticide residues can lead to both acute poisoning and organic damage. Additionally, long-term exposure to pesticides is in association with several diseases (Kamel and Hoppin, 2004, Ascherio et al., 2006). Given their high toxicity and severe harm to public health security, many organizations and governments have paid great attention on the issue of pesticide residues, and they have enacted strict limits on pesticide residues in various agricultural and related products. Therefore, developing reliable and facile methods for pesticide residue monitoring turns to be of great significance (Yan et al., 2018a, Zhao et al., 2018a).

Up to now, a large number of approaches (Hogendoorn and Zoonen, 2000, Fan et al., 2015, Ishibashi et al., 2015, Sivaperumal et al., 2015, Duford et al., 2013, Rajangam et al., 2018, Pundir and Malik, 2019, Cao et al., 2020, Jiang et al., 2018, Jiang et al., 2018, Alex and Mukherjee, 2021, Xie et al., 2022, Yao et al., 2020) have been explored and applied to the detection of pesticide residues, which can mainly be divided into the following two categories: one is chromatographic methods (Hogendoorn and Zoonen, 2000, Fan et al., 2015, Ishibashi et al., 2015, Sivaperumal et al., 2015), and the other is enzyme inhibition-based methods (Duford et al., 2013, Rajangam et al., 2018, Pundir and Malik, 2019, Cao et al., 2020, Alex and Mukherjee, 2021). In comparison with the former requiring expensive instruments and professional operation, enzyme inhibition-based assays can be performed with convenient detection, fast response, and low cost, thus attracting increasing interest in the monitoring of pesticide residues in environmental and food matrices. Typically, cholinesterases (acetylcholinesterase and butyrylcholinesterase) are employed as enzyme probes to realize the sensing of pesticides by combining the analyte-induced enzyme inhibition principle with optical (Yan et al., 2019, Yan et al., 2018b, Li et al., 2011, Liang et al., 2013, Wang et al., 2019, Chu et al., 2020, Long et al., 2015, Wu et al., 2017, Wang et al., 2019, Satnami et al., 2018) or electrochemical (Wang et al., 2016, Nasir et al., 2017, Zhao et al., 2018b, Li et al., 2020, Wu et al., 2019) detection modules. With the merits of simple signal reading and result visualization, optical pesticide biosensors have drawn considerable attention to be explored in recent years (Yan et al., 2018a, Kaur and Singh, 2020). Nonetheless, most of them are based on the target-triggered change of a single signal (Li et al., 2011, Li et al., 2020, Liang et al., 2013, Wang et al., 2019, Chu et al., 2020, Long et al., 2015, Wu et al., 2017, Wu et al., 2019, Wang et al., 2019, Satnami et al., 2018, Yan et al., 2018b, Wang et al., 2016, Nasir et al., 2017, Zhao et al., 2018b), which possibly causes false or inaccurate results during practical applications. Compared to single-signal pesticide assays, multi-mode detection with good anti-interference is expected to offer more reliable results, because it can provide different signals for self-validation and self-correction (Juan-Colás et al., 2017), thus greatly minimizing false results and incorrect ones. With this consideration, it is highly desired to develop multi-signal multi-mode methods for pesticide residue analysis. However, how to develop a simple and robustness system to realize the high-performance multi-mode detection of pesticides is still a challenge currently.

In the present work, we develop a dual-mode fluorescence and colorimetric method for the sensing of pesticides via integrating stimulus-responsive luminescence with oxidase-mimicking activity into cerium-based coordination polymer nanoparticles (Ce(Ⅳ)-ATP-Tris, further abbreviated as CPNs(Ⅳ)). As illustrated in Scheme 1, the CPNs(Ⅳ) are able to provide the oxidase-mimetic catalytic capacity of inducing the oxidation of colorless 3,3′,5,5′-tetramethylbenzidine (TMB) to its blue oxide TMBox, giving a visible colorimetric signal at approximately 652 nm; when ascorbic acid 2-phosphate (AAP) is employed to be hydrolyzed under the catalysis of acid phosphatase (ACP), the generated ascorbic acid (AA) with reducibility can trigger the chemical reduction of Ce⁴⁺ in CPNs(Ⅳ) to Ce³⁺, resulting in the formation of Ce(Ⅲ)-ATP-Tris (abbreviated as CPNs(Ⅲ)). Compared to the former, the formed CPNs(Ⅲ), on the one hand, exhibit sharply decreased oxidase-like activity, resulting in the significant suppression of the catalytic TMB chromogenic reaction, and on the other hand, offer a notable fluorescence signal at around 356 nm; with the presence of organophosphorus or carbamate pesticides, the enzymatic activity of ACP is irreversibly inhibited (Cao et al., 2020). As a result, the hydrolytic process of AAP to AA is blocked, and such that the conversion of CPNs(Ⅳ) to CPNs(Ⅲ) is inhibited, leading to the recovery of the catalytic TMB chromogenic reaction, while the fluorescence signal originating from CPNs(Ⅲ) is suppressed again. According to the strategy, dual-mode ‘off-on-off’ fluorescence and ‘on-off-on’ colorimetric detection of pesticides with good performance was demonstrated by employing malathion as a model. Excellent reliability, interference-tolerance and practicability of our method were also verified by using it to detect the pesticide in real sample matrices.