Lab-on-a-Molecule Probe: Multitarget Detection of Five Aromatic Pesticides Using a Supramolecular Probe under Single Wavelength Excitation

A supramolecular fluorescence sensor array for the differentiation of multiple anions and prediction of iodine in artificial urine using machine learning

The simultaneous discrimination and detection of multiple anions in an aqueous solution has been a major challenge due to their structural similarity and low charge radii. In this study, we have constructed a supramolecular fluorescence sensor array based on three host-guest complexes to distinguish five anions (F-, Cl-, Br-, I-, and ClO-) in an aqueous solution using anionic-induced fluorescence quenching combined with linear discriminant analysis. Due to the different affinities of the three host-guest complexes for each anion the anion quenching efficiency for each host-guest complex was likewise different, and the five anions were well recognized. The fluorescence sensor array not only distinguished anions at different concentrations (0.5, 10, and 50 µM) with 100% accuracy but also showed good linearity within a certain concentration range. The limit of detection (LOD) was < 0.5 µM. Our interference study showed that the developed sensor array had good anti-interference ability. The practicability of the developed sensor array was also verified by the identification and differentiation of toothpaste brands with different fluoride content and the prediction of the iodine concentration in urine combined with machine learning.

Exploring Various Photochemical Processes in Optical Sensing of Pesticides by Luminescent Nanomaterials: A Concise Discussion on Challenges and Recent Advancements

Food safety is a burning global issue in this present era. The prevalence of harmful food additives and contaminants in everyday food is a significant cause for concern as they can adversely affect human health. More particularly, among the different food contaminants, the use of excessive pesticides in agricultural products is severely hazardous. So, the optical detection of residual pesticides is an effective strategy to counter the hazardous effect and ensure food safety. In this perspective, nanomaterials have played a leading role in defending the open threat against food safety instigated by the reckless use of pesticides. Now, nanomaterial-based optical detection of pesticides has reached full pace and needs an inclusive discussion. This Review covers the advancement of photoprocess-based optical detection of pesticides categorically using nanomaterials. Here, we have thoroughly dissected the photoprocesses (aggregation and aggregation-induced emission (AIE), charge transfer and intramolecular charge transfer (ICT), electron transfer and photoinduced electron transfer (PET), fluorescence resonance energy transfer (FRET), hydrogen bonding, and inner filter effect) and categorically demarcated their significant role in the optical detection of pesticides by luminescent nanomaterials over the last few years.

Portable Sensor Array for On-Site Detection and Discrimination of Pesticides and Herbicides Using Multivariate Analysis

Modern agricultural practice relies heavily on pesticides and herbicides to increase crop productivity, and consequently, their residues have a negative impact on the environment and public health. Thus, keeping these issues in account, herein we developed an azodye-based chromogenic sensor array for the detection and discrimination of pesticides and herbicides in food and soil samples, utilizing machine learning approaches such as hierarchical clustering analysis, principal component analysis, linear discriminant analysis (LDA), and partial least square regression (PLSR). The azodye-based sensor array was developed in combination with various metal ions owing to their different photophysical properties, which led to distinct patterns toward various pesticides and herbicides. The obtained distinct patterns were recognized and processed through automated multivariate analysis, which enables the selective and sensitive identification and discrimination of various target analytes. Further, the qualitative and quantitative determination of target analytes were performed using LDA and PLSR; the results obtained show a linear correlation with varied concentrations of target analytes with R2 values from 0.89 to 0.96, the limit of detection from 5.3 to 11.8 ppm with a linear working range from 1 to 30 μM toward analytes under investigation. Further, the developed sensor array was successfully utilized for the discrimination of a binary mixture of pesticide (chlorpyrifos) and herbicide (glyphosate).

Core-shell Au@ZIF-67-based pollutant monitoring of thiram and carbendazim pesticides

A sensitive and stable substrate plays a vital role in the Raman spectroscopic techniques as an analytical method for detecting pesticides effectively from the environment. Enhancing signals from nanoparticles are weak and inconsistent in repeatability since analytes tend to degrade quickly under laser exposure. Herein, a novel substrate of Au@ZIF-67 is prepared on octahedral AuNPs by trapping pesticide molecules with small three-dimensional volumes by the flexibility of ZIF-67 for rapid detection with high sensitivity and stability. The two types of thiram and carbendazim pesticides, which are environmental pollutants that affect biodiversity, were successfully absorbed in Au@ZIF-67 nanostructures by adsorption-desorption equilibrium for analytical purposes in Raman spectroscopy. Spectra calculations of the thiram and carbendazim molecules on 8 atoms of Au using DFT were compared with the experimental data. The SERS enhancement factors for thiram and carbendazim were estimated to be 1.91 × 10⁸ and 3.12 × 10⁸, respectively, with the LOD values of trace amounts of ∼10^-10 mol L^-1. The novel substrate of Au@ZIF-67 is a propitious platform for detecting thiram and carbendazim in trace amounts, providing a helpful strategy for detecting residues with high performance in the environment at the laboratory and practical scales.

Fluorescent Detection of Two Pesticides Based on CRISPR-Cas12a and Its Application for the Construction of Four Molecular Logic Gates

An intelligent detection platform was developed through molecular logic gate operation based on CRISPR-Cas12a and signal amplification circuits using two kinds of pesticides [acetamiprid (ACE) and atrazine (ATR)] as inputs. The pesticide-aptamer bindings activate the signal amplification process to produce numerous double-stranded DNA, which can be identified by CRISPR-Cas12a. Under the optimal assay conditions, the sensor exhibits excellent analytical performance, with the detection limits for ACE and ATR of 2.5 and 0.2 pM, respectively. The practicality of the platform was verified by testing pesticide concentrations in food samples. Several molecular logic gates (OR, AND, XOR, and INHIBIT) were constructed using "0" and "1" to encode the target pesticides and the fluorescence readout. The logic detection platform with simple operation, high sensitivity, and multiple logic functions is promising to become a powerful sensing system for the intelligent assay of different pesticides in food samples.

Production of Antibacterial Questiomycin A in Metabolically Engineered Pseudomonas chlororaphis HT66

Pseudomonas chlororaphis has been demonstrated as a valuable source of antimicrobial metabolites for plant disease biocontrol and biopesticide development. Although phenazine-1-carboxylic acid (PCA) secreted by P. chlororaphis has been commercialized as an antifungal biopesticide, it shows poor antibacterial activity. Questiomycin A, with versatile antibacterial activities, is mainly discovered in some well-known phenazine-producing strains but not in Pseudomonas. Its low titer hinders practical applications. In this work, a metabolite was first identified as Questiomycin A in P. chlororaphis-derived strain HT66ΔphzBΔNat. Subsequently, Questiomycin A has been elucidated to share the same biosynthesis process with PCA by gene deletion and in vitro assays. Through rational metabolic engineering, heterologous phenoxazinone synthase introduction, and medium optimization, the titer reached 589.78 mg/L in P. chlororaphis, the highest production reported to date. This work contributes to a better understanding of Questiomycin A biosynthesis and demonstrates a promising approach to developing a new antibacterial biopesticide in Pseudomonas.