Rapid and robust analysis of aristolochic acid I in Chinese medicinal herbal preparations by surface-enhanced Raman spectroscopy

SERS-based microdroplet platform for high-throughput screening of Escherichia coli strains for the efficient biosynthesis of D-phenyllactic acid

D-Phenyllactic acid (D-PLA) is a potent antimicrobial typically synthesized through chemical methods. However, due to the complexity and large pollution of these reactions, a simpler and more eco-friendly approach was needed. In this study, a strain for D-PLA biosynthesis was constructed, but the efficiency was restricted by the activity of D-lactate dehydrogenase (DLDH). To address this issue, a DLDH mutant library was constructed and the Surface-Enhanced Raman Spectroscopy (SERS) was employed for the precise quantification of D-PLA at the single-cell level. The TB24 mutant exhibited a significant improvement in D-PLA productivity and a 23.03-fold increase in enzymatic activity, which was attributed to the enhanced hydrogen bonding and increased hydrophobicity within the substrate-binding pocket. By implementing multi-level optimization strategies, including the co-expression of glycerol dehydrogenase (GlyDH) with DLDH, chassis cell replacement, and RBS engineering, a significant increase in D-PLA yields was achieved, reaching 128.4 g/L. This study underscores the effectiveness of SERS-based microdroplet high-throughput screening (HTS) in identifying superior mutant enzymes and offers a strategy for large-scale D-PLA biotransformation.

Development and Application of a Comprehensive Nontargeted Screening Strategy for Aristolochic Acid Analogues

Aristolochic acid analogs (AAAs) are naturally occurring carcinogenic and toxic compounds that pose a safety threat to pharmaceuticals and the environment. It is challenging to screen AAAs due to their lack of characteristic mass spectral fragmentation and their presence of structural diversity. A comprehensive nontargeted screening strategy was proposed by taking into account diverse factors and incorporating various self-developed techniques, and a Python3-based toolkit called AAAs_finder was developed for its implementation. The main procedures consist of virtual structure and ultraviolet and visible (UV) spectra database creation, exact mass and UV spectra-based suspect data extraction, tandem mass spectra (MS/MS) anthropomorphic interpretation, and multicondition retention time (RT) prediction-based candidate structures ranking. To initially assess screening feasibility, eight hypothetical unknown samples were subjected to nontargeted screening using the AAAs_finder toolkit and two other advanced tools. The results showed that the former successfully identified all, while the latter two only managed to identify two and three, respectively, indicating that our strategy was more feasible. After that, the strategy was carefully evaluated for false positives and false negatives, instrument dependence, reproducibility, and sensitivity. After the evaluation, the strategy was successfully applied to the screening of AAAs in real samples, such as herbal medicine, spiked soil, and water. Overall, this study proposed a nontargeted screening strategy and toolkit independent of characteristic mass spectral fragmentation and able to overcome challenges posed by structural diversity for the AAAs screening, which is also valuable for other classes of compounds.

Multivariate surface self-assembly strategy to fabricate ionic covalent organic framework surface grafting monolithic sorbent for enrichment of aristolochic acids prior to high performance liquid chromatography analysis

Herein, an ionic covalent organic framework (iCOF) surface grafting monolithic sorbent was prepared by the multivariate surface self-assembly strategy for in-tube solid-phase microextraction (SPME) of trace aristolochic acids (AAs) in serum, traditional Chinese medicines (TCMs) and Chinese patent drug. Via adjusting the proportion of ionic COF building block during the self-assembly, the density of quaternary ammonium ions in the iCOF was modulated for the enhanced adsorption of AAs. The successful preparation of iCOF surface grafting monolithic sorbent was confirmed by different means. A multiple mode mechanism involving π-π stacking, hydrophobic, electrostatic and hydrogen-bonding interactions was primarily attributed to the adsorption. Several in-tube SPME operating conditions, such as the dosage of ionic COF building block, ACN percentage and TFA percentage in the sampling solution, ACN percentage and TFA percentage in eluent and the collection time span, were optimized to develop the online in-tube SPME-HPLC method for analysis of AAs. Under the optimized conditions, a good linearity was obtained in the concentration range of 20-1000 ng/mL for target AAs in serum samples, the limits of detection (LODs) were less than 10 ng/mL, while the recoveries ranged from 90.3 % to 98.7 % with RSDs (n = 5) below 7.9 %. This study developed a feasible approach to iCOF functionalized monolithic sorbent for SPME and further exhibited the vast potential for the application of COF based monolithic sorbent in sample preparation.

Rapid identification and detection of aristolochic acids in the herbal extracts by Raman spectroscopy

Herbs containing aristolochic acids (AAs) have already been proven to be highly carcinogenic and nephrotoxic. In this study, a novel surface-enhanced Raman scattering (SERS) identification method was developed. Ag-APS nanoparticles with a particle size of 3.53 ± 0.92 nm were produced by combining silver nitrate and 3-aminopropylsilatrane. The reaction between the carboxylic acid group of aristolochic acid I (AAI) and amine group of Ag-APS NPs was used to form amide bonds, and thus, concentrate AAI, rendering it easy to detect via SERS and amplified to obtain the best SERS enhancement effect. Detection limit was calculated to be approximately 40 nM. Using the SERS method, AAI was successfully detected in the samples of four Chinese herbal medicines containing AAI. Therefore, this method has a high potential to be applied in the future development of AAI analysis and rapid qualitative and quantitative analysis of AAI in dietary supplements and edible herbs.