MRMS aXelerate – rapidly detected micropollutants and plant response metabolites in poplar leaves

Significance of the topic

Environmental micropollutants such as pharmaceuticals and pesticides can accumulate in plant tissues, posing risks to ecosystems and human health. Rapid, non‐targeted detection of these compounds alongside endogenous plant metabolites is essential for monitoring phytoremediation performance and environmental exposure. MRMS aXelerate offers a chromatography‐free, high‐resolution workflow to profile complex plant extracts with high throughput.

Objectives and study overview

This study demonstrates the application of MRMS aXelerate for simultaneous profiling of plant metabolites and micropollutants in poplar leaves. Two contrasting growth conditions—a poplar near a constructed wetland effluent (“polluted”) and a control poplar irrigated by rainwater—were compared. The goals were to assess sample throughput, annotation confidence using MetaboScape 4.0, and the method’s ability to reveal differential accumulation of drugs and pesticides.

Methodology and used instrumentation

Sample preparation and analysis comprised:

• Leaf harvest from two poplar trees after two years of growth in Alsace wetlands (eight biological replicates per condition).
• Extraction of 300 mg fresh weight in methanol (three times), drying, reconstitution in methanol with deuterated abscisic acid internal standard, and QC pooling.
• Flow injection analysis on a UHPLC Elute HT system with a 20 µL loop delivering 100 µL/min (reduced to 10 µL/min during acquisition) to the scimaX 7T MRMS source.
• MS acquisition in positive and negative electrospray ionization over m/z 107–3,000 at 1,350,000 resolving power, with lock‐mass calibration.
• Data processing in MetaboScape 4.0 using T-ReX 2D for feature extraction, SmartFormula for formula assignment, and AnalyteList matching against plant metabolite, drug, and pesticide databases.

Main results and discussion

A total of 3,452 features were extracted from combined ESI(+) and ESI(–) data. Annotation yielded:

• 2,638 (0.2 ppm) to 3,116 (0.5 ppm) molecular formulas via SmartFormula with isotopic pattern and fine structure confidence.
• 326 (0.2 ppm) to 383 (0.5 ppm) putative compound identifications from the AnalyteList.

Classes of plant metabolites detected included chlorophyll derivatives, lipids, flavonoids, sugars, hormones, and other low‐abundance compounds. Comparative t-tests and volcano plots revealed significant accumulation of several drugs (e.g., ketobemidone, oxymorphone) and pesticides (e.g., benalaxyl, furalaxyl) in polluted poplar samples, confirmed by box‐plot intensity differences. The results demonstrate clear differentiation of environmental exposure profiles.

Benefits and practical application

MRMS aXelerate combines rapid flow injection analysis with ultra‐high mass resolution to:

• Eliminate lengthy chromatographic separations, reducing analysis time per sample to under two minutes.
• Maintain sensitivity for low‐abundance metabolites in crude extracts without additional purification.
• Provide high-confidence molecular formula assignments using a three‐tier confidence engine.
• Enable non‐targeted screening for environmental pollutants co-detected with endogenous metabolites.

This approach is well suited for environmental monitoring, phytoremediation assessment, QA/QC labs, and metabolomics studies requiring high throughput.

Future trends and potential applications

Advancements may include:

• Integration of expanded compound databases and spectral libraries for broader coverage of xenobiotics and natural products.
• Coupling MRMS aXelerate data with machine learning for automated feature prioritization and risk assessment.
• Development of portable or field‐deployable MRMS platforms for real‐time monitoring of plant and water matrices.
• Enhanced workflows combining rapid FIA screening with targeted MS/MS for structural confirmation.

Conclusion

The MRMS aXelerate workflow delivers a powerful, high‐throughput solution for non‐targeted profiling of crude plant extracts. It successfully identifies and quantifies both endogenous metabolites and environmental micropollutants without chromatography, offering significant time savings and confident annotations. This approach opens new avenues for environmental analytics, metabolomics research, and rapid screening of phytoremediation processes.