1. An Expedited Qualitative Profiling of Free Amino Acids in Plant Tissues Using Liquid Chromatography‐Mass Spectrometry (LC–MS) in Conjunction With MS‐DIAL.
- Author
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Kaachra, Anish, Tamang, Anish, and Hallan, Vipin
- Subjects
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BOTANISTS , *AMINO acids , *PLANT cells & tissues , *LIQUID chromatography , *MASS spectrometry , *NICOTIANA benthamiana - Abstract
The estimation of relative levels of amino acids is crucial for understanding various biological processes in plants, including photosynthesis, stress tolerance, and the uptake and translocation of nutrients. A wide range of liquid chromatography (LC; HPLC/UHPLC)‐based methods is available for measuring the quantity of amino acids in plants. Additionally, the coupling of LC with mass spectrometry (MS) significantly enhanced the robustness of existing chromatographic methods used for amino acid quantification. However, accurate annotation and integration of mass peaks can be challenging for plant biologists with limited experience in analyzing MS data, especially in studies involving large datasets with multiple treatments and/or replicates. Further, there are instances when the experiment demands an overall view of the amino acids profile rather than focusing on absolute quantification. The present protocol provides a detailed LC–MS method for obtaining a qualitative amino acids profile using MS‐DIAL, a versatile and user‐friendly program for processing MS data. Free amino acids were extracted from the leaves of control and Tomato leaf curl Palampur virus (ToLCPalV)‐infected Nicotiana benthamiana plants. Extracted amino acids were derivatized and separated using UHPLC‐QTOF, with each amino acid subsequently identified by aligning mass data with a custom text library created in MS‐DIAL. Further, MS‐DIAL was employed for internal standard‐based normalization to obtain a qualitative profile of 15 amino acids in control and virus‐infected plants. The outlined method aims to simplify the processing of MS data to quickly assess any modulation in amino acid levels in plants with a higher degree of confidence. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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