Protocol for optimizing the measurement of plant leaves from common model plants, including Arabidopsis, rice, and tomato, is presented. Given the large chemical diversity and dynamic range of metabolites produced by plants, the extraction of these metabolites can be strongly influenced by growth conditions and can vary significantly between different tissue and organ types. As a result, the volume of extraction buffer required to obtain a representative sample may vary based on the specific plant species and tissue type being analyzed. Therefore, it is important to optimize the extraction buffer volume to ensure that the resulting samples are representative of the plant material being studied.
1 Plant Cultivation And Sampling
(a) Cultivate plants of your interest under optimal growth conditions.
(b) Harvest plant leaves using clean scissors or razor.
(c) Place collected plant material into 2.0 mL round bottom shaped microcentrifuge tubes.
(d) Put a zirconia bead or metal ball into each sample tube, close the lid properly, and freeze it immediately in liquid nitrogen.
(e) Grind the frozen plant tissue with a Mixer Mill for 2 min at 25 Hz.
(f) Store frozen ground samples at -80 ℃ until further use.
2 Sample Aliquoting
(a) Keep all the samples in liquid nitrogen; make sure that liquid nitrogen does not enter to the sample tubes.
(b) Dip a new 2.0 mL round bottom-shaped microcentrifuge tube into liquid nitrogen for 5 s, put it on steady position of the electric analytical balance and switch "automatic zero correction" on quickly.
(c) Aliquot and transfer the frozen powder (e.g., 50 mg ± 5 mg) into the sample tube as quickly as possible to prevent sample from thawing.
(d) Check the sample weight for each sample tube.
(e) Close the lid of the sample tube and put the sample back into liquid nitrogen.
(f) Write down the sample weight.
(g) Store all sample aliquots at -80 ℃ until extraction.
3 Extraction of Plant Metabolites
(a) Open the lid of the sample tube containing frozen ground sample.
(b) Put a precooled zirconia bead into the sample tube.
(c) Add 5 μL of extraction solution per 1 mg of frozen ground sample (e.g., 256 μL extraction solution for 51.2 mg of frozen ground sample).
(d) Close the lid of the sample tube and put the sample back into liquid nitrogen.
(e) Homogenize the sample with a Mixer Mill for 4 min at 25 Hz.
(f) Centrifuge the sample tube for 10 min at 20,000 × g at 4 ℃.
(g) Transfer the supernatant to a new 1.5 mL round bottom-shaped microcentrifuge tube.
(h) Centrifuge the new sample tube for 5 min at 20,000 × g at 4 ℃.
(i) Transfer the supernatant to a new 1.5 mL round bottom-shaped microcentrifuge tube.
(j) Store extracts at 4 ℃ until LC-MS analysis.
4 LC-MS Analysis
(a) Set up an LC-MS system with autosampler for plant secondary metabolite analysis.
(b) Set HPLC bottles of both elution buffers.
(c) Transfer the sample extract to a glass vial suitable for LC-MS analysis and put it in the autosampler tray.
(d) Analyze your samples after the measurement of extraction buffer blanks to equilibrate the LC-MS system.
5 Data Analysis
(a) Analyze the obtained data with software provided by MS manufacturer (e.g., Xcalibur by Thermofisher, Analyst by SCIEX, MassHunter by Agilent) or freely available software (e.g., MSFact, XCMS2, BINBASE, MZmine2, and TagFinder).
(b) Evaluate the data by peak area or peak height considering peak shape and peak shift.
(c) Export the signal intensity data of all the detected peaks and make a whole data matrix.
(d) Normalize the whole data using sample weight and peak intensity of IS.
6 Peak Prediction, Annotation, and Identification
The identification and annotation of plant secondary metabolites can be particularly challenging due to their complex structures. When attempting to identify a peak, there are two best practices that are commonly used: either the target peak is purified from plant extracts and identified through NMR studies, or the peak is identified through coelution profiling with an authentic standard compound. However, in the case of a metabolomics approach for plant secondary metabolites, the availability of authentic standard compounds is limited due to the complexity and diversity of these compounds' structures. Therefore, the greatest challenge in plant metabolomics is often "peak annotation." This involves providing chemical and structural specifications for the peak using various sources of structural information, such as MS/MS analysis, reference extracts, mutant analysis, and web-resources. While "peak identification" provides complete characterization, "peak annotation" is a way to provide as much information as possible, given the limitations of the available resources.
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Reference
- António, C. (Ed.). (2018). Plant metabolomics: Methods and protocols. Humana Press.