Unraveling the secrets of plant roots: Simplified method for large scale root exudate sampling and analysis in Arabidopsis thaliana
Authors/Creators
- 1. Department of Molecular Biology and Genetics - Plant Molecular Biology, Aarhus University, 8000 Aarhus C, Denmark
- 2. Department of Chemistry, Aarhus University, 8000 Aarhus C, Denmark
- 3. Department of Ecoscience, Aarhus University, 8000 Aarhus C, Denmark
Description
Background: Plants exude a plethora of compounds to communicate with their environment. Although much is known about above-ground plant communication, we are only beginning to fathom the complexities of below-ground chemical communication channels. Studying root-exuded compounds and their role in plant communication has been difficult due to the lack of standardized methodologies. Here, we develop an interdisciplinary workflow to explore the natural variation in root exudate chemical composition of the model plant Arabidopsis thaliana. We highlight key challenges associated with sampling strategies and develop a framework for analyzing both narrow- and broad-scale patterns of root exudate composition in a large set of natural A. thaliana accessions.
Methods: Our method involves cultivating individual seedlings in vitro inside a plastic mesh, followed by a short hydroponic sampling period in small quantities of ultrapure water. The mesh makes it easy to handle plants of different sizes and allows for large-scale characterization of individual plant root exudates under axenic conditions. This setup can also be easily extended for prolonged temporal exudate collection experiments. Furthermore, the short sampling time minimizes the duration of the experiment while still providing sufficient signal even with small volume of the sampling solution. We used ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) for untargeted metabolic profiling, followed by tentative compound identification using MZmine3 and SIRIUS 5 software, to capture a broad overview of root exudate composition in A. thaliana accessions.
Results: Based on 28 replicates of the Columbia genotype (Col-0) compared with 10 random controls, MZmine3 identified 354 metabolites to be present only in Col-0 by negative ionization. Of these, 254 compounds could be annotated by SIRIUS 5 software.
Conclusions: The methodology developed in this study can be used to broadly investigate the role of root exudates as chemical signals in plant belowground interactions.
Files
openreseurope-3-17459.pdf
Files
(1.9 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:4fb36c055a4b905ff04c8fb31cda135e
|
1.9 MB | Preview Download |
Additional details
References
- Wang NQ, Kong CH, Wang P (2021). Root exudate signals in plant–plant interactions. Plant Cell Environ. doi:10.1111/pce.13892
- Subrahmaniam HJ, Libourel C, Journet EP (2018). The genetics underlying natural variation of plant–plant interactions, a beloved but forgotten member of the family of biotic interactions. Plant J. doi:10.1111/tpj.13799
- Subrahmaniam HJ, Roby D, Roux F (2021). Toward Unifying Evolutionary Ecology and Genomics to Understand Positive Plant–Plant Interactions Within Wild Species. Front Plant Sci. doi:10.3389/fpls.2021.683373
- Ehlers BK, Berg MP, Staudt M (2020). Plant Secondary Compounds in Soil and Their Role in Belowground Species Interactions. Trends Ecol Evol. doi:10.1016/j.tree.2020.04.001
- Canarini A, Kaiser C, Merchant A (2019). Root exudation of primary metabolites: Mechanisms and their roles in plant responses to environmental stimuli. Front Plant Sci. doi:10.3389/fpls.2019.00157
- Kong CH, Xuan TD, Khanh TD (2019). Allelochemicals and Signaling Chemicals in Plants. Molecules. doi:10.3390/molecules24152737
- Novoplansky A (2019). What plant roots know?. Semin Cell Dev Biol. doi:10.1016/j.semcdb.2019.03.009
- Rizaludin MS, Stopnisek N, Raaijmakers JM (2021). The chemistry of stress: Understanding the 'cry for help' of plant roots. Metabolites. doi:10.3390/metabo11060357
- Rolfe SA, Griffiths J, Ton J (2019). Crying out for help with root exudates: adaptive mechanisms by which stressed plants assemble health-promoting soil microbiomes. Curr Opin Microbiol. doi:10.1016/j.mib.2019.10.003
- Semchenko M, Saar S, Lepik A (2014). Plant root exudates mediate neighbour recognition and trigger complex behavioural changes. New Phytol. doi:10.1111/nph.12930
- Bawa KS (2016). Kin Selection and the Evolution of Plant Reproductive Traits. Proc Biol Sci. doi:10.1098/rspb.2016.0789
- Oburger E, Jones DL (2018). Sampling root exudates – Mission impossible?. Rhizosphere. doi:10.1016/j.rhisph.2018.06.004
- Pantigoso HA, He Y, DiLegge MJ (2021). Methods for root exudate collection and analysis. Methods Mol Biol. doi:10.1007/978-1-0716-1040-4_22
- Oburger E, Schmidt H (2016). New Methods To Unravel Rhizosphere Processes. Trends Plant Sci. doi:10.1016/j.tplants.2015.12.005
- Vives-Peris V, de Ollas C, Gómez-Cadenas A (2020). Root exudates: from plant to rhizosphere and beyond. Plant Cell Rep. doi:10.1007/s00299-019-02447-5
- Vranova V, Rejsek K, Skene KR (2013). Methods of collection of plant root exudates in relation to plant metabolism and purpose: A review. J Soil Sci Plant Nutr. doi:10.1002/jpln.201000360
- Williams A, Langridge H, Straathof AL (2021). Comparing root exudate collection techniques: An improved hybrid method. Soil Biol Biochem. doi:10.1016/j.soilbio.2021.108391
- Casas ME, Matamoros V (2021). Analytical challenges and solutions for performing metabolomic analysis of root exudates. Trends in Environmental Analytical Chemistry. doi:10.1016/j.teac.2021.e00130
- Strehmel N, Böttcher C, Schmidt S (2014). Profiling of secondary metabolites in root exudates of . Phytochemistry. doi:10.1016/j.phytochem.2014.10.003
- Loyola-Vargas VM, Broeckling CD, Badri D (2007). Effect of transporters on the secretion of phytochemicals by the roots of . Planta. doi:10.1007/s00425-006-0349-2
- Badri DV, de-la-Peña C, Lei Z (2012). Root Secreted Metabolites and Proteins Are Involved in the Early Events of Plant-Plant Recognition Prior to Competition. PLoS One. doi:10.1371/journal.pone.0046640
- Ziegler J, Schmidt S, Chutia R (2016). Non-targeted profiling of semi-polar metabolites in Arabidopsis root exudates uncovers a role for coumarin secretion and lignification during the local response to phosphate limitation. J Exp Bot. doi:10.1093/jxb/erv539
- Rosenkranz T, Oburger E, Baune M (2021). Root exudation of coumarins from soil-grown in response to iron deficiency. Rhizosphere. doi:10.1016/j.rhisph.2020.100296
- Chaparro JM, Badri DV, Bakker MG (2013). Root Exudation of Phytochemicals in Arabidopsis Follows Specific Patterns That Are Developmentally Programmed and Correlate with Soil Microbial Functions. PLoS One. doi:10.1371/journal.pone.0055731
- Conn SJ, Hocking B, Dayod M (2013). Protocol: optimising hydroponic growth systems for nutritional and physiological analysis of and other plants. Plant Methods. doi:10.1186/1746-4811-9-4
- Biedrzycki ML, Jilany TA, Dudley SA (2010). Root exudates mediate kin recognition in plants. Commun Integr Biol. doi:10.4161/cib.3.1.10118
- Mönchgesang S, Strehmel N, Schmidt S (2016). Natural variation of root exudates in -linking metabolomic and genomic data. Sci Rep. doi:10.1038/srep29033
- Schmidt H, Günther C, Weber M (2014). Metabolome analysis of roots identifies a key metabolic pathway for iron acquisition. PLoS One. doi:10.1371/journal.pone.0102444
- Aulakh MS, Wassmann R, Bueno C (2008). Characterization of Root Exudates at Different Growth Stages of Ten Rice ( L.) Cultivars. Plant Biol. doi:10.1055/s-2001-12905
- McLaughlin S, Zhalnina K, Kosina S (2023). The core metabolome and root exudation dynamics of three phylogenetically distinct plant species. Nat Commun. doi:10.1038/s41467-023-37164-x
- Dietz S, Herz K, Gorzolka K (2020). Root exudate composition of grass and forb species in natural grasslands. Sci Rep. doi:10.1038/s41598-019-54309-5
- Herz K, Dietz S, Gorzolka K (2019). Correction: Linking root exudates to functional plant traits. PLoS One. doi:10.1371/journal.pone.0213965
- Schmid C, Bauer S, Müller B (2013). Belowground neighbor perception in studied by transcriptome analysis: roots of cause biotic stress. Front Plant Sci. doi:10.3389/fpls.2013.00296
- Badri DV, Loyola-Vargas VM, Broeckling CD (2010). Root secretion of phytochemicals in is predominantly not influenced by diurnal rhythms. Mol Plant. doi:10.1093/mp/ssq004
- Onat B, Rosales-Solano H, Ferrier L (2021). Identification of the metabolites regulated in soybean- symbiosis through solid phase microextraction coupled with LC-MS. J Chromatogr A. doi:10.1016/j.chroma.2021.461934
- Walker TS, Bais HP, Halligan KM (2003). Metabolic profiling of root exudates of . J Agric Food Chem. doi:10.1021/jf021166h
- Gorrochategui E, Jaumot J, Lacorte S (2016). Data analysis strategies for targeted and untargeted LC-MS metabolomic studies: Overview and workflow. TrAC - Trends in Analytical Chemistry. doi:10.1016/j.trac.2016.07.004
- Shaffer JP, Nothias LF, Thompson LR (2022). Standardized multi-omics of Earth's microbiomes reveals microbial and metabolite diversity. Nat Microbiol. doi:10.1038/s41564-022-01266-x
- Tetyuk O, Benning UF, Hoffmann-Benning S (2013). Collection and analysis of phloem exudates using the EDTA-facilitated Method. J Vis Exp. doi:10.3791/51111
- Dührkop K, Scheubert K, Böcker S (2013). Molecular Formula Identification with SIRIUS. Metabolites. doi:10.3390/metabo3020506
- Blaženović I, Kind T, Ji J (2018). Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics. Metabolites. doi:10.3390/metabo8020031
- Wang S, Su Y, Li J (2022). Integration of LC/MS-based molecular networking and molecular docking allows in-depth annotation and prediction of the metabolome: A study of Bunge. Industrial Crops and Products. doi:10.1016/j.indcrop.2022.115298
- Kim HW, Wang M, Leber CA (2021). NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products. J Nat Prod. doi:10.1021/acs.jnatprod.1c00399
- Hua Y, Wainhaus SB, Yang Y (2001). Comparison of negative and positive ion electrospray tandem mass spectrometry for the liquid chromatography tandem mass spectrometry analysis of oxidized deoxynucleosides. J Am Soc Mass Spectrom. doi:10.1016/S1044-0305(00)00191-4
- Subrahmaniam HJ, Salomonsen CL, Radutoiu S (2022). Zenodo.
- Obata T, Fernie AR (2012). The use of metabolomics to dissect plant responses to abiotic stresses. Cell Mol Life Sci. doi:10.1007/s00018-012-1091-5
- Szecowka M, Heise R, Tohge T (2013). Metabolic fluxes in an illuminated rosette. Plant Cell. doi:10.1105/tpc.112.106989
- Ipsen A, Ebbels TMD (2012). Prospects for a Statistical Theory of LC/TOFMS Data. J Am Soc Mass Spectrom. doi:10.1007/s13361-012-0340-z
- van Dam NM, Bouwmeester HJ (2016). Metabolomics in the Rhizosphere: Tapping into Belowground Chemical Communication. Trends Plant Sci. doi:10.1016/j.tplants.2016.01.008
- Dahl Dueholm J (2023). Targeted and Nontargeted Analysis of Root Exudate Composition from Different Arabidopsis thaliana Genotypes using Ultra-High-Performance Liquid Chromatography - Mass Spectrometry.
- Subrahmaniam HJ (null). The genetics of intraspecific plant-plant cooperation in Arabidopsis thaliana.