Plant Hormonomics: Multiple Phytohormone Profiling by Targeted Metabolomics
PLANT PHYSIOLOGY 2018, 177 (2):476-489
Simura J, Antoniadi I, Siroka J, Tarkowska D, Strnad M, Ljung K, Novak O

Abstract
Phytohormones are physiologically important small molecules that play essential roles in intricate signaling networks that regulate diverse processes in plants. We present a method for the simultaneous targeted profiling of 101 phytohormone-related analytes from minute amounts of fresh plant material (less than 20 mg). Rapid and nonselective extraction, fast one-step sample purification, and extremely sensitive ultra-high-performance liquid chromatography-tandem mass spectrometry enable concurrent quantification of the main phytohormone classes: cytokinins, auxins, brassinosteroids, gibberellins, jasmonates, salicylates, and abscisates. We validated this hormonomic approach in salt-stressed and control Arabidopsis (Arabidopsis thaliana) seedlings, quantifying a total of 43 endogenous compounds in both root and shoot samples. Subsequent multivariate statistical data processing and cross-validation with transcriptomic data highlighted the main hormone metabolites involved in plant adaptation to salt stress.

During the last decade, the techniques used in metabolomic analyses have advanced tremendously. In plant science, the most widely used methods are based on separation by liquid chromatography (LC) or gas chromatography combined with tandem mass spectrometric detection (MS/MS). The main advantages of these combinations are high sensitivity and versatility. To enhance signals of trace compounds, such as the plant hormones (phytohormones) considered here, it is essential to reduce the influence of abundant interfering compounds present in plant matrices by rigorous purification of extracts before the instrumental analysis (Du et al., 2012). The sample preparation steps usually include solid-phase extraction (SPE) with general-purpose sorbents or more selective immunosorbents that specifically target the selected compounds (Pencík et al., 2009; Turečková et al., 2009; Oklestkova et al., 2017; Plačková et al., 2017). Many analytical methods (particularly the immunological methods) have been described for the determination of a single compound or a specific class of phytohormones (Du et al., 2012; Tarkowská et al., 2014). However, there is growing interest in methods capable of simultaneously analyzing phytohormones of several classes together with their precursors and metabolites, for the following reasons.

Phytohormones are naturally occurring signaling molecules that play key roles in the regulation of plant physiology, development, and adaptation to environmental stimuli. Generally, their concentrations in plant tissues are extremely low (fmol to pmol g−1 fresh weight). They are also exceptionally diverse compounds with wide ranges of physicochemical properties and are divided into several structural classes: cytokinins (CKs) and 2-methylthiocytokinins (2MeSCKs), auxins (AXs), ethylene, gibberellins (GAs), abscisic acid and its metabolic products (hereafter referred to as abscisates [ABAs]), brassinosteroids (BRs), jasmonates (JAs), salicylic acid (SA), and strigolactones (Davies, 2010; Zwanenburg et al., 2016). Their biological activities depend on their availability, which is controlled by their biosynthetic and metabolic rates, cellular and subcellular localization, transport, and responses of the signal perception and transduction pathways (Davies, 2010). Modulations at any of these levels can directly affect myriad physiological processes. Although certain phytohormones are usually related to specific biological functions or responses, there is increasing evidence that plant hormone signaling involves complex interactions (cross talk) among all the pathways involved (Vanstraelen and Benková, 2012). Indeed, this is hardly surprising, as plants in natural environments may have to cope simultaneously with (for example) salt, water, and temperature stresses, pathogen attack, competition, and a need to complete certain physiological processes within environmentally dictated time frames. Thus, plants’ physiological regulation involves challenging coordination of the biosynthesis, transport, and metabolism of multiple hormones, their highly interacting signal transduction pathways, transcription factors, and responsive genes.

Clearly, a convenient method to simultaneously quantify as wide a range as possible of plant signaling molecules of all known classes would greatly facilitate the investigation of hormone functions and networks. Thus, several plant hormone-profiling techniques have been published, and the number of covered compounds is increasing (Chiwocha et al., 2003; Pan et al., 2008; Kojima et al., 2009; Farrow and Emery, 2012; Cao et al., 2016; Wang et al., 2017). The most extensive analysis of primary and secondary metabolites published to date included 53 plant hormone-related compounds (Schäfer et al., 2016), and a more focused analysis of plant growth substances covered 54 compounds (Cai et al., 2016). However, there is scope for further extension. An ideal method should provide both a qualitative overview and precise quantitative information for all covered compounds. It also requires appropriate sample preparation and high instrumental performance (in terms of both robustness and sensitivity), due to the low concentrations of phytohormones (relative to those of primary and secondary metabolites) and wide ranges of chemical structure and stability.

Here, we present a methodology with these features, designed to afford rapid, sensitive, and simultaneous LC-MS/MS-based profiling of 101 CKs, AXs, GAs, BRs, ABAs, JAs, and SA. The analytes include bioactive forms of the hormones, their precursors, and metabolites to acquire quantitative snapshots of the physiological status of sampled tissues (Supplemental Table S1). The protocol for isolating all 101 compounds combines rapid, one-step, nonselective extraction from milligram amounts of plant tissues (less than 20 mg fresh weight) followed by their LC separation and extremely sensitive MS-based quantification. To assess the practical utility of this hormonomic approach, the method was applied to characterize phytohormone profiles in root and shoot tissues of control and salt-stressed Arabidopsis (Arabidopsis thaliana) seedlings. Our results highlight the value of such analysis, which (together with multivariate data analysis and cross-validation with transcriptomic data) revealed the seedlings’ hormonal responses to salinity stress, one of the major factors limiting crop production (Munns and Tester, 2008), and differences in the responses of their roots and shoots.

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