A Companion to Plant Physiology, Fifth Edition by Lincoln Taiz and Eduardo Zeiger
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Essay 13.7

The Plant Volatilome

Massimo Maffei, Plant Physiology Unit, Department of Plant Biology, University of Turin, Innovation Centre, Turin, Italy

May, 2011

Definitions

The plant volatilome is defined as the complex blend of volatile organic compounds (VOCs) fed by different biosynthetic pathways and produced by plants, constitutively and/or after induction, as a defense strategy against biotic and abiotic stress (Maffei et al. 2007). Almost all plants are able to emit VOCs and the content and composition of these organic compounds shows both genotypic variation and phenotypic plasticity. VOCs are released from leaves, flowers, and fruits into the atmosphere and from roots into the soil. The primary functions of airborne VOCs are to defend plants against herbivores and pathogens, to attract pollinators, seed dispersers, and other beneficial animals and microorganisms, and to serve as signals in plant–plant communication (Dudareva and Pichersky 2008). In some plants, released VOCs may also act as wound sealers. Some plants use the volatilome as a direct defense through constitutive secretion in specialized tissues that accumulate deterrent compounds, whereas others produce VOCs as indirect defense. In both strategies biotic and abiotic stresses may alter or increase the plant volatilome content. The plant volatilome is also involved in plant–plant interactions, signaling between symbiotic organisms and for the attraction of pollinating insects (Figure 1). The biochemistry and molecular biology of the plant volatilome is vast and complex; it includes several biochemical pathways and thousands of genes. The plant volatilome has wide agricultural and industrial applications, from the search for sustainable methods for pest control to the valuable production of flavours, fragrances, and phytochemicals.

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Figure 1   The plant volatilome. Plants emit a wide array of volatile compounds for pollinator attraction and in response to biotic and abiotic stress. Flowers emit compounds belonging to several major classes of VOCs to attract pollinators. Extrafloral nectaries attract both ants and butterflies and their activation is inducible by insect herbivory. Several beetles, such as Chrysolina herbacea, feed on aromatic plants despite their toxic compounds and induce increased VOC plant emissions. Aphids feeding on plants trigger the emission of several monoterpenes and homoterpenes. Sucking herbivores, like spider mites, induce VOC emissions that attract their predators. Chewing herbivores, like Spodoptera littoralis, induce plant emission of several monoterpenes, sesquiterpenes, and homoterpenes that attract predatory wasps. Oviposition induces plant volatile emission for host and prey location by parasitoids and predators. Insect-induced below-ground plant signals include the emission of several sesquiterpenoids which strongly attract entomopathogenic nematodes. Plant–bacteria interactions promote plant synthesis of sesquiterpenoid precursors, which are eventually transformed into an array of chemically diverse VOCs. (Click image to enlarge.)

Volatilomics, the study of the volatilome, includes the qualitative and quantitative analysis of VOCs emitted by plants, headspace analysis of plant VOCs emitted by the whole organism, organs, or enzymes, as well as advanced on-line analysis of methods for simultaneous measurements of VOC emissions with other physiological parameters. Improvements in analytical techniques and molecular and biochemical methods have made VOCs one of the best-studied groups of plant secondary metabolites (Tholl et al. 2006, Pichersky et al. 2006). Furthermore, the development of static and dynamic techniques for headspace collection of volatiles in combination with gas chromatography-mass spectrometry (GC-MS) analysis has significantly improved our understanding of the biosynthesis and ecology of plant VOCs. Moreover, advances in automated analysis of VOCs have allowed the monitoring of fast changes in VOC emissions and facilitated in vivo studies of VOC biosynthesis. Volatilomics has reached threshold levels allowing the characterization and quantification of VOCs with limits resembling the detection ability of molecular sensors present in living organisms.

The aim of this essay is to present some techniques that are used for the detection of the plant volatilome.

Instruments and techniques for the detection of the plant volatilome

All methods for the analysis of plant volatiles attempt to identify the authentic profile of volatile blends emitted by a plant. However, the choice of which system to use in a particular experiment for collection and analysis of plant volatiles usually depends on the biological problem and plant material being investigated. Plants producing essential oils are usually distilled and the extracted oils analyzed by gas chromatography, often coupled to mass spectrometry (Figure 2).

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Figure 2   Gas chromatography and mass spectrometry. Picture of a typical GC-MS apparatus. (Click image to enlarge.)

Physiological experiments aimed to detect VOC emission often require that the plant tissue remain intact and make use of non-invasive/destructive techniques that rely on the detection and analysis of molecules emitted by plants in the surrounding atmosphere. Volatiles can be analyzed from plants growing under laboratory conditions or in their natural habitat. Field collections of VOCs require portable, robust, and often simplified equipment, whereas system set-ups in the laboratory can include computer-assisted sample collection and additional devices to reduce contamination and to precisely control environmental conditions. In order to distinguish local or systemic responses or to correlate VOC emissions with tissue-specific responses, whole plant VOC analysis is not sufficient, thus it is often required to sample VOCs from plant parts or organs. VOCs have been investigated most extensively in the “head space” surrounding above-ground plant parts, giving a realistic picture of the volatile profile emitted by plants and detected by insects that respond to plant volatiles. A variety of sorbents is available for the sampling of airborne organic pollutants. However, choosing the right sorbent for a certain analytical target is still a challenge. Frequently used sorbents are Tenax TA, Chromosorb 106, Porapak N, and Carbopack F. The simplest way to trap VOCs is to force an air flux containing volatiles through these sorbents, which usually fill a small glass column. Elution with appropriate organic solvents allows extraction of the analytes from the sorbent for subsequent GC analysis. Tenax TA has smaller polar and van der Waals interaction properties than Chromosorb 106 and Porapak N. This rather weak sorption capacity makes Tenax TA very suitable for less volatile compounds for which a quantitative desorption is the critical issue.

The relatively new technique of Solid Phase Microextraction (SPME), originally introduced for water analysis, was promptly optimized for the headspace analysis of volatile compounds in air. Headspace (HS) SPME has strongly contributed to a renewal in the interest in headspace sampling that has taken place over the last fifteen years. The SPME process involves the performance of two basic steps: (a) partitioning of analytes between the extraction phase and the sample matrix and (b) desorption of concentrated extracts into an analytical instrument. This technique is based on the use of polydimethylsiloxane (PDMS) as an extraction medium for analytes. Owing to the specific characteristics of PDMS, superior performance is encountered because analytes are not retained on an active surface, as is the case with adsorbents, but are partitioned or sorbed into the bulk of the PDMS phase and retained within the bulk of the sorbent. Since sorption is a much weaker process than adsorption, degradation of unstable analytes is significantly less or absent on PDMS compared to adsorbents. Moreover, the retaining capacity of PDMS for a certain compound is not influenced by the presence of high amounts of water or other analytes since all solutes have their own partitioning equilibrium into the PDMS phase and displacement does not occur. Exposed SPME fibers are then thermally desorpted inside the GC injector port and the analytes separated through the GC column for final detection. Although SPME is a simple and rapid technique, the applicability of SPME is limited by the small amount of PDMS on the needle, typically less than 0.5 μL, which results in low extraction efficiencies. In order to improve efficiency, stir bars were incorporated in a glass tube giving an outer diameter (o.d.) of 1.2 mm and coated with a layer of 1 mm PDMS which represents a total thickness of the stir bars of 3.2 mm o.d. The amount of PDMS can be varied with the length; typically 10 mm (5 μL of PDMS) to 40 mm (219 μL of PDMS) are applied to small and large volumes, respectively. After a certain exposure time, the stir bar is removed, introduced in a glass tube, and transferred to a thermal desorption instrument where the analytes are thermally released and transferred to the GC-mass spectrometry MS instrument (Baltussen et al. 1999). This technique is called Stir Bar Sorptive Extraction (SBSE) when used in liquid extraction, or Head Space Sorptive Extraction (HSSE) when used in gas phase (Figure 3).

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Figure 3   SPME and SBSE: A. Schematic representation of Solid Phase Micro Extraction (SPME). B. Schematic representation of Stir Bar Sorptive Extraction (SBSE). (Click image to enlarge.)

Other methods used to detect VOCs include chemiluminescence or infrared photoacoustic (PA) spectroscopy, supercritical extraction (SFE) that exploits the dissolving power of supercritical fluids (SF), microwaves for high efficiency extraction and sample direct injection. In proton transfer reaction mass spectrometry (PTR-MS), the air containing VOCs to be analyzed is continuously pumped through a drift tube reactor, and a fraction of the VOCs is ionized in proton-transfer reactions with hydronium ions (H3O+), overcoming some of the disadvantages of GC methods at the cost of chemical detail. VOCs can also be detected by the use of the so-called “z-Nose.” The z-Nose operates at the speed of an electronic nose while delivering the precision and accuracy of a GC. The z-Nose consists of a sensor head containing the hardware necessary to separate and detect the compounds in the analyte. The analyzer is based on a single, uncoated quartz based surface acoustic wave sensor (SAW) with an uncoated piezoelectric quartz crystal that vibrates at a fundamental frequency. The crystal is in contact with the thermoelectric element, which controls the temperature for cooling during vapor adsorption and for heating during cleaning, and operates by maintaining a highly focused and resonant surface acoustic wave at 500 MHz on its surface. Upon adsorption of the mass, the frequency of the surface acoustic wave will change in proportion to the adsorbant (Tewari and Irudayaraj 2005).

Rapid sensing of VOCs has been achieved by electronic noses. Electronic noses (e-noses) are instruments which mimic the sense of smell. These devices are typically arrays of sensors used to detect and distinguish odors precisely in complex samples and at low cost. The sensor array consists of broadly tuned (non-specific) sensors that are treated with a variety of odor-sensitive biological or chemical materials. Sensors with different transducer principles will be selective for different classes of substances and can therefore often provide additional information. Hence, in recent years the original sensor types used for electronic noses were not only enhanced, but also complemented by other technologies introduced in this field (Rock et al. 2008).

Other techniques make direct use of insects to detect the presence and biological activity of plant VOCs. Alternatively, the effluent from GC can be linked to electrophysiological recordings from insect antennae, the main sensory organs of these organisms. By either using the whole antenna (the electroantennogram, EAG) or recording from individual olfactory neurons (single cell recording, SCR), it can be determined which peaks eluting from the GC are of significance to the insect. Finally, functional genomics approaches for dissecting the metabolic pathways of plant VOCs have provided a means for high-throughput profiling of volatile metabolites of mutant and transgenic plant lines. Future trends in volatilomics will be at the level of systems biology, linking dynamic chemical signals to physiological responses.

Analyzing the plant volatilome in vivo

The majority of VOCs entering the atmosphere are of biogenic origin and over 90 percent of natural emission of VOCs is related to plants. Dominant sources of VOCs are tropical forests—the most important among them is the Amazonian rainforest—and extra-tropical forests, all emitting large quantities of VOCs such as isoprene, α- and Β-pinene, and methanol. Among numerous techniques for the determination of VOCs, GC-MS with thermal desorption is one of the most widespread.

In the atmosphere, VOCs are removed by photochemical and deposition processes on timescales varying from minutes to months. Measurements of VOCs in the atmosphere have largely been made using gas chromatographic analysis of air samples that were either collected in canisters, on adsorbents, or in cryostats. However, GC measurements provide highly detailed snapshots of the atmospheric VOC composition, but are generally too slow to follow rapid changes in air mass composition. PTR-MS has been used since 1998 for field measurements of atmospheric VOCs from a wide variety of aircraft, ship- and ground-based platforms. For a review of the use of PTR-MS, see De Gouw and Warneke (2007).

Besides global studies on atmospheric VOC emissions, most of the studies are performed in the lab by treating plants either with biotic or abiotic stress agents. Herbivory, repeated mechanical damage, and application of some xenobiotics or elicitors have been demonstrated to induce leaf tissues to emit VOCs both from plants rooted in pots and cuttings.

There are several ways to detect VOC plant emission from stressed plants, from very simple to highly sophisticated. VOC detection can be performed in static and dynamic conditions. The simplest way to run dynamic VOC analysis is to place rooted plants or cuttings inside a sealed glass container containing an inlet and an outlet in order to flush inside clean air and to remove air containing plant-emitted VOCs. Usually a pure GC-grade air tank (or a GC-grade air generator) provides the air flushing in, whereas a trapping system is connected to the air-out connection. VOCs can be trapped in small glass columns filled with specific sorbents (i.e., Tenax TA, Chromosorb 106, Porapak N, or Carbopack F), or to Pasteur pipettes hosting PDMS covered supports (i.e., SPME or SBSE). Sorbents can be eluted with organic solvents and then the eluate injected directly to a GC injector port, while SPME can be used for direct injection/desorption and HSSE thermally desorpted with a thermal desorption unit. Static analysis can be performed with the sorbents, SPME and HSSE without the use of flushing clean air. In this method plants (or plant tissues) are allowed to saturate the sorbents in a sealed chamber for a give time and then the sorbent analyzed as above (Figure 4A).

Monitoring of induced plant VOC emissions can be performed with on-time VOC analysis by fast and transportable GC (zNose®). For example, detached plantlets of Lima bean (Phaseolus lunatus) are placed in a sealed 4-L glass vessel. Pressurized purified air passes through the glass container at a given flow rate and exits. Simultaneously, air samples are time-course analyzed by the zNose®. Volatile emissions can be monitored for several days. Recordings of VOC emission profiles are comparable between conventional adsorbent trapping and zNose® measurements, with a significantly higher time resolution obtained by zNose® analysis (Figure 4B).

A sensor array made up of metal oxide thin films has also been developed for the detection of stress VOCs produced by plants in greenhouses. This sensor array was coupled with other sensors for illumination, CO2, and humidity to realize an advanced hybrid electronic nose that was successfully employed to monitor plant health inside a greenhouse. The electronic nose was able to detect the onset of abiotic and biotic plant stresses. Upon chemical, mechanical, or biotic stress plant cells respond immediately with the production of stress VOCs, among which the most important is the gas hormone ethylene. Sensor arrays appeared to be able to detect as an early signal the emission of VOCs and ethylene by plants and acted as stress sensors (Figure 4C). Headspace analysis performed using both SPME and SBSE may give supplementary information on the type of volatiles emitted by plants, but sometimes the resolution is too low to identify ethylene. Instead, metal oxide thin film array EOS 835 allow for the recognition of biotic or abiotic plant stress, by better detecting VOCs emitted by plants (Baratto et al. 2005).

Today, it is not only metal oxide sensors of varying selectivities which are available for VOC detection, but also other transducers with electrochemical readouts such as conducting polymers, metal oxide field effect transistors, or amperometric sensors. Furthermore, gravimetric, thermal, and optical sensors which have a completely different transduction principle are also in use.

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Figure 4   Some methods used to detect VOC emission from plants in vivo. A. On the left, in the dynamic extraction, plants are placed in a sealed glass container connected to a pure air tank that provides a flushing stream of air that enters the container, and forces the VOCs emitted by the plants to pass through either a vial filled with different sorbents or a Pasteur pipette hosting SPME and/or SBSE. On the right, in the static extraction, the glass container is sealed and non-flushed with air. SPME is directly exposed to the container, in which atmosphere is saturated by the emitte plant VOCs. Alternatively, a gas syringe can be used to sample the VOCs for subsequent GC analysis. B. Monitoring of induced plant VOC emissions by fast and transportable GC (zNose®). Detached plantlets of Phaseolus lunatus were placed in a sealed 4-L glass vessel. Pressurized purified air passes through the glass container (dashed arrows) and exits the chamber through a charcoal filter adsorbent trap (“push” system). Volatiles are trapped on adsorbent cartridges in 4-h sampling periods. Simultaneously, air samples are analyzed every 15 minutes by the zNose® with a sampling time of 20 seconds. Volatile emissions were monitored for 4 days. Recordings of VOC emission profiles were comparable between adsorbent trapping and zNose® measurements, with a significantly higher time resolution obtained by zNose® analysis (reprinted with permission from Tholl et al. 2006). C. Detecting plant emissions with the electronic nose. The diagram on the left illustrates the logic of the experiment. Plants are placed into a glass container connected to an electronic nose and to other sensors (CO2, temperature, humidity). The air is circulated by a peristaltic pump and cooled to prevent overheating. The pictures on the right illustrate the equipment used for this experiment. (Click image to enlarge.)

Conclusion

There has been enormous progress in the analysis of plant VOCs that has been stimulated by very different areas of research, such as plant physiology, ecology, atmospheric chemistry, and molecular biology. The ever-demanding need to shorten analysis time and increase data accuracy has challenged the development of a wide array of sorbing resins and detecting methods. These advances have created opportunities for detailed views on the time courses of VOC emissions in many fields of research, from involvement of plant VOCs in the attraction of pollinators or the deterrence of herbivores to the early detection of pest and pathogen infestation in both open and closed environments of major crops and/or ornamental plants. The new frontier is represented by electronic devices made with cheap, reliable, light, and repeatable performances, such as the new generation electronic noses. Despite the success in some areas, the efforts to arrive at a universal mechanism that can make fine discrimination of flavours, perfumes, and smells and eventually replace the human nose are somehow disappointing. However, sensors with new sensitive layers are under development, based, for instance, on DNA, molecular imprinted molecules, or even immobilizer natural receptors (up to whole cells), which promise to increase the sensitivity and importantly selectivity.

References

Baltussen, E., Sandra, P., David, F., and Cramers, C. (1999) Stir bar sorptive extraction (SBSE), a novel extraction technique for aqueous samples: Theory and principles. Journal of Microcolumn Separations 11: 737–747.

Baratto, C., Faglia, G., Pardo, M., Vezzoli, M., Boarino, L., Maffei, M., Bossi, S., and Sberveglieri, G. (2005) Monitoring plants health in greenhouse for space missions. Sensors and Actuators B-Chemical 108: 278–284.

de Gouw, J., and Warneke, C. (2007) Measurements of volatile organic compounds in the earth’s atmosphere using proton-transfer-reaction mass spectrometry. Mass Spectrometry Reviews 26: 223–257.

Dudareva, N., and Pichersky, E. (2008) Metabolic engineering of plant volatiles. Current Opinion in Biotechnology 19: 181–189.

Maffei, M.E., Mithofer, A., and Boland, W. (2007) Insects feeding on plants: Rapid signals and responses preceding the induction of phytochemical release. Phytochemistry 68: 2946–2959.

Pichersky, E., Noel, J.P., and Dudareva, N. (2006) Biosynthesis of plant volatiles: Nature’s diversity and ingenuity. Science 311: 808–811.

Rock, F., Barsan, N., and Weimar, U. (2008) Electronic nose: Current status and future trends. Chemical Reviews 108: 705–725.

Tewari, J.C., and Irudayaraj, J.M.K. (2005) Floral classification of honey using mid-infrared spectroscopy and surface acoustic wave based z-Nose sensor. Journal of Agricultural and Food Chemistry 53: 6955–6966.

Tholl, D., Boland, W., Hansel, A., Loreto, F., Rose, U.S.R., and Schnitzler, J.P. (2006) Practical approaches to plant volatile analysis. Plant Journal 45: 540–560.

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