Detection of Fungi and Oomycetes by Volatiles Using E-Nose and SPME-GC/MS Platforms

Abstract

Fungi and oomycetes release volatiles into their environment which could be used for olfactory detection and identification of these organisms by electronic-nose (e-nose). The aim of this study was to survey volatile compound emission using an e-nose device and to identify released molecules through solid phase microextraction-gas chromatography/mass spectrometry (SPME-GC/MS) analysis to ultimately develop a detection system for fungi and fungi-like organisms. To this end, cultures of eight fungi (Armillaria gallica, Armillaria ostoyae, Fusarium avenaceum, Fusarium culmorum, Fusarium oxysporum, Fusarium poae, Rhizoctonia solani, Trichoderma asperellum) and four oomycetes (Phytophthora cactorum, P. cinnamomi, P. plurivora, P. ramorum) were tested with the e-nose system and investigated by means of SPME-GC/MS. Strains of F. poae, R. solani and T. asperellum appeared to be the most odoriferous. All investigated fungal species (except R. solani) produced sesquiterpenes in variable amounts, in contrast to the tested oomycetes strains. Other molecules such as aliphatic hydrocarbons, alcohols, aldehydes, esters and benzene derivatives were found in all samples. The results suggested that the major differences between respective VOC emission ranges of the tested species lie in sesquiterpene production, with fungi emitting some while oomycetes released none or smaller amounts of such molecules. Our e-nose system could discriminate between the odors emitted by P. ramorum, F. poae, T. asperellum and R. solani, which accounted for over 88% of the PCA variance. These preliminary results of fungal and oomycete detection make the e-nose device suitable for further sensor design as a potential tool for forest managers, other plant managers, as well as regulatory agencies such as quarantine services.

Keywords: EI mass spectrometry; SPME-GC/MS; VOCs; e-nose; fungi; oomycetes; sesquiterpenes.

Figure 1

Distribution of the overall averaged values of twelve differential sensor original signals for the respective 14 treatments; e.g., (a) control 1 (empty flask); (b) control 2 (PDA medium); (c) A. gallica; (d) A. ostoyae; (e) F. avenaceum; (f) F. culmorum; (g) F. oxysporum; (h) F. poae; (i) P. cactorum; (j) P. cinnamomi; (k) P. plurivora; (l) P. ramorum; (m) R. solani; (n) T. asperellum.

Figure 2

Variability of twelve differential sensor signals assigned to the twelve investigated microorganisms. Vectors were colored according to their contribution to total variance: orange—low, blue—high. Blue dots represent controls: 1—empty flask, and 2—PDA medium; red dots—microorganisms with the most pronounced eigenvalues, black dots—microorganisms with less pronounced eigenvalues (cf. Table S2, Figure S1).

Figure 3

Representative view of the differential electronic nose apparatus. (a) Introduction of the air intake tube inside the sample; (b) Twelve chemical sensors in an array chamber; (c) General scheme of the e-nose principle of measurement: (1) Sample flask; (2) Ambient air; (3) Tested material; (4) Sensor chambers; (5) Inducting pump and flow-meter. Adapted from Brudzewski et al. [22], Osowski et al. [114].