Hostname: page-component-74656f9884-8r8nv Total loading time: 0 Render date: 2026-11-08T08:24:36.654Z Has data issue: false hasContentIssue false
  • English
  • Français

Resolution of three cryptic agricultural pests (Ceratitis fasciventris, C. anonae, C. rosa, Diptera: Tephritidae) using cuticular hydrocarbon profiling

Published online by Cambridge University Press:  04 June 2014

L. Vaníčková ,
M. Virgilio ,
A. Tomčala ,
R. Břízová ,
S. Ekesi ,
M. Hoskovec ,
B. Kalinová ,
R. R. Do Nascimento  and
M. De Meyer
L. Vaníčková*
Affiliation:
Institute of Chemistry and Biotechnology, Federal University of Alagoas, BR 104 Norte Km 14, 57072-970 Maceió, Alagoas, Brazil Institute of Organic Chemistry and Biochemistry of the ASCR, Flemingovo nám. 2, CZ-166 10 Prague 6, Czech Republic
M. Virgilio
Affiliation:
Royal Museum for Central Africa, Leuvensesteenweg 13, B-3080 Tervuren, Belgium
A. Tomčala
Affiliation:
Institute of Organic Chemistry and Biochemistry of the ASCR, Flemingovo nám. 2, CZ-166 10 Prague 6, Czech Republic
R. Břízová
Affiliation:
Institute of Organic Chemistry and Biochemistry of the ASCR, Flemingovo nám. 2, CZ-166 10 Prague 6, Czech Republic Institute of Chemical Technology in Prague, Technická 5, CZ-166 28 Prague 6, Czech Republic
S. Ekesi
Affiliation:
International Centre of Insect Physiology and Ecology, PO Box 30772-00100 GPO, Nairobi, Kenya
M. Hoskovec
Affiliation:
Institute of Organic Chemistry and Biochemistry of the ASCR, Flemingovo nám. 2, CZ-166 10 Prague 6, Czech Republic
B. Kalinová
Affiliation:
Institute of Organic Chemistry and Biochemistry of the ASCR, Flemingovo nám. 2, CZ-166 10 Prague 6, Czech Republic
R. R. Do Nascimento
Affiliation:
Institute of Chemistry and Biotechnology, Federal University of Alagoas, BR 104 Norte Km 14, 57072-970 Maceió, Alagoas, Brazil
M. De Meyer
Affiliation:
Royal Museum for Central Africa, Leuvensesteenweg 13, B-3080 Tervuren, Belgium
*
*Author for correspondence E-mail: luci.vanickova@gmail.com
Rights & Permissions [Opens in a new window]

Abstract

Discrimination of particular species within the species complexes of tephritid fruit flies is a very challenging task. In this fruit-fly family, several complexes of cryptic species have been reported, including the African cryptic species complex (FAR complex). Cuticular hydrocarbons (CHCs) appear to be an excellent tool for chemotaxonomical discrimination of these cryptic species. In the present study, CHC profiles have been used to discriminate among three important agricultural pests from the FAR complex, Ceratitis fasciventris, Ceratitis anonae and Ceratitis rosa. Hexane body surface extracts of mature males and females were analyzed by two-dimensional gas chromatography with mass spectrometric detection and differences in CHC profiles between species and sexes tested through multivariate statistics and compared with species identification by means of microsatellite markers. Quantitative as well as qualitative CHC profile differences between sexes and species are reported. The CHC profiles consisted of a mixture of linear, internally methyl-branched and mono-, di- and tri-unsaturated alkanes. Twelve compounds were pinpointed as potential chemotaxonomical markers. The present study shows that presence or absence of particular CHCs might be used in the chemical diagnosis of the FAR complex. Moreover, our results represent an important first step in the development of a useful chemotaxonomic tool for cryptic species identification of these important agricultural pests.

Keywords

cryptic species complexgenus Ceratitiscuticular hydrocarbonspolymorphic microsatellite locichemotaxonomy

Information

Type
Research Paper
Information
Bulletin of Entomological Research , Volume 104 , Issue 5 , October 2014 , pp. 631 - 638
Copyright
Copyright © Cambridge University Press 2014 

Introduction

The genus Ceratitis (Diptera: Tephritidae) consists of approximately 100 species, some of them being important agricultural pests. In addition, due to the polyphagous diet of many fruit flies, some species may potentially become cosmopolitan pests in the near future (Yuval & Hendrichs, Reference Yuval, Hendrichs, Aluja and Norrbom2001). The Afro-tropical fruit flies Ceratitis fasciventris, Ceratitis anonae and Ceratitis rosa constitute the so-called FAR species complex (Virgilio et al., Reference Virgilio, Backeljau and De Meyer2007a, Reference Virgilio, Backeljau and De Meyerb). Historically, C. fasciventris was considered as a variety of C. rosa (Bezzi, 1920), yet recently it has been recognized as a separate species (De Meyer, Reference De Meyer2001). Unlike Ceratitis capitata, which has spread from its home range in East Africa and attained an almost worldwide distribution over the past century, C. fasciventris, C. anonae and C. rosa have so far not been reported outside the African continent (except for C. rosa on La Réunion and Mauritius islands). Nevertheless, they are potentially invasive (Fletcher, Reference Fletcher, Robinson and Hooper1989; White & Elson-Harris, Reference White and Elson-Harris1992; De Meyer et al., Reference De Meyer, Robertson, Peterson and Mansell2008). As it is difficult to distinguish some members of the FAR complex morphologically (De Meyer & Freidberg, Reference De Meyer, Freidberg and Freidberg2006), especially females, a number of molecular approaches for species recognition was developed in the past (Baliraine et al., Reference Baliraine, Bonizzoni, Guglielmino, Osir, Lux, Mulaa, Gomulski, Zheng, Quilici, Gasperi and Malacrida2004; Barr & McPheron, Reference Barr and McPheron2006; Virgilio et al., Reference Virgilio, Backeljau, Barr and Meyer2008; Steinke et al., Reference Steinke, Virgilio, Jordaens, Breman, Backeljau and De Meyer2012; Virgilio et al., Reference Virgilio, Jordaens, Breman, Backeljau and De Meyer2012). Virgilio et al. (Reference Virgilio, Delatte, Quilici, Backeljau and De Meyer2013) have specified five genotypic groups within the FAR complex using comparison of allelic variations at 16 microsatellite loci. These genotypic groups were labeled as R1 and R2 (representing C. rosa), F1 and F2 (representing C. fasciventris) and A (representing C. anonae). However, the use of microsatellite variability for cryptic species discrimination is rather laborious and expensive. The uncertain taxonomic status of particular populations has important practical implications on the effective development and use of the sterile insect techniques (SIT), with respect to rearing the sterile males of the correct species, and in consequence affects the international movement of fruits and vegetables due to trade barriers to important agricultural commodities which are hosts to pest tephritids (Dyck et al., Reference Dyck, Hendrichs and Robinson2005). Moreover, the identification of cryptic species is crucial for an accurate assessment of biodiversity estimates, for facilitating disease and crop–plant–pathogen control and for directing conservation efforts toward vulnerable endemic species (Paterson, Reference Paterson and Zalucki1991; Besansky, Reference Besansky1999; Copren et al., Reference Copren, Nelson, Vargo and Haverty2005; Garros et al., Reference Garros, Van Bortel, Trung, Coosemans and Manguin2006; Bickford et al., Reference Bickford, Lohman, Sodhi, Ng, Meier, Winkler, Ingram and Das2007). All these reasons prompt us to search for alternative tools for fruit-fly cryptic species identification.

In this study, we consider cuticular hydrocarbons (CHCs) as a potential tool for cryptic species discrimination. CHCs are the main constituents of insect epicuticle and play an important role in waterproofing of the cuticle (Gibbs, Reference Gibbs2011) and inter-individual recognition of insects (Howard & Blomquist, Reference Howard and Blomquist2005; Blomquist & Bagnères, Reference Blomquist and Bagnères2010; Curtis et al., Reference Curtis, Sztepanacz, White, Dyer, Rundle and Mayer2013; Jennings et al., Reference Jennings, Etges, Schmitt and Hoikkala2014). They are most widely analyzed in numerous insect lineages since they are often distinct and stable over large geographical areas (Martin et al., Reference Martin, Helantera and Drijfhout2008; Martin & Drijfhout, Reference Martin and Drijfhout2009). Biochemical investigations have shown that insects synthesize de novo most of their hydrocarbons themselves (Wakayama et al., Reference Wakayama, Dillwith and Blomquist1985; Gozansky et al., Reference Gozansky, Soroker and Hefetz1997; Martin et al., Reference Martin, Helantera and Drijfhout2008). The CHC composition is genetically determined and has a taxonomic potential (Lockey, Reference Lockey1991; Blomquist & Bagnères, Reference Blomquist and Bagnères2010; Guillem et al., Reference Guillem, Drijfhout and Martin2012; Kather & Martin, Reference Kather and Martin2012). Recently, CHC profiles have been used to resolve insect species complexes of the fruit-fly Drosophila buzzatii (Oliveira et al., Reference Oliveira, Manfrin, Sene, Jackson and Etges2011), the ants Pachycondyla villosa (Lucas et al., Reference Lucas, Fresneau, Kolmer, Heinze, Delabie and Pho2002) and Tetramorium caespitum/impurum (Schlick-Steiner et al., Reference Schlick-Steiner, Steiner, Moder, Seifert, Sanetra, Dyreson, Stauffer and Christian2006), termites (Haverty et al., Reference Haverty, Woodrow, Nelson and Grace2000), orchid bees (Pokorny et al., Reference Pokorny, Lunau, Quezada-Euan and Eltz2014) or mirids Macrolophus (Gemeno et al., Reference Gemeno, Laserna, Riba, Valls, Castañé and Alomar2012). Studies of CHCs of tephritid fruit flies (C. rosa, C. capitata, Anastrepha ludens, Anastrepha suspensa, Anastrepha fraterculus, Dacus cucurbitae and Dacus dorsalis) have shown the presence of n-alkanes, methyl-branched alkanes, alkenes and alkadienes (Carlson & Yocom, Reference Carlson and Yocom1986; Lavine et al., Reference Lavine, Carlson and Calkins1992; Sutton & Steck, Reference Sutton and Steck1994; Vaníčková, Reference Vaníčková2012; Vaníčková et al., Reference Vaníčková, Svatoš, Kroiss, Kaltenpoth, Nascimento, Hoskovec, Břízová and Kalinová2012). However, according to our present knowledge, there are no reports on the characterization of the CHC profiles of C. anonae and C. fasciventris concerning the sex- and species-specific differences.

Our objectives are: (a) to characterize the CHC profiles of C. fasciventris, C. anonae and C. rosa, (b) to quantify the differences between species and sexes and (c) to explore the possibility of using CHC profiling as a diagnostic tool.

Materials and methods

Insects

The experiments were performed with male and female laboratory-reared specimens of C. fasciventris, C. anonae and C. rosa. In order to evaluate the CHC differences within the FAR complex and between the FAR complex and a congeneric outgroup, laboratory-reared males and females of C. capitata were also included. The pupae of C. fasciventris, C. anonae and C. rosa were obtained from the International Centre of Insect Physiology and Ecology (ICIPE, Nairobi, Kenya), whereas pupae of C. capitata came from the entomological laboratory of the Food and Agriculture Organization/International Atomic Energy Agency (FAO/IAEA, Seibersdorf, Austria, originally from Argentina). The pupae were kept under identical laboratory conditions at the Institute of Organic Chemistry and Biochemistry (IOCB, Prague, Czech Republic). Eclosed adult flies were fed on artificial diet consisting of sugarcane:yeast (3:1) and mineral water and were kept at a relative humidity of 60%, at 25 °C and a 12L:12D photoperiod.

Chemical analyses

Prior to chemical analyses, 20-day-old adult flies were frozen at −18 °C and placed for 15 min into a desiccator to remove the surface moisture. In order to extract CHCs from insect body surface individual fly was placed in small glass vials, which contained 0.5 ml of hexane (Fluka, Germany) and gently agitate for 5 min. Bromdecane was used as an internal standard for quantification (50 ng per 1 ml of the extract). Each extract was concentrated to approximately 100 μl by a constant flow of nitrogen and stored in a freezer until analysis.

Two-dimensional (2D) gas chromatography with time-of-flight mass spectrometric detection (GC×GC/TOFMS) was used for the quantification and identification of CHC profiles. The analyses were performed on a LECO Pegasus 4D instrument (LECO Corp., St Joseph, MI, USA) equipped with a non-moving quad-jet cryomodulator. A DB-5 column (J&W Scientific, Folsom, CA, USA; 30 m×250 μm i.d.×0.25 μm film) was used for GC in the first dimension. The second-dimension analysis was performed on a polar BPX-50 column (SGE Inc., Austin, TX, USA; 2 m×100 μm i.d.×0.1 μm film). Helium was used as a carrier gas at a constant flow of 1 ml min−1. The temperature program for the primary GC oven was as follows: 150 °C for 2 min, then 150–300 °C at 5 °C min−1 and finally a 10 min hold at 320 °C. The program in the secondary oven was 10 °C higher than in the primary one and was operated in an iso-ramping mode. The modulation period, the hot-pulse duration and the cool time between the stages were set to 3.0, 0.4 and 1.1 s, respectively. The transfer line to the TOFMS was operated at 260 °C. The source temperature was 250 °C with a filament bias voltage of −70 eV. The data-acquisition rate was 100 Hz (scans sec−1) for the mass range of 29–400 amu. The detector voltage was 1750 V. For each sample, 1 μl was injected in the splitless mode. The inlet temperature was 200 °C. The purge time was 60 s at a flow of 60 ml min−1. The data were processed and consecutively visualized on 2D and three-dimensional chromatograms using LECO ChromaTOF™ software. The n-alkane standard (C8–C38; Sigma-Aldrich) was co-injected with authentic samples to determine the retention indices (RIs) of the analytes. The hydrocarbons were identified by a comparison of their MS fragmentation patterns and RI (Van Den Dool & Kratz, Reference Van Den Dool and Kratz1963; Pomonis et al., Reference Pomonis, Fatland, Nelson and Zaylskie1978; Carlson & Yocom, Reference Carlson and Yocom1986; Carlson et al., Reference Carlson, Roan, Yost and Hector1989; Lavine et al., Reference Lavine, Carlson and Calkins1992; Goh et al., Reference Goh, Ooi, Chuah, Yong, Khoo and Ong1993; Sutton & Carlson, Reference Sutton and Carlson1993; Sutton & Steck, Reference Sutton and Steck1994; Carlson et al., Reference Carlson, Bernier and Sutton1998; Geiselhardt et al., Reference Geiselhardt, Otte and Hilker2009; Vaníčková, Reference Vaníčková2012; Vaníčková et al., Reference Vaníčková, Svatoš, Kroiss, Kaltenpoth, Nascimento, Hoskovec, Břízová and Kalinová2012).

Statistics

The relative peak areas of 59 CHC compounds (as identified by the GC×GC/TOFMS in the deconvoluted total-ion chromatogram mode) were calculated in ten replicate specimens for each sex of the four species (N=80). Principal component analysis (PCA) was used for the unconstrained ordination of multivariate data (Anderson, Reference Anderson2003) and the percentage contribution of each CHC to the average dissimilarity between (a) species and (b) sexes within each species was calculated with similarity percentage analysis (SIMPER) (Clarke, Reference Clarke1993). Permutation multivariate analysis of variance (PERMANOVA: Anderson, Reference Anderson2001) was used to verify the differences in the CHC distribution patterns across species and sexes. PERMANOVA considered species (four levels: C. fasciventris, C. anonae, C. rosa, C. capitata) as a random factor and sex (two levels: male, female) as a fixed factor orthogonal to species. The tests were based on 105 unrestricted permutations of raw data. Pair-wise a posteriori comparisons of factor levels were then implemented using the PERMANOVA t-statistic (Anderson, Reference Anderson2001). Following Clarke (Reference Clarke1993), we log-transformed the multivariate data in order to reduce the differences in scale among the variables while preserving information on the relative abundance of CHCs across specimens.

Molecular genetic analyses

All chemically characterized FAR specimens were then genotyped at 16 polymorphic microsatellite loci using the primers and laboratory protocols described in Anderson et al. (Reference Anderson, Aparicio, Atangana, Beaulieu, Bruford, Cain, Campos, Cariani, Carvalho, Chen, Chen, Clamens, Clark, Coeur D'Acier, Connolly, Cordero-Rivera, Coughlan and Cross2010). The genetic data were combined with those of Virgilio et al. (Reference Virgilio, Backeljau, Nevado and De Meyer2010) and a PCA was performed to assign the FAR specimens of this study to one of the five genotypic clusters previously described (Virgilio et al., Reference Virgilio, Delatte, Quilici, Backeljau and De Meyer2013) (C. fasciventris F1, F2, C. anonae A, C. rosa R1, R2). The PCA was based on Euclidean distances among a total of 669 multilocus genotypes and computed using the R-package adegenet 1.3–4 (Jombart, Reference Jombart2008).

Results

The CHC profiles of the four African fruit-fly species of the genus Ceratitis are complex mixtures of straight-chained and methyl-branched alkanes, alkenes, alkadienes and alkatrienes with a wide range of carbon backbones (C23–C38). Altogether, the GC×GC/TOFMS analysis identified 59 CHC peaks, whose log-transformed areas were used for the statistical analyses. The subsequent PCA of the quantified data is depicted in fig. 1. The first two axes of the unconstrained PCA explained 63.6% of the variability (35.1 and 28.5%, respectively). The PCA clearly separated the three species of the FAR complex and the out-group C. capitata, as well as males from females of C. capitata, C. fasciventris and C. rosa. The PERMANOVA analyses and a posteriori pairwise permutational tests (table 1) showed highly significant differences both across species and across species and sexes and indicated that (a) all species have significantly different CHC profiles and (b) within each species, males and females have significantly different CHC profiles.

Fig. 1.

PCAs of Euclidean distances between males and females C. capitata, C. fasciventris, C. anonae and C. rosa (as calculated from peak areas of 59 CHCs).

Table 1.

PERMANOVA and a posteriori comparison (t-statistic) testing differences in multivariate patterns of 59 CHCs in relation to species (C. fasciventris, C. anonae, C. rosa, C. capitata) and sex (male×female) of 80 tephritid fruit flies.

P-values were obtained using 105 unrestricted permutations of raw data. Probability of Monte Carlo simulations: n.s.: not significant P<0.05; ***: P<0.001, **: P<0.01; *: P<0.05. df: degrees of freedom; MS: mean-square estimates; F: pseudo-F.

For each pairwise comparison, SIMPER (tables S1 and S2, Supplementary Materials) allowed the identification of the first ten CHCs that contributed the most to the differentiation between the three species of the FAR complex. Bray–Curtis dissimilarity between the FAR species ranged from 6.54 (between C. anonae and C. rosa) to 9.24 (between C. anonae and C. fasciventris) and it was comparably higher between the out-group C. capitata and the three FAR species (range 10.0–11.06, table S1 in Supplementary Material). The CHCs that contributed the most to the differences between the FAR species were the ones occurring only in one or two species (fig. 2, table 2, tables S1 and S2, Supplementary Materials). The Bray–Curtis dissimilarity between sexes within each of the FAR species was comparably lower and ranged from 2.58 to 3.99 (in C. rosa and C. fasciventris, respectively, table S2 in Supplementary Material). The 12 CHC compounds that contributed (>2% contribution to species dissimilarity) the most to interspecific differentiation (fig. 2, table 2, table S1 in Supplementary Material) comprised nine methyl-branched alkanes, two alkenes and one alkatriene. The RIs of all 12 CHCs were calculated. Among them, RI 3077 (3-MeC30) was detected in the females but not in the males of C. fasciventris and RI 2859 (4-MeC28) was detected in the females but not in the males of C. rosa. The differences between the peak areas of C. anonae were comparably lower (table S2 in Supplementary Material). In the case of dimethyl alkanes (RI 3269) the given RIs represented co-eluting mixture of three compounds. In C. capitata, the compounds specific for the males were RI 3488 (branched pentatriacontane) and RI 3630 (branched heptatriacontene C37:1) (table 2).

Fig. 2.

Average log-transformed CHCs peak areas (standard deviations as error bars), represented by RIs that contributed the most to the differences (>2% contribution to species dissimilarity) between C. fasciventris, C. anonae and C. rosa (see Supplementary Material, table 2).

Table 2.

Compounds identified by chemical analyses (GC×GC/TOFMS) and statistical analyses (SIMPER and PERMANOVA) of body surface extracts of females and males of C. fasciventris, C. anonae, C. rosa and C. capitata.

N=10 for each combination of gender and species. RI: retention index; *: present, –: absent, C36:1 hexatriacontene, C37:1 heptatriacontene, C37:3 heptatriacontatriene.

The PCA of microsatellite genotypes showed that the C. fasciventris and C. rosa specimens sampled in this study (males and females) belong to the genotypic clusters C. fasciventris F2 and C. rosa R2 (Virgilio et al., Reference Virgilio, Delatte, Quilici, Backeljau and De Meyer2013) (fig. 3). Surprisingly, the overall genetic diversity of the specimens from colonies was relatively high, as shown by the patterns of multivariate dispersion in fig. 3. This suggests that the material used for the analyses was not particularly subjected to inbreeding depression, probably because the gene pool of the laboratory colonies was periodically renovated through the addition of wild individuals.

Fig. 3.

PCAs of Euclidean distances among the individual genotypes of specimens sampled in this study (grouped according to the species and the sex, represented in black) and 621 genotypes of C. fasciventris, C. anonae and C. rosa assigned to five genotypic clusters (C. fasciventris F1 and F2, C. anonae A, C. rosa R1 and R2) like in Virgilio et al. (Reference Virgilio, Delatte, Quilici, Backeljau and De Meyer2013). The genotype groups are labeled inside their 95% inertia ellipses and connected to the corresponding group centroids.

Discussion

The CHCs identified in C. fasciventris, C. anonae, C. rosa and C. capitata are branched and unsaturated alkanes. These compounds have been proven to be suitable chemotaxonomical markers in Diptera (Sutton & Carlson, Reference Sutton and Carlson1993; Horne & Priestman, Reference Horne and Priestman2002; Caputo et al., Reference Caputo, Dani, Horne, Petrarca, Turillazzi, Coluzzi, Priestman and della Torre2005; Ye et al., Reference Ye, Li, Zhu, Zhu and Hu2007; Blomquist & Bagnères, Reference Blomquist and Bagnères2010; Everaerts et al., Reference Everaerts, Farine, Cobb and Ferveur2010), Hymenoptera (Dahbi et al., Reference Dahbi, Hefetz and Lenoir2008; Martin & Drijfhout, Reference Martin and Drijfhout2009; Guillem et al., Reference Guillem, Drijfhout and Martin2012; Pokorny et al., Reference Pokorny, Lunau, Quezada-Euan and Eltz2014), Hemiptera (Gemeno et al., Reference Gemeno, Laserna, Riba, Valls, Castañé and Alomar2012), Isoptera (Haverty et al., Reference Haverty, Nelson and Page1990), Orthoptera (Chapman et al., Reference Chapman, Espelie and Sword1995) as well as in other insect orders (Everaerts et al., Reference Everaerts, Maekawa, Farine, Shimada, Luykx, Brossut and Nalepa2008). Carlson & Yocom (Reference Carlson and Yocom1986) showed qualitative and quantitative species- and sex-specific CHC differences among six fruit-fly species (A. ludens, A. suspensa, C. capitata, C. rosa, D. cucurbitae, D. dorsalis) and identified straight chain hydrocarbons (RI 2900 for C29, 3100 for C31), methyl branched hydrocarbons (RI 2865 for 2-MeC28, RI 3065 for 2-MeC30 and RIs 3125–3140 for 11-/13-/15-MeC31) and alkadienes (RI 3250 for tritriacontadiene C33:2, RI 3450 for pentatriacontadiene C35:2 and RI 3650 for heptatriacontadiene C37:2). Monomethyl alkanes were previously used to distinguish between the morphologically similar larvae of C. capitata and A. suspensa (Sutton & Steck, Reference Sutton and Steck1994).

Our results show that C. anonae, C. fasciventris – genotypic cluster F2 and C. rosa – genotypic cluster R2 (see Virgilio et al., Reference Virgilio, Delatte, Quilici, Backeljau and De Meyer2013) have markedly different CHC profiles and that the main compounds responsible for these differences are methyl-branched alkanes (4-MeC28, 7-MeC29, 4-MeC29, 3-MeC29, 3-MeC30, 11,13-/13,17-/12,14-DiMeC31 and branched C35), alkenes (hexatriacontene, branched heptatriacontene) and alkatriene (heptatriacontatriene). The configurations of the double-bond positions still remain to be resolved; further chemical analyses are scheduled for this purpose.

To a lesser extent, the CHC profiles also differ between sexes within each species (with more pronounced differences in C. fasciventris and C. rosa as compared to C. anonae). Thus, the variation of the CHC profiles seems to be hierarchically organized, with interspecific differentiation being higher than the gender-related differences. The CHC compounds that contributed the most to the separation of sexes within species were monomethyl alkanes and unsaturated alkanes. These types of CHCs were also identified in other fruit-fly species (Carlson & Yocom, Reference Carlson and Yocom1986; Goh et al., Reference Goh, Ooi, Chuah, Yong, Khoo and Ong1993; Rouault et al., Reference Rouault, Marican, Wicker-Thomas and Jallon2004; Vaníčková et al., Reference Vaníčková, Svatoš, Kroiss, Kaltenpoth, Nascimento, Hoskovec, Břízová and Kalinová2012) and were responsible for the quantitative and qualitative CHC differences observed between sexes in a number of dipteran species (Caputo et al., Reference Caputo, Dani, Horne, Petrarca, Turillazzi, Coluzzi, Priestman and della Torre2005; Everaerts et al., Reference Everaerts, Farine, Cobb and Ferveur2010; Oliveira et al., Reference Oliveira, Manfrin, Sene, Jackson and Etges2011; Suarez et al., Reference Suarez, Nguyen, Ortiz, Lee, Kim, Krzywinski and Schug2011). Fruit-fly courtship behavior is a relatively complex process and includes chemical, auditory and visual stimuli (Wicker-Thomas, Reference Wicker-Thomas2007). The importance of CHCs in insect mate choice is well established (e.g., Lahav et al., Reference Lahav, Soroker, Hefetz and Vander Meer1999; Thomas & Simmons, Reference Thomas and Simmons2008; Blomquist & Bagnères, Reference Blomquist and Bagnères2010). Accordingly, cuticular signals have been shown to play an important role in the mate choice of fruit flies (Thomas & Simmons, Reference Thomas and Simmons2008; Blomquist & Bagnères, Reference Blomquist and Bagnères2010; Kather & Martin, Reference Kather and Martin2012). As suggested for Drosophila spp., sexual selection might promote inter- and intra-specific differences in CHC patterns (Shirangi et al., Reference Shirangi, Dufour, Williams and Carroll2009; Takahashi et al., Reference Takahashi, Fujiwara-Tsujii, Yamaoka, Itoh, Ozaki and Takano-Shimizu2012; Curtis et al., Reference Curtis, Sztepanacz, White, Dyer, Rundle and Mayer2013; Havens & Etges, Reference Havens and Etges2013; Jennings et al., Reference Jennings, Etges, Schmitt and Hoikkala2014).

These results suggest that CHC profiles might be a suitable tool for the chemotaxonomical identification of the tephritid species that are difficult to recognize based on morphological or molecular characteristics. The methodology of the extraction and identification of the CHC markers described here might be useful when a large number of samples are to be determined. For an easy CHC extraction, pentane, hexane or dichloromethane can be used, and the subsequent chemical analyses may be performed using a variety of GC/MS setups equipped with a non-polar column (DB-5). The time needed for the analysis is much shorter when compared to molecular genetic approaches, and the overall cost of the analysis is significantly lower.

The present study shows that the presence or absence of particular CHCs might be used in the chemical diagnosis of the FAR complex. As such, our results represent an important first step in the development of a useful chemotaxonomic tool for cryptic species identification. Validation of the method would require further analyses that include samples from a larger geographic area. In the near future, additional analyses of the CHC profiles, including the other two morphotypes, C. fasciventris (F1) and C. rosa (R1), will be performed.

The supplementary materials for this paper can be found at http://www.journals.cambridge.org/BER

Acknowledgements

The funding was provided through the Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, Prague and trough research contracts 16106 and 16965 as a part of the FAO/IAEA Coordinated Research Project on Resolution of Cryptic Species Complexes of Tephritid Pests to Overcome Constrains to SIT and International Trade. We acknowledge Dr Antonio Pompeiano (University of Pisa, Italy) and Dr Robert Hanus (IOCB, Czech Republic) for the proofreading and valuable comments on the paper.

References

Anderson, M.J. (2001) A new method for non-parametric multivariate analysis of variance. Australian Journal of Ecology 26, 32–46.Google Scholar
Anderson, M.J. (2003) PCO: a FORTRAN Computer Program for Principal Coordinate Analysis. New Zealand, Department of Statistics, University of Auckland.Google Scholar
Anderson, C.M., Aparicio, G.J., Atangana, A.R., Beaulieu, J., Bruford, M.W., Cain, F., Campos, T., Cariani, A., Carvalho, M.A., Chen, N., Chen, P.P., Clamens, A.L., Clark, A.M., Coeur D'Acier, A., Connolly, P., Cordero-Rivera, A., Coughlan, J.P., Cross, T.S. et al. (2010) Permanent genetic resources added to molecular ecology resources database 1 December 2009–31 January 2010. Molecular Ecology Resources 10, 576–579.Google ScholarPubMed
Baliraine, F.N., Bonizzoni, M., Guglielmino, C.R., Osir, E.O., Lux, S.A., Mulaa, F.J., Gomulski, L.M., Zheng, L., Quilici, S., Gasperi, G. & Malacrida, A.R. (2004) Population genetics of the potentially invasive African fruit fly species, Ceratitis rosa and Ceratitis fasciventris (Diptera: Tephritidae). Molecular Ecology 13, 683–695.CrossRefGoogle Scholar
Barr, N.B. & McPheron, B.A. (2006) Molecular phylogenetics of the genus Ceratitis (Diptera: Tephritidae). Molecular Phylogenetics and Evolution 38, 216–230.CrossRefGoogle Scholar
Besansky, N.J. (1999) Complexities in the analysis of cryptic taxa within the genus Anopheles. Parassitologia 41, 97–100.Google ScholarPubMed
Bickford, D., Lohman, D.J., Sodhi, N.S., Ng, P.K.L., Meier, R., Winkler, K., Ingram, K.K. & Das, I. (2007) Cryptic species as a window on diversity and conservation. Trends in Ecology and Evolution 22, 148–155.CrossRefGoogle ScholarPubMed
Blomquist, G.J. & Bagnères, A.G. (2010) Insect Hydrocarbons Biology, Biochemistry, and Chemical Ecology. New York, Cambridge University Press.CrossRefGoogle Scholar
Caputo, B., Dani, F.R., Horne, G.L., Petrarca, V., Turillazzi, S., Coluzzi, M., Priestman, A.A. & della Torre, A. (2005) Identification and composition of cuticular hydrocarbons of the major Afrotropical malaria vector Anopheles gambiae s.s. (Diptera: Culicidae): analysis of sexual dimorphism and age-related changes. Journal of Mass Spectrometry 40, 1595–1604.CrossRefGoogle ScholarPubMed
Carlson, D.A. & Yocom, S.R. (1986) Cuticular hydrocarbons from six species of tephritid fruit flies. Archives of Insect Biochemistry and Physiology 3, 397–412.CrossRefGoogle Scholar
Carlson, D.A., Roan, C.S., Yost, R.A. & Hector, J. (1989) Dimethyl disulfide derivatives of long chain alkenes, alkadienes, and alkatrienes for gas chromatography/mass spectrometry. Analytical Chemistry 61, 1564–1571.CrossRefGoogle Scholar
Carlson, D.A., Bernier, U.R. & Sutton, B.D. (1998) Elution patterns from capillary GC for methyl-branched alkanes. Journal of Chemical Ecology 11, 1845–1865.CrossRefGoogle Scholar
Chapman, R.F., Espelie, K.E. & Sword, G.A. (1995) Use of cuticular lipids in grasshopper taxonomy: a study of variation in Schistocerca shoshone (Thomas). Biochemical Systematics and Ecology 23, 383–398.CrossRefGoogle Scholar
Clarke, K.R. (1993) Non-parametric multivariate analyses of changes in community structure. Australian Journal of Ecology 18, 117–143.CrossRefGoogle Scholar
Copren, K.A., Nelson, L.J., Vargo, E.L. & Haverty, M.I. (2005) Phylogenetic analyses of mtDNA sequences corroborate taxonomic designations based on cuticular hydrocarbons in subterranean termites. Molecular Phylogenetics and Evolution 35, 689–700.CrossRefGoogle ScholarPubMed
Curtis, S., Sztepanacz, J.L., White, B.E., Dyer, K.A., Rundle, H.D., & Mayer, P. (2013) Epicuticular compounds of Drosophila subquinaria and D. recens: identification, quantification, and their role in female mate choice. Journal of Chemical Ecology 39, 579–590.CrossRefGoogle Scholar
Dahbi, A., Hefetz, A. & Lenoir, A. (2008) Chemotaxonomy of some Cataglyphis ants from Morocco and Burkina Faso. Biochemical Systematics and Ecology 36, 564–572.CrossRefGoogle Scholar
De Meyer, M. (2001) On the identity of the Natal fruit fly Ceratitis rosa Karsch (Diptera, Tephritidae). Bulletin de l'Institut Royal des Sciences Naturelles de Belgique Entomologie 71, 55–62.Google Scholar
De Meyer, M. & Freidberg, A. (2006) Revision of the subgenus Ceratitis (Pterandrus) Bezzi (Diptera: Tephritidae). In Freidberg, A. (Ed.) Biotaxonomy of Tephritoidea. Israel Journal of Entomology 35/36, 197–315.Google Scholar
De Meyer, M., Robertson, M., Peterson, T. & Mansell, M. (2008) Climatic modeling for the med fly and Natal fruit fly. Journal of Biogeography 35, 270–281.CrossRefGoogle Scholar
Dyck, V.A., Hendrichs, J. & Robinson, A.S. (2005) Steril Insect Technique Principles and Practice in Area-Wide Integrated Pest Management Dordrecht. Springer.Google Scholar
Everaerts, C., Maekawa, K., Farine, J.P., Shimada, K., Luykx, P., Brossut, R. & Nalepa, C.A. (2008) The Cryptocercus punctulatus species complex (Dictyoptera: Cryptocercidae) in the eastern United States: comparison of cuticular hydrocarbons, chromosome number, and DNA sequences. Molecular Phylogenetics and Evolution 47, 950–959.CrossRefGoogle ScholarPubMed
Everaerts, C., Farine, J.-P., Cobb, M. & Ferveur, J.-F. (2010) Drosophila cuticular hydrocarbons revisited: mating status alters cuticular profiles. PLoS ONE 5, 9607.CrossRefGoogle ScholarPubMed
Fletcher, B.S. (1989) Life history strategies of tephritid fruit flies. pp. 195–208in Robinson, A.S. & Hooper, G.H. (Eds) Fruit Flies: Their Biology, Natural Enemies and Control. Amsterdam, Netherlands, Elsevier.Google Scholar
Garros, C., Van Bortel, W., Trung, H.D., Coosemans, M. & Manguin, S. (2006) Review of the minimus complex of Anopheles, main malaria vector in Southeast Asia: from taxonomic issues to vector control strategies. Tropical Medicine and International Health 11, 102–114.CrossRefGoogle ScholarPubMed
Geiselhardt, S., Otte, T. & Hilker, M. (2009) The role of cuticular hydrocarbons in male mating behavior of the mustard leaf beetle, Phaedon cochleariae (F.). Journal of Chemical Ecology 35, 1162–1171.CrossRefGoogle ScholarPubMed
Gemeno, C., Laserna, N., Riba, M., Valls, J., Castañé, C. & Alomar, O. (2012) Cuticular hydrocarbons discriminate cryptic Macrolophus species (Hemiptera: Miridae). Bulletin of Entomological Research 102, 624–631.CrossRefGoogle ScholarPubMed
Gibbs, A.G. (2011) Thermodynamics of cuticular transpiration. Journal of Insect Physiology 57, 1066–1069.CrossRefGoogle ScholarPubMed
Goh, S.H., Ooi, K.E., Chuah, C.H., Yong, H.S., Khoo, S.G. & Ong, S.H. (1993) Cuticular hydrocarbons from two species of Malaysian Bactrocera fruit flies. Biochemical Systematics and Ecology 21, 215–226.CrossRefGoogle Scholar
Gozansky, T.K., Soroker, V. & Hefetz, A. (1997) The biosynthesis of Dufour's gland constituents of the honeybee (Apis mellifera). Invertebrate Neuroscience 3, 239–243.CrossRefGoogle Scholar
Guillem, R.M., Drijfhout, F.P. & Martin, S.J. (2012) Using chemo-taxonomy of host ants to help conserve the large blue butterfly. Biological Conservation 148, 39–43.CrossRefGoogle Scholar
Havens, J.A. & Etges, W.J. (2013) Premating isolation is determined by larval rearing substrates in cactophilic Drosophila mojavensis. IX. Host plant and population specific epicuticular hydrocarbon expression influences mate choice and sexual selection. Journal of Evolutionary Biology 26, 562–576.CrossRefGoogle ScholarPubMed
Haverty, M.I., Nelson, L.J. & Page, M. (1990) Cuticular hydrocarbons of four populations of Coptotermes formosanus Shikari in the United States: similarities and origins of introductions. Journal of Chemical Ecology 16, 1635–1647.CrossRefGoogle Scholar
Haverty, M.I., Woodrow, R.J., Nelson, L.J. & Grace, J.K. (2000) Cuticular hydrocarbons of termites of the Hawaiian Islands. Journal of Chemical Ecology 26, 1167–1191.CrossRefGoogle Scholar
Horne, G.L. & Priestman, A.A. (2002) The chemical characterization of the epicuticular hydrocarbons of Aedes aegypti (Diptera: Culicidae). Bulletin of Entomological Research 92, 287–294.CrossRefGoogle ScholarPubMed
Howard, R.W. & Blomquist, G.J. (2005) Ecological, behavioral, and biochemical aspects of insect hydrocarbons. Annual Review of Entomology 50, 371–393.CrossRefGoogle ScholarPubMed
Jennings, J.H., Etges, W.J., Schmitt, T. & Hoikkala, A. (2014) Cuticular hydrocarbons of Drosophila montana: geographic variation, sexual dimorphism and potential roles as pheromones. Journal of Insect Physiology 61, 16–24.CrossRefGoogle ScholarPubMed
Jombart, T. (2008) Adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405.CrossRefGoogle Scholar
Kather, R. & Martin, S.J. (2012) Cuticular hydrocarbon profiles as a taxonomic tool: advantages, limitations and technical aspects. Physiological Entomology 37, 25–32.CrossRefGoogle Scholar
Lahav, S., Soroker, V., Hefetz, A. & Vander Meer, R.K. (1999) Direct behavioral evidence for hydrocarbons as ant recognition discriminators. Naturwissenschaften 86, 246–249.CrossRefGoogle Scholar
Lavine, B.K., Carlson, D.A. & Calkins, C.O. (1992) Classification of tephritid fruit fly larvae by gas chromatography/pattern recognition techniques. Microchemical Journal 45, 50–57.CrossRefGoogle Scholar
Lockey, K.H. (1991) Insect hydrocarbon classes: implications for chemotaxonomy. Insect Biochemistry 21, 91–97.CrossRefGoogle Scholar
Lucas, C., Fresneau, D., Kolmer, K., Heinze, J., Delabie, J.H.C. & Pho, D.B. (2002) A multidisciplinary approach to discriminating different taxa in the species complex Pachycondyla villosa (Formicidae). Biological Journal of the Linnean Society 75, 249–259.CrossRefGoogle Scholar
Martin, S. & Drijfhout, F. (2009) A review of ant cuticular hydrocarbons. Journal of Chemical Ecology 35, 1151–1161.CrossRefGoogle ScholarPubMed
Martin, S.J., Helantera, H. & Drijfhout, F.P. (2008) Evolution of species-specific cuticular hydrocarbon patterns in Formica ants. Biological Journal of the Linnean Society 95, 131–140.CrossRefGoogle Scholar
Oliveira, C., Manfrin, M.H., Sene, F., Jackson, L.L. & Etges, W.J. (2011) Variations on a theme: diversification of cuticular hydrocarbons in a clade of cactophilic Drosophila. BMC Evolutionary Biology 11, 1–19.CrossRefGoogle Scholar
Paterson, H.E.H. (1991) The recognition of cryptic species among economically important insects. pp. 1–10in Zalucki, M.P. (Ed.) Heliothis: Research Methods and Prospects. Springer.Google Scholar
Pokorny, T., Lunau, K., Quezada-Euan, J.J.G. & Eltz, T. (2014) Cuticular hydrocarbons distinguish cryptic sibling species in Euglossa orchid bees. Apidologie 45, 276–283.CrossRefGoogle Scholar
Pomonis, J.G., Fatland, C.F., Nelson, D.R. & Zaylskie, R.G. (1978) Insect hydrocarbons corroboration of structure by synthesis and mass spectrometry of mono- and dimethylalkanes. Journal of Chemical Ecology 4, 27–39.CrossRefGoogle Scholar
Rouault, J.D., Marican, C., Wicker-Thomas, C. & Jallon, J.M. (2004) Relations between cuticular hydrocarbon (HC) polymorphism, resistance against desiccation and breeding temperature; a model for HC evolution in D. melanogaster and D. simulans. Genetica 120, 195–212.CrossRefGoogle Scholar
Schlick-Steiner, B.C., Steiner, F.M., Moder, K., Seifert, B., Sanetra, M., Dyreson, E., Stauffer, C. & Christian, E. (2006) A multidisciplinary approach reveals cryptic diversity in western palearctic tetramorium ants (Hymenoptera: Formicidae). Molecular Phylogenetics and Evolution 40, 259–273.CrossRefGoogle ScholarPubMed
Shirangi, T.R., Dufour, H.D., Williams, T.M. & Carroll, S.B. (2009) Rapid evolution of sex pheromone-producing enzyme expression in Drosophila. PLoS Biology 7, e1000168.CrossRefGoogle ScholarPubMed
Steinke, D., Virgilio, M., Jordaens, K., Breman, F.C., Backeljau, T. & De Meyer, M. (2012) Identifying insects with incomplete DNA barcode libraries, African fruit flies (Diptera: Tephritidae) as a test case. PLoS ONE 7, e31581.Google Scholar
Suarez, E., Nguyen, H.P., Ortiz, I.P., Lee, K.J., Kim, S.B., Krzywinski, J. & Schug, K.A. (2011) Matrix-assisted laser desorption/ionization-mass spectrometry of cuticular lipid profiles can differentiate sex, age, and mating status of Anopheles gambiae mosquitoes. Analytica Chimica Acta 706, 157–163.CrossRefGoogle ScholarPubMed
Sutton, B.D. & Carlson, B.D. (1993) Interspecific variation in tephritid fruit fly larvae surface hydrocarbons. Archives of Insect Biochemistry and Physiology 23, 53–65.CrossRefGoogle Scholar
Sutton, B.D. & Steck, G.J. (1994) Discrimination of Carribean and Mediterranean fruit fly larvae (Diptera:Tephritidae) by cuticular hydrocarbon analysis. Florida Entomologist 77, 231–237.CrossRefGoogle Scholar
Takahashi, A., Fujiwara-Tsujii, N., Yamaoka, R., Itoh, M., Ozaki, M. & Takano-Shimizu, T. (2012) Cuticular hydrocarbon content that affects male mate preference of Drosophila melanogaster from West Africa. International Journal of Evolutionary Biology 2012, 1–10.Google Scholar
Thomas, M.L. & Simmons, L.W. (2008) Sexual dimorphism in cuticular hydrocarbons of the Australian field cricket Teleogryllus oceanicus (Orthoptera: Gryllidae). Journal of Insect Physiology 54, 1081–1089.CrossRefGoogle ScholarPubMed
Van Den Dool, H. & Kratz, P.D. (1963) A generalization of the retention index system including linear temperature programmed gas–liquid partition chromatography. Journal of Chromatograpy A 11, 463–471.CrossRefGoogle Scholar
Vaníčková, L. (2012) Chemical Ecology of Fruit Flies: Genera Ceratitis and Anastrepha. Prague, Department of Chemistry of Natural Compounds, Institute of Chemical Technology.Google Scholar
Vaníčková, L., Svatoš, A., Kroiss, J., Kaltenpoth, M., Nascimento, R.R., Hoskovec, M., Břízová, R. & Kalinová, B. (2012) Cuticular hydrocarbons of the South American fruit fly Anastrepha fraterculus: variability with sex and age. Journal of Chemical Ecology 38, 1133–1142.CrossRefGoogle ScholarPubMed
Virgilio, M., Backeljau, T. & De Meyer, M. (2007 a) FAR complex and barcoding. p. 142 in Proceedings of the Second International Barcode of Life Conference, Taipei, Taiwan.Google Scholar
Virgilio, M., Backeljau, T. & De Meyer, M. (2007 b) Incongruence of phylogenetic signals and shared polymorphisms prevent the molecular characterization of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera: Tephritidae). p. 520 in Proceedings of the 11th Congress of the European Society for Evolutionary Biology, Upsalla, Sweden.Google Scholar
Virgilio, M., Backeljau, T., Barr, N. & Meyer, M.D. (2008) Molecular evaluation of nominal species in the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera: Tephritidae). Molecular Phylogenetics and Evolution 48, 270–280.CrossRefGoogle Scholar
Virgilio, M., Backeljau, T., Nevado, B. & De Meyer, M. (2010) Comparative performances of DNA barcoding across insect orders. BMC Bioinformatics 11, 206–216.CrossRefGoogle ScholarPubMed
Virgilio, M., Jordaens, K., Breman, F.C., Backeljau, T. & De Meyer, M. (2012) Identifying insects with incomplete DNA barcode libraries, African fruit flies (Diptera: Tephritidae) as a test case. PLoS ONE 7, e31581.CrossRefGoogle ScholarPubMed
Virgilio, M., Delatte, H., Quilici, S., Backeljau, T. & De Meyer, M. (2013) Cryptic diversity and gene flow among three African agricultural pests: Ceratitis rosa, Ceratitis fasciventris and Ceratitis anonae (Diptera, Tephritidae). Molecular Ecology 22, 2526–2539.CrossRefGoogle Scholar
Wakayama, E.J., Dillwith, J.W. & Blomquist, G.J. (1985) Occurrence and metabolism of arachidonic acid in the housefly, Musca domestica (L.). Insect Biochemistry 15, 367–374.CrossRefGoogle Scholar
White, I.M. & Elson-Harris, M. (1992) Fruit Flies of Economic Significance: Their Identification and Bionomics. Oxon, UK, CAB International and The Australian Center for Agricultural Research Canberra, Australia, p. 601.CrossRefGoogle Scholar
Wicker-Thomas, C. (2007) Pheromonal communication involved in courtship behavior in Diptera. Journal of Insect Physiology 53, 1089–1100.CrossRefGoogle ScholarPubMed
Ye, G., Li, K., Zhu, J., Zhu, G. & Hu, C. (2007) Cuticular hydrocarbon composition in pupal exuviae for taxonomic differentiation of six necrophagous flies. Journal of Medical Entomology 44, 450–456.CrossRefGoogle ScholarPubMed
Yuval, B. & Hendrichs, J. (2001) Behavioral of flies in the genus Ceratitis (Dacinae: Ceratitidini). in Aluja, M. & Norrbom, A.L. (Eds) Fruit Flies (Tephritidae) Phylogeny and Evolution of Behavior. Boca Raton, FL, CRC Press.Google Scholar
Figure 0

Fig. 1. PCAs of Euclidean distances between males and females C. capitata, C. fasciventris, C. anonae and C. rosa (as calculated from peak areas of 59 CHCs).

Figure 1

Table 1. PERMANOVA and a posteriori comparison (t-statistic) testing differences in multivariate patterns of 59 CHCs in relation to species (C. fasciventris, C. anonae, C. rosa, C. capitata) and sex (male×female) of 80 tephritid fruit flies.

Figure 2

Fig. 2. Average log-transformed CHCs peak areas (standard deviations as error bars), represented by RIs that contributed the most to the differences (>2% contribution to species dissimilarity) between C. fasciventris, C. anonae and C. rosa (see Supplementary Material, table 2).

Figure 3

Table 2. Compounds identified by chemical analyses (GC×GC/TOFMS) and statistical analyses (SIMPER and PERMANOVA) of body surface extracts of females and males of C. fasciventris, C. anonae, C. rosa and C. capitata.

Figure 4

Fig. 3. PCAs of Euclidean distances among the individual genotypes of specimens sampled in this study (grouped according to the species and the sex, represented in black) and 621 genotypes of C. fasciventris, C. anonae and C. rosa assigned to five genotypic clusters (C. fasciventris F1 and F2, C. anonae A, C. rosa R1 and R2) like in Virgilio et al. (2013). The genotype groups are labeled inside their 95% inertia ellipses and connected to the corresponding group centroids.