has also been defined as a product causing the insect “to leave the prospective host, with true behavioral repellency involving avoidance of the source of the repellent material, whether placed on the prospective host or near it” (Pickett et al., 2008). While these definitions are based on behavioral effects, the mechanisms of action of repellents are not considered. Repellents are used to stop a pest from finding a valued resource; topical repellents are usually applied onto the skin offering individual protection, while spatial repellents volatilize into the air, creating a vector-free space which provides protection for multiple individuals (Achee et al., 2012). Typically, volatile repellents are used to protect humans from insect (and other arthropod) bites, particularly from arthropods which are vectors of diseases (Foster and Harris, 1997). Repellents have also been used to protect crops: for example, the alarm pheromone of a number of aphids has been used against these pests (Foster and Harris, 1997; Pickett et al., 1997).

For centuries humans have used diverse parts of plants to repel biting insects (Moore and Lenglet, 2004). Among these so-called “botanical repellents,” various species of basil (Ocimum spp.) have been historically used to repel mosquitoes. In addition, oil extract from the leaves of neem (Azadirachta indica) has also been used as a personal mosquito and sandfly repellent (Yarnell and Abascal, 2004). Other botanical insect repellents include the oil from leaves of citronella (Cymbopogon nardus), palmarosa (C. martinii martinii), lemongrass (C. citratus), and Eucaliptus (Eucalyptus spp.). The active components of these botanical repellents are often unknown although citral, a major ingredient in volatiles from lemongrass oil, and p-menthane-3,8-diol, from lemon eucalyptus, have repellent effects on a variety of mosquitoes (Yarnell and Abascal, 2004). Repellents can also be derived from other natural sources such as insects (as in the case of alarm pheromones or defense secretions), or may be purely artificial (Foster and Harris, 1997).

The world's most widely used synthetic topical insect repellent, with broad effectiveness against many insects, is N,N-diethyl-3-methylbenzamide, also known as N,N-diethyl-m-toluamide (DEET; White, 2007; Syed et al., 2011). Other synthetic repellents include Picaridin and IR3535 (or EBAAP, Ethyl Butyl-acetylaminopropionate). A full understanding of the mechanism of action of insect repellents and in particular, the identification of their molecular targets, can help design safer and more effective compounds. DEET appears to act both as a contact chemo-repellent that stimulates insect gustatory receptor cells that respond to aversive compounds (Lee et al., 2010), and as a volatile chemo-repellent acting on the olfactory system.

The mode of action of volatile repellents is still under debate and has been comprehensively reviewed recently (Leal, 2014); therefore, here we briefly summarize the most relevant investigations. In *D. melanogaster* and in the mosquitoes *Aedes aegypti* and *Anopheles gambiae* DEET appears to modulate the responses of ORCs to attractive odors (Davis and Sokolove, 1976; Ditzen et al., 2008). This effect depends both on ORCO (Ditzen et al., 2008) and on the molecular identity of the OR in the OR-ORCO complex (Pellegrino et al., 2011). However, for other repellents, it was proposed that DEET acts by just blocking ORCO (Tsitoura et al., 2015). On the other hand, Syed and Leal

(2008) suggested that the mosquito *C. quinquefasciatus* can smell DEET directly and that that stimulation results in avoidance even in the absence of other odor cues. Similar results were reported in triatomines, suggesting a common mode of action for the repellent action of DEET (Zermoglio et al., 2015). Moreover, other additional findings further support the hypothesis that insects can smell DEET: (1) the existence of an ORC in *D. melanogaster* which is sensitive to DEET, picaridin and IR3535 (Syed et al., 2011) and, (2) electroantennogram (EAG) and single sensillum responses to DEET in *A. aegypti* (Stanczyk et al., 2010, 2013).

In an attempt to clarify some of these apparently contradictory results, Bohbot and Dickens (2010) characterized the effects of a number of repellents [DEET, 2-undecanone (2-U), IR3535 and Picaridin] on two OR-ORCO heteromers of *A. aegypti* individually expressed in *Xenopus* oocytes. Their results suggest that different mechanisms mediate the action of different repellents. That is, repellents could be smelled directly (acting as receptor agonists) or could inhibit the responses to odors (acting as receptor antagonists; Bohbot and Dickens, 2010).

It is now well established that insects can smell DEET (Leal, 2014). Studies in mosquitos suggest that ORCO and the OR pathway are necessary for the repellent effects of DEET as: (1) wild-type *A. aegypti* avoid DEET whereas ORCO mutants do not (DeGennaro et al., 2013) and, (2) in *C. quinquefasciatus*, different repellents activate a particular OR (*CquiOR136*) in a dose-dependent manner, whereas knockdown of this OR resulted in loss of EAG and behavioral responses to DEET (Xu et al., 2014). These results suggest that an OR is involved in the direct detection of DEET (Xu et al., 2014). As the natural plant repellent methyl jasmonate elicits responses in ORCs expressing *CquiOR136*, it has been proposed that this OR is tuned to natural repellents with long insect-plant evolutionary histories (Xu et al., 2014).

In summary, different hypotheses have been suggested to explain the mechanisms involved in the olfactory repellency of DEET in blood-sucking insects. They include: (1) DEET may silence ORs responsive to attractive odors, a hypothesis that has now little support; (2) DEET is detected by one or a few ORs; (3) DEET may act as a “confusant” by modulating the activity of many ORs. Although it is possible that more than one of these mechanisms act simultaneously, it is likely that they are species-specific. Because all these proposed mechanisms involve ORs, these are relevant candidate molecular targets for the development of new repellents (Leal, 2014). Thus, based on knowledge on the molecular receptors, more efficient and safer volatile mosquito repellents could be developed. The need to develop new repellents is emphasized by the finding that some populations of *A. aegypti* are insensitive to DEET (Stanczyk et al., 2010). Besides the repellent effects of DEET discussed above, application of DEET on human skin results in an altered host odor chemical profile due to a fixative effect of DEET, and that effect could also contribute to repellency (Syed and Leal, 2008; Section Odor Masking). Finally, certain constituents of non-host odors can act as arthropod repellents (e.g., interaction between cattle flies and heifers: Birkett et al., 2004; interaction between fruit flies and fruit: Linn et al., 2005; interaction between
ticks and dogs: Borges et al., 2015), providing opportunities for the development of natural, safer repellents. It should be noted that the response to an attractive host odor blend can be manipulated by adding non-host odorants (e.g., Linn et al., 2005), and also by altering the proportions of one or more host odorants (Section Odor Masking), causing either repellency (avoidance), or masking (loss of attraction; Section Odor Masking).

# DISRUPTION OF NATURAL OLFACTORY BEHAVIOR

## Mating Disruption

The most common behavior that has been disrupted using semiochemicals is mating. This strategy has been used to eradicate insects that became resistant to pesticides, including pests of apples, peaches, cotton, and grapes (see Wyatt, 2003; Witzgall et al., 2010). The basic idea of mating disruption involves the broadcasting of a chemical signal similar to the sex pheromones of the target species. The first registration of a mating disruption product in the USA was for the pink bollworm (Brooks et al., 1979); currently there are more than 120 disruption products registered in the US. Mating disruption usually involves the release of large amounts of species-specific synthetic sex pheromones (e.g., Witzgall et al., 2010); these high concentrations often “overload” the insects’ sensory system, interfering with the detection of the usually lower amounts of pheromone released by mating partners (Cardé, 1990, see below). Besides this traditional approach (see below), new techniques and approaches are being developed to improve efficacy. A new design, which is literally an auto-confusion disruption method, involves the application of electrostatically charged wax powder (dubbed Entostat) onto the cuticle of male moths. Because the powder can be loaded with large quantities of female sex pheromone, male moths function as mobile dispensers. Indeed, Entostat-exposed codling moth males remained as attractive as a 0.1-mg pheromone lure for up to 24 h in laboratory experiments (Huang et al., 2010). The behavior of male moths that are normally attracted to natural sources of pheromone was completely disrupted after treatment with Entostat powder. Moreover, the males’ ability to orientate to the pheromone lure remained significantly impaired 6 days post-application, arguing that Entostat augments the effect of sensory (peripheral) adaptation and CNS habituation (Huang et al., 2010).

According to Miller and Gut (2015), mating disruption methods can be broadly divided into two categories, i.e., non-competitive and competitive. Non-competitive methods involve interference with the sensory capabilities of males or females, or hampering pheromone emission, and examples include mating/calling suppression, camouflage, sensory imbalance, and desensitization. Competitive methods do not involve changes on the insects’ sensory capabilities or on pheromone emission and, therefore, insects can respond equally well to other insects and trap lures. Thus, several mechanisms can mediate pheromonal mating disruption, including loss of sensitivity in ORCs (sensory adaptation), loss of sensitivity at the CNS level (habituation), camouflaging of the female’s odor trail, competition between

dispensers and natural pheromone, and unbalanced components in the synthetic pheromone (Cardé, 1990). We next discuss sensory adaptation and habituation.

Stimulation with high concentrations of pheromones generally reduce the response sensitivity of pheromone ORCs (i.e., ORCs adapt to the stimulus), a phenomenon which can be quantified using EAG. For instance, in male oriental fruit moths, the EAG amplitude decreased as animals approached high emission-rate sources, and this reduction was correlated with upwind flight cessation (Baker and Haynes, 1989). In another moth species, long-lasting EAG adaptation after pheromone pre-exposure occurred over a range of pheromone dosages and lasted more than 10 min (Stelinski et al., 2005). There appear to be significant species-specific variations in the capability of the olfactory system to adapt to pheromones. For instance, *Grapholita molesta* moths have a three-fold greater level of sensory adaptation after pre-exposure than *Choristoneura rosaceana* (Trimble and Marshall, 2010), a finding which may explain why *G. molesta* is readily more controllable using mating disruption than *C. rosaceana*. The mechanisms underlying sensory adaptation were investigated in the moth *M. sexta*. After presentation of an adapting pheromone stimuli, and in response to the pheromone test stimulus, type I trichoid sensilla produced sensillar potentials of lower amplitude than those from non-adapted sensilla, while the pheromone ORC spike frequency of adapted sensilla was concomitantly lower (Dolzer et al., 2003). Furthermore, pheromone stimuli lasting several seconds strongly activated protein kinase C in pheromone ORCs, while minute-long stimuli elevated cGMP concentrations. These results indicate the existence of distinct intracellular signaling mechanisms mediating short-term and long-term adaptation (Dolzer et al., 2008).

In order to produce habituation in AL neurons and, therefore, disrupt behavior, unnaturally high stimulus concentrations and/or frequencies can be used. In AL PNs, pheromone stimulation typically produces a burst of action potentials followed by an after-hyperpolarization (AHP) inhibitory phase (Christensen and Hildebrand, 1988; Lei et al., 2009). The AHP is critical to enable PNs to resolve intermittent stimuli, which is a universal feature of natural odor plumes (Murlis et al., 1992; Lei et al., 2009). Within a certain range of stimulus frequencies, PNs respond with a burst of action potentials (followed by a short AHP) to each odor pulse, faithfully reporting the temporal structure of the stimulus train. However, when the pulsing rate exceeds the response range of PNs (>10 Hz), neurons can only respond with a single burst of action potentials followed by a prolonged AHP (Christensen and Hildebrand, 1988; Lei and Hansson, 1999; Heinbockel et al., 2004). In addition, the excitatory and inhibitory phases can be both habituated by high stimulus concentrations. Increasing stimulus concentrations decreases the delay to the onset of the excitatory phase and increases firing rate eventually reaching saturation (Heinbockel et al., 2004; Fujiwara et al., 2009), while also decreases the delay to the onset of the inhibitory phase and increases its duration. In the upper range of concentrations, PNs only produce a brief (high-rate) burst that is followed by a lengthy AHP, which is similar to the habituating pattern evoked
by high frequency stimuli. Thus, under sustained stimulation and high concentrations, PNs show responses which are not likely linked to natural behaviors. Because PNs also receive input from LNs, these may also contribute to PN habituation, as observed in *D. melanogaster* (Seki et al., 2010). Because many LNs are GABAergic and can therefore inhibit PNs (Hoskins et al., 1986; Christensen et al., 1993; Wilson and Laurent, 2005; Seki and Kanzaki, 2008), LN habituation would produce sustained PN disinhibition, potentially interfering with triggering natural behavior. Although the roles of LNs are still being investigated, it is thought that they may render the response of some PNs concentration-independent (e.g., Asahina et al., 2009; Olsen et al., 2010). In summary, investigations on sensory adaptation and habituation can be helpful to find the most effective chemicals that can be used to disrupt mating.

## Odor Masking

As mentioned above (Sections Use of Sex Pheromones and Use of Host Odors), not just the identity of the constituents of an odor mixture but also their proportions (ratios) are important for attraction. For instance, humans are differentially attractive to mosquitoes and this could be due to individual host odor mixture variability (Logan et al., 2008 and references therein). In some cases low attractiveness has been linked to low levels of some odors. For example, in *A. aegypti*, addition of lactic acid to the skin of formerly unattractive humans can increase their attractiveness (Steib et al., 2001). Low or no-attractiveness to a natural host odor blend could also result from higher-than-normal concentrations of a natural constituent of the attractive blend (e.g., Birkett et al., 2004; Logan et al., 2008, 2009), a phenomenon attributed to blend repellency or masking (see also Section Effects of Background Odor).

Comparisons of the odor profiles of individuals with different attractiveness revealed that a few compounds are present in higher relative amounts in less-attractive individuals, including 6-methyl-5-hepten-2-one (Logan et al., 2008, 2009). When low and naturally occurring doses of this odor were added to naturally attractive human odor, upwind flight and probing were reduced. Although a repellent-blend effect can occur (Logan et al., 2009), a small increase in the amount (ratio) of a particular compound within the natural host odor mixture could also produce masking of the target odor so that the host is no longer recognized as such (Logan et al., 2008; see also Bruce and Pickett, 2011 for examples in phytophagous insects).

Many semiochemicals can be used in conjunction with other chemical tools in “push-pull” strategies. These strategies divert insects away from a valuable resource (the “push” away from, for example, a host) into an attractant (the “pull” component; Pickett et al., 1997; Cook et al., 2007). Masking odors could be used in push-pull control strategies to prevent host location (“pushing” insects away from the hosts) while at the same time, attractive odors could be used as baits in traps to “pull” the insects away from hosts (Cook et al., 2007; Logan et al., 2008). Neuroethology approaches could readily speed up the discovery of effective masking odors for use in control strategies. For instance, one strategy could be to test the degree of odor-object transformation in the AL (i.e., the change in the spatio-temporal response pattern

of an ensemble of AL neurons) that is evoked by altered ratios of different compounds within the natural host odor mixture.

Carbon dioxide is an important odor that mediates the behavior of many harmful insects (Guerenstein and Hildebrand, 2008). Therefore, manipulation of the odors that modulate the response of the CO₂ receptors (Section Effects of Background Odor; Turner et al., 2011), including inhibitory odorants that can mask human scent (Tauxe et al., 2013), can profoundly impact CO₂-mediated behaviors. Moreover, large CO₂ fluctuations can “confuse” the insect’s detection of natural CO₂ sources (Abrell et al., 2005 and references therein), which may be used for interfering with the behavior of CO₂-sensing insects.

## Odor Antagonism

As in many lepidopterans, *Heliothine* females release a sex pheromone that attracts conspecific males. However, certain compounds of the somewhat similar sex pheromone of a sympatric *Heliothine* species make the former blend unattractive. Indeed, the addition of such interspecific compounds to a species' sex pheromone blend can eliminate attraction in conspecific males, thus acting as antagonists (Vickers and Baker, 1997). In the AL of both *H. virescens* and *H. zea* the two essential components of their species-specific pheromone blends are represented in two separate MGC glomeruli. Odorants that antagonize attraction, when added to the respective pheromonal blends, evoked excitatory activity in PNs restricted to a third MGC glomerulus in both species (Vickers et al., 1998). Therefore, attractive and antagonist odor blends are represented in distinct combinations of MGC glomeruli, thus providing a combinatorial code for sex pheromone discrimination in sympatric species.

While approaching a female, male moths also emit volatile chemicals through specialized male structures such as the hairpencils (Birch et al., 1990). It has been shown that *H. virescens* hairpencil volatiles have both aphrodisiac and repellent effects on conspecific females and males, respectively. Interestingly, the male ORCs that respond to a conspecific hairpencil compound also respond to an interspecific sex pheromone antagonist (Hillier et al., 2006). Antagonist compounds (including both interspecific sex pheromone and conspecific hairpencil volatiles) are certainly amongst the important chemicals that can be used to manipulate harmful-insect behavior.

## PLASTICITY IN THE RESPONSES TO SEMIOCHEMICALS

Behavioral plasticity (including associative and non-associative learning) affects chemosensory-guided behaviors in all insects. For simplicity, we define learning as a permanent change in behavior resulting from experience (Papaj, 2009). Associative learning involves pairing of two stimuli in a way that the response to one of the stimulus is altered as a consequence of the pairing, which is typically evaluated in classical/Pavlovian or operant/instrumental paradigms. For instance, a well-studied case of classical learning involves the pairing of an appetitive stimulus (e.g., sugar) that elicits a reflexive response (e.g., extension of the proboscis) with an odor; when an association
between the two stimuli is formed, the sole presentation of the odor stimulus elicits proboscis extension (Bitterman et al., 1983). Behavioral habituation, a form of non-associative learning, reduces responsiveness to stable and repetitive stimuli, which can be important for detecting predators, food, and/or mate odors in an irrelevant and/or even complex olfactory background (Kadohisa and Wilson, 2006; Linster et al., 2007; Riffell et al., 2014; see also Section Effects of Background Odor). Behavioral sensitization is also a form of non-associative learning in which repeated presentation of a stimulus can result in amplification of responses to that and/or a related stimulus (Papaj, 2009).

Learning has profound effects on the chemosensory behavior of insects, including harmful ones. This is true even in the case of innate signals of prime biological relevance, such as sex pheromones. In moths, the action of sex pheromones depends on factors such as the presence of host-odors, sexual maturity, and mating status (Barrozo et al., 2011; Chaffiol et al., 2012, 2014; Guerrieri et al., 2012). Furthermore, moths can be trained to associate food with a sex pheromone (Hartlieb et al., 1999; Hartlieb and Hansson, 1999). In other cases, recognition of pheromones necessarily involves learning. In social insects, kin and nest-mate pheromones are learned by young larvae inside the nest, and maggot flies need to experience their own host-marking pheromone before they can discriminate between an occupied and an unoccupied fruit in which to lay eggs (Roitberg and Prokopy, 1981). Furthermore, in phytophagous insects, this kind of olfactory learning can promote the transition to new hosts of agricultural importance (Prokopy and Papaj, 1988; Papaj and Prokopy, 1989).

The way in which plasticity affects many different behaviors in herbivorous insects has been recently reviewed (see Anderson and Anton, 2014). In herbivorous insects, both larval feeding and adult experience can affect olfactory-guided oviposition, mate choice, and feeding (Riffell et al., 2008; Thöming et al., 2013; Anderson and Anton, 2014; Carrasco et al., 2015). In moths, plant volatiles can enhance male orientation toward the conspecific female sex pheromone (Chaffiol et al., 2012, 2014; Guerrieri et al., 2012). The learning abilities of pest insects should be particularly considered in control strategies. For instance, a “trap crop” (which always represents a small proportion of the cropping area) might be completely inefficient if insects first find the profitable crop and prefer this over the trap crop (Cook et al., 2007). Thus, the selection of the most effective crop border plants is crucial, and this can be achieved by screening plant cultivars coupled with identification of behaviorally and electrophysiological bioactive volatiles (Schröder et al., 2015). Other cognitive processes, such as habituation, have important implications in the management of pest insects (Section Mating Disruption). In diamondback moths, exposure to non-hosts can increase oviposition preference toward these plants, perhaps leading to host range expansion (Zhang and Liu, 2006).

In the case of insects vectors of human and animal diseases, learning and previous experience can have important epidemiological implications for disease transmission (McCall and Kelly, 2002). For instance, mosquito host choice is influenced by prior foraging experience, which causes them to return to

less-defensive hosts and to hosts where feeding was more successful (McCall and Kelly, 2002; Lyimo and Ferguson, 2009). Not only that, but variation in the physical and chemical properties of blood can influence fitness and cause host feeding preferences (see Lyimo and Ferguson, 2009 for details). Thus, it has been suggested that pathogen transmission can be reduced by altering host choice (Lyimo and Ferguson, 2009). Also, mosquitoes tend to return to the same villages, houses, host species, and oviposition sites (McCall and Kelly, 2002). Then, it is not surprising that research in this area has expanded in the last couple of years, and it is now clear that blood-sucking insects can indeed learn and form new memories (Kaur et al., 2003; Jhumur et al., 2006; Tomberlin et al., 2006; Bouyer et al., 2007; Sanford and Tomberlin, 2011; Vinauger et al., 2011a,b, 2013, 2014; Chilaka et al., 2012; Sanford et al., 2013). Classical and operant paradigms showed that blood-sucking insects can associate stimuli of different modality (thermal, odor, gustatory, visual) while searching for a host and selecting oviposition sites. In *A. aegypti*, the association between odorants and a thermal appetitive stimulus is odor-dependent (e.g., certain odors can be readily learned, others are untrainable, etc). Furthermore, associative learning can modify the aversive deterrent effect of DEET in both kissing bugs and mosquitoes (Stanczyk et al., 2013; Vinauger et al., 2014). Learning processes also affect the responses to odors which are crucial for survival (e.g., pheromones). In triatomine bugs, a brief exposure to the alarm pheromone produces sensitization and increases the tendency to respond, while long-term pre-exposure elicits behavioral habituation (Minoli et al., 2013a). In blood sucking insects, however, our knowledge on the neural mechanisms underlying the effects of experience on chemosensory responses is mostly restricted to the periphery, as we discuss below.

In both blood-sucking and herbivorous insects the activity of ORCs can be affected by experience (e.g., long-term odor exposure and sensory adaptation to deterrents; see Section Mating Disruption). Experience can also cause downregulation of olfactory responses according to the feeding/mating status, and the time of the day (e.g., Almaas et al., 1991; Fox et al., 2001; Takken et al., 2001; Glendinning et al., 2009; Saveer et al., 2012; Stanczyk et al., 2013; Anderson and Anton, 2014; Claudianos et al., 2014; Reisenman, 2014). In general, associative learning is not usually represented at this level, although recent work in honeybees revealed that olfactory memories downregulate the expression of specific ORs. Furthermore, these changes occurred after conditioning and concomitantly, the population activity of antennal ORCs (measured as changes in EAG responses) decreased after learning (Claudianos et al., 2014). In mosquitoes, a reduction in the EAG responses to DEET correlates well with a post-exposure reduction in behavioral sensitivity to this repellent (Stanczyk et al., 2013).

The mushroom bodies mediate behaviors affected by learning and experience (e.g., Fahrbach et al., 1998; Zars et al., 2000; Huetteroth et al., 2015). However, in fruit flies and honeybees, learning already produces changes in glomerular volume and in synaptic distribution and density (e.g., Winnington et al., 1996; Devaud et al., 2001; Brown et al., 2002; Sachse et al.,
2007; Arenas et al., 2012), and can modify neural representations at the AL level (e.g., Faber et al., 1999; Chen et al., 2015), including glomerulus-specific neural plasticity (Rath et al., 2011). In moths, pre-exposure to the conspecific female sex pheromone increases the response of male PNs (Anderson et al., 2007), and associative learning with an appetitive cue causes recruitment of additional responsive neurons (Daly et al., 2001, 2004). Furthermore, learning of the scent of flowers which are profitable but are not innately preferred increases activity in AL neurons (Riffell, 2012; Riffell et al., 2013), and serotonin and octopamine are both involved in this process (Dacks et al., 2008, 2012). Experience might also have important effects facilitating segregation between a target odor and its odor background (see Section Effects of Background Odor), by modifying the balance of excitation and inhibition in AL neurons (Riffell et al., 2014; Szyszka, 2014; Chen et al., 2015). Noctuid moths switch their olfactory preference from food odors to egg-laying (e.g., cotton) odors following mating, and calcium imaging experiments demonstrated that this switch is due to changes in the representation of these odors across the AL glomerular array (Saveer et al., 2012). The mechanisms involving AL plasticity include modulation of the activity of ORCs by inhibitory interneurons (Ignell et al., 2009; Chou et al., 2010; Root et al., 2011), and neuromodulation by biogenic amines, neuropeptides and hormones (Nässel and Homberg, 2006; Dacks et al., 2008; Saveer et al., 2012).

In summary, experience and learning readily affect the odor oriented behavior of harmful insects through many neurophysiological mechanisms, which need to be considered in control strategies that include baits, repellents, use of trap crops, etc. Neurophysiological studies could help discover the most effective control methods; e.g., through high through-output screening of potential repellents that do not cause adaptation in ORCs.

## CONCLUSIONS

Odor sources are widely used to manipulate the behavior of harmful insects. In recent decades, the neurobiological bases underlying insect olfactory behavior started to be unraveled. The insect olfactory system is able to encode the quality, quantity, and temporal features of the odor stimuli. Information about odor mixtures is also encoded, including the ratio between their components and discrimination in complex backgrounds. Moreover, responses to odors are modulated by the animal's internal and external state, and by experience and learning. Natural odors are usually odor mixtures (against a "noisy" background), and are represented as particular odor objects in the AL. Those odor objects signify relevant odor sources such as a host or a conspecific that, at least in some cases, could be

"mimicked" in a simplified way using synthetic compounds, e.g., a male moth can be lured into a trap using synthetic versions containing few sex pheromone constituents. This facilitates the development of relatively simple and long-lasting odor baits to manipulate insect behavior. The simplified and optimal imitation of a natural odor mixture is challenging because it requires using only key mixture constituents, and this sometimes includes minor components within the natural mixture. Insect behavior can also be manipulated using repellents or "confusants." The studies mentioned in this work and others are helping us to understand how the olfactory system processes information about odors, making possible to design very efficient odor baits, repellents, or ways to confound the insects. Moreover, those studies also generate predictions about natural olfactory behavior that are useful to devise odor-based strategies for insect control. Clearly, the fields of neuroethology and insect control could certainly benefit from reciprocal interactions, which need to be fostered by all partners involved, including funding agencies. Encouraging new steps are being taken in this direction such as a recent initiative between different agencies on the beneficial and antagonistic interactions between plants (including agricultural plants) and their pathogens (including insects). We hope that the information provided in this review will help find gaps in the knowledge about the neural bases of olfactory behavior that are worth filling, encourage related studies, and promote the application of existing information in the development of better methods to manipulate insect behavior for control purposes.

## AUTHOR CONTRIBUTIONS

PG contributed the general idea, wrote several sections, corrected the whole manuscript, and prepared the final version. CR wrote several sections, made several general suggestions, corrected the whole manuscript, and prepared the final version. HL wrote several sections, made general suggestions, and corrected the whole manuscript.

## ACKNOWLEDGMENTS

HL was supported by an award from NSF (DMS 2100004). PG thanks Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT), Argentina, for funding during part of this project through grant PICT-PRH-2009-43. We thank Dr. John Hildebrand (University of Arizona) for continuous inspiration, support, advice and encouragement throughout the years. CR also thanks Dr. Kristin Scott (UC Berkeley) for support and encouragement. We sincerely thank the reviewers for their many insightful comments and suggestions that substantially improved this manuscript.

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Reisenman, Lei and Guerenstein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
<figure><img src="image_109.png" /></figure>

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# BdorOBP83a-2 Mediates Responses of the Oriental Fruit Fly to Semiochemicals

Zhongzhen Wu¹, Jintian Lin², He Zhang² and Xinnian Zeng¹*

¹Key Laboratory of Natural Pesticide and Chemical Biology of the Ministry of Education, College of Natural Resources and Environment, South China Agricultural University, Guangzhou, China, ²Institute for Management of Invasive Alien Species, Zhongkai University of Agriculture and Engineering, Guangzhou, China

The oriental fruit fly, *Bactrocera dorsalis* (Diptera: Tephritidae), is one of the most destructive pests throughout tropical and subtropical regions in Asia. This insect displays remarkable changes during different developmental phases in olfactory behavior between sexually immature and mated adults. The olfactory behavioral changes provide clues to examine physiological and molecular bases of olfactory perception in this insect. We comparatively analyzed behavioral and neuronal responses of *B. dorsalis* adults to attractant semiochemicals, and the expression profiles of antenna chemosensory genes. We found that some odorant-binding proteins (OBPs) were upregulated in mated adults in association with their behavioral and neuronal responses. Ligand-binding assays further showed that one of OBP83a orthologs, BdorOBP83a-2, binds with high affinity to attractant semiochemicals. Functional analyses confirmed that the reduction in BdorOBP83a-2 transcript abundance led to a decrease in neuronal and behavioral responses to selected attractants. This study suggests that BdorOBP83a-2 mediates behavioral responses to attractant semiochemicals and could be a potential efficient target for pest control.

**Keywords:** *Bactrocera dorsalis*, olfactory, odorant binding proteins, functional analysis, attractive semiochemicals

**OPEN ACCESS**

**Edited by:**
Anders Garm,
University of Copenhagen, Denmark

**Reviewed by:**
Nicolas Montagné,
Pierre-and-Marie-Curie University,
France
Sylvia Anton,
French National Institute for
Agricultural Research (INRA), France

**\*Correspondence:**
Xinnian Zeng
zengxn@scau.edu.cn

**Specialty section:**
This article was submitted to *Invertebrate Physiology*, a section of the journal *Frontiers in Physiology*

**Received:** 28 June 2016
**Accepted:** 21 September 2016
**Published:** 05 October 2016

**Citation:**
Wu Z, Lin J, Zhang H and Zeng X (2016) BdorOBP83a-2 Mediates Responses of the Oriental Fruit Fly to Semiochemicals. *Front. Physiol.* 7:452.
doi: 10.3389/fphys.2016.00452

## INTRODUCTION

In insects, olfaction plays a key role in behavior such as host-seeking, mating, and oviposition. At the molecular level, soluble binding proteins and membrane-bound receptors have crucial functions in chemical signal transduction (Pelosi et al., 2006, 2014; Zhou, 2010; Leal, 2013; Oppenheim et al., 2015). Odorant molecules penetrate into the sensilla via pore tubules and diffuse through sensillar lymph to membrane-bound receptor proteins. Activation of these proteins generates action potentials in receptor neurons. Two families of soluble binding proteins, odorant binding proteins (OBPs; Pelosi and Maida, 1995; Zhou, 2010) and chemosensory proteins (CSPs; Pelosi et al., 2005, 2006), are involved in this process.

Various functional studies support a role of insect OBPs in olfactory perception. Expression of moth pheromone receptors in heterologous systems (Grosse-Wilde et al., 2006, 2007; Forstner et al., 2009; Chang et al., 2015) and studies *in vivo* using the *Drosophila melanogaster* "empty neuron system" (Hallem et al., 2004; Syed et al., 2006) have demonstrated that the presence of a corresponding pheromone-binding protein significantly enhances the sensitivity of insects to pheromones. The OBP Lush with a mutation led to reduction in sensitivity of olfactory receptor
neuron reception to the pheromone 11-cis-vaccenylacetate in *Drosophila* (Xu et al., 2005; Laughlin et al., 2008). RNA interference (RNAi) knockdown of OBPs lead to altered olfactory behavior in *Drosophila* (Swarup et al., 2011) and decreased electrophysiological responses in mosquito antennae (Biemann et al., 2010; Pelletier et al., 2010a,b). There are two different hypotheses regarding the mechanisms of odor receptor (OR) activation. In moths and mosquitoes, OBPs act as solubilizers and carriers for the release of ligands onto ORs, thus contributing to the sensitivity of the insect olfactory system (Syed et al., 2006; Biemann et al., 2010; Pelletier et al., 2010a). In *D. melanogaster*, LUSH (DmelOBP76a) forms an OBP-odorant complex that activates an OR, which is required for olfaction (Xu et al., 2005; Laughlin et al., 2008).

Insect CSPs are highly expressed in the sensillar lymph and exhibit binding activity toward odorants and pheromones (Jacquin-Joly et al., 2001; Gu et al., 2012; Iovinella et al., 2013; Zhang et al., 2014). CSPs of *Locusta migratoria* in antennae are involved in the physiological shift from solitary to gregarious phase (Guo et al., 2011), and an antenna-specific CSP of *Glossina morsitans morsitans* is thought to be associated with host searching behavior (Liu et al., 2012). However, there is no direct evidence to confirm a role of CSPs in olfaction.

The oriental fruit fly, *Bactrocera dorsalis* (Diptera: Tephritidae), is one of the most important pests throughout tropical and subtropical regions in Asia (Drew and Hancock, 1994). This insect pest can damage over 117 species of fruits and vegetables (Allwood et al., 1999), suggesting that it can detect and recognize a wide range of odorants. *B. dorsalis* exhibits remarkable developmental phases in olfactory behavior. When male adults reach sexual maturity, they are strongly attracted to and compulsively feed on methyl eugenol (4-allyl-1,2-dimethoxybenzene; Tan and Nishida, 2012). During the oviposition period, gravid females become more sensitive to a wide variety of volatile compounds, which have been shown to attract and/or stimulate oviposition (Jayanthi et al., 2014). These changes in olfactory behavior provide clues to study the physiological and molecular bases of olfactory perception in this pest, and may offer the possibility to explore alternative methods for pest control. Our previous transcriptome analysis of *B. dorsalis* provided a set of chemosensory genes and their expression profiles (Wu et al., 2015). Those antenna-specific or antenna-predominant chemosensory genes could be involved in recognition of specific ligands and contribute to olfactory behavioral changes in *B. dorsalis*.

The objective of the present study is to determine if there is a correlation between olfactory behavioral changes and those OBPs that are specifically or predominantly expressed in antennae. Specifically, we conducted behavioral assays, analyzed electroantennogram (EAG) responses to selected plant volatiles, and examined expression profiles of antenna-specific or antenna-predominant chemosensory genes in sexually immature and mated *B. dorsalis* adults. Using fluorescence competitive binding assays and molecular docking (in silico), binding affinity of selected OBPs to selected semiochemicals was also measured. The impact of the most abundant OBP, BdorOBP83a-2, on olfactory behavior was studied through RNAi. Our results suggest a likely

involvement of antenna-specific or antenna-predominant OBPs in olfaction, especially in regulating foraging and oviposition behaviors.

# MATERIALS AND METHODS

## Insect Rearing and Collection

*B. dorsalis* used in this study was reared at the Institute for Management of Invasive Alien Species, Zhongkai University of Agriculture and Engineering, Guangzhou, China. Insects were reared under a photoperiod of 14:10 h (L:D) at 28°C and 70% relative humidity (Jayanthi and Abraham, 2002).

Sexually immature individuals (2 days old) and mated individuals (mated males and gravid females of 15 days old) were collected and used for the analyses of olfactory behavioral changes, olfactory sensitivity changes, and transcriptional changes of olfactory genes that are potentially induced by mating and gravidity. To obtain mated males and gravid females, 9 days old virgin adults of each sex were introduced into a 30 × 30 × 30 cm cage for mating. Once copulating pairs were formed for at least 60 min, they were transferred to another cage and maintained there until 15 days old.

## Semiochemicals

All semiochemicals used to investigate olfactory behavioral responses, EAG responses, and binding assays were purchased from Sigma-Aldrich (St. Louis, MO, USA) and with more than 95% purity (Table S1).

## Olfactory Behavioral Assays

Olfactory attraction was tested using a modified two-choice trap system based on the body size of *B. dorsalis* (Figure S1; Faucher et al., 2013). Odor traps were constructed from 250 ml conical flasks to which a silicone top containing 15 ml centrifuge tube (cut for 4.5 cm) was securely placed. Each trap contained a cotton-foam plug to which either 0.2 ml of 1% semiochemicals dissolved in paraffin oil or paraffin oil alone were added. Olfactory behavioral assays were conducted for 6 h in a dark humidified room at 28°C. Testing insects were starved for 4 h (6:00–10:00) in insect rearing cages with only water. Thirty insects per assay were then transferred to a new rearing cage. A performance index (PI) was used to measure olfactory attraction, which was calculated using the following formula: Performance index (PI) = (flies in odor vial – flies in control vial)/total of flies. Each trap assay was replicated five times.

## Electroantennogram (EAG) Recording

EAG recordings (Syntech, Kirchzarten, Germany) were used to investigate *B. dorsalis* antennal responses to different semiochemicals according to standard protocols (Hayase et al., 2009). Insects were again starved for 4 h (6:00–10:00) before assays. The whole antennae of males and females were excised, cut on both ends and attached to two electrodes with Spectra 360 conducting gel (Parker Lab., Inc., Hellendoorn, Netherlands). Pure chemicals were dissolved in paraffin oil and tested at a final concentration of 10⁻² v/v. A 10 µl aliquot of paraffin oil was used as a control. The neuronal responses of antennae from five males
and five females were tested in each treatment. Five stimulations of each chemical were applied at intervals of 10 s on the antennae. EAG signals were amplified, filtered, digitized, and analyzed with an EAG Pro program (Syntech).

## Olfactory Gene Expression Analysis

qRT-PCR was used to investigate the variation of the transcription levels of olfactory genes in sexually immature and mated adults. From each experiment, 100 whole antennae for each gender were excised and immediately transferred to a polypropylene tube cooled over liquid nitrogen. The frozen antennae were crushed, and total RNA was extracted with an RNeasy Mini kit (Qiagen), following the manufacturer's protocol. cDNA was synthesized from total RNA using a First strand cDNA synthesis kit (Takara). Specific primer pairs for the qRT-PCR were the same to those used in our previous study (Wu et al., 2015). The α-tublin (α-TUB; GenBank Acc. GU269902) of *B. dorsalis* was used for normalizing the target gene expression (Shen et al., 2010). qRT-PCR analysis was conducted on a LightCycler 480 system (Roche) with a SYBR Premix ExTaq kit (Takara). Negative controls without template were included in each experiment. To ensure reproducibility, each qRT-PCR reaction was performed using technical triplicates and biological triplicates. Relative gene expression data was estimated using the 2⁻^ΔΔCT^ method (Livak and Schmittgen, 2001).

## Bacterial Expression and Purification of BdorOBPs and BdorCSP

The sequences of BdorOBPs and BdorCSPs encoding mature proteins (without signal peptide) were amplified by PCR using specific primers carrying a restriction site EcoRI or XhoI (Table S2). PCR fragments were digested with both EcoRI and XhoI enzymes and the released DNA fragments were cloned into a PET-32a vector (Invitrogen), which were used to transform BL21 (DE3) *E. coli* competent cells (Invitrogen). A selected positive clone was grown overnight in 5 mL liquid LB/ampicillin medium overnight at 37°C. Protein expression was induced with 1 mM IPTG for 3 h when the culture had reached an OD₆₀₀-value of 0.7-0.9. Cells were then harvested by centrifugation and lysed by sonication. After sonication and centrifugation, most recombinant proteins were present in inclusion bodies. Protein extracts were dissolved in extraction buffer (8 M urea, 0.5 M NaCl, 5 mM Imidazole, 1 mM β-mercaptoethanol, and 20 mM Tris-HCl pH 7.4) and purified using HisTrap affinity columns (GE Healthcare Biosciences, Uppsala, Sweden). Renaturation of purified proteins were accomplished by gradient dilution at 4°C. His-tag was removed by digestion with recombinant enterokinase (Novagen) and the digested mixtures were passed through a HisTrap affinity column to remove any undigested protein. At each step during protein preparation and purification, protein extracts, and purified proteins were examined on 15% SDS-PAGE.

## Fluorescence Competitive Binding Assay

To measure the affinity of the recombinant proteins to the fluorescent probe N-phenyl-1-naphthylamine (1-NPN), a 2 µM solution of each target protein in 50 mM Tris-HCl buffer, pH

7.4, was titrated with aliquots of 1 mM 1-NPN in methanol to final concentrations of 1–16 µM. The affinity of the proteins to other ligands was measured in competitive binding assays, where a solution of the protein and 1-NPN, both at the concentration of 2 µM, was titrated with 1 mM methanol solution containing a competitor with concentrations in the range of 5–50 µM. Fluorescence spectra were measured on an F-7000 FL Fluorescence Spectrophotometer (Hitachi) in a 10 mm light path quartz cuvette at 25°C. All were excited at 337 nm with emission and excitation slit of both 10 nm. The emission spectra were recorded between 350 and 500 nm. Data analysis and plot binding curves were accomplished in the Prism software, assuming that the target protein had a 100% activity with a stoichiometry of 1:1 protein: ligand at saturation. All measurements were performed in triplicates and mean values and standard errors are calculated. The dissociation constants of the competitors were calculated from the corresponding IC₅₀-values (the concentration of ligand halving the initial fluorescence value of 1-NPN), by the equation: K<sub>D</sub> = [IC₅₀]/1 + [1-NPN]/K₁-<sub>NPN</sub>, where [1-NPN] is the free concentration of 1-NPN and K₁-<sub>NPN</sub> is the dissociation constant of the complex Protein/1-NPN.

## Three-Dimensional Modeling and Molecular Docking

Two different strategies were employed to predict three-dimensional modeling of OBPs and CSP of *B. dorsalis*. Those that have more than 30% homology with the OBP or CSP templates in the Protein Database (http://www.rcsb.org/pdb) were predicted using the on-line program SWISS MODEL (Guex and Peitsch, 1997; Arnold et al., 2006; Guex et al., 2009), while others <30% were generated using an online protein threading (PHYRE 2; Kelley et al., 2015). The information of the templates was shown in Tables S3, S4. Alignments of BdorOBP83a-1, BdorOBP83a-2, BdorCSP3, BdorOBP84a-1, BdorOBP84a-2, and BdorOBP56h with the template protein are shown in Figure S2. Furthermore, rapid energy minimization of protein molecules was carried out using discrete molecular dynamics with an all-atom representation for each residue in the protein in Chiron (http://troll.med.unc.edu/chiron/login.php; Ramachandran et al., 2011). Molecular docking was performed using "Docking server" (Bikadi and Hazai, 2009). All compounds from previous studies were used for docking studies. Three-dimensional structures of compounds were obtained from NCBI. Docking was performed 255 times with selected OBPs and ligands. For each run, the 10 highest docking poses were saved and were further processed for molecular dynamics simulations. Free binding energies were calculated as previously described (Okimoto et al., 2009).

## Phylogenetic Analysis and Sequence Alignment

Phylogenetic analyses of the newly identified *B. dorsalis* OBPs were performed in conjunction with previously identified *B. dorsalis* OBPs and OBPs from other species, including 31 OBPs from *B. dorsalis* (Wu et al., 2015), 52 OBPs from *D. melanogaster* (Hekmat-Scafe et al., 2002; Vieira et al., 2007; Vieira and Rozas,
2011), 16 OBPs from *Ceratitis capitata* (Siciliano et al., 2014a), 15 OBPs from *Rhagoletis pomonella* (Schwarz et al., 2009), 9 OBPs from *Rhagoletis suavis* (Ramsdell et al., 2010), Obp83a orthologs from *G. m. morsitans* (Liu et al., 2010; Macharia et al., 2016), *Musca domestica* (Scott et al., 2014), and *Calliphora stygia* (Leitch et al., 2015). After removal of signal peptide sequences, OBP amino acid sequences were aligned using MAFFT v6.935b (Katoh and Toh, 2010; Katoh and Standley, 2013) with the E-INS-I strategy, BLOSUM62 matrix, 1000 maxiterate and offset 0. The maximum-likelihood trees were constructed using FastTree 2.1.7 (Price et al., 2009, 2010) with 1000 bootstrap replications. The phylogenetic tree was visualized in FigTree (http://tree.bio.ed.ac.uk/software/figtree). For comparative purpose, the analyzed sequences were aligned using the E-INS-I strategy in MAFFT and visualized with Jalview 2.0.1 (Waterhouse et al., 2009).

## RNA Interference and Bioassay

dsRNAs for BdorOBP83a-2 and Bdorβ-gal (Glyceraldehyde-3-phosphate dehydrogenase) were synthesized through *in vitro* transcription from PCR products generated using a MEGAscript T7 transcription kit (Ambion). Briefly, the pMD18-T vector containing the target-gene insert (constructed as described above) was used as template for PCR amplification. PCR was performed using two specific primers with a T7 promoter sequence (5'-TAATACGACTCACTATAGGG-3') at the 5'-end of each primer (Table S5). Large-scale dsRNAs were purified using a MEGAclear kit (Ambion) and precipitated with 5 M ammonium acetate to yield 30-50 µg/µL dsRNA. Ten days old adults were used for all injection experiments. Individuals receiving injection were placed on a stereomicroscope and surface-sterilized with 70% ethanol. One microgram of dsRNA was injected into each individual at the suture between third and fourth abdominal segments (100 ng/mg equivalent) using an automatic microinjection apparatus (Nanoject II Auto-Nanoliter). The injected insects were then transferred to new rearing cages for continuous culture (at 25 ± 1°C, 50% humidity) until 15 days old.

Given that rapid degradation of dsRNA fragments has been observed in insect hemolymph in other studies (Garbutt et al., 2013), we performed a pre-assay for the stability of dsRNA fragments under our conditions before starting dsRNA microinjection experiment. In the pre-assay, peripheral hemolymph was extracted from thoraxes of 10 days old adults individually using a microsyringe. Hemolymph from individual insects was combined into a precooled 50 µl PCR tube containing phenylthiourea to avoid melanization (Arakawa, 1995). The BdorOBP83a-2 dsRNA (1 µg) and hemolymph (3 µl) mixture was incubated at 25°C for 0-3 h. A control was included by mixing dsRNA with DEPC-water under the same conditions. After incubation, dsRNA was re-extracted with 20 µl nuclease-free water using an RNeasy Mini Kit (Qiagen, Valencia, CA) according to the RNA Cleanup instruction. Re-extracted dsRNA (8 µl) was separated on 1% agarose gels. Our *ex vivo* experiments showed that dsRNA fragments were stable in adult hemolymph, with a residence time of at least 3 h (Figure S3), indicating that dsRNA is likely to be stable in *B. dorsalis* for RNAi testing.

For PCR analysis, 30 pairs of antennae from 15 days old male and female adults, were excised and used for RNA isolation. Detailed procedures for RNA isolation, cDNA synthesis, and PCR amplification were the same as described previously. An α-tubulin (α-TUB; GenBank Acc. GU269902) of *B. dorsalis* was used as an internal reference. qRT-PCR primers used for BdorOBP83a-2 and Bdorβ-gal genes were designed with the Primer 3 program (http://primer3.ut.ee/) and the primer sequences are listed in Table S6. Technical triplicates and three biological replicates were carried out for each treatment.

EAG recordings were used to investigate any changes in antennal responses to attractant compounds (methyl eugenol and γ-octalactone) in water-treated, β-galactosidase-dsRNA-injected, BdorOBP83a-2-dsRNA-injected adults (both male and female). EAG responses were recorded for at least five individuals of water-treated control, β-galactosidase-dsRNA-injected control, and BdorOBP83a-2-dsRNA-injected insects. Each EAG observation was recorded with 10 individuals of each sex. Behavioral phenotypes of water-treated, β-galactosidase-dsRNA-injected, BdorOBP83a-2-dsRNA-injected insects were also assessed using a wind tunnel (Figure S4).

A fixed setting of 300 ml/min air-flow was used during the assays. Odor molecules pass through the glass tube from the odor source to the other end of the pipe along with the air flow. In each trial, one tested fly was placed in the opposite end of the odor source as the starting point. The time needed for insects to reach the odor source from the starting point was determined. The odor source was made by dissolving the test chemicals into paraffin oil at a final concentration of $10^{-2}$ v/v. Twenty microliters of the resulting mixture were added onto an absorbent cotton ball, which was used immediately as odor source. The wind tunnel experiment was recorded with 10 individuals of each sex, and performed in triplicates. Both EAG and wind tunnel experiments were performed at 25°C with relative humidity 90%.

## Statistical Analysis

Statistical analyses were performed using Prism 6.0 (GraphPad Software, CA, USA). Statistical significance levels were derived through ANOVA and adjusted by a Tukey multiple comparison test.

## RESULTS AND DISCUSSION

### OBP Gene Expression Levels and Changes in Insect Olfactory Behavior

To determine olfactory behavioral changes in different stages of *B. dorsalis*, we used traps with different attractants to measure olfactory reactions in sexually immature and mated individuals from both sexes. We conducted olfactory assays with attractants that have been previously reported effective to *B. dorsalis* adults (Table S1; Chiu, 1990; Hwang et al., 2002; Tan et al., 2010; Hu et al., 2012; Tan and Nishida, 2012; Kamala Jayanthi et al., 2014; Jayanthi et al., 2014; Pagadala Damodaram et al., 2014). We found that immature males and females responded relatively weakly to nearly all tested attractant compounds (left part of Figure 1, Table S7). In contrast, both mated males and females responded strongly to most of the tested attractant compounds (right part of
<figure><img src="image_110.png" /><figcaption>**FIGURE 1** | Olfactory behavior responses of sexually immature and mated males and females of *B. dorsalis* to selected attractant chemicals. Asterisks indicate significant differences in performance index of males and females (\*P < 0.05, \*\*P < 0.01, \*\*\*P < 0.0001, unpaired two-tailed *t*-tests).</figcaption></figure>

**Figure 1**). To some chemicals including E-coniferyl alcohol, γ-octalactone, and benzothiazole, mated males and females reacted differently. We also examined EAG responses on the same types of insects with the same set of chemicals. The EAG data exhibited similar differences between immature and mated flies as observed in olfactory behavior except that immature insects responded more strongly to the tested chemicals than what was observed in olfactory response assays (**Figure 2**). Mated males and females

also responded differently to the attractants E-coniferyl alcohol and γ-octalactone, but reacted similarly to benzothiazole.

Previous reports indicate that expression levels of olfactory genes correlate with antennal odorant receptivity in the mosquito *Anopheles gambiae* (Rinker et al., 2013a,b), the tsetse fly *G. m. morsitans* (Liu et al., 2010, 2012), and the beet armyworm *Spodoptera exigua* (Wan et al., 2015). Here, we wanted to investigate whether expression levels of
<figure><img src="image_111.png" /><figcaption>**FIGURE 2** | EAG responses of sexually immature and mated males and females of *B. dorsalis* to selected chemicals. Asterisks indicate significant differences in EAG responses of males and females (\*\*P < 0.01, \*\*\*P < 0.0001, unpaired two-tailed t-tests).</figcaption></figure>

olfactory genes could regulate both behavioral and neuronal responses in *B. dorsalis* at different physiological status. Previously, we determined the expression profiles of individual genes (Wu et al., 2015). The following antenna-specific or antenna-predominant olfaction genes, including 10 OBPs (BdorOBPlush, BdorOBP19a, BdorOBP19d-1, BdorOBP28a,

BdorOBP56h, BdorOBP69a, BdorOBP83a-1, BdorOBP83a-2, BdorOBP84a-1), one CSP (BdorCSP3), one ORco (BdorORCO), and two SNMPs (BdorSNMP1-1 and BdorSNMP1-2), are expressed exclusively or predominantly in antennae. At the present study, we further determined if these antenna-specific genes were differentially expressed in different developmental
stages of male and female adults. We found that five OBP
genes were significantly upregulated in mated females during
oviposition compared with immature females, whereas only
one was significantly upregulated in mated males (Figure 3).
These observations suggested that the specific upregulation
of OBPs in mated adults might be involved in changes in
olfactory perception. However, CSPs and ORco genes were not
significantly upregulated in either mated females or males, and a
significant down-regulation of SNMMP1-1 in females was observed
under our conditions (Figure 4). Expression of genes encoding
antenna-specific chemosensory proteins varies in different insect
species. In G. m. morsitans, antenna-specific CSPs (GmmCSP2),
the orthologs of BdorCSP3, are up-regulated during starvation
in female adults, and are thought to be linked to olfactory
perception of hosts (Liu et al., 2012). In A. gambiae, a subset
of OBP genes are upregulated post a blood feeding whereas
most other chemosensory genes are not affected or even down-
regulated (Rinker et al., 2013a); and such changes following
blood feeding are coincident with a switch from host-seeking to
oviposition behaviors. These observations suggest that different
mechanisms likely exist for chemosensory perception in different
insects under different conditions.

Olfactory behavior of most insects displays remarkable phase
changes associated with different physiological status, such as
sexually immature and mated adults. Typically, mated male
fruit flies are strongly attracted to and compulsively feed on
methyl eugenol, but sexually immature males showed a weak
behavioral response to methyl eugenol (Mitchell et al., 1985; Tan
and Nishida, 2012). In addition, various fruit volatiles attract
gravid females, which lay their eggs in host fruits (Cornelius
et al., 2000; Hwang et al., 2002; Siderhurst and Jang, 2006;
Jayanthi et al., 2012; Kamala Jayanthi et al., 2014; Pagadala
Damodaram et al., 2014). On the contrary, sexually immature
females showed limited responses to food-type attractants, such
as fermenting sugars, hydrolyzed protein, and yeast. In this study,
the expression level of BdorOBP83a-2 along with other antenna-
specific OBPs correlated with increased olfactory sensitivity,
indicating that specific OBPs were likely responsible for detection
of specific attractants.

Binding Assays of OBPs to Attractant Semiochemicals

To determine the roles of specific OBPs in recognition of
attractants in *B. dorsalis*, recombinant proteins of selected

<figure><img src="image_112.png" /><figcaption>**FIGURE 3** | Transcript abundance of selected OBP genes in the antennae of 1 day immature (1 dV), and 15 days old mated (15 dM) males and females.

Asterisks indicate significant differences in transcript abundances (*P* < 0.05, **P** < 0.01, ***P** < 0.0001, unpaired two-tailed *t*-tests).</figcaption></figure>

<figure><img src="image_113.png" /><figcaption>**FIGURE 4** | Transcript abundance of BdorCSP3, BdorOrco, BdorSNMP1-1, BdorSNMP1-2 in the antennae of 1 day immature (1 dV), and 15 days old mated (15 dM) males and females. Asterisks indicate significant differences in transcript abundances (*P* < 0.05, unpaired two-tailed *t*-tests).</figcaption></figure>
antenna-abundant OBPs and CSPs were obtained using a prokaryotic expression system (Figure 5). Purified OBPs and CSPs were used to determine binding affinity of each protein via

fluorescence competitive binding assays. Thirteen pure attractant compounds were tested against each recombinant protein. Six antenna-rich proteins (five OBPs and one CSP) exhibited high

<figure><img src="image_114.png" /></figure>

<figure><img src="image_115.png" /></figure>

<figure><img src="image_116.png" /></figure>

<figure><img src="image_117.png" /></figure>

<figure><img src="image_118.png" /></figure>

<figure><img src="image_119.png" /></figure>

**FIGURE 5** | Recombinant BdorOBPs and a BdorCSP analyzed on SDS-PAGE. M, Molecular weight marker; 1, Total protein extract from non-induced pET32a transformed BL21 (DE3) cells; 2, Protein extract from isolated inclusion body of pET32a transformed cells; 3, Supernatant of ultrasonated pET32a transformed cells; 4, Proteins purified through Ni-NTA columns; 5, Purified proteins with His-tag cleaved using recombinant enterrokinase; (A), BdorCSP3; (B), BdorOBP56h; (C), BdorOBP83a-1; (D), BdorOBP83a-2; (E), BdorOBP84a-1; (F), BdorOBP84a-2.
affinity to the fluorescent probe 1-NPN (Figure 6). Except for BdorCSP3 and BdorOBP84a-2, all remaining OBPs could bind to the tested compounds (Figure 6; Table S8). The binding inability of BdorCSP3 and BdorOBP84a-2 might suggest that other compounds could be ligands for these two proteins. Alternatively they might be involved in functions other than odor detection. Among the analyzed proteins, BdorOBP83a-1 and BdorOBP83a-2 showed higher affinity than the remaining OBPs to all tested attractant chemicals, with BdorOBP83a-2 being the highest (Table S8). For BdorOBP83a-2, attractants methyl eugenol and esters exhibited the lowest dissociation constants (Figure 7; Table S8). The binding affinity decreased in order for attractants methyl eugenol, γ-nonanoic lactone, δ-octalactone, γ-undecalactone, and γ-octalactone. Overall, we observed lower binding affinity with our recombinant proteins and tested attractants. As shown in Figure 7, the highest binding affinity was with BdorOBP83a-2, which reached approximately 40% of displacement in competitive binding assays. In other studies, much higher affinity has been reported. For example, competitive binding assays with a lepidopteran pheromone-binding protein can reach nearly 100% displacement (Hooper

et al., 2009; Gu et al., 2013), and competitive binding assays with an aphid OBP (OBP7) can reach about 80% displacement with the alarm pheromone (E)-ss-farnesene (Sun et al., 2012). The biological significance of the observed lower affinity with *B. doralis* OBPs here remains to be determined. It could be due to diverse binding mechanisms between different functional OBPs and the corresponding compounds. Alternatively, BdorOBP83a-2 may interact with high affinity with other odor chemicals not yet identified.

Possible 3-dimensional structures of five OBPs and one CSP were predicted through molecular simulation (Figure S5), and the interactions between each of the six proteins and thirteen compounds were tested through docking (Table S9). Each protein displayed distinct spectra of binding affinity with the tested chemicals. Among them, BdorOBP83a-1 and BdorOBP83a-2 showed the highest affinity on average. Our overall simulation and docking data were in agreement with binding assays.

Phylogenetic analysis revealed that two OBP83a homologs, BdorOBP83a-1 and BdorOBP83a-2, clustered together with orthologous OBPs from other Dipterans (Figure S6), consistent

<figure><img src="image_120.png" /></figure>

<figure><img src="image_121.png" /><figcaption>FIGURE 6 | Binding assays of recombinant OBPs and a CSP with the fluorescent probe 1-NPN. Data are means of three independent experiments.</figcaption></figure>
<figure><img src="image_122.png" /><figcaption>FIGURE 7 | Binding assays of recombinant OBPs and a CSP with selected ligands. Data are means of two independent experiments.</figcaption></figure>
A

BdorOBP83a-2 Transcript Levels

<figure><img src="image_123.png" /></figure>

Bdorβ-gal Transcript Levels

<figure><img src="image_124.png" /></figure>

B

Response to ME

<figure><img src="image_125.png" /></figure>

Response to γ-octalactone

<figure><img src="image_126.png" /></figure>

C

<figure><img src="image_127.png" /></figure>

Response to ME

<figure><img src="image_128.png" /></figure>

D

<figure><img src="image_129.png" /></figure>

Response to ME

<figure><img src="image_130.png" /></figure>

E

<figure><img src="image_131.png" /></figure>

Response to γ-octalactone

<figure><img src="image_132.png" /></figure>

F

<figure><img src="image_133.png" /></figure>

Response to γ-octalactone

<figure><img src="image_134.png" /></figure>

**FIGURE 8** | Effect of RNAi treatments on electrophysiological responses to methyl eugenol and γ-octalactone. (A) Upper part: BdorOBP83a-2 transcript levels in water-treated (orange), β-galactosidase-dsRNA-injected (blue), and BdorOBP83a-2-dsRNA-injected the oriental fruit fly (lime); lower part: Bdorβ-gal transcript levels in water-treated (orange), β-galactosidase-dsRNA-injected (blue), and BdorOBP83a-2-dsRNA-injected the oriental fruit fly (lime); (B) upper part: EAG responses to methyl eugenol in water-treated (orange), β-galactosidase-dsRNA-injected (blue), and BdorOBP83a-2-dsRNA-injected; lower part: EAG responses to γ-octalactone in water-treated (orange), β-galactosidase-dsRNA-injected (blue), and BdorOBP83a-2-dsRNA-injected; EAG traces recorded from antennae of water-treated, β-galactosidase-dsRNA-injected, and BdorOBP83a-2-dsRNA-injected male and female challenged with methyl eugenol (C,D) and γ-octalactone (E,F). MA, male antennae; FA, female antennae. Different lowercase letters above each bar denote significant differences between samples (*p* < 0.05).
<figure><img src="image_135.png" /></figure>

<figure><img src="image_136.png" /></figure>

<figure><img src="image_137.png" /></figure>

<figure><img src="image_138.png" /></figure>

**FIGURE 9** | Effect of RNAi treatments on olfactory behavior to the attractants methyl eugenol and γ-octalactone. Olfactory behavior to methyl eugenol in non-treated (purple), water-treated (orange), β-galactosidase-dsRNA-injected (blue), and BdorOBP83a-2-dsRNA-injected (green) in males (A) and females (B); and to γ-octalactone in males (C) and females (D) (\*P < 0.01, \*\*P < 0.0001).

with exceptional conservation in function among OBP83a orthologs from different species (Figure S7). OBP83a orthologs, which were exclusively expressed in antennae, have been reported to play crucial roles in olfactory perception, such as in starved females in host seeking of *G. m. morsitans* (Liu et al., 2010), and pheromone components detection in *C. capitata* (Siciliano et al., 2014a,b). These results correspond well to its specific tissue distribution within antennae which could give a functional implication that BdorOBP83a-1 and BdorOBP83a-2 would share a relatively conserved physiological function with its orthologs.

## Roles of BdorOBP83a-2 in Attractant Perception

Since BdorOBP83a-2 was upregulated in both mated males and females, and exhibited the highest ligand-binding affinity, we further analyzed its potential role in olfactory perception via RNAi. Microinjection of BdorOBP83a-2 dsRNA inhibited approximately 50% expression of the gene in antennae

based on qPCR analysis (Figure 8A). Males and females with BdorOBP83a-2 knocked down were examined for possible impact on olfactory behavior changes. As shown in Figures 8B(upper part),C,D, knockdown of BdorOBP83a-2 resulted in 60-70% reduction of EAG response activity to methyl eugenol. Similarly, knockdown of BdorOBP83a-2 resulted in approximately 40% reduction of EAG response activity to γ-octalactone (lower part of Figures 8B,E,F). In comparison, knockdown of olfactory-unrelated control genes resulted in no significant changes in EAG response activities. Males and females with BdorOBP83a-2 knocked down were also used for olfactory behavior analysis. Flight time to reach the odor source for insects with BdorOBP83a-2 knocked down increased 30-50% with methyl eugenol as attractant. Knockdown of control genes resulted in no apparent changes in flight time (Figures 9A,B). Our data strongly suggest that BdorOBP83a-2 contributes to the changes observed in chemosensory and behavioral function. Our observation is consistent with reports that knockdown of a single OBP gene led to a significant
decrease in the sensitivity of *C. quinquefasciatus* and *A. gambiae* adults to major oviposition attractants (Biessmann et al., 2010; Pelletier et al., 2010a). Mutations in a single OBP gene can also cause significant changes in odorant perception and courtship behavior of Drosophila adults (Xu et al., 2005; Laughlin et al., 2008).

## CONCLUSIONS

We have comparatively analyzed olfactory attraction and EAG responses to semiochemicals in sexually immature and mated males and females. The expression of antenna-predominant OBPs was upregulated in the mated flies, and this increase may be related to the need for an increased ability to detect some key volatiles. Our ligand-binding assays demonstrated that OBP83a homologs exhibited the highest affinity to the attractant semiochemicals. Reduction in BdorOBP83a-2 transcript abundance led to a decrease in neuronal responses to representative attractants as well as behavioral responses. Together, these results suggest that BdorOBP83a-2 is likely to participate in mediating responses of *B. dorsalis* adults to attractant semiochemicals.

## AUTHOR CONTRIBUTIONS

ZW and XZ designed the experiments. ZW and HZ performed the experiments. ZW and JL contributed reagents/materials/gene identification. ZW analyzed the data. ZW and XZ wrote and revised the paper.

## ACKNOWLEDGMENTS

We thank Dr. Mingshun Chen (Kansas State University, USA), Dr. Paolo Pelosi (University of Pisa, Italy), and Dr. Guirong Wang (Chinese Academy of Agricultural Sciences, China) for comments and editorial assistance on the manuscript. This work was supported financially by Guangdong Engineering Research Center for Insect Behavior Regulation (2015B0909 03076).

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## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fphys. 2016.00452

**Table S1** | Detailed information of semiochemicals. IUPAC nomenclature, CAS number (CAS #), Behavioral output, Odor resource, Chemical structure, and References are shown.

**Table S2** | Primers for heterologous expression of OBP and CSP proteins.

**Table S3** | Three-dimensional modeling of proteins using SWISS-MODEL.

**Table S4** | Three-dimensional modeling of proteins using Phyre2.

**Table S5** | Primers used for producing constructs for BdorOBP83a-2 and Bdorβ-gal genes and for PCR amplification of templates for dsRNA synthesis.

**Table S6** | Primers used for qRT-PCR to determine transcript levels of BdorOBP83a-2 and Bdorβ-gal genes.

**Table S7** | Performance index (PI) of response to different compounds in sexual immaturity and sexual maturity.

**Table S8** | Binding characteristics of four recombinant BdorOBPs with selected semiochemicals.

**Table S9** | Outputs of *in silico* docking analyses of selected semiochemicals with putative OBPs and a CSP through the "Docking Server."

**Figure S1** | Schematic presentation of olfactory trap assays.

**Figure S2** | Alignments of BdorOBP83a-1, BdorOBP83a-2, BdorCSP3, BdorOBP84a-1, BdorOBP84a-2, and BdorOBP56h with the template protein.

**Figure S3** | *Ex vivo* degradation assay of dsRNA fragments using hemolymph. H₂O: H₂O+dsRNA; 0-3 h: hemolymph plasma+dsRNA

**Figure S4** | The device used for olfactory behavior assays (A), its dimensions (B) and sketches (C).

**Figure S5** | Three-dimensional modeling of putative proteins BdorOBP56h, BdorOBP83a-1, BdorOBP83a-2, BdorOBP84a-1, BdorOBP83a-2, and BdorCSP3.

**Figure S6** | Phylogenetic relationship of OBPs from *B. dorsalis* and other dipterans. Bars indicate branch lengths in proportion to amino acid substitutions per site. Bdor, *Bactrocera dorsalis*; Csty, *Calliphora stygia*; Dmel, *Drosophila melanogaster*; Gmm, *Glossina morsitans morsitans*; Mdom, *Musca domestica*; Rpom, *Rhagoletis pomonella*; Rsua, *Rhagoletis suavis*.

**Figure S7** | An amino acid alignment of BdorOBP83a-2 with orthologs from other dipterans. Signal peptides were removed from all amino acid sequences. All conserved cysteine residues are displayed under the alignment.

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2016 Wu, Lin, Zhang and Zeng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
<figure><img src="image_139.png" /></figure>

CrossMark

# The Mouthparts Enriched Odorant Binding Protein 11 of the Alfalfa Plant Bug *Adelphocoris lineolatus* Displays a Preferential Binding Behavior to Host Plant Secondary Metabolites

Liang Sun<sup>1,2†</sup>, Yu Wei<sup>2†</sup>, Dan-Dan Zhang<sup>3</sup>, Xiao-Yu Ma<sup>2</sup>, Yong Xiao<sup>2</sup>, Ya-Nan Zhang<sup>4</sup>, Xian-Ming Yang<sup>2</sup>, Qiang Xiao<sup>1</sup>, Yu-Yuan Guo<sup>2</sup> and Yong-Jun Zhang<sup>2*</sup>

**OPEN ACCESS**

**Edited by:**

Sylvia Anton,
Institut National de la Recherche
Agronomique, France

**Reviewed by:**
Ewald Grosse-Wilde,
Max Planck Institute for Chemical
Ecology, Germany
William Benjamin Walker,
Swedish University of Agricultural
Sciences, Sweden

*Correspondence:
Yong-Jun Zhang
yjzhang@ippcaas.cn

**Specialty section:**
This article was submitted to
Invertebrate Physiology,
a section of the journal
Frontiers in Physiology

**Received:** 01 February 2016

**Accepted:** 17 May 2016

**Published:** 01 June 2016

**Citation:**
Sun L, Wei Y, Zhang D-D, Ma X-Y, Xiao Y, Zhang Y-N, Yang X-M, Xiao Q, Guo Y-Y and Zhang Y-J (2016) *The Mouthparts Enriched Odorant Binding Protein 11 of the Alfalfa Plant Bug Adelphocoris lineolatus Displays a Preferential Binding Behavior to Host Plant Secondary Metabolites*. *Front. Physiol.* 7:201.
doi: 10.3389/fphys.2016.00201

Odorant binding proteins (OBPs) are proposed to be directly required for odorant discrimination and represent potential interesting targets for pest control. In the notoriously agricultural pest *Adelphocoris lineolatus*, our previous functional investigation of highly expressed antennal OBPs clearly supported this viewpoint, whereas the findings of the current study by characterizing of AlinOBP11 rather indicated that OBP in hemipterous plant bugs might fulfill a different and tantalizing physiological role. The phylogenetic analysis uncovered that AlinOBP11 together with several homologous bug OBP proteins are potential orthologs, implying they could exhibit a conserved function. Next, the results of expression profiles solidly showed that *AlinOBP11* was predominantly expressed at adult mouthparts, the most important gustatory organ of Hemiptera mirid bug. Finally, a rigorously selective binding profile was observed in the fluorescence competitive binding assay, in which recombinant AlinOBP11 displayed much stronger binding abilities to non-volatile secondary metabolite compounds than the volatile odorants. These results reflect that *AlinOBP11*, even its orthologous proteins across bug species, could be associated with a distinctively conserved physiological role such as a crucial carrier for non-volatiles host secondary metabolites in gustatory system.

**Keywords:** *Adelphocoris lineolatus*, odorant binding protein, expression profiles, phylogenetic analysis, Fluorescence competitive binding assay

## INTRODUCTION

Smell is undoubtedly the most important sensory for insects survival and reproduction (Li and Liberles, 2015; Groot et al., 2016). Olfactory system that can sensitively and selectively detect biologically active odorants attracts great attention from researchers who attempt to explore alternative environment-friendly pest management strategy. In insect olfactory signal transduction pathway, several classes of membrane-bound proteins such as odorant receptor (ORs), ionotropic receptors (IRs), and sensory neuron membrane proteins (SNMPs) have been proven to play

<footnote n="1"><sup>1</sup>Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China, <sup>2</sup>State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China, <sup>3</sup>Department of Biology, Lund University, Lund, Sweden, <sup>4</sup>College of Life Sciences, Huaibei Normal University, Huaibei, China</footnote>

<footnote>† These authors have contributed
equally to this work.</footnote>
central roles in facilitating the conversion of the chemical message to an electrical signal, while the carrier proteins like odorant binding proteins (OBPs) or chemosensory proteins (CSPs) are proposed to bind, deliver and even recognize specific pheromones and odorants to their relevant receptors (Jacquin-Joly and Merlin, 2004; Leal, 2013). For decades, various functional studies toward important olfactory protein families such as OBPs or ORs actually lead to a quick discovering of some high-efficiency pest repellents or attractants (Tanaka et al., 2009; Sun Y. F. et al., 2012; Sun L. et al., 2013). For instance, in the alfalfa plant bug, *A. lineolatus*, behavioral active compounds were successfully screened via ligand binding assay of an antennae highly expressed AlinOBP10 (Sun L. et al., 2013). Synthetic compounds targeting OBP3 or OBP7 which was proven to be responsible for (E)-β-farnesene perception elicited significantly behavioral responses in aphids (Sun Y. F. et al., 2012).

Insect OBPs which were first identified in antennal sensillum of silk moth, *Antheraea polyphemus* (Vogt and Riddiford, 1981) belong to the superfamily of small acidic soluble carrier proteins and could be recognized by six highly conserved cysteines (Leal et al., 1999; Sandler et al., 2000; Tegoni et al., 2004; Pelosi et al., 2014). Studies of both immunocytochemical localization and *in situ* hybridization revealed that OBPs were synthesized by non-neuronal auxiliary cells (trichogen and tormogen cells) and secreted into the sensillum lymph with a very high concentration (up to 10 mM) (Steinbrecht et al., 1995; Hekmat-Scafe et al., 1997; Michael, 2000; De Santis et al., 2006; Sun Y. P. et al., 2013; Sun et al., 2014a). So far, various investigations elucidated that antennal sensillum enriched OBPs indeed played essential roles in recognition of physiologically relevant odorants (Jacquin-Joly et al., 2000; Pophof, 2004; Große-Wilde et al., 2006; He et al., 2010). For example, one subclass of OBP families named pheromone binding proteins, PBPs, was highly abundant in long trichoid sensilla and showed significantly specific binding affinities to insect sex pheromones (Vogt and Riddiford, 1981; Krieger et al., 1996; Leal et al., 1999; Klusák et al., 2003; Pophof, 2004; Große-Wilde et al., 2006; De Santis et al., 2006). Sensilla basiconica expressed OBPs were proposed to be involved in terpenoids or other plant volatiles detection (Feng and Prestwich, 1997). Meanwhile, in two Lepidopteran species, the cotton leafworm *Spodoptera littoralis* (Poivet et al., 2012) and the diamondback moth *Plutella xylostella* (Zhu et al., 2016), OBPs were even demonstrated to be associated with the interesting behavior why larvae are attracted by conspecific moth sex pheromone.

However, the functions of insect OBPs may be more complicated and could not be restrict within olfactory cue recognition. In *Drosophila melanogaster*, most OBPs were detected in both gustatory and olfactory sensilla and some numbers were even expressed exclusively in taste organs (Galindo and Smith, 2001). Jeong et al. (2013) proposed that feeding behavior of *D. melanogaster* can be suppressed by a gustatory organ expressed OBP49a responding to bitter compounds. Two OBP genes, *Obp57d* and *Obp57e* in *D. sechellia* have been demonstrated to be involved in the evolution of taste perception and host-plant preference (Matsuo et al., 2007). Particularly, expressions of *Aedes aegypti* OBP22 in antennae

and reproductive organs indicated its multiple functions (Li et al., 2008). Likewise, physiological roles of male reproductive organs expressed orthologous OBP10 in two sibling moth species has been proposed to act as a specific carrier for female oviposition deterrents that could help *Helicoverpa* offspring avoid cannibalism (Sun Y. L. et al., 2012).

The alfalfa plant bug, *A. lineolatus*, a typical polyphagous insect pest outbreaks frequently in cotton field since the transgenic *Bacillus thuringiensis* cotton largely cultivation in China (Lu et al., 2010). Worse still, flight behavior enable it to migrate among different host plants (Lu et al., 2009), and many other important crops like alfalfa (*Medicago sativa* L.), green bean (*Phaseolus vulgaris*), and tea plant (*Camellia sinensis*) suffer from its serious destroy (Lu and Wu, 2008). Evidence suggested that this bug heavily relies on chemical cues for host plant location and migration (Lu and Wu, 2008). Thus, studies aiming at the physiological and molecular basis of insect chemosensation may help explore an alternatively effective pest control method.

Previously, 14 OBP transcripts of *A. lineolatus* were identified (Gu et al., 2011a) and functional studies of several antennae highly expressed OBPs such as AlinOBP1, AlinOBP5, AlinOBP10, and AlinOBP13 indicated their potential olfactory roles (Gu et al., 2011b; Sun L. et al., 2013; Wang et al., 2013; Sun et al., 2014a). Subsequently, Hull et al. (2014) identified 33 putative OBP transcripts in the tarnished plant bug, *Lygus lineolaris*, and suggested that several OBP genes included *LylinOBP19* can be expressed in gustatory organs, implying they may be related to taste compound detected. However, whether OBPs could express at taste organs and fulfill potential gustatory functions in *A. lineolatus* remains largely unknown. In the current study, we mainly focus our attention on AlinOBP11, a putative orthologous OBP gene of *LylinOBP19* in *A. lineolatus* and our current results of tissue distribution pattern, ligand binding assay, and phylogenetic analysis would provide detail cues for its functional discussion.

# MATERIALS AND METHODS

## Insect Rearing and Tissue Collection

*A. lineolatus* adults were collected from alfalfa fields at the Langfang Experimental Station of Chinese Academy of Agricultural Sciences, Hebei Province, China. The laboratory colony was established in plastic containers (20 × 13 × 8 cm), which were maintained at 29 ± 1°C, 60 ± 5% relative humidity, and 14 h light:10 h dark cycle. The adults and newly emerged nymphs were reared on green beans and 10% honey. Different tissues from *A. lineolatus* adults of both sexes including antennae, mouthparts, heads (without antennae and mouthparts), thoraxes, abdomens, legs, and wings were collected for qRT-PCR. Each tissue was collected from three biological pools and all the specimens were immediately stored in -80°C for further process.

## RNA Isolation and cDNA Synthesis

Total RNA of each sample was isolated using the Trizol reagent (Invitrogen, Carlsbad, CA, USA), and the first-strand cDNA was synthesized by FastQuant RT-kit with gDNA Eraser (TianGen, Beijing, China) according to the manufacturer's instructions.
## qRT-PCR

qRT-PCR assay regarding different developmental stages and tissues were carried out using an ABI 7500 Real-Time PCR System (Applied Biosystems, Carlsbad, CA). Two house-keeping genes *Alinβ-actin* (GenBank No.GQ477013) and *AlinElongation factor* (GenBank No.AEY99651) were used as endogenous controls to normalize the target gene expression and correct for sample-to-sample variation. Taqman primers of *Alinβ-actin* and *AlinOBP11* cited Gu et al. (2011a) and primers of *AlinElongation factor* were designed using Primer Express 3.0 (Applied Biosystems) and listed in Table S1. For the qRT-PCR reaction, the cDNA was diluted to concentration of 200 ng /µL. Each reaction was performed in a 25 µL mixture of 12.5 µL of Premix Ex Taq (TaKaRa), 1 µL of each primer (10 mM), 0.5 µL probe (10 mM), 0.5 µL of Rox Reference Dye II, 1 µL of sample cDNA (200 ng), and 8.5 µL of sterilized H₂O. Negative controls were non-template reactions (H₂O instead of cDNA). The reaction cycling parameters were as follows: 95°C for 10 s, 40 cycles at 95°C for 20 s, 60°C for 34 s. For the data reproducibility, qRT-PCR reaction for each sample was performed in three technical replicates and three biological replicates. Since our preliminary experiment demonstrated that the amplification efficiency between targeted genes and reference gene was similar (data not shown), the comparative 2^(-ΔΔCT) method was used to calculate the relative quantification between tissues (Livak and Schmittgen, 2001).

The comparative analyses of target gene among different tissues and developmental stages were determined using a one-way nested analysis of variance (ANOVA), followed by Tukey's honestly significance difference (HSD) test using the software SPSS Statistics 18.0 (SPSS Inc., Chicago, IL, USA).

## Phylogenetic Construction and Selective Pressure Analysis

The 92 OBP sequences of five mirid bug species (GenBank accession numbers and references can be seen in Table S2) were used to infer the evolutionary history with the software MEGA 6.0 with a *p*-distance model and a pairwise deletion of gaps (Tamura et al., 2013). The bootstrap support of tree branches was assessed by re-sampling amino acid positions 1000 times. Estimation of the non synonymous (dN) to synonymous (dS) substitution rate (ω) was performed by the maximum likelihood method (Anisimova et al., 2001) using the Codeml program in the PAML 4.6 package (Yang, 1997).

## Western Blot Assay

The polyclonal antiserum against the recombinant AlinOBP11 was produced by injecting robust adult rabbits subcutaneously and intramuscularly with the highly purified recombinant protein. Recombinant protein was emulsified with an equal volume of Freund's complete adjuvant (Sigma, St. Louis, MO, USA) for the first time injection (500 µg) and then with incomplete adjuvant for the three additional injections (300 mg each time). The interval between each injection was approximately half a month, and blood was collected 7 days after the last injection and centrifuged at 6000 rpm for 20 min. The serum was purified based on a MAb Trap kit (GE Healthcare)

following the manufacturer's instructions. The rabbits were maintained in large cages at room temperature, and all of the operations were performed according to ethical guidelines to minimize the pain and discomfort of the animals.

Crude extracts from different tissues of female and male adult bugs included the antennae, mouthparts, legs, wings, and bodies (without aforesaid parts) were separated on 15% SDS-PAGE, respectively. Samples were transferred to a polyvinylidene fluoride membrane (PVDF, Millipore, Carrigtwohill, Ireland) at the condition of 200 mA for 50 min, and then membrane was blocked using 5% dry skimmed milk (BD Biosciences, San Jose, CA, USA) in phosphate-buffered saline (PBS) containing 0.1% Tween-20 (PBST) for 2 h at room temperature. After washing three times with PBST (10 min each time), the blocked membrane was incubated with purified rabbit anti-AlinOBP11antiserum (dilution 1:2000) for 1 h. Three times washing with PBST again, the membrane was incubated with anti-rabbit IgG horseradish peroxidase (HRP) conjugate and HRP-streptavidin complex (Promega, Madison, WI, USA) at a dilution of 1:10000 for 1 h. The membrane was then incubated with the western blot substrates of the enhanced chemiluminescence western blot kit (CoWinbiotech, China), and the bands were visualized by exposing to X-OMATBT films (Kodak, New York, USA).

## Fluorescence Competitive Binding Assay

The recombinant protein expression and purification was performed according to our previous protocols (Sun L. et al., 2013; Sun et al., 2014a). Briefly, the plasmid containing *AlinOBP11* gene was constructed and transformed into *Escherichia coli* BL21 (DE3) competent cells for recombinant protein expression, and the protein was largely induced with 1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG) at 37°C for 3-6 h. The purification was performed using two rounds of Ni ion affinity chromatography (GE-Healthcare), and the His-tag was removed with recombinant enterokinase (Novagen). The highly purified proteins were desalted through extensive dialysis, and then the size and purity of the recombinant proteins were verified by 15% SDS-PAGE.

For the ligand binding assays, 45 compounds include 41 volatiles and four non-volatiles were selected based on previously reported isolation from *A. lineolatus* host plants (Meisner et al., 1977; Halloin, 1982; Aldrich, 1988; Loughrin et al., 1995; Röse and Tumlinson, 2004; Millar, 2005). The binding assay was performed on an F-380 fluorescence spectrophotometer (Tianjin, China) at room temperature (25°C) with a 1-cm light path quartz cuvette and 10-nm slits for both excitation and emission. The excitation wavelength was 337 nm, and the emission spectrum was recorded between 390 and 460 nm. Firstly, the constant of AlinOBP11 with the fluorescent probe N-phenyl-1-naphthylamine (1-NPN) was measured, a final concentration of 2 µM protein solution in 50 mM Tris-HCl (pH 7.4) was titrated with aliquots of 1 mM 1-NPN dissolved in methanol to final concentrations ranging from 1 to 16 µM. Then the affinities of other ligands were tested through competitive binding assays using 1-NPN as the fluorescent reporter at a concentration of 2 µM, and the concentration of each competitor ranged from 2 to 30 µM. The fluorescence intensities at the
maximum fluorescence emission between 390 and 460 nm were plotted against the free ligand concentration to determine the binding constants. The bound chemical was evaluated based on its fluorescence intensity with the assumption that the protein was 100% active with a stoichiometry of 1:1 (protein: ligand) saturation. The binding curves were linearized using a Scatchard plot, and the dissociation constants of the competitors were calculated from the corresponding IC₅₀ values based on the following equation: Ki= [IC₅₀] / (1+ [1-NPN]/K₁-NPN), where [1-NPN] is the free concentration of 1-NPN and K₁-NPN is the dissociation constant of the complex protein/1-NPN.

# RESULTS

## Phylogenetic Tree Construction and Selective Pressure Analysis

A phylogenetic tree of 92 OBPs was constructed using the neighbor-joining method to analyze evolutional relationships between AlinOBP11 and other OBPs of different mirid species. **Figure 1** revealed a divergent OBP repertoire. AlinOBP11 and four other OBPs i.e., AlucOBP36, AfasOBP11, AsutOBP11, and LylinOBP19 from each bug species clustered into one same clade with bootstrap support value up to 74 (Figure 1A). Sequence alignment analysis showed AlinOBP11 has 94, 95, 94, and 60% identity to AsutOBP11, AlucOBP36, AfasOBP11, and LylinOBP19, respectively (Figures 1B,C). These results reflect AlinOBP11 and these four OBPs form a clear orthologous group across bug species.

To evaluate potential selective pressure acting on this *OBP11* orthologous cluster, we calculated the ratio of non synonymous to synonymous substitutions (dN/dS or ω) of this cluster with branch models using PAML and compared the log likelihoods (lnL) for the one ratio model M0 (assuming one ω ratio for all branches) and the free ratio model M1 (assuming one ω ratio for each branch) in likelihood ratio tests. The results uncovered that the one ratio model (M0) could not be rejected (*p* > 0.01) and all branches shared a normalized ω ratio of 0.2954 (Figure 1A), implying that purifying selection was acting on this cluster and *AlinOBP11* would share a relatively conserved physiological function with its orthologous genes (Qiao et al., 2009; Zhou et al., 2010; Vandermoten et al., 2011).

## Specific Tissue and Developmental Expression Profiles of *AlinOBP11*

The results of our western blot assay showed that clear protein bands could be found at mouthparts, legs, antennae as well as other tissues, which seems that AlinOBP11 can be ubiquitously expressed at adult tissues of both sexes (Figure 2). To compare the expression levels of *AlinOBP11* among different tissues, we then conducted the qRT-PCR assay. Interestingly, unlike previously reported uniformly antennae predominant expressed *AlinOBPs* (Gu et al., 2011a; Sun L. et al., 2013; Sun et al., 2014a), our current results revealed that *AlinOBP11* was strongly expressed at mouthparts, and slightly expressed at legs, antennae, and other tissues (Figure 3). Meanwhile, *AlinOBP11* transcript abundance varied among different developmental instars and

<figure><img src="image_140.png" /></figure>
<figure><img src="image_141.png" /></figure>

significantly higher expression level was observed in adult bugs (Figure 3).

## In vitro Expression and Purification of AlinOBP11

The recombinant AlinOBP11 was successfully expressed using a bacterial system. Induced targeted recombinant appeared at both supernatant and insoluble inclusion bodies and the former was selected to be purified using two rounds of Ni ion affinity chromatography (GE Healthcare, Little Chalfont, UK). The finally purified AlinOBP11 recombinant protein on the sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis displayed a single band (Figure S1).

## Ligand-Binding of Recombinant AlinOBP11

Before the ligand-binding analysis, we measured the binding affinities of fluorescence probe 1-NPN with purified AlinOBP11. The results showed AlinOBP11 could solidly bind to 1-NPN with binding affinity of 5.86 ± 0.47 µM (Figure 4A). Consequently, the binding properties of AlinOBP11 to compounds with different functional groups were analyzed and the results suggested it had a relatively narrow binding profile. Notably, all the tested non-volatile compounds showed strong binding

abilities to AlinOBP11, and quercetin was the best ligand ($K_i$ = 2.63 ± 0.23 µM), followed by gossypol ($K_i$ = 3.43 ± 0.32 µM), rutin hydrate ($K_i$ = 7.78 ± 1.23 µM), and (-)-catechin ($K_i$ = 15.26 ± 0.70 µM). Additionally, the tested host volatiles such as aliphatic alcohols, aldehydes, ketones, esters, aromatics could hardly bind to recombinant AlinOBP11, except of three terpenoids α-phellandrene, nerolidol, and *trans*, *trans*-farnesol, which can bind to AlinOBP11 and their binding constant $K_i$ was 20.07 ± 0.41, 20.76 ± 0.55, and 19.26 ± 1.78 µM, respectively (Figures 4B,C; Table 1).

## DISCUSSION

Insect OBPs may serve as important molecular target for designing and screening new effectively behavioral blocking agents used in the application of eco-friendly pest management strategies as they are considered to be strongly expressed in antennal sensillum lymph and are involved in olfactory cues discrimination, binding and transduction (Qiao et al., 2009; He et al., 2011; Sun Y. F. et al., 2012; Pelosi et al., 2013, 2014; Sun L. et al., 2013; Sun et al., 2014a). However, a plenty of studies suggested that OBPs' expression patterns are not restricted in olfactory organs and thus their physiological functions would be more complex and diversified (Park et al., 2000; Foret and Maleszka, 2006; Li et al., 2008; Sun Y. F. et al., 2012; Yuan et al., 2015). To confirm whether OBPs in the Hemiptera mirid bug species could fulfill putative gustatory function, in the present study we especially focus on a putative non-olfactory organ biased OBP gene, the *OBP11* in *A. lineolatus*.

Previously, Gu et al. identified 14 putative OBP genes from the antennal cDNA library of *A. lineolatus* and suggested *AlinOBP11* was strongly expressed at adult legs of both sexes (Gu et al., 2011a). Subsequently, a large number of potential OBP genes were identified in the tarnished plant bug, *L. lineolaris* and the green plant bug, *Apolygus lucorum* via transcriptome strategy, and more OBP transcripts were found to be expressed at gustatory organs such as legs and mouthparts (Hull et al., 2014; Yuan et al., 2015). Therefore, we firstly re-confirmed the tissue expression profiles of *AlinOBP11* after taking mouthparts into account, the most important gustatory organs of Hemiptera species. The results of our western blot analysis revealed that clear single bands could be seen at mouthparts, legs as well as antennae of both male and female adult bugs (Figure 2). Interestingly, we found that relative mRNA level of *AlinOBP11* was extraordinarily higher at adult mouthparts of both sexes than that of previous reported legs and other tissues (Figure 3). In addition, higher expression level was also observed in adult bugs than different instars of nymph (Figure 3). If we considered the tissue distribution patterns of all the 14 identified OBP genes, according to the inference that mRNA expression is indicative of physiological function of its encoded protein, a putative functional subdivision of different OBP genes in the same species of *A. lineolatus* would occur and the mouthparts-biased *AlinOBP11* could be separated from other OBPs such as *AlinOBP1*, *10*, *13* which have been demonstrated strongly
<figure><img src="image_142.png" /><figcaption>**FIGURE 3** | The relative transcript levels of *AlinOBP11* at different developmental stages and adult tissues of both sexes analyzed by qRT-PCR. All data were normalized to endogenous house-keeping genes *Alinβ-actin* (GenBank No. GQ477013) and relative fold changes are normalized to transcript level of the first instar nymph or abdomen. The error bars represents the standard errors, and the different letters a, b, c, and d indicate significant differences (p < 0.05) among different samples. The similar results were obtained with *AlinElongation factor* (GenBank No. AEY99651) as internal control (Figure S2).</figcaption></figure>

<figure><img src="image_143.png" /><figcaption>**FIGURE 4** | Fluorescence competitive binding assay. (A) Binding curve and relative Scatchard plot of 1-NPN to AlinOBP11. The dissociation constant of the AlinOBP11/1-NPN complex was calculated as 5.86 ± 0.47 µM. (B) Competitive binding curves of selected host plant compounds to AlinOBP11. (C) The reverse values of the dissociation constants (Ki) measured with putative ligands of AlinOBP11. A mixture of the recombinant AlinOBP11 protein and N-phenyl-1-naphthylamine (1-NPN) in 50 mM Tris-Hcl buffer (pH 7.4) both at the concentration of 2 µM was titrated with 1 mM solutions of each competing ligand to the final concentration range of 2 to 30 µM. Fluorescence intensities are reported as percent of the values in the absence of competitor. Data are represented as means of three independent experiments.</figcaption></figure>
<table><caption>TABLE 1 | Binding affinities of all of the selected compounds to the recombinant AlinOBP11 protein.</caption><thead><tr><th rowspan="2">Ligand</th><th rowspan="2">CAS Number</th><th colspan="2">AlinOBP11</th></tr><tr><th>IC<sub>50</sub> (µM)</th><th>K<sub>i</sub> (µM)</th></tr></thead><tbody><tr><td colspan="4"><strong>GENERAL ODORANTS</strong></td></tr><tr><td>2-Hexanol</td><td>626-93-7</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Pentanol</td><td>71-41-0</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Valeraldehyde</td><td>110-62-3</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Hexanal</td><td>66-25-1</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Heptanal</td><td>111-71-7</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Octanal</td><td>124-13-0</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Nonanal</td><td>124-19-6</td><td>u.d.</td><td>u.d.</td></tr><tr><td>2-Hexanone</td><td>591-78-6</td><td>u.d.</td><td>u.d.</td></tr><tr><td>2-Heptanone</td><td>110-43-0</td><td>u.d.</td><td>u.d.</td></tr><tr><td>2-Octanone</td><td>111-13-7</td><td>u.d.</td><td>u.d.</td></tr><tr><td>3-Hexanone</td><td>589-38-8</td><td>u.d.</td><td>u.d.</td></tr><tr><td>6-Methyl-5-hepten-2-one</td><td>110-93-0</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Amyl acetate</td><td>628-637-7</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Nonyl acetate</td><td>1143-13-5</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Undecane</td><td>1120-21-4</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Indole</td><td>120-72-9</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Benzaldehyde</td><td>100-52-7</td><td>u.d.</td><td>u.d.</td></tr><tr><td>3,4-Dimethyl-benzaldehyde</td><td>5973-71-7</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Acetophenone</td><td>98-86-2</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Methyl salicylate</td><td>119-36-8</td><td>u.d.</td><td>u.d.</td></tr><tr><td colspan="4"><strong>GREEN LEAF VOLATILES</strong></td></tr><tr><td>1-Hexanol</td><td>111-27-3</td><td>u.d.</td><td>u.d.</td></tr><tr><td>cis-3-Hexen-1-ol</td><td>928-96-1</td><td>u.d.</td><td>u.d.</td></tr><tr><td>trans-2-Hexenal</td><td>6278-26-3</td><td>u.d.</td><td>u.d.</td></tr><tr><td>cis-3-hexenyl acetate</td><td>3681-71-8</td><td>u.d.</td><td>u.d.</td></tr><tr><td colspan="4"><strong>TERPENOIDS</strong></td></tr><tr><td>E-β-Ocimene</td><td>3016-19-1</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Limonene</td><td>5989-27-5</td><td>u.d.</td><td>u.d.</td></tr><tr><td>α-Phellandrene</td><td>99-83-2</td><td>26.16 ± 0.52</td><td>20.07 ± 0.41</td></tr><tr><td>β-Pinene</td><td>18172-67-3</td><td>u.d.</td><td>u.d.</td></tr><tr><td>(+)-α-Pinene</td><td>7785-70-8</td><td>u.d.</td><td>u.d.</td></tr><tr><td>β-Ionone</td><td>79-77-6</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Myrcene</td><td>123-35-3</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Nerolidol</td><td>7212-44-4</td><td>27.23 ± 0.71</td><td>20.76 ± 0.55</td></tr><tr><td>β-Caryophyllene</td><td>87-44-5</td><td>u.d.</td><td>u.d.</td></tr><tr><td>α-Humulene</td><td>6753-98-6</td><td>u.d.</td><td>u.d.</td></tr><tr><td>trans-β-Farnesene</td><td>18794-84-8</td><td>u.d.</td><td>u.d.</td></tr><tr><td>trans,trans-Farnesol</td><td>106-28-5</td><td>25.21 ± 2.36</td><td>19.26 ± 1.78</td></tr><tr><td colspan="4"><strong>PUTATIVE SEX PHEROMONES</strong></td></tr><tr><td>Hexyl butyrate</td><td>2639-63-6</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Hexyl hexanoate</td><td>6378-65-0</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Butyl butyrate</td><td>109-21-7</td><td>u.d.</td><td>u.d.</td></tr><tr><td>Ethyl butyrate</td><td>105-54-4</td><td>u.d.</td><td>u.d.</td></tr><tr><td>trans-2-hexenyl butyrate</td><td>53398-83-7</td><td>u.d.</td><td>u.d.</td></tr><tr><td colspan="4"><strong>HOST PLANT SECONDARY METABOLITES</strong></td></tr><tr><td>(–)-Catechin</td><td>18829-704</td><td>19.26 ± 0.93</td><td>15.26 ± 0.70</td></tr><tr><td>Rutin hydrate</td><td>207671-50-9</td><td>9.89 ± 1.61</td><td>7.78 ± 1.23</td></tr><tr><td>Quercetin</td><td>117-39-5</td><td>3.36 ± 0.30</td><td>2.63 ± 0.23</td></tr><tr><td>Gossypol</td><td>303-45-7</td><td>4.45 ± 0.34</td><td>3.43 ± 0.32</td></tr></tbody></table>

U.d. means that the IC₅₀ value exceeds 30 µM and thus that the binding affinities (Kᵢ) of the candidate competitive ligand were not calculated in this study.

expressed at antennae sensillum and fulfilled vital roles in bug olfactory cue perception (Gu et al., 2011b; Sun L. et al., 2013; Sun et al., 2014a). Indeed, unlike the antennae which are equipped with various olfactory sensilla (Chinta et al., 1997; Sun et al., 2014b), mouthparts of Hemiptera bug species consist of piercing-sucking stylets and labium, the former is used to eject saliva for food ingestion and is considered to be directly related to oviposition behavior (Romani et al., 2005), while the latter has 11–12 uniporous gustatory sensilla which are responsible for assessing the suitability of food substrates (Ave et al., 1978; Hatfield and Frazier, 1980). Our current results of tissue expression pattern merely confirmed that *AlinOBP11* was preferentially expressed at *A. lineolatus* adult mouthparts. Although it is not known whether *AlinOBP11* was expressed in stylets or the gustatory sensillum of labium, we can conceivably speculate that this provocatively specific expression profile would benefit the alfalfa plant bugs, to a great extent, in many importantly behavioral performances such as egg laying, host plants selection, and even of toxic substances avoidance.

Our fluorescence competition assay provides further insight into understanding of physiological roles of AlinOBP11. The results clearly showed that recombinant AlinOBP11 protein displayed preferential binding abilities to tested non-volatile host plant secondary metabolites than all the volatile compounds (Figures 4B,C; Table 1). These results correspond well to its specific tissue distribution within mouthparts which could give a functional implication that AlinOBP11 could function as carrier in gustatory system for non-volatile compounds detection when plant bugs begin to search suitable food substrates by using the mouthparts to rub or tap on plant surfaces or insert plant tissues. Additionally, plant secondary compounds play key roles in the long-term evolution of plant-herbivore interactions (Elsayed, 2011; Mithöfer and Boland, 2012), and the content level variation of quercetin, gossypol, and rutin hydrate, three AlinOBP11 best ligands, over the course of host plant maturation have been demonstrated to be involved in herbivore defense. In particular, gossypol and rutin hydrate were proposed to increase the resistance of cotton plants in response to mirid bug feeding, while the content of quercetin in cotton tended to perform a negatively correlation between their interactions (Lin et al., 2011). Thus, *A. lineolatus* might employ the mouthparts-biased expressed AlinOBP11 to perceive and discriminate these functional different non-volatile secondary metabolites; however, this speculation still needs to be supported by more evidences.

Gene duplication was pointed to be the main mechanism underlying the fast expansion and functional evolution of chemosensory genes (Zhou et al., 2010; Zhang and Löfstedt, 2013); nevertheless, physiological functions of putative orthologs also attract great interest. In aphid species, the distribution of orthologous OBP genes may reflect their life styles and host relationships. As an example, homologous OBP3 proteins of different aphid species were proved to be associated with recognition of alarm pheromone (*E*)-β-farnesene (Qiao et al., 2009; Vandermoten et al., 2011; Sun Y. F. et al., 2012). We reconstructed the phylogenetic trees used reported OBPs of several bug species (Figure 1) and the results clearly suggest AlinOBP11 and AsutOBP11, AlucOBP36, AfasOBP11, and LylinOBP19 fall