Volatile Signals Research Articles

Targeting Insect Olfaction in vivo and in vitro Using Functional Imaging.

Insects decode volatile chemical signals from its surrounding environment with the help of its olfactory system, in a fast and reliable manner for its survival. In order to accomplish this task, odorant receptors (ORs) expressed in olfactory sensory neurons (OSNs) in the fly’s antenna process such odor information. In order to study such a sophisticated process, we require access to the sensory neurons to perform functional imaging. In this article, we present different preparations to monitor odor information processing in Drosophila melanogaster OSNs using functional imaging of their Ca2+ dynamics. First, we established an in vivo preparation to image specific OSN population expressing the fluorescent Ca2+ reporter GCaMP3 during OR activation with airborne odors. Next, we developed a method to extract and to embed OSNs in a silica hydrogel with OR activation by dissolved odors. The odor response dynamics under these different conditions was qualitatively similar which indicates that the reduction of complexity did not affect the concentration dependence of odor responses at OSN level.

Generalist herbivore response to volatile chemical induction varies along a gradient in soil salinization

Elevated soil salinity directly modifies plant physiology and indirectly alters the biotic interactions that shape plant performance. However, it is unclear how soil salinization interacts with plant defenses to alter patterns of leaf consumption or herbivore survival, development, and performance. In this study, we carried out laboratory feeding trials and a common garden experiment to investigate how gradients in soil salinization interact with plant induction status (modified via exogenous application of methyl jasmonate [MeJA]) to influence feeding consumption and performance of the generalist herbivore Spodoptera exigua on tomato (Solanum lycoperscium) plants. Our results showed that S. exigua consumed less leaf tissue from tomatoes treated with ≥ 50 mM NaCl; at these higher salinity treatments, these herbivores were less likely to pupate and died more quickly. Treatment with MeJA only reduced leaf consumption in the 0 mM NaCl treatment. Our common garden study demonstrated that natural populations of leaf chewing herbivores were less likely to damage tomatoes treated with > 50 mM NaCl solutions. Treatment with MeJA in the common garden reduced damage from natural populations of herbivores, but only for salt treatments at the 50 mM NaCl concentration level and we did observe variation in herbivore damage between cohorts in common garden trials. These results suggest that both soil salinization and volatile jasmonate signals may generate complementary shifts in decreased plant quality for herbivores. Overall, our study concludes that soil salinization could be a potential driver in spatial patterns of variation in both herbivory and herbivore demography.

Strategic pheromone signalling by mate searching females of the sexually cannibalistic spider Argiope bruennichi.

Reproduction often requires finding a mating partner. To this end, females of many arthropods advertise their presence to searching males via volatile chemical signals. Such pheromones are considered low-cost signals, although this notion is based on little evidence and has recently been challenged. Even when using comparatively low-cost signals, females should signal as little as possible to minimize costs while still ensuring mate attraction. Here, we test the strategic-signalling hypothesis using Argiope bruennichi. In this orb-weaving spider, egg maturation commences with adult moult, and females that do not attract a male in time will lay a large batch of unfertilized eggs approximately three weeks after maturation. Using GC-MS analyses, we show that virgin females enhance their signalling effort, i.e. pheromone quantity per unit body mass, with increasing age and approaching oviposition. We further demonstrate that pheromone release is condition dependent, suggesting the occurrence of physiological costs. Mate choice assays revealed that pheromone quantity is the only predictor of female attractiveness for males. In support of the strategic-signalling hypothesis, pheromone signals by female A. bruennichi become stronger with increased need as well as body condition, and might thus qualify as an honest signal of female quality.

Turning a bacterial gaseous virulence trigger off.

Recently, Sieber et al. discovered the new diazeniumdiolate volatile signaling molecule, leudiazen. They confirmed that inactivation of leudiazen by KMnO4 can reduce the production of mangotoxin. This alleviates the pathogenicity of Pseudomonas syringae pv. syringae on mango trees, providing a new strategy for plant protection, compatible with organic farming.

Deep Learning Based Compressive Sensing for UWB Signal Reconstruction

Compressive sensing(CS) can greatly reduce the number of sampling points of signals, and therefore it is widely adopted in ultra-wideband(UWB) sensor systems. However, how to reconstruct the sensing signal from the compressed signal accurately is still an open problem because original signals do not always satisfy the sparse hypothesis that is required in CS. Typically, an appropriate CS reconstruction algorithm should be designed for a particular scenario, such as signal encoding, optical imaging and soil dynamic monitoring, etc. Unfortunately, soil data is susceptible to climatic factors, which leads to unsatisfactory performance of traditional reconstruction algorithms. To improve the accuracy of CS reconstruction for volatile signals as UWB soil echoes, we propose a novel deep learning based CS algorithm, named SFDLCS (select-first-decide-later compressive sensing) for UWB sensor signal reconstruction. In this algorithm, a search network is designed to perform the non-linear mapping from compressed residuals to non-zero elements in sensor signal, and a decision network is designed to characterize the distribution of UWB signals. These two networks form a ”select first, decide later” structure, which greatly improves the accuracy of signal reconstruction by utilizing the correlation of non-zero elements of the sensor signal. The effectiveness of this SFDLCS is demonstrated based on measured UWB soil data acquired by a P440 UWB sensor. Compared with traditional reconstruction algorithms, the proposed algorithm achieves both lower reconstruction error and stronger robustness in the noisy environment.

Structural and Functional Characterization of European Corn Borer, Ostrinia nubilalis, Pheromone Binding Protein 3.

Ostrinia nubilalis, a lepidopteran moth, also known as the European corn borer, has a major impact on the production of economically important crops in the United States and Europe. The female moth invites the male moth for mating through the release of pheromones, a volatile chemical signal. Pheromone binding proteins (PBPs) present in the male moth antennae are believed to pick up the pheromones, transport them across the aqueous sensillum lymph, and deliver them to the olfactory receptor neurons. Here we report for the first time the cloning, expression, refolding, purification, and structural characterization of Ostrinia nubilalis PBP3 (OnubPBP3). The recombinant protein showed nanomolar affinity to each isomer of the Ostrinia pheromones, E- and Z-11-tetradecenyl acetate. In a pH titration study by nuclear magnetic resonance, the protein exhibited an acid-induced unfolding at pH below 5.5. The molecular dynamics simulation study demonstrated ligand-induced conformational changes in the protein with both E- and Z-isomers of the Ostrinia pheromone. The simulation studies showed that while protein flexibility decreases upon binding to E-pheromone, it increases when bound to Z-pheromone. This finding suggests that the OnubPBP3 complex with E-pheromone is more stable than with Z-pheromone.

Robustness of collective scenting in the presence of physical obstacles

Honey bees (Apis mellifera L.) aggregate around the queen by collectively organizing a communication network to propagate volatile pheromone signals. Our previous study shows that individual bees “scent” to emit pheromones and fan their wings to direct the signal flow, creating an efficient search and aggregation process. In this work, we introduce environmental stressors in the form of physical obstacles that partially block pheromone signals and prevent a wide open path to the queen. We employ machine learning methods to extract data from the experimental recordings, and show that in the presence of an obstacle that blocks most of the path to the queen, the bees need more time but can still effectively employ the collective scenting strategy to overcome the obstacle and aggregate around the queen. Further, we increase the complexity of the environment by presenting the bees with a maze to navigate to the queen. The bees require more time and exploration to form a more populated communication network. Overall, we show that given volatile pheromone signals and only local communication, the bees can collectively solve the swarming process in a complex unstructured environment with physical obstacles and hit a limit when the obstacle is a much more complex maze.

Eight-carbon volatiles: prominent fungal and plant interaction compounds.

Signaling via volatile organic compounds (VOCs) has historically been studied mostly by entomologists; however, botanists and mycologists are increasingly aware of the physiological potential of chemical communication in the gas phase. Most research to date focuses on the observed effects of VOCs on different organisms such as differential growth or metabolite production. However, with the increased interest in volatile signaling, more researchers are investigating the molecular mechanisms for these effects. Eight-carbon VOCs are among the most prevalent and best-studied fungal volatiles. Therefore, this review emphasizes examples of eight-carbon VOCs affecting plants and fungi. These compounds display different effects that include growth suppression in both plants and fungi, induction of defensive behaviors such as accumulation of mycotoxins, phytohormone signaling cascades, and the inhibition of spore and seed germination. Application of '-omics' and other next-generation sequencing techniques is poised to decipher the mechanistic basis of volatiles in plant-fungal communication.

Elicitation of biomolecules as host defense arsenals during insect attacks on tea plants (Camellia sinensis (L.) Kuntze).

The most consumed and economically important beverage plant, tea (Camellia sinensis), and its pests have coevolved so as to maintain the plant-insect interaction. In this review, findings of different research groups on pest responsive tolerance mechanisms that exist in tea manifested through the production of secondary metabolites and their inducers are presented. The phytochemicals of C. sinensis have been categorized into volatiles, nonvolatiles, enzymes, and phytohormones for convenience. Two types of pests, namely the piercing-sucking pests and chewing pests, are associated with tea. Both the insect groups can trigger the production of those metabolites and inducers through several primary and secondary biosynthetic pathways. These induced biomolecules can act as insect repellents and most of them are associated with lowering the nutrient quality of plant tissue and increasing the indigestibility in the pest's gut. Moreover, some of them also act as predator attractants of particular pests. The herbivore-induced plant volatiles secreted from tea plants during pest infestation were (E)-nerolidol, α-farnesene, (Z)-3-hexenol, (E)-4,8-dimethyl-1,3,7-nonatriene, indole, benzyl nitrile (BN), linalool, and ocimenes. The nonvolatiles like theaflavin and L-theanine were increased in response to the herbivore attack. Simultaneously, S-adenosyl-L-methionine synthase, caffeine synthase activities were affected, whereas flavonoid synthesis and wax formation were elevated. Defense responsive enzymes like peroxidase, polyphenol oxidase, phenylalanine ammonia-lyase, ascorbate peroxidase, and catalase are involved in pest prevention mechanisms. Phytohormones like jasmonic acid, salicylic acid, abscisic acid, and ethylene act as the modulator of the defense system. The objective of this review is to discuss the defensive roles of these metabolites and their inducers against pest infestation in tea with an aim to develop environmentally sustainable pesticides in the future.Key points• Herbivore-induced volatile signals and their effects on neighboring tea plant protection• Stereochemical conversion of volatiles, effects of nonvolatiles, expression of defense-responsive enzymes, and phytohormones due to pest attack• Improved understanding of metabolites for bio-sustainable pesticide development.

Mitigation of Pseudomonas syringae virulence by signal inactivation.

Pseudomonas syringae is an important plant pathogen of many valuable crops worldwide, with more than 60 identified pathovars. The phytotoxins produced by these organisms were related to the severity of the damage caused to the plant. An emerging strategy to treat bacterial infections relies on interference with their signaling systems. In this study, we investigated P. syringae pv. syringae, which produces the virulence factor mangotoxin that causes bacterial apical necrosis on mango leaves. A previously unknown signaling molecule named leudiazen was identified, determined to be unstable and volatile, and responsible for mangotoxin production. A strategy using potassium permanganate, compatible with organic farming, was developed to degrade leudiazen and thus to attenuate the pathogenicity of P. syringae pv. syringae.

Volatile chemical signals underlying the host plant preferences of Tuta absoluta

AbstractThe South American leaf miner, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae), is a serious pest of tomato causing substantial annual economic losses at a global scale. Our study comprised choice and no‐choice bioassays, aimed at understanding the preference of this oligophagous pest for a few selected solanaceous hosts (tomato, potato, eggplant, ashwagandha, black nightshade, wild tomato, tobacco, and datura), and the identification of the volatile cues that influence its host selection process. In choice assays, T. absoluta females preferred tomato for oviposition over all the other plants, whereas ashwagandha, tobacco, and datura were the least preferred; on datura zero eggs were laid. A similar trend was observed in the subsequent number of larval mines formed. The moth’s preference for host plants of the genus Solanum was quite evident in both the choice and no‐choice assays. Tomato plant volatiles were found to be more attractive to the female moths in single‐ and dual‐choice olfactometer assays. In electroantennographic bioassays, the mean depolarization was significant for tomato, potato, ashwagandha, and eggplant compared to empty air and honey. In total 76 volatile compounds were identified in the GC‐MS analysis across the eight previously selected host–plant headspace samples. Principal component analysis revealed that 1‐fluorododecane and p‐quinone mainly contributed to the observed variation among the host plant volatiles. Of all the host plants, tomato, wild tomato, and tobacco were found to share similarities with respect to volatile cues, whereas ashwagandha, eggplant, and datura were found to be closely related. The other two hosts, potato and black nightshade, had fewer volatiles in common. Volatile cues, namely p‐quinone, 2‐carene, δ‐curcumene, and 1,2‐diethylbenzene, in tomato could serve as oviposition stimulants to T. absoluta, whereas the presence of 1‐fluorododecane in host plants such as datura, eggplant, ashwagandha, and black nightshade, might have deterred T. absoluta from ovipositing. 1‐Fluorododecane was found to be completely absent in tomato.

Direction‐of‐arrival estimation using estimator banks in low‐angle tracking for S‐band radar

AbstractTracking low‐angle targets over an uneven surface are challenging because of the highly correlated, complicated, and volatile multipath signals encountered in radar. Especially, in the context of irregular reflector modulated by rough sea, which results in performance depravation of the existing direction‐of‐arrival (DOA) estimation methods. An effective DOA estimation approach is based on maximum likelihood (ML) estimator which is referred to as optimal synthetic vector maximum likelihood (OSVML) method. The approach is essentially different, multipath signals are present that without known prior information of ideal model. The optimal projection space in estimator banks is spanned with direct subspace and indirect subspace to match the signals received by S‐band radar. Then, the performance of the proposed method is evaluated by simulations in terms of the signal‐to‐noise ratio (SNR) and snapshot. Finally, field data sets acquired from S‐band radar are carried out to verify the practicability of the proposed method in a naval environment.

Is Establishing a New Partnership Useful Information for Investors in the Smartphone Supply Market?

This study analyzed partner volatility (new, old, revocation partners) and country-specific signal effects (United States (US), Taiwan, Japan, and South Korea) for Apple iPhone parts suppliers from 2007 to 2018. Mid- to long-term stock price movements were also analyzed to define trading patterns by investor type. The results using logit regression analysis revealed that new partners and revocation partners each have a signaling effect perceived as positive and negative information in the short term, and the excess returns by country showed a positive signaling effect in the order of the US, Taiwan, South Korea, and Japan. The findings also suggest that the change in the new partners’ stock price after the preannouncement of new products was useful investment information. Moreover, information asymmetry was found between individual investors, institutions, and foreigners. Results indicate that new partner selection in the smartphone market impacts corporate value and serves as useful investment information.

Indole-3-glycerolphosphate synthase, a branchpoint for the biosynthesis of tryptophan, indole, and benzoxazinoids in maize.

The maize (Zea mays) genome encodes three indole-3-glycerolphosphate synthase enzymes (IGPS1, 2, and 3) catalyzing the conversion of 1-(2-carboxyphenylamino)-l-deoxyribulose-5-phosphate to indole-3-glycerolphosphate. Three further maize enzymes (BX1, benzoxazinoneless 1; TSA, tryptophan synthase alpha subunit; and IGL, indole glycerolphosphate lyase) convert indole-3-glycerolphosphate to indole, which is released as a volatile defense signaling compound and also serves as a precursor for the biosynthesis of tryptophan and defense-related benzoxazinoids. Phylogenetic analyses showed that IGPS2 is similar to enzymes found in both monocots and dicots, whereas maize IGPS1 and IGPS3 are in monocot-specific clades. Fusions of yellow fluorescent protein with maize IGPS enzymes and indole-3-glycerolphosphate lyases were all localized in chloroplasts. In bimolecular fluorescence complementation assays, IGPS1 interacted strongly with BX1 and IGL, IGPS2 interacted primarily with TSA, and IGPS3 interacted equally with all three indole-3-glycerolphosphate lyases. Whereas IGPS1 and IGPS3 expression was induced by insect feeding, IGPS2 expression was not. Transposon insertions in IGPS1 and IGPS3 reduced the abundance of both benzoxazinoids and free indole. Spodoptera exigua (beet armyworm) larvae show improved growth on igps1 mutant maize plants. Together, these results suggest that IGPS1 and IGPS3 function mainly in the biosynthesis of defensive metabolites, whereas IGPS2 may be involved in the biosynthesis of tryptophan. This metabolic channeling is similar to, though less exclusive than, that proposed for the three maize indole-3-glycerolphosphate lyases.

Symbiotic bacteria mediate volatile chemical signal synthesis in a large solitary mammal species

Mammalian chemosignals—or scent marks—are characterized by astounding chemical diversity, reflecting both complex biochemical pathways that produce them and rich information exchange with conspecifics. The microbiome of scent glands was thought to play prominent role in the chemical signal synthesis, with diverse microbiota metabolizing glandular products to produce odorants that may be used as chemosignals. Here, we use gas chromatography–mass spectrometry and metagenomic shotgun sequencing to explore this phenomenon in the anogenital gland secretions (AGS) of the giant panda (Ailuropoda melanoleuca). We find that this gland contains a diverse community of fermentative bacteria with enzymes that support metabolic pathways (e.g., lipid degradation) for the productions of volatile odorants specialized for chemical communication. We found quantitative and qualitative differences in the microbiota between AGS and digestive tract, a finding which was mirrored by differences among chemical compounds that could be used for olfactory communication. Volatile chemical compounds were more diverse and abundant in AGS than fecal samples, and our evidence suggests that metabolic pathways have been specialized for the synthesis of chemosignals for communication. The panda’s microbiome is rich with genes coding for enzymes that participate in the fermentation pathways producing chemical compounds commonly deployed in mammalian chemosignals. These findings illuminate the poorly understood phenomena involved in the role of symbiotic bacteria in the production of chemosignals.

Volatility spillovers between WTI and Brent spot crude oil prices: an analysis of granger causality in variance patterns over time

There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.

Deep-Reinforcement-Learning-Based Capacity Scheduling for PV-Battery Storage System

Investor-owned photovoltaic-battery storage systems (PV-BSS) can gain revenue by providing stacked services, including PV charging and frequency regulation, and by performing energy arbitrage. Capacity scheduling (CS) is a crucial component of PV-BSS energy management, aiming to ensure the secure and economic operation of the PV-BSS. This article proposes a Proximal Policy Optimization (PPO)-based deep reinforcement learning (DRL) agent to perform the CS of PV-BSS. Unlike previous work that uses value-based methods with the discrete action space, PPO can readily handle continuous action space and determine the specific amount of charging/discharging. To enforce the safety constraints of BSS’s energy and power capacity, a safety control algorithm using a serial strategy is proposed to cooperate with the PPO agent. The PPO agent can exploit the capacity of BSS safely while maximizing the accumulated net revenue. After training, the PPO agent can adapt to the highly uncertain and volatile market signals and PV generation profiles. The efficacy of the proposed CS scheme is substantiated by using real market data. The comparative results demonstrate that the PPO agent outperforms the Deep Deterministic Policy Gradient agent, Advantage Actor-Critic agent, and Double Deep Q Network agent in terms of profitability and sample efficiency.

Deployment of Aggregation-Sex Pheromones of Longhorned Beetles (Coleoptera: Cerambycidae) Facilitates the Discovery and Identification of their Parasitoids.

Longhorned beetles (Coleoptera: Cerambycidae) include many species that are among the most damaging pests of managed and natural forest ecosystems worldwide. Many species of cerambycids use volatile chemical signals (i.e., pheromones) to locate mates. Pheromones are often used by natural enemies, including parasitoids, to locate hosts and therefore can be useful tools for identifying host-parasitoid relationships. In two field experiments, we baited linear transects of sticky traps with pheromones of cerambycid beetles in the subfamily Cerambycinae. Enantiomeric mixtures of four linear alkanes or four linear alkanes and a ketol were tested separately to evaluate their attractiveness to hymenopteran parasitoids. We hypothesized that parasitoids would be attracted to these pheromones. Significant treatment effects were found for 10 species of parasitoids. Notably, Wroughtonia ligator (Say) (Hymenoptera: Braconidae) was attracted to syn-hexanediols, the pheromone constituents of its host, Neoclytus acuminatus acuminatus (F.) (Coleoptera: Cerambycidae). Location and time of sampling also significantly affected responses for multiple species of parasitoids. These findings contribute to the basic understanding of cues that parasitoids use to locate hosts and suggest that pheromones can be used to hypothesize host relationships between some species of cerambycids and their parasitoids. Future work should evaluate response by known species of parasitoids to the complete blends of pheromones used by the cerambycids they attack, as well as other odors that are associated with host trees of cerambycids.

Virus-Infected Melon Plants Emit Volatiles that Induce Gene Deregulation in Neighboring Healthy Plants.

It is well described that viral infections stimulate the emission of plant volatiles able to recruit viral vectors thereby promoting virus spread. In contrast, much less is known on the effects that emitted volatiles may have on the metabolism of healthy neighboring plants, which are potential targets for new infections through vector transmission. Watermelon mosaic virus (WMV) (genus Potyvirus, family Potyviridae) is an aphid-transmitted virus endemic in cucurbit crops worldwide. We have compared gene expression profiles of WMV-infected melon plants with those of healthy or healthy-but-cohabited-with-infected plants. Pathogenesis-related (PR) and small heat shock protein encoding genes were deregulated in cohabited plants, and PR deregulation depended on the distance to the infected plant. The signaling was short distance in the experimental conditions used, and cohabiting had a moderate effect on the plant susceptibility to WMV. Static headspace experiments showed that benzaldehyde and γ-butyrolactone were significantly over-emitted by WMV-infected plants. Altogether, our data suggest that perception of a volatile signal encoded by WMV-infected tissues triggers a response to prepare healthy tissues or/and healthy neighboring plants for the incoming infections.

The potential of volatile organic compound analysis in cervicovaginal mucus to predict estrus and ovulation in estrus-synchronized heifers

Cervicovaginal mucus is a mixture of mucins, ions, salts, and water, the proportions of which change during the reproductive cycle. It is suspected that this mucus emits an important volatile signal indicative of the reproductive state of the female. The objective of this study was to identify volatile organic compounds (VOC) in bovine cervicovaginal mucus that are modulated during the estrous cycle and could potentially be used as biomarkers of estrus and ovulation. Cervicovaginal mucus was collected from crossbred beef heifers (n = 8), which were synchronized using an 8-d controlled internal drug release (CIDR) protocol and in which onset of estrus and time of ovulation were determined by visual observation and ultrasonography, respectively. Mucus samples were collected between 0 and 96 h after CIDR removal (estrus onset occurred at 49.1 ± 3.3 h after CIDR removal). A validation study was performed on an independent group of 15 heifers from which cervicovaginal mucus samples were collected every 8 h from 40 to 80 h after CIDR removal. The VOC in mucus were identified using gas chromatography-mass spectrometry and selected compounds were quantified using selected-ion flow-tube mass spectrometry. The presence of 47 VOC was detected in mucus samples by gas chromatography-mass spectrometry with those exhibiting highest abundance including 2-butanone, acetone, 2-pentanone, 4-methyl-2-pentanone, 1-(1-methylethoxy)-2-propanone, ethanol, 2-methyl-2-propanol, and 2-butanol. All VOC peaked between 24 to 47 h after the onset of estrus (ovulation occurred 26.6 ± 5.6 h after estrus onset). Two VOC, 2-pentanone and 4-methyl-2-pentanone, exhibited a significant increase at the onset of estrus, whereas concentration of 2-butanone increased significantly just after estrus onset, indicating that these VOC may be used as putative biomarkers of estrus. The results of our study may contribute to the development of a sensor device based on VOC to aid the detection of estrus and ovulation in cattle, with particular relevance for the dairy industry where the majority of females are bred by artificial insemination.