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34 results for “chemotypes”
Data from: Geographic distribution of terpenoid chemotypes in Tanacetum vulgare mediates tansy aphid occurrence but not abundance
<p>Intraspecific variation of specialized metabolites in plants, such as terpenoids, are used to determine chemotypes. Tansy (<em>Tanacetum vulgare</em> L.) exhibits diverse terpenoid profiles that affect insect communities. However, it is not fully known whether patterns of their chemical composition and associated insects vary beyond the community scale. Here, we investigated the geographic distribution of mono- and sesquiterpenoid chemotypes in tansy leaves and their relationships with specific insect communities across Germany. We sampled tansy leaves from ten plants with and five plants without aphids in each of 26 sites along a north-south and west-east transect in Germany. Hexane-extracted metabolites from leaf tissues were analyzed by gas chromatography-mass spectrometry (GC-MS). Plant morphological traits, aphid occurrence and abundance, and occurrence of ants were recorded locally. The effect of plant chemotype, plant morphological parameters, and abiotic site parameters such as soil types, temperature and precipitation on insect occurrences were analyzed. Plants clustered into four monoterpenoid and four sesquiterpenoid chemotype classes. Monoterpene classes differed in their latitudinal distribution, whereas sesquiterpenes were more evenly distributed across the transect. Aphid and ant occurrence was influenced by monoterpenoids. Plants of monoterpenoid class 1 were colonized by aphids and ants significantly more often than expected by chance, whereas in other classes there were no significant differences. Aphid abundance was affected by soil type, and average annual temperature positively correlated with the occurrence of ants. We found significant geographic patterns in the distribution of tansy chemodiversity and show that monoterpenoids affect aphid and ant occurrence, while the soil type can influence aphid abundance. We show that geographic variation in plant chemistry influences insect community assembly on tansy plants.</p>
Fig. 3 in Response of two chemotypes of Melaleuca quinquenervia (Myrtales: Myrtaceae) saplings to colonization by specialist herbivores
Fig. 3. Total mean (± SE) leaf biomass shed via abscission by Melaleuca quinquenervia saplings subjected to unrestricted or restricted herbivory by Oxyops vitiosa and Boreioglycaspis melaleucae. **: P = 0.01.
Fig. 1 in Response of two chemotypes of Melaleuca quinquenervia (Myrtales: Myrtaceae) saplings to colonization by specialist herbivores
Fig. 1. Mean (± SE) dry weight biomass of leaves shed via abscission by saplings of 2 Melaleuca quinquenervia chemotypes subjected to 2 levels of herbivory by Oxyops vitiosa and Boreioglycaspis melaleucae.
FIGURE 5 in Linalool chemotype essential oil from Lippia alba in the anesthesia of fat snook (Centropomus parallelus): ventilatory rate, biochemical, antioxidant, and oxidative status parameters
FIGURE 5 | Antioxidant and oxidative stress parameters in the liver after transferring to recovery aquariums of fat snook (Centropomus parallelus) anesthetized with the essential oil from Lippia alba (EOLA). A = GST (glutathione S-transferase). B = SOD (superoxide dismutase). C = CAT (catalase). D = LPO (lipid peroxidation). Data are presented as the mean ± SEM (n = 5 fish per treatment each time). Capital letters indicate significant differences between time points within the same treatment. Lowercase letters indicate significant differences between treatments at the same time point. Two-way ANOVA and Tukey's tests were used to determine statistical significance (P <0.05).
FIGURE 1 in Linalool chemotype essential oil from Lippia alba in the anesthesia of fat snook (Centropomus parallelus): ventilatory rate, biochemical, antioxidant, and oxidative status parameters
FIGURE 1 | Time (s) required for mild and deep anesthesia and recovery in fat snook angelfish (Centropomus parallelus) with increasingly essential oil from Lippia alba (EOLA) concentrations. Data are presented as the mean ± SEM (n = 10 fish per treatment). Different letters indicate significant differences between treatments. One-way ANOVA and Tukey's tests were used to determine statistical significance (P <0.05). Mild and deep anesthesia times showed regression.
FIGURE 4 in Linalool chemotype essential oil from Lippia alba in the anesthesia of fat snook (Centropomus parallelus): ventilatory rate, biochemical, antioxidant, and oxidative status parameters
FIGURE 4 | Blood glucose (A) and whole-body cortisol (B) levels after transferring to recovery aquariums of anesthetized fat snook (Centropomus parallelus) with essential oil from Lippia alba (EOLA). Data are presented as the mean ± SEM (n = 5 fish per treatment each time). Capital letters indicate significant differences between time points within the same treatment. Lowercase letters indicate significant differences between treatments at the same time point. Two-way ANOVA and Tukey's tests were used to determine statistical significance (P <0.05).
FIGURE 2 in Linalool chemotype essential oil from Lippia alba in the anesthesia of fat snook (Centropomus parallelus): ventilatory rate, biochemical, antioxidant, and oxidative status parameters
FIGURE 2 | Time (s) required for mild and deep anesthesia and recovery in fat snook (Centropomus parallelus) exposed to essential oil from Lippia alba (180 µL L−1). Smaller fish = 6.03 ± 0.09 g; 9.30 ± 0.05 cm. Larger fish = 38.49 ± 2.07 g; 16.55 ± 0.26 cm. Data are presented as the mean ± SEM (n = 10 fish per treatment). Different letters indicate significant differences between fish body size classes. One-way ANOVA and Tukey's tests were used to determine statistical significance (P <0.05).
FIGURE 3 in Linalool chemotype essential oil from Lippia alba in the anesthesia of fat snook (Centropomus parallelus): ventilatory rate, biochemical, antioxidant, and oxidative status parameters
FIGURE 3 | Ventilatory rate (VR) of fat snook (Centropomus parallelus) during exposure to the essential oil from Lippia alba (EOLA). Data are presented as the mean ± SEM (n = 8 fish per treatment). Capital letters indicate significant differences between time points within the same treatment. Lowercase letters indicate significant differences between treatments at the same time point. Two-way ANOVA and Tukey's tests were used to determine statistical significance (P <0.05).
Data from: Geographic distribution of terpenoid chemotypes in Tanacetum vulgare mediates tansy aphid occurrence but not abundance
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Data from: Chemodiversity affects preference for Tanacetum vulgare chemotypes in two aphid species
<p>Plants of the same species can strongly differ in their specialized metabolite profiles, which can affect insect presence and abundance in the field. However, how specialized chemistry shapes plant attractiveness to herbivorous insects is not fully understood. Here, we used common tansy (<em>Tanacetum vulgare</em> L., Asteraceae) – a perennial plant that is highly diverse in terpenoid composition and is known to have variable chemotypes – to test whether 1) plants with different chemotype profiles differ in attractiveness to two specialist aphid species, <em>Macrosiphoniella tanacetaria</em> and <em>Uroleucon tanaceti</em>, in pairwise choice assays; 2) the diversity of the terpenoid blend affects plant attractiveness to aphids; 3) how plant chemical traits relate to plant morphological traits and which traits best explain aphid preference. We found that <em>M. tanacetaria</em> preferred two out of five chemotypes, dominated by α-thujone/β-thujone and β-trans-chrysanthenyl acetate, while avoiding a chemotype dominated by α-pinene/sabinene. <em>Uroleucon tanaceti</em> showed no clear preference towards chemotypes, but when given a choice between chemotypes dominated by α-thujone/β-thujone and by α-pinene/sabinene, they preferred the former. Importantly, plant attractiveness to aphids was marginally negatively correlated with chemodiversity, i.e., the number of terpenoid compounds, in <em>M. tanacetaria</em>, but not in <em>U. tanaceti</em>. Interestingly, the relative concentration and number of terpenoids were generally higher in larger and bushier plants. Hence, we did not observe a tradeoff between plant growth and defence. We conclude that plant chemical composition affects plant attractiveness to aphids and hence may contribute to variation in natural aphid colonization patterns on plants of the same species.</p>
Data from: Chemodiversity affects preference for Tanacetum vulgare chemotypes in two aphid species
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Modeling cannabinoids from a large-scale sample of Cannabis sativa chemotypes
<p>The widespread legalization of <i>Cannabis</i> has opened the industry to using contemporary analytical techniques for chemotype analysis. Chemotypic data has been collected on a large variety of oil profiles inherent to the cultivars that are commercially available. The unknown gene regulation and pharmacokinetics of dozens of cannabinoids offer opportunities of high interest in pharmacology research. Retailers in many medical and recreational jurisdictions are typically required to report chemical concentrations of at least some cannabinoids. Commercial cannabis laboratories have collected large chemotype datasets of diverse <i>Cannabis</i> cultivars. In this work a data set of 17,600 cultivars tested by Steep Hill Inc., is examined using machine learning techniques to interpolate missing chemotype observations and cluster cultivars into groups based on chemotype similarity. The results indicate cultivars cluster based on their chemotypes, and that some imputation methods work better than others at grouping these cultivars based on chemotypic identity. Due to the missing data and to the low signal to noise ratio for some less common cannabinoids, their behavior could not be accurately predicted. These findings have implications for characterizing complex interactions in cannabinoid biosynthesis and improving phenotypical classification of <i>Cannabis</i> cultivars.</p>
Data from: Additive effects of plant chemotype, mutualistic ants and predators on aphid performance and survival
1. Cascading effects in ecological systems acting across three or more trophic levels can be either of a resource-based (bottom-up) or natural enemy-based (top-down) nature. But, due to their complexity these effects are often considered separately and their relative strength, acting simultaneously, remains unknown. 2. In a semi-natural field experiment using tansy (Tanacetum vulgare L.) and the specialised tansy aphid Metopeurum fuscoviride Stroyan as a model system, we compared the effects of four distinct plant chemotypes (i.e. bottom-up), defined by the bouquet of their volatile terpenoids, on aphid population dynamics by manipulating the presence/absence of mutualistic ants and presence/absence of naturally-occurring predators (i.e. top-down). 3. Predators reduced aphid abundance and colony survival but did not reduce initial growth rate due to a time lag until predators arrived on the plants. Ants directly benefited initial aphid growth rates and abundance, even in the absence of predators, but not the number of days an aphid colony persisted on the plant. 4. Plant chemotype directly affected aphid growth rate and final abundances across the different plants and indirectly affected the abundances of tending ants and predators through effects on aphids. We found that tending ants were more abundant on one plant chemotype. Although ant abundance did not affect aphid population development, it became clear that ants had a preference towards aphids on certain chemotypes. However, a higher number of predators led to a lower number of aphids. 5. The results confirm the importance of plant chemical variation, acting through multiple effects on many species in arthropod communities, and support results from field studies. In a natural population, with a diverse selection of host-plant variants, aphid populations and their interacting species can therefore be structured at the level of an individual plant. Specialist aphids on patchily-distributed host plants can exhibit metacommunity dynamics at very local scales. Plant within-species variation within a local population is often ignored in metacommunity ecology, yet our work shows that this can have strong effects on insect-ant-natural enemy dynamics and therefore future research should incorporate this into current theory and experimental studies.
Raw data and metadata associated with the manuscript: "Organ and ontogeny-specific steroidal glycoside diversity is associated with differential expression of steroidal glycoside pathway genes in two Solanum dulcamara leaf chemotypes"
<p>Raw LC-MS and RT-qPCR data and metadata associated with the manuscript: "Ontogeny and organ-specific steroidal glycoside diversity is associated with differential expression of steroidal glycoside pathway genes in two <em>Solanum dulcamara</em> leaf chemotypes", accepted at Plant Biology.</p>
Fig. 4 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 4. Monoterpene composition of the two proposed cotton chemotypes. (a) Scatterplot of the relative abundance of the pinene group (α-Pinene + β-Pinene) against the relative abundance of the summed values of the γ-Terpinene group. (b) Representative chromatograms of plants belonging to chemotype classes A (upper panel) and B (lower panel). 1: (E)-2-Hexenal; 2: 2,4-Hexadienal (E,E); 3: α-Thujene; 4: α-Pinene; 5: Camphene; 6: Sabinene; 7: β-Pinene; 8: β-Myrcene; 9: α-Phellandrene; 10: α-Terpinene; 11: p-Cymene; 12: Limonene; 13: β-Phellandrene; 14: β-Ocimene; 15: γ-Terpinene; 16: Terpinolene; 17: Bornyl acetate; 18: γ-Elemene; 19: β-Caryophyllene; 20: α-Humulene; 21: Bicyclogermacrene. (c) visualisation of proportion of monoterpene compounds from panel (b), for each chemotype class.
Fig. 1 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 1. Map showing locations of the wild Gossypium hirsutum populations from which seeds were collected along the Yucatan Peninsula.
Fig. 3 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 3. Theorised monoterpenoid biosynthesis pathway. Compounds highlighted in blue comprise the γ-terpinene compound group, those highlighted in grey comprise the α-pinene compound group. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 5. Principal coordinate analysis on relative abundance of monoterpenes in plants grown from seed, showing samples separated based on their compositional similarity.
Fig. 6 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 6. Ridgeline plot showing the distribution of the summed values of the γ-terpinene compound group (γ-terpinene, limonene, α-thujene, α-terpinene, terpinolene, and p-cymene; as % relative to total monoterpenes in each plant). In order from top to bottom: the plots coloured red (Celestún) and orange (Sisal) are located at the west of the peninsula. The plot coloured yellow (Chicxulub) is in the centre, and the cream coloured plot (Coloradas) is located at the east of the peninsula. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Terpene chemotypes in Gossypium hirsutum (wild cotton) from the Yucatan Peninsula, Mexico
Fig. 2. Correlation analysis of all mono- and sesquiterpenes analysed in the wild Gossypium hirsutum plants. Red rectangles indicate highly supported groups of monoterpenes (approximately unbiased (AU) p <0.05). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
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