The Stereochemistry of Some Resin Acid Derivatives1

1959 ◽  
Vol 81 (3) ◽  
pp. 688-693 ◽  
Author(s):  
Ernest Wenkert ◽  
James W. Chamberlin
Keyword(s):  
Resin Acid

Cytochrome P450 mono-oxygenases in conifer genomes: discovery of members of the terpenoid oxygenase superfamily in spruce and pine

2006 ◽  
Vol 34 (6) ◽  
pp. 1209-1214 ◽  
Author(s):  
B. Hamberger ◽  
J. Bohlmann
Keyword(s):  
Cytochrome P450 ◽  
Loblolly Pine ◽  
Large Scale ◽  
Expressed Sequence Tag ◽  
Resin Acid ◽  
Functional Characterization ◽  
Structural Diversity ◽  
Resin Acids ◽  
Full Length Sequence ◽  
Diterpene Resin Acids

Diterpene resin acids, together with monoterpenes and sesquiterpenes, are the most prominent defence chemicals in conifers. These compounds belong to the large group of structurally diverse terpenoids formed by enzymes known as terpenoid synthases. CYPs (cytochrome P450-dependent mono-oxygenases) can further increase the structural diversity of these terpenoids. While most terpenoids are characterized as specialized or secondary metabolites, some terpenoids, such as the phytohormones GA (gibberellic acid), BRs (brassinosteroids) and ABA (abscisic acid), have essential functions in plant growth and development. To date, very few CYP genes involved in conifer terpenoid metabolism have been functionally characterized and were limited to two systems, yew (Taxus) and loblolly pine (Pinus taeda). The characterized yew CYP genes are involved in taxol diterpene biosynthesis, while the only characterized pine terpenoid CYP gene is part of DRA (diterpene resin acid) biosynthesis. These CYPs from yew and pine are members of two apparently conifer-specific CYP families within the larger CYP85 clan, one of four plant CYP multifamily clans. Other CYP families within the CYP85 clan were characterized from a variety of angiosperms with functions in terpenoid phytohormone metabolism of GA, BR, and ABA. The recent development of EST (expressed sequence tag) and FLcDNA (where FL is full-length) sequence databases and cDNA collections for species of two conifers, spruce (Picea) and pine, allows for the discovery of new terpenoid CYPs in gymnosperms by means of large-scale sequence mining, phylogenetic analysis and functional characterization. Here, we present a snapshot of conifer CYP data mining, discovery of new conifer CYPs in all but one family within the CYP85 clan, and suggestions for their functional characterization. This paper will focus on the discovery of conifer CYPs associated with diterpene metabolism and CYP with possible functions in the formation of GA, BR, and ABA in conifers.

scholarly journals Resin-acid derivatives as potent electrostatic openers of voltage-gated K channels and suppressors of neuronal excitability

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Nina E Ottosson ◽  
Xiongyu Wu ◽  
Andreas Nolting ◽  
Urban Karlsson ◽  
Per-Eric Lund ◽  
...  
Keyword(s):  
Neuronal Excitability ◽  
Resin Acid ◽  
K Channels ◽  
Voltage Gated

Effect of Resin Acid and Hemicelluloses on Alkyl Ketene Dimer Sizing

2011 ◽  
Vol 25 (6-7) ◽  
pp. 743-760 ◽  
Author(s):  
Jérôme Da Silva Mourao ◽  
Elisa Zeno ◽  
Evelyne Mauret
Keyword(s):  
Resin Acid ◽  
Alkyl Ketene Dimer

Relationship between cortical resin acids and resistance of Sitka spruce to the white pine weevil

1996 ◽  
Vol 74 (4) ◽  
pp. 599-606 ◽  
Author(s):  
Elizabeth S. Tomlin ◽  
John H. Borden ◽  
Harold D. Pierce Jr.
Keyword(s):  
Discriminant Analysis ◽  
Resin Acid ◽  
Sitka Spruce ◽  
Canonical Discriminant Analysis ◽  
Picea Sitchensis ◽  
Resin Acids ◽  
White Pine ◽  
Pissodes Strobi ◽  
Pine Weevil ◽  
White Pine Weevil

Cortical resin acids were analyzed both quantitatively and qualitatively among 10 provenances and 11 genotypes of Sitka spruce, Picea sitchensis Bong (Carr.), putatively resistant to the white pine weevil, Pissodes strobi (Peck), and compared with susceptible trees. Trees in 5 of the 11 resistant genotypes had significantly greater amounts of cortical resin acid than susceptible trees. Of seven individual acids analyzed, pimaric, isopimaric, levopimaric, dehydroabietic, abietic, and neoabietic acid, but not palustric acid, were found in significantly greater amounts in trees from resistant than susceptible provenances. Eighteen percent of the variation in resin acid content could be accounted for by variation in the capacity of cortical resin ducts, indicating that the other 82% of variation is a result of differences in resin acid concentration in the resin. Trees with very high resin acid levels may have a greater capacity for resinosis than susceptible trees, may deter feeding, or may produce resin that is toxic to eggs and larvae. Canonical discriminant analysis revealed that several resistant clones, particularly two from the Kitwanga provenance, could be distinguished from others on the basis of their resin acid profiles. Because it separated trees on the basis of genotype, but not according to degree of resistance, canonical discriminant analysis may be more useful in "chemotyping" trees than in screening for resistance. Keywords: Picea, cortex, resin acids, Pissodes strobi, resistance.

scholarly journals Exposure Determinants of Wood Dust, Microbial Components, Resin Acids and Terpenes in the Saw- and Planer Mill Industry

2020 ◽  
Vol 64 (3) ◽  
pp. 282-296 ◽  
Author(s):  
Anne Straumfors ◽  
Marine Corbin ◽  
Dave McLean ◽  
Andrea ‘t Mannetje ◽  
Raymond Olsen ◽  
...  
Keyword(s):  
Prediction Models ◽  
Resin Acid ◽  
Fungal Spores ◽  
Resin Acids ◽  
High Exposure ◽  
Airborne Measurements ◽  
Exposure Response ◽  
Wood Type ◽  
Exposure Determinants ◽  
And Task

Abstract Objectives Sawmill workers have an increased risk of adverse respiratory outcomes, but knowledge about exposure–response relationships is incomplete. The objective of this study was to assess exposure determinants of dust, microbial components, resin acids, and terpenes in sawmills processing pine and spruce, to guide the development of department and task-based exposure prediction models. Methods 2474 full-shift repeated personal airborne measurements of dust, resin acids, fungal spores and fragments, endotoxins, mono-, and sesquiterpenes were conducted in 10 departments of 11 saw- and planer mills in Norway in 2013–2016. Department and task-based exposure determinants were identified and geometric mean ratios (GMRs) estimated using mixed model regression. The effects of season and wood type were also studied. Results The exposure ratio of individual components was similar in many of the departments. Nonetheless, the highest microbial and monoterpene exposure (expressed per hour) were estimated in the green part of the sawmills: endotoxins [GMR (95% confidence interval) 1.2 (1.0–1.3)], fungal spores [1.1 (1.0–1.2)], and monoterpenes [1.3 (1.1–1.4)]. The highest resin acid GMR was estimated in the dry part of the sawmills [1.4 (1.2–1.5)]. Season and wood type had a large effect on the estimated exposure. In particular, summer and spruce were strong determinants of increased exposure to endotoxin (GMRs [4.6 (3.5–6.2)] and [2.0 (1.4–3.0)], respectively) and fungal spores (GMRs [2.2 (1.7–2.8)] and [1.5 (1.0–2.1)], respectively). Pine was a strong determinant for increased exposure to both resin acid and monoterpenes. Work as a boilerman was associated with moderate to relatively high exposure to all components [1.0–1.4 (0.8–2.0)], although the estimates were based on 13–15 samples only. Cleaning in the saw, planer, and sorting of dry timber departments was associated with high exposure estimates for several components, whereas work with transportation and stock/finished goods were associated with low exposure estimates for all components. The department-based models explained 21–61% of the total exposure variances, 0–90% of the between worker (BW) variance, and 1–36% of the within worker (WW) variances. The task-based models explained 22–62% of the total variance, 0–91% of the BW variance, and 0–33% of the WW variance. Conclusions Exposure determinants in sawmills including department, task, season, and wood type differed for individual components, and explained a relatively large proportion of the total variances. Application of department/task-based exposure prediction models for specific exposures will therefore likely improve the assessment of exposure–response associations.

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