Effects of cold acclimation on rectal macromorphology, ultrastructure, and cytoskeletal stability in Gryllus pennsylvanicus crickets.

Cold-acclimated insects maintain ion and water balance in the cold, potentially by reducing permeability or increasing diffusion distance across ionoregulatory epithelia such as the rectum. We explored whether cold acclimation induces structural modifications that minimize water and ion diffusion across the rectum and maintain rectal cell integrity. We investigated rectal structure and cytoskeletal stability in chill-susceptible adult Gryllus pennsylvanicus crickets acclimated for one week to either warm (25 °C) or cold (12 °C) conditions. After acclimation, we used light and transmission electron microscopy to examine rectal macromorphology and rectal pad paracellular ultrastructure. We also used fluorescence microscopy and a filamentous-actin (F-actin) specific phalloidin stain to compare the polymerization state of the actin cytoskeleton for each of the acclimation groups before and after a cold shock (1 h at -4 °C). Cold acclimation did not alter rectal pad cell density, or the thickness of the rectal pads, muscle, or cuticle. The tortuosity and width of the rectal pad paracellular channels also did not differ between warm- and cold-acclimated crickets. Rectal pad cells had clear basal and apical regions with differing densities of F-actin. Cold shock reduced the density of F-actin in warm-acclimated crickets, whereas cold-acclimated crickets appeared to have unchanged (basal) or enhanced (apical) F-actin density after cold shock. This suggests that while cold acclimation does not modify rectal permeability through structural modifications to increase diffusion distance for water and ions, cold-acclimated crickets have a modified cytoskeleton that resists the depolymerising effects of cold shock

Rapid desiccation hardening changes the cuticular hydrocarbon profile of Drosophila melanogaster.

The success of insects in terrestrial environments is due in large part to their ability to resist desiccation stress. Since the majority of water is lost across the cuticle, a relatively water-impermeable cuticle is a major component of insect desiccation resistance. Cuticular permeability is affected by the properties and mixing effects of component hydrocarbons, and changes in cuticular hydrocarbons can affect desiccation tolerance. A pre-exposure to a mild desiccation stress increases duration of desiccation survival in adult female Drosophila melanogaster, via a decrease in cuticular permeability. To test whether this acute response to desiccation stress is due to a change in cuticular hydrocarbons, we treated male and female D. melanogaster to a rapid desiccation hardening (RDH) treatment and used gas chromatography to examine the effects on cuticular hydrocarbon composition. RDH led to reduced proportions of unsaturated and methylated hydrocarbons compared to controls in females, but although RDH modified the cuticular hydrocarbon profile in males, there was no coordinated pattern. These data suggest that the phenomenon of RDH leading to reduced cuticular water loss occurs via an acute change in cuticular hydrocarbons that enhances desiccation tolerance in female, but not male, D. melanogaster

Real-time measurement of metabolic rate during freezing and thawing of the wood frog, Rana sylvatica: Implications for overwinter energy use

Ectotherms overwintering in temperate ecosystems must survive low temperatures while conserving energy to fuel post-winter reproduction. Freeze-tolerant wood frogs, Rana sylvatica, have an active response to the initiation of ice formation that includes mobilising glucose from glycogen and circulating it around the body to act as a cryoprotectant. We used flow-through respirometry to measure CO2 production (VCO2) in real time during cooling, freezing and thawing. CO2 production increases sharply at three points during freeze-thaw: at +1°C during cooling prior to ice formation (total of 104±17 μl CO2 frog-1 event-1), at the initiation of freezing (565±85 μl CO 2 frog-1 freezing event-1) and after the frog has thawed (564±75 μl CO2 frog-1 freezing event-1). We interpret these increases in metabolic rate to represent the energetic costs of preparation for freezing, the response to freezing and the re-establishment of homeostasis and repair of damage after thawing, respectively. We assumed that frogs metabolise lipid when unfrozen and that carbohydrate fuels metabolism during cooling, freezing and thawing, and when frozen. We then used microclimate temperature data to predict overwinter energetics of wood frogs. Based on the freezing and melting points we measured, frogs in the field were predicted to experience as many as 23 freeze-thaw cycles in the winter of our microclimate recordings. Overwinter carbohydrate consumption appears to be driven by the frequency of freeze-thaw events, and changes in overwinter climate that affect the frequency of freeze-thaw will influence carbohydrate consumption, but changes that affect mean temperatures and the frequency of winter warm spells will modify lipid consumption

Non-structural carbohydrates in woody plants compared among laboratories

Non-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g⁻¹ for soluble sugars, 6–533 (mean = 94) mg g⁻¹ for starch and 53–649 (mean = 153) mg g⁻¹ for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R² = 0.05–0.12 for soluble sugars, 0.10–0.33 for starch and 0.01–0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g⁻¹ for total NSC, compared with the range of laboratory estimates of 596 mg g⁻¹. Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41–0.91), but less so for total NSC (r = 0.45–0.84) and soluble sugars (r = 0.11–0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Oxford University Press. The published article can be found at: http://treephys.oxfordjournals.org/Keywords: soluble sugars, starch, particle size, reference method, standardization, non-structural carbohydrate chemical analysis, extraction and quantification consistenc

Non-structural carbohydrates in woody plants compared among laboratories

International audienceNon-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g(-1) for soluble sugars, 6-533 (mean = 94) mg g-1 for starch and 53-649 (mean = 153) mg g-1 for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R-2 = 0.05-0.12 for soluble sugars, 0.10-0.33 for starch and 0.01-0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g-1 for total NSC, compared with the range of laboratory estimates of 596 mg g-1. Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41-0.91), but less so for total NSC (r = 0.45-0.84) and soluble sugars (r = 0.11-0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods

Non-structural carbohydrates in woody plants compared among laboratories

Non-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g⁻¹ for soluble sugars, 6-533 (mean = 94) mg g⁻¹ for starch and 53-649 (mean = 153) mg g⁻¹ for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R² = 0.05-0.12 for soluble sugars, 0.10-0.33 for starch and 0.01-0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g⁻¹ for total NSC, compared with the range of laboratory estimates of 596 mg g⁻¹. Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41-0.91), but less so for total NSC (r = 0.45-0.84) and soluble sugars (r = 0.11-0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods