We present a protocol to determine the optimal extraction solvent to measure cortisol from koala fur. The solvents used in this protocol are methanol, ethanol and isopropanol. Determining an optimal extraction solvent will aid in reliably measuring fur to determine the impact of chronic stress on koalas.
Optimal methods of hormone extraction used to measure stress in animals across sample types are not always the same. Australia's iconic marsupial species, the koala (Phascolarctos cinereus), faces prolonged exposure to anthropogenic-induced stressors and assessment of chronic stress in wild populations is urgently warranted. One of the most effective ways to measure chronic stress is through analyzing the glucocorticoid hormone cortisol in hair or fur, as it supports physiological and behavioral responses. This laboratory validation study aims to test current techniques to validate an optimal hormone extraction method to be used as a non-invasive measure of cortisol in koala fur. It is recognized that using non-invasive techniques to measure stress hormones is preferred over traditional, invasive techniques due to their ideal practical and ethical standpoints. Additionally, it is comparatively easier to acquire fur from koalas than it is to acquire samples of their blood. This study used samples of koala fur acquired from the Adelaide Koala and Wildlife Hospital to run a number of hormone extraction techniques in an attempt to validate an optimal cortisol extraction method. Results showed that 100% methanol provided the most optimal solvent extraction compared to 100% ethanol or 100% isopropanol based on parallelism results. In conclusion, this method of cortisol extraction from koala fur provided a reliable non-invasive assay that could be used to study chronic stress in koalas.
Australian ecosystems sustain human life through the provision of services including food and fiber among many other dynamic interactions1. Ironically, it is human activity that operates as the dominant driver of ecosystem disruption through biodiversity change2. Habitat fragmentation, known as the process of dividing large continuous habitats into small patches of land, isolated from each other, is the major anthropogenic biodiversity change threatening Australian ecosystems2. Habitat fragmentation modifies the structure and diversity of species composition in any given area, thus reducing the area of habitat necessary for these species to maintain viable populations2. The result of this is increased competition between species for resources including food, fuel, fiber, and water3. The destruction of Australian ecosystems through biodiversity change is having catastrophic consequences on many Australian native species1.
Australia's most iconic marsupial species, the koala (Phascolarctos cinereus), depends on Australian ecosystems remaining healthy for their survival4. The introduction of the European Settlement caused a rapid decline in Australian populations of koalas, as they were slaughtered for their pelts in pursuit of profit in a large export trade5. This practice was banned in the 1980's and populations of koalas were then able to stabilize5. However, exponential growth of the human population has resulted in this species competing for much of their habitat, and their survival is again under threat6. According to the International Union for the Conservation of Nature (IUCN), all populations of Australian koalas are listed as vulnerable to extinction with a decreasing population trend7. This listing is attributed to the uncertainty around relevant population parameters and marked variation in population trends for this species7. As the most iconic and endemic animals, koalas largely benefit the Australian economy through tourism (NSW Office of Environment and Heritage 2018). An estimation suggests that koala related tourism has generated approximately 9,000 jobs and contributes between $1.1 and $2.5 billion to the economy (NSW Office of Environment and Heritage 2018). The removal of any one species has the potential to be catastrophic, and can be seen in the steady decline of native Australian wildlife6. Additionally, the Australia economy will feel the ramifications if populations of Australian koalas continue to decline at the rate they are6.
It is suggested that prevalence of death and disease in response to habitat fragmentation is the result of chronic stress8. Already, twenty-four marsupial species have been declared extinct in Australia due to habitat fragmentation, with koalas following a similar trend8. The complexity of habitat fragmentation and biological systems is synergistic but can be unpacked through analysis of the stress response6. Generally, any disturbance in an animals natural surroundings activates a complex cascade of neurohormonal events, known as a 'fight or flight' response9,10. This response to stress is a process that begins in the brain where the hypothalamic-pituitary-adrenal (HPA) axis is activated11. A component of the brain called the hypothalamus releases corticotrophin-releasing hormone (CRH), which then signals the anterior pituitary to release adrenocorticotrophic hormone (ACTH)11. This in turn stimulates the glucocorticoid secretion from the adrenal medulla. The body circulates glucocorticoids through the blood, which diverts the storage of glucose from glycogen and mobilizes glucose from stored glycogen11. This cascade of neurohormonal events is the response used by the animal to deal with unpredictable stimuli11. However, when glucocorticoids are being released and remain elevated for a prolonged period of time, the animal is considered to be experiencing chronic stress12,13. This process involves diverting energy away from other corporal bodily functions, as it is needed for ongoing glucocorticoid production13. As a result, chronic stress can prohibit growth, reproduction and immunity, all being key fitness traits required for survival14.
Measuring an animal's glucocorticoid production is a common indicator used to determine whether or not the animal is experiencing physiological stress15. To do so, glucocorticoids can be measured in blood plasma, serum, saliva, urine or faeces16. However, evidence suggests that hair is a much more effective indicator of chronic stress, as opposed to the aforementioned16. This is because hair is thought to incorporate blood-borne hormones during its growth phase; it is relatively stable; and any cortisol detected in hair reflects physiological stress experienced over the period of hair growth, which can be weeks through to months16. Furthermore, any collection of cortisol should be non-invasive in order to minimise the stress associated with capture and handling16. However, any stress experienced during this event would not impact glucocorticoid levels in hair16. There have been many studies that explore the proficiency of using hair to measure long-term stress in a number of animals, and include studies on reindeer, grizzly bears, rhesus monkeys, muskoxen, and brown bears17,18,19,20,21. Hair cortisol is usually extracted by first washing the sample to ensure sweat and sebum-derived cortisol deposited on the surface of the hair is not co-extracted with cortisol and then pulverizing the sample in a bead-beater22. After washing, the sample needs to be dried to ensure complete evaporation22. Finally, using a solvent, the sample can be extracted and reconstituted to facilitate the assay of cortisol22. The most common solvent used to extract cortisol from fur is methanol21,23; however, there are some studies that use ethanol and isopropanol in their cortisol extraction techniques. For example, a study that used ethanol was successful for extracting cortisol from human amniotic fluid24. Additionally, a study that used isopropanol was successful for extracting cortisol from human hair and nails25,26. For this reason, this study tested all three solvents (methanol, ethanol, and isopropanol) to determine which was the most successful for extraction of cortisol from samples of koala fur.
The primary objective of this study was to use current techniques to validate an optimal hormone extraction technique to be used as a non-invasive measure of cortisol from koala fur. This was achieved by testing three extraction solvents (methanol, ethanol, and isopropanol). We hypothesized that methanol will be the optimal solvent used for extracting cortisol from koala fur because it is the recommended solvent of extraction by Arbor assay cortisol kits27.
This project was performed under strict animal and human care guidelines. Animal ethics was granted by Western Sydney University (A12373). Additionally, a lab risk assessment and biosafety and radiation form were submitted and accepted by Western Sydney University to safely undertake this research (B12366).
NOTE: Koala fur samples for this project were obtained from the Adelaide Koala and Wildlife Hospital, located at 282 Anzac Highway, Plympton South Australia. Fur was taken from one koala which had been admitted to the hospital and euthanized due to their severe injuries. The deceased koala had been stored in a freezer within a body bag soon after death. After removing the deceased koala from the body bag, 1.2 g of fur was shaved from the nape of the neck using standard animal clippers. The fur was shaved as close as possible to the skin, so as to ensure the skin was not cut. Once shaved, the deceased koala was put back into the body bag and placed in the freezer. The fur was then placed in a pouch made of aluminum foil and stored below -20 °C. In transit, the fur was kept at ambient temperature, and on arrival to the laboratory, the fur was stored at -80 °C.
1. Koala fur cortisol extraction
2. Internal controls
3. Cortisol analysis in koala fur extracts
Assay detection of hormone metabolites of interest is determined using parallelism. Using a parallelism curve, the 50% binding point also determines the sample dilution factor on the standard curve (Figure 1). As shown in the parallelism graph (Figure 1), the 100% ethanol and 100% Isopropanol extracts did not provide parallel displacement against the cortisol standard. However, the 100% methanol extract provided parallel displacement against the cortisol standard. Dried extracts were run neat through dilution in assay buffer (100 µL of 100% ethanol and 400 µL of assay buffer).
Intra- (within) and inter- (between) assay coefficients of variation (CV) were determined from high- (approximately 70%) and low- (approximately 30%) binding sample extracts run in all the assays. Based on the parallelism graph (Figure 1), the 30% (low) binding internal controls were neat koala extract pool while the 70% (high) binding internal controls were 1:2 diluted koala extract pool. CV% for internal high and low internal controls were <15%.
Error margin within the assay can be determined using quality control including the intra- and inter- assay coefficients of variation, which should be <15%. Assay sensitivity was calculated as the value 2 standard deviations from the mean response of the blank (zero binding) samples, and expressed as 81.26 pg/well.
Figure 1: Parallelism of pooled koala fur extracted using 3 different solvents (100% ethanol, 100% isopropanol or 100% methanol) against cortisol standard curve under a cortisol enzyme-immunoassay. B/TB is the percentage of binding over total binding. The serial dilution factor (e.g., 1:2X mean dilution factor of 2) has been provided together with the concentration of each standard. Please click here to view a larger version of this figure.
Secondly, the association between each solvent extract and cortisol standard was determined using a regression plot (Figure 2). As shown in Figure 2, the 100% methanol extract provided the best line of regression with the highest R2 value compared to the 100% ethanol and 100% isopropanol extracts.
Figure 2: Regression plots for percentage binding of the cortisol standard against each of the 3 solvents (ethanol, methanol, and isopropanol) used to extract koala fur. The R2 value was obtained from the line of best fit. Please click here to view a larger version of this figure.
Furthermore, sub-set of koala fur extracted using each of the three solvents were assayed and the results are provided in Table 1 below. As shown in Table 1, the observed concentration of cortisol standard was within the range of 2879.61-125.70 pg/well. Neither the ethanol or isopropanol extraction method could achieve consistency in the result as the fur extract concentrations obtained using either of the methods resulted in very high min-max range of hormone concentrations (see Table 1 numbers marked in red), which were beyond the detection limit of the cortisol assay. However, the methanol extracts resulted in cortisol concentrations within the range of the cortisol standard (as shown in bold black numbers in Table 1). Furthermore, the concentrations of fur cortisol detected using methanol extraction method was highly consistent compared to the results obtained using the other two methods (see Table 1). Thus, we accept the null hypothesis that methanol is the most suitable solvent for koala fur hormone extraction compared to ethanol and isopropanol.
Table 1: The cortisol concentration (ng/mg) for koala fur (n = 18) extracted using 3 different solvents (ethanol, isopropanol or methanol) and run against cortisol standard curve under a cortisol enzyme-immunoassay. Bold red numbers show inconsistent concentrations for ethanol and isopropanol extracts which were beyond the assay range (pg/well). Bold black numbers show the concentrations for fur cortisol extracted using methanol which fell within the range of the cortisol standards (pg/well). Please click here to view a larger version of this figure.
There are a number of studies that use a range of techniques to detect cortisol in mammalian fur. This study presents results for the detection of cortisol in fur collected from a wild koala exposed to current anthropogenic stress. This ground-breaking study used fur to test which of the three commonly used solvents are best at extracting cortisol, a measure of chronic stress, from koala fur. Results showed that 100% methanol was the recommended solvent for cortisol extraction in this type of mammalian fur.
Ethanol, methanol and isopropanol are all primary alcohols that are bonded by hydrogen molecules and are commonly used as solvents in hormone extraction experiments28. Generally, polar substances dissolve best in other polar substances, whereas non-polar substances dissolve best in other non-polar substances. The alcohol group containing methanol is very polar, whereas the alcohol group containing isopropanol is very non-polar. Due to its molecular build, alcohol group containing ethanol has the advantage of being both a polar and non-polar solvent. Steroid hormones such as cortisol are considered non-polar, meaning that cortisol should have a strong binding association with polar solvents.
For a more comprehensive analysis of extraction solvents used to assess physiological stress in koala fur, future research projects should attempt identical methods in that order as described in Figure 3. Similar studies have historically performed the wash before grinding22, so as to ensure there is no unintended sweat and/or sebum derived cortisol deposited into the fur sample. Furthermore, it is important that measuring cortisol alone cannot guarantee a complete indication of chronic stress. Hair cortisol readings are a valuable tool when attempting to understand physiological stress experienced by an animal, but elevated HPA activity can occur under a variety of conditions including physical exercise, metabolic abnormalities and the presence of infectious disease22. Other important factors that should be taken into consideration to main integrity of hormone data include the following. (1) Acceptable level of random error – the coefficients of variation obtained from internal controls (CV1 and CV2) should be averaged to <15% for all assays. (2) Random error within sample assay―duplicate samples run on each plate should have a CV% of <15%; otherwise the sample will need to be re-run. (3) Assay detection limit – concentration of hormone quantified within each assay should be within the assay detection limit (between readings for highest dilution and neat standard); otherwise samples may require further dilution (if levels detected for samples are greater than the concentration of neat standard) or may not be analyzed within the assay (if levels detected for samples are less than the concentration of the highest diluted standard). (4) Assay sensitivity – this can be affected by background reading (non-specific binding), therefore it is important to maintain the highest level of quality assurance for the assay (e.g., equipment such as plate washer and plate reader must be serviced regularly). (5) Sample extract drying – this step could result in potential cross-contamination or loss of samples. It is recommended that samples be dried under steam of N2 gas individually and to replace the Pasteur pipette used for extraction between each sample.
Figure 3: Conceptual flow diagram showing the key steps involved in the koala fur cortisol enzyme-immunoassay (EIA). Please click here to view a larger version of this figure.
The procedure outlined in this study (Figure 3) is one that can be easily replicated as it is relatively easy to perform, step-by-step methodology which incorporates readily available chemicals, reagents, and supplies with equipment that is likely to be found in a standard analytical laboratory. The application of this study enables a non-invasive technique to be used to assess physiological stress in both wild and captive koalas.
The authors have nothing to disclose.
This work was supported through start-up research funding for Edward Narayan through the Western Sydney University, School of Science and Health. The authors thank Jack Nakhoul for assistance with sample processing.
Centrifuge Tubes | n/a | n/a | 1.5 mL |
Chrome Steel Beads | n/a | n/a | 3.2 mm x 3 |
Cortisol Kit | Arbor Assays | K003-H1W | Manufactured in Michigan USA |
DetectX Cortisol Enzyme Immunoassay Kit | Arbor Assays | K003-H5 | Used first-time for cortisol testing in koala fur |
Ethanol | n/a | n/a | HPLC Grade |
Isopropanol | n/a | n/a | HPLC Grade |
Methanol | n/a | n/a | HPLC Grade |
Micro Pipette | n/a | n/a | n/a |
Micro Precision Sieve | n/a | n/a | 0.5 mm |
Microplate Reader | Bio Radi | n/a | n/a |
Microplate Washer | Bio Radi | n/a | n/a |
Orbital Shaker | Bio Line | n/a | n/a |
Plastic Weighing Boat | n/a | n/a | n/a |
Plate Sealer | n/a | n/a | n/a |
Precision Balance | n/a | n/a | n/a |
Vortex Mixer | Eppendorf | n/a | n/a |