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Water Balance and Cation Levels in Drosophila: Can Early Physiological Decline Predict Aging and Longevity?

School of Biological Sciences, Monash University, Victoria, Australia.

Address correspondence to David Clancy, School of Biological Sciences, Monash University, Clayton 3800, Victoria, Australia. E-mail: david.clancy{at}sci.monash.edu.au

	Abstract

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Many studies demonstrate changes in physiology, biochemistry, or behavior with age, but almost no studies demonstrate such changes being predictive of aging. We subsampled from 10 genetically distinct strains of Drosophila melanogaster as they aged, at three time points, measuring change over time of parameters related to water balance (water content, desiccation survival, and K⁺, Mg²⁺, and Ca²⁺ levels). We then determined whether the change over time in any parameters is predictive of mean life span or time of onset of aging. We observed a schedule of aging-related changes. Time of onset of aging was negatively correlated with decline in desiccation resistance and with decline in K⁺ between days 0 and 15, and was positively correlated with decline in Ca²⁺ between days 15 and 24. We suggest that the potassium result, at least, may be due to loss of functional cytoplasm. We also discuss the use of different estimates of aging in the context of this study.

There is a fairly general opinion among researchers that aging is the result of a cascade of damage, from macromolecular damage to organ and system failure, with loss of homeostasis progressing from the cellular to a whole-organism level. And it is likely that damage begins early. Sgro and Partridge (5) showed that excess early fecundity is associated with excess later mortality in Drosophila melanogaster. Thus life events which occur early, before demographic aging (mortality rate acceleration) has begun, may cause mortality differences which only appear later, after the rate of aging of the population has begun to increase. It is this early damage that we wish to investigate. It would be valuable to have an early life index of age-related damage that is predictive of eventual life span.

To try to get closer to the causes of aging and death in Drosophila we examined indices of water balance. Apart from the ability to find food, in most cases the capacity of poikilotherms to maintain water balance is one of their most important survival attributes (6). In 13 of 14 Drosophila species studied, whose habitats span the range from mesic to arid to desert, desiccation stress resistance decreased with age (7,8). Percentage of body water also decreased with age in D. melanogaster (6,9).

Because measuring most reported age-related parameters is destructive, we use an approach which essentially treats cohorts/strains of D. melanogaster as if they were individuals, allowing us to take subsamples throughout the life span of the cohort. We use laboratory wild-type strain adults which differ for life span, examining males only to avoid the potentially confounding effects of female reproduction. We measure water content, desiccation stress resistance, and whole-body concentration of three cations: K⁺, which is secreted and reabsorbed in large amounts by the Malpighian tubules (10) and is likely to contribute to water balance; Ca²⁺, which is essential for nervous and muscular activity, and is also actively excreted by Malpighian tubules (10); and Mg²⁺, the levels of which are related to those of Ca²⁺. During a life-span assay we take these measures at the beginning (baseline), at day 15 (before cohort mortality begins to accelerate), and at day 24 (as cohort mortality begins to accelerate). Because the best measure of any underlying causal process is likely to be the early-life rate of change in the parameters, we correlate the change over time in the measured parameters of water balance with measures of cohort life span to see whether any of these measures are indices of age-related damage and, if so, are predictive of eventual life span. We also correlate absolute measures at each time point with life-span measures to see if any might predict cohort life span. We then discuss the results in the context of insect water-balance physiology.

	METHODS

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The Drosophila strains used were each the progeny of a single female, origins as follows: 5905 (stock number from Bloomington Stock Center, w¹¹¹⁸, isogenic for chromosomes 1,2, and 3, constructed by John Roote, Cambridge, U.K.); Alstonville (northern New South Wales, Australia, collected 2002); Argentina [La Plata, Argentina, from David Rand (11)]; Armenia (thought to be "Armenia 1977," originally from Umea Stock Center, collected in Ashtarak); Athens (Greece, derived from stock started with four females, 1965, Bloomington Stock Center); Dahomey [now Benin, Africa, derived from mass-bred stock (12)]; Japan [Jume, Japan, from David Rand (11)]; Madang [Papua New Guinea, derived from mass-bred stock (13)]; Seattle (WA, collected in 2001); Tasmania (Red Knight, Tasmania, Australia, collected 2002). Stocks were maintained at 18°C in a 12-hour light/dark cycle on a dextrose/yeast/semolina medium. Experimental flies were generated by moving parentals to 25°C and feeding overnight with live yeast before collecting eggs and seeding 450 into bottles for consistent larval densities (14).

Longevity Experiment
Males only were used. Initially, 1200 males were collected to supply enough flies for longevity as well as for baseline assays of desiccation stress resistance and cation concentration, these baseline assays on males 2–4 days old. To assay longevity, males were collected from bottle cultures at 0–2 days old, sexed using CO₂ anesthesia, and the next day introduced into modified 2-liter juice bottles with holes for two replaceable food vials and adequate ventilation. Medium was poured into the vials on a slope, making the available surface area of food about 300% c.f. normal food vials. These were refreshed every 2–3 days, and the numbers of deaths were scored. Dead flies were removed at four points throughout the experiment to avoid excessive buildup of dead flies. The experiment was run at 27°C, 75% relative humidity on a 12-hour light/dark cycle. The 10 strains were represented by three replicate longevity bottles per strain, each containing 320 males. At days 15 and 24 of the longevity experiment, 70 flies were removed from each bottle for physiological measurements, giving a total of 210 flies removed and censored per strain per interval.

Desiccation Stress Resistance
The mean ambient relative humidity in a 25°C constant temperature room was 40% (2.6% standard deviation) on day 0 and 41% (1.3% standard deviation) on day 24. Extrapolating from meteorological data, relative humidity on day 15 was very similar to that on day 24, perhaps 0.5% higher but with slightly less variability. After recovery from anesthesia on food for at least 5 hours, 10 males were introduced into each of five empty vials per strain, which were kept in darkness, and deaths were scored every 30 minutes until all were dead.

Water Content and Cation Chromatography
Using a Cahn C-33 electrobalance, we weighed (to ± 2 µg) 10 groups of 15 males per strain per collection in preweighed tubes after the flies were killed by freezing. Tube lids were then punctured and flies dried at 50°C for 20 hours. Dried flies in tubes were then kept at ambient humidity overnight before reweighing to determine water content. These dried flies were then transferred to Eppendorf tubes and autoclaved before 10-minute homogenization in 200 µl of Milli-Q water using a Retsch (Retsch GmbH, Haan, Germany) mixer mill and tungsten carbide beads at a shaking frequency of 20 Hz. Water (800 µl) was added to the homogenate, which was then centrifuged for 15 minutes at 15,000 rpm; 400 µl of supernatant was diluted to 1.0 ml for cation chromatography.

Chromatography equipment was supplied by Alltech (Deerfield, IL). We used a model 526 high performance liquid chromatography (HPLC) pump running 3 mM methanesulfonic acid eluant at 1.0 ml/min, a model 570 autosampler with 100-µl injection volume, a Universal Cation column and guard column with a model 530 column heater set at 35°C, and a model 550 conductivity detector at a sensitivity of 100 µs. Data were collected using a PE Nelson interface, and peak heights were measured using Turbochrom software. Concentrations of K⁺, Mg²⁺, and Ca²⁺ were determined using dilutions of cation standards, and were converted to % wet body mass. Rarely during homogenization a tube leaked; therefore, low outliers were excluded.

Analysis
We measured three life-span and aging parameters: rate of aging, time of onset of aging, and mean life span. Rate of aging was estimated using Weibull and Gompertz-like model fitting. Using the survival analysis platform of JMP (SAS Institute, Cary, NC) we estimated the Weibull parameter , which reflects age-dependent mortality rate and is independent of the so-called initial mortality rate (15). In contrast, the logistic parameter "b" reflects the slope of the survival curve in the early section of increasing mortality rate, before the increase begins to level off, and is affected by initial mortality rate. Using the program Winmodest (16), we fitted the data to a Logistic-Makeham model for parameter estimation using a maximum likelihood approach. Where the cohort data better fit models with fewer parameters (Logistic, Gompertz, or Gompertz-Makeham), the relevant additional parameter(s) approached zero, which tends to reduce the Logistic-Makeham to the appropriate model, allowing consistent estimation of the "b" parameter. We estimated the time of onset of aging using daily mortality data. First, we computed _{t ... t + 2}/_{t ... t – 2} to give an idea on which scoring day the rate of change of slope was maximal. This number was checked by eye against the daily mortality curves for each strain and against a smoothed version obtained by fitting a two-period moving average trendline, and was amended where clearly necessary.

Physiological decline of strains was measured by, for example, (mean at day 15 – mean at day 24)/mean at day 15. An exception was the change in % body water, which was measured by, e.g., mean % body water at day 24/mean % body water at day 15. These quantities were then linearly regressed on measures of life span and aging so that each strain was effectively a replicate in the regression. We also regressed absolute physiological measures at days 0, 15, and 24 in case any of these predicted cohort life span. Chromatography flies had several measures performed on them, some of which are likely to be functionally related, so separate regressions for % body water and K⁺ and for Mg²⁺ and Ca²⁺ were done. Initial screening by mixed stepwise multiple regression on life-span measures was undertaken to identify potential significant effects, which were then included in the least squares regression. This was not necessary for desiccation, in which regressions it was the sole predictor variable.

A confounding problem was that significant differential cumulative mortality between strains occurred by days 15 and especially 24 which might be expected to skew physiological measures. Therefore, we performed regressions initially excluding and then including the relevant mortality term (day 15, day 24, days 24 – day 15). Where its inclusion clearly affected the relationship between response and predictor variables, this result was reported; otherwise, the term was excluded. We used JMP (SAS Institute) for statistical summaries and analyses.

	RESULTS

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Life Span
Survival curves are shown in Figure 1, and summary survival data in Table 1. The survival curves of the strains differed using a log-rank test (p <.0001), there was significant variation among strains for aging parameters, and the rank order of strains varied depending on the parameter measured or estimated. For instance, the curve for Armenia was more "square" than for Madang; aging began earlier but was less rapid for the Madang strain, such that the two had similar mean life spans. Because the two measures of rate of aging ranked the strains differently, only mean life span and estimated time of onset of aging were used in the analyses.

View larger version (27K): [in this window] [in a new window]   Figure 1. Survival curves for 10 isofemale strains/cohorts of Drosophila melanogaster. Dashed vertical lines = sampling times at days 0, 15, and 24

View larger version (14K): [in this window] [in a new window]   Figure 2. Mean desiccation survival time (95% confidence interval) for Drosophila melanogaster strains, days 0, 15, and 24

View larger version (12K): [in this window] [in a new window]   Figure 3. Correlation of decrease in mean desiccation survival from days 0–15 with estimated day of onset of aging across Drosophila melanogaster strains

View larger version (11K): [in this window] [in a new window]   Figure 4. Correlation of increase in mean desiccation survival from days 15–24 with mean life span across Drosophila melanogaster strains

View larger version (13K): [in this window] [in a new window]   Figure 5. Mean % body water (w/w; 95% confidence interval) for Drosophila melanogaster strains, days 0, 15, and 24

View larger version (18K): [in this window] [in a new window]   Figure 6. K+ as mean % body mass (95% confidence interval) for Drosophila melanogaster strains, days 0, 15, and 24

View larger version (17K): [in this window] [in a new window]   Figure 7. Mg2+ as mean % body mass (95% confidence interval) for Drosophila melanogaster strains, days 0, 15, and 24

View larger version (18K): [in this window] [in a new window]   Figure 8. Ca2+ as mean % body mass (95% confidence interval) for Drosophila melanogaster strains, days 0, 15, and 24

	DISCUSSION

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Many studies have looked for differences in a physiological or biochemical measure associated with aging phenotypes. Typically the effective sample size is only two, for example, caloric restricted versus ad libitum fed, high activity versus low activity, or long lived mutant versus control, such that the parameter is not investigated in a way that adequately demonstrates predictivity of aging. Negative results in such studies are important although seemingly rare (e.g., 17), but positive results must remain inconclusive. Our work treated 10 cohorts/strains of D. melanogaster as individuals and took subsamples at three time points during the life span of the cohort. Thus, the large sample sizes adequately allowed us to investigate predictivity of aging. We were also able to sample destructively and quantify a number of phenotypes that cannot be observed in nondestructive approaches, such as used by Huang and colleagues (18).

Measuring Aging
The homozygous isogenic strain, 5905, showed the most rapid rate of aging but also the highest level of age-independent mortality and one of the clearest onsets of aging. Pletcher and colleagues (19) indicate that a rapid rate of aging in inbred lines is expected, but that initial mortality rate might be reduced by a selection process during the inbreeding. In the case of 5905, achieving homozygosity was forced by the use of balancer chromosomes (and therefore relatively rapid), so we might expect the observed high initial mortality rates. With regard to rate of aging as a measure in this study, strain 5905 highlights several problems. The 5905 Weibull estimate is clearly too low, perhaps unsurprising given the poor fit of the Weibull model to its data. There was little correlation of aging estimates between different models; the survival curves clearly contradicted the estimated Weibull rate parameter in several cases, and it was clear that the spread of estimates provided by the Logistic-Makeham model was not explainable by any of our physiological measures. Therefore, because degree of genetic variation within strains can influence rate of aging comparisons between strains, it is an inappropriate measure of aging for this study and for any studies in which there are widely varying levels of inbreeding between groups.

The method we used for determining time of onset of aging is not analytic, but no commonly used objective method is known (20). The mathematical method we used to observe changes in slope resulted in some smoothing. To improve validation by eye of our estimation method we used a 2-point moving average fit to daily log mortality curves because it did not result in any differential x-axis shift between strains and in all cases seemed to preserve the shape of the curve well. The time at which mortality began to accelerate was then generally quite clear by visual examination of curves, although not determinable on a fine scale. It was less easy for strains Alstonville and especially Seattle, which did not show typical survival curve shapes. These strains may have other causes of mortality which partially obscure the onset of aging-related deaths. Excluding Seattle from analyses which used onset as dependent variable did not alter the results significantly. Because determinations could not be made on a fine scale, choosing a nonanalytical measure of aging was necessary because the quantity is such a important factor in the study of cohort aging, especially in the context of a damage-accumulation model (e.g., 21).

Desiccation Survival
The recovery over time of desiccation survival in D. melanogaster was not observed in males or females by Gibbs and Markow (7) although given the timing of their scorings it might have been missed. Neither was it seen in females by Nghiem and colleagues (9), who assayed at 6 time points to day 40. However, both studies used practically 0% relative humidity (a commonly applied laboratory stress), so it is likely that some of the mechanisms involved in surviving harsh versus mild desiccation stress differ. In nature it is likely that flies are almost never exposed to 0% humidity for a protracted period or, if they are, it is so rarely that the mechanisms specific for surviving harsh desiccation are unimportant in the context of natural selection for desiccation survival.

It is likely that desiccation stress resistance is related to activity levels in Drosophila, especially in males; spontaneous locomotor activity is lowest during the hottest parts of the day (22), it was decreased in flies selected for desiccation resistance (23), and it necessarily promotes water loss due to the requirement for gas exchange through opening spiracles (24). Certainly our Japan strain, by far the most desiccation-resistant strain, was uniquely sedentary. A desiccation survival–activity tradeoff could explain our observed negative correlation between rebound in desiccation survival from days 15–24 and mean life span, a result whose meaning is not readily obvious. In houseflies, loss of flight is considered an indicator of physiological age; flies which no longer fly will generally die sooner than flies of the same chronological age which still fly (25). Minois and colleagues (26) document little decline in D. melanogaster activity to day 16 but significant decline to day 26 (at 25°C). Thus it is possible that our strains showing lowest mean life span contained the greatest number of "low activity" flies at day 24 whereas at day 15, activity in most strains would not yet have substantially declined in a substantial number of individuals. If less active flies resist desiccation stress better, we might expect such flies to contribute to a greater increase in desiccation survival from days 15–24.

Because little activity decrease is likely to day 15, the observed decline in desiccation survival to day 15, correlated as it is with time of onset of aging, is likely to be a real example of aging-related physiological decline; the smaller the decline, the later the onset of aging. If it were related to activity as in the example above, the sign of the correlation would be in the opposite direction. In the context of "wear," therefore, we can broadly say that the early damage that causes reduced desiccation survival also promotes aging. Alternatively (or in addition), in a context of "repair," we might conclude that desiccation resistance and longevity assurance have significant shared mechanisms and that (some of) these mechanisms are damaged or otherwise decline early, prior to age 15 days.

Water and Cation Content
One might expect that the U-shaped pattern over time in % body water occurred for the same reason as that seen for desiccation survival; however, changes in the two with time are not correlated across strains. Lamb (27) observed the same pattern for water content over time in male D. melanogaster.

The more K⁺ declined to day 15, the more rapid the onset of aging; it never increased significantly to day 15, only decreasing or remaining similar to day 0. Although the change in % body water was not correlated with aging, it was positively correlated with change in K⁺ (p =.005, r² = 0.65). The K⁺ result could reflect a loss of functional cells and/or cytoplasm. K⁺ exists largely in the cytosol, where its concentration is actively maintained (28), so when a cell becomes unable to properly maintain itself, it could lose K⁺ quite rapidly. Those strains with more nonfunctional cells may be expected to begin to age more quickly. Mg²⁺ also exists mainly in the cytosol and is actively maintained, although perhaps less so than K⁺ (28), and so the same explanation might account for the decreasing Mg²⁺ levels over time, although its noncorrelation with aging might reflect a process several steps removed from the primary aging damage.

In the case of Ca²⁺ we must first reconcile our clearly observed decline from days 15–24 with the reported increase in total calcium with age observed by Massie and colleagues (29) using atomic absorption spectroscopy. Our sample preparation, while attempting to maximize breakdown of tissue to aid solubilization of cations, certainly discarded a significant amount of insoluble material. So the decrease may reflect a sequestration of Ca²⁺ into insoluble fractions with age which would be removed by centrifugation during preparation of our samples. Hence, we need to be aware that our results may be an artefact of our methodology; indeed, it might be expected. Lipofuscin, often regarded as a biomarker of aging, can be detected in postmitotic cells of human infants (30), so is likely to appear early in Drosophila also, and calcium is found in lipofuscin granules from human retinal pigment epithelium (31). If this is occurring, though, we cannot tell if it is an aging-related process.

This complicates interpretation of the correlation between onset of aging and calcium decline from days 15–24; those strains in which calcium decrease was greatest showed later onset of aging, corrected for survival during the period. If the decline in soluble, or ionic, calcium is due to an aging-related sequestration into insoluble fractions, the result seems counterintuitive. In humans, aging shows increasing cytosolic Ca²⁺ (healthy cells actively exclude calcium, so nonfunctional cells are likely to allow inward diffusion) and decreasing cytosolic Mg²⁺ (32,33), which reflects our observed correlation between onset of aging and Ca²⁺/Mg²⁺ ratio from days 15–24. However, the decreases are much less marked in humans compared with our fly data. Excess calcium itself may be harmful to organisms in later life. If so, flies that dispose of it better, perhaps through more effective turnover mechanisms, may survive better. This echoes the original hypothetical example of antagonistic pleiotropy, the evolutionary explanation for the existence of aging proposed by Williams (34) in which he suggested that a gene optimizing bone calcification could be beneficial in early life but through promoting atherosclerosis be harmful in later life. In this case, however, the meaning of the result is still unclear.

Conclusion
Different cohorts can have the same rates of aging but different mean life spans, the difference often being due to different times for the onset of aging. In human terms, we tend to be most interested in delaying senescence; therefore, it is desirable to measure onset of aging where possible. When dealing with mechanistic questions of aging, this measure is probably the most useful. Unfortunately it can also be difficult to measure. Rate of aging and time of onset of aging are the most important measures in a context of studying aging mechanisms. These quantities together, along with age-independent mortality rate, result in mean cohort life span. Thus it is perhaps no surprise that mean life span was uncorrelated with almost all physiological measures.

In D. melanogaster, decline in desiccation resistance can be detected quite early and is correlated with time of onset of aging. Later rebound in resistance, negatively correlated with mean life span, is probably due to reduced activity among members of physiologically "older" strains, which frees resources for desiccation survival.

Early changes in Mg²⁺ and Ca²⁺ level are much less substantial than are the later changes, and do not seem to be important in predicting onset of aging, whereas earlier changes in K⁺ and in desiccation survival seem to be important. Using Drososphila we have observed and characterized a schedule of aging-related physiological changes.

	Acknowledgments

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This work was supported by a Monash University Small Grant (D.J.C., S.W.M.) and by the Centre for Environmental Stress and Adaptation Research.

For helpful advice, we thank Professor Gerry Quinn (statistical), Dr. Simon Roberts (technical), and Dr. Chris Driver (general).

	Footnotes

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Decision Editor: James R. Smith, PhD

Received April 19, 2005

Accepted August 8, 2005

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