|
| |
|
|
|
|
||||
| Home Help Feedback Subscriptions Archive Search Table of Contents | ||||
First published online July 20, 2007
Journal of Experimental Biology 210, 2649-2656 (2007)
Published by The Company of Biologists 2007
doi: 10.1242/jeb.003350
Critical thermal maxima in knockdown-selected Drosophila: are thermal endpoints correlated?
Department of Biology, College of William and Mary, Williamsburg, VA 23187, USA
* Author for correspondence (e-mail: dgfolk{at}roadrunner.com)
Accepted 2 May 2007
 |
Summary |
|---|
 TOP Summary IntroductionMaterials and methodsResultsDiscussionReferences |
|---|
40°C, whereas the low knockdown flies fall out of the
column at much cooler temperatures (
35°C, on average). The critical
thermal maximum (CTmax) for respiratory control in the
selected knockdown populations was determined by analyzing CO2
output of individuals during exposure to a temperature ramp (from 30°C to
>45°C) and was indicated by an abrupt alteration in the pattern of
CO2 release. The CTmax for locomotor function
was determined by monitoring activity (concurrent with CO2
analysis) during the temperature ramp and was marked by the abrupt cessation
of activity. We hypothesized that selection for high knockdown temperature may
cause an upward shift in CTmax, whereas selection for low
knockdown may lower CTmax. Correlations among the three
thermal endpoints varied between the high and low knockdown flies. Finally, we
compared metabolic profiles, as well as Q10 values, among the high
and low knockdown males and females during the temperature ramp.
Key words: Drosophila melanogaster, laboratory selection, thermotolerance, knockdown, critical thermal maximum, thermolimit respirometry, metabolic rate, Q10
|
Introduction |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
). A relevant concern of physiological and evolutionary
ecologists is the capacity of organisms to deal with such challenges. The
extent to which organisms can respond to thermal stress has a `profound effect
on evolutionary fitness' (Huey and
Bennett, 1990).
Drosophilids are model organisms in which thermotolerance has been studied
extensively (Hoffmann et al.,
2003) by a variety of methods, including assessment of mortality
or survivorship following heat shock (Huey
et al., 1991; Hoffmann et al.,
1997; Berrigan and Hoffmann,
1998; Stratman and Markow,
1998; Berrigan,
2000; Sørensen et al.,
2001; Folk et al.,
2006; Rashkovetsky et al.,
2006), knockdown time (McColl
et al., 1996; Hoffmann et al.,
1997; Berrigan and Hoffmann,
1998; Berrigan,
2000; Sørensen et al.,
2001; Kellett et al.,
2005), knockdown temperature
(Gilchrist and Huey, 1999;
Berrigan, 2000;
Folk et al., 2006), and
locomotor functioning during or following heat shock
(Krebs et al., 2001;
Zatsepina et al., 2001;
Roberts et al., 2003;
Newman et al., 2005).
Although an array of traits linked to thermotolerance in flies has been
studied, some of the traits may have different physiological bases and thus
may not be correlated with each other. This idea was supported by Hoffmann et
al. who examined the correlation of different measures of thermotolerance in
replicate lines of Drosophila melanogaster selected for increased
knockdown time at a high temperature
(Hoffmann et al., 1997). They
tested the flies for recovery time and survivorship following thermal stress.
The flies selected for the highest knockdown times did not recover more
quickly or show improved survivorship. In other words, the populations
selected for highest knockdown had not evolved enhanced thermotolerance in a
broad sense. If traits typically used to gauge thermotolerance lack
correlation, the ecological and evolutionary relevance of some of the traits
may require re-evaluation.
We are currently using populations of Drosophila melanogaster
artificially selected for knockdown temperature as a model for investigating
the complexities of thermotolerance
(Gilchrist and Huey, 1999;
Folk et al., 2006). Knockdown
temperature (TKD) is the temperature at which flies drop
out of a heated knockdown column (Huey et
al., 1992). This study system comprises four replicate populations
that have undergone directional selection for high TKD,
four replicate populations that have undergone stabilizing selection on lower
TKD values, and four replicate control populations. The
High TKD populations have evolved high knockdown
thermotolerance (average TKD=41°C), whereas the
Low TKD populations experience knockdown at 35°C.
The mechanistic underpinnings of the knockdown phenotypes are unclear.
Critical thermal maximum (CTmax) estimations have been
used to define the thermal tolerance of vertebrate and invertebrate taxa for
over six decades (Cowles and Bogert,
1944; Lutterschmidt and
Hutchison, 1997). Historically, CTmax is
defined as the thermal endpoint at which "...locomotory activity
becomes disorganized and the animal loses the ability to escape from
conditions that will promptly lead to its death"
(Cowles and Bogert, 1944).
Lutterschmidt and Hutchison assert that "...CTmax is an
excellent index and standard for evaluating the thermal requirements and
physiology of an organism."
The physiological states used traditionally to define
CTmax are variable and include the `loss of righting
response', `onset of muscular spasms', `heat paralysis' or `heat coma', and
even `knockdown' (Lutterschmidt and
Hutchison, 1997; Berrigan and
Hoffmann, 1998). Here we define CTmax in the
flies as the upper temperature at which normal locomotory functions and
spiracular control are compromised. The central question addressed in the
present study is: are thermal endpoints correlated? Specifically, we question
whether selection for high (or low) knockdown temperature has resulted in high
(or low) critical thermal maximum for heat paralysis. Exposure to either
CTmax or TKD would presumably result
in disruption of normal neuromuscular functions.
Traditionally, CTmax has been estimated by determining
body (or ambient) temperature at the onset of one of the physiological states
mentioned above (Lutterschmidt and
Hutchison, 1997). To estimate CTmax in
individual flies we used a more objective method, namely thermolimit
respirometry, in conjunction with constant monitoring of activity
(Lighton and Turner, 2004).
Thermolimit respirometry allows the estimation of CTmax
for involuntary muscle function, as indicated by loss of spiracular control,
whereas activity monitoring allows estimation of CTmax for
voluntary muscle function, as indicated by cessation of movement. The loss of
spiracular control is evidenced by a distinct alteration in the pattern of
CO2 output, characterized by a dramatic reduction in the variance.
In addition, we explore the feasibility of using thermolimit respirometry and
activity monitoring to detect TKD, which would be possible
only if the patterns of spiracular and locomotor activity were altered
significantly at knockdown.
|
Materials and methods |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
).
Briefly, in 1992 a subset of flies from a founding population of
Drosophila melanogaster (collected by L. Harshmann and M. Turelli in
1991 in Escalon, CA, USA) was used to establish discrete lines. From these
lines, six High Knockdown lines (`High TKD'), three Low
knockdown lines (`Low TKD'), and six Control lines were
established (Fig. 1). These
lines were subjected to artificial selection (described below) for 46
generations until September 1997. Selection was resumed for 7 generations in
June 2004. In January 2005, we combined flies from all replicate lines within
each selection (and control) group and randomly chose individuals to generate
new replicate High TKD, Low TKD, and
Control lines (Fig. 1),
referred to as the HN1-4, LN1-4 and CN1-4
lines, respectively. We generated the new knockdown selection lines to reduce
inbreeding by crossing the original lines within each treatment group, and to
create equal numbers of lines within the treatment groups.
|
Measuring knockdown temperature
The knockdown protocol is detailed fully elsewhere
(Folk et al., 2006). To begin a
knockdown experiment, 1000 flies from each line are released into the
inner tube of a Weber column (Weber,
1988). The inner tube is surrounded by a water jacket, through
which water circulates via a heat pump (Haake-Buchler Inc., Paramus,
NJ, USA) immersed in a water bath. The flies are transferred immediately from
a 25°C incubator into the column, which is initially heated to 30°C.
The temperature setting of the heat pump is then increased to 50°C.
Consequently, the inner tube heats up (0.4°C min-1); the
flies fall out and are collected at 0.5°C intervals between 32-46°C.
After falling out of the heated column, the flies resume an upright posture
nearly instantaneously (Gilchrist and Huey,
1999). Following knockdown, the flies are anesthetized with
CO2, sexed and counted. The distribution of knockdown temperatures
is computed separately for males and females from each line.
Selection regime and experimental protocols
The selection regime and fly maintenance are detailed fully elsewhere
(Folk et al., 2006). Briefly,
after each High TKD line (HN1-4) is run through
the knockdown column, 30% of the flies with the highest
TKD are retained for breeding. For each Low
TKD line (LN1-4), 30% of the flies with
TKD values of 35.5-37°C are retained for
breeding. After each Control line (CN1-4) is run through the
column, 30% of all the flies are randomly chosen for retention and
breeding. The selected flies are maintained for 6-7 days at 25°C to ensure
remating (Gilchrist and Huey,
1999), following which eggs are collected for rearing of the
subsequent generation. Selection on adults occurs 4-5 days post-eclosion.
For all respirometry experiments, eggs (50 eggs/food vial; 7 vials/line) from each HN1-4, LN1-4, and CN1-4 line were collected from a subset of adults removed from selection. The flies were reared at 25°C. At 2-4 days post-eclosion, 12 flies (6 males, 6 females) from each line were haphazardly chosen, anesthetized with CO2, weighed to the nearest 0.001 mg, and placed individually into food vials for 20-28 h. We then haphazardly chose four individuals (2 males, 2 females) from the larger group of 12, and measured CO2 output and activity of individuals across a temperature range from 30°C to >45°C. All respirometry and activity measurements of flies from a line were made on the same day.
Respirometry, activity detection, and monitoring/controlling temperature
To measure CO2 output, we used a flow-through respirometry
system (Sable Systems International, Las Vegas, NV, USA). The respirometer
chambers were constructed from 2-dram, glass shell vials (19 mm
diameterx51 mm length, Kimble Glass, Inc., Vineland, NJ, USA), each
fitted with a two-holed, solid-rubber stopper (no. 2). A piece of aluminum
tubing (50 mm length, 4.76 mm i.d.; K&S Engineering, Chicago, IL,
USA) was pushed into each hole of the stopper until the end of the tube was
flush with the bottom surface. A piece of fine mesh was glued to the bottom
surface of the stopper to keep flies from escaping. Space between the stopper
holes and the aluminum tubes was filled with silicone sealant (Devcon, Riviera
Beach, FL, USA). The two sections of aluminum tubing (23 mm length)
protruding from the top of the stopper were used to attach tubing (1.5875 mm
i.d., PharMed, Cole-Parmer Instrument Co., Vernon Hills, IL, USA), which
directed air flow to an RM8 Intelligent Multiplexer (Sable Systems
International). A thermocouple (Type T) wire was inserted into the PharMed
tubing and threaded into the respirometer chamber, allowing us to record the
chamber temperature at 1 s intervals. [The thermocouple wire was connected to
a digital thermometer (Omega HH509R, Stamford, CT, USA).] The wire insertion
site was sealed with silicone sealant.
An air pump (Topfin, XP-125, Pacific Coast Distributors, Inc., Phoenix, AZ,
USA) pulled air into the respirometry system. The air stream was then pushed
through three scrubbing columns: (1) silica gel (Type III, Sigma-Aldrich, St
Louis, MO, USA), (2) silica gel and (3) Drierite/Ascarite II/Drierite
(DrieriteTM: Fisher Scientific, Pittsburgh, PA, USA; Ascarite IITM:
Thomas Scientific, Swedesboro, NJ, USA), and then through a mass flow control
valve (Side-Trak, Sierra Instruments, Inc., Monterey, CA, USA) at a mass flow
rate of 50 ml min-1, maintained by a Mass Flow Controller (Sable
Systems International, Version 1.1). The air stream flowed next through tubing
and a coil of aluminum tubing (350 mm length; 3 mm i.d.) held in a
temperature-control incubator (DigiTherm Incubator, Tritech Research, Los
Angeles, CA, USA), to promote thermal equilibration of the air (see
Lighton and Turner, 2004). The
temperature-equilibrated air then flowed through the respirometer chamber and
into the Li-Cor 7000 CO2 infrared gas analyzer (LI-COR, Inc.,
Lincoln, NE, USA). (Before the air stream reached the CO2 analyzer,
H2O released by the fly was scrubbed with magnesium
perchlorate.)
In order to measure CO2 output within a temperature-controlled environment, we kept the RM8 Intelligent Multiplexer (Sable Systems International, the RM8 controls the air flow through different respirometer chambers) inside the incubator. We used only two respirometer chambers in each experiment: no. 1 for obtaining the zero-CO2 baseline, and no. 2 for measuring CO2 output from a fly. The temperature of the incubator was set initially at 30°C. When the temperature inside chamber no. 2 reached 30±0.5°C, we inserted a fly and allowed it to equilibrate for 5 min, during which time we set zero-CO2 baseline from the empty chamber (no. 1). After equilibration, we started measuring CO2 output; and at the same time, we increased the incubator temperature setting to 50°C. The temperature within the fly respirometer chamber increased at an average rate of 0.24±0.02°C min-1. We continued to measure CO2 output of each fly until the temperature inside the chamber reached >45°C, well beyond the lethal temperature. ExpeData software (Sable Systems International, Version 1.01) was used to control the respirometry system and for data acquisition.
An AD-1 activity detector (Sable Systems International, Version 2) was used to monitor fly activity in conjunction with the CO2 data acquisition. The respirometer chamber fit securely into the cradle of the AD-1, which generates an infrared light (880 nm) field. Movements of the fly cause fluctuations in the light field intensity, which are detected and recorded (by ExpeData software) as deviations from a zero-activity baseline. Activity was recorded at 1 s intervals.
Data analysis and CTmax
We used the methods of Klok et al. to estimate both
CTmax endpoints (Klok
et al., 2004). CTmax for spiracular function
was indicated on each respirometry tracing by a distinctive and abrupt
alteration in the pattern of CO2 output, characterized by a
dramatic reduction in the variance (Fig.
2). Using the data analysis functions of ExpeData software, we
were able to select the transitional point on each tracing at which the
CO2 output was altered. The CO2 data were aligned with
the temperature data (using the timing of both recordings), allowing us to
estimate the temperature at which spiracular function was compromised
(CTmax). The CO2 data were transformed using
R, version 2.2.1 (R Development
Core Team, 2006) by: (1) correcting for baseline drift, (2)
converting from p.p.m. to µl h-1 (mass flow rate=50 ml
min-1) and (3) normalizing with body mass (µg).
CTmax for locomotor function was estimated in a similar
manner. Using the data analysis functions of ExpeData software, we marked the
point on each activity tracing beyond which activity was no longer apparent
(Fig. 2). The activity data
were aligned with the temperature data (as above), allowing us to estimate
this CTmax.
|
|
Results |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
). Essentially, the High TKD lines
have evolved significantly enhanced knockdown thermotolerance with an overall
mean TKD that is >5°C above that of the Low
TKD lines, and >4°C above that of the control
lines. Populations of D. melanogaster typically have a bimodal
distribution for TKD
(Gilchrist and Huey, 1999). We
show in Table 1 the mean
TKD values of the upper and lower modes of the knockdown
populations (Folk et al.,
2006). In response to selection, the HN lines have a significant
reduction in the numbers of individuals in the lower mode; conversely, the LN
lines have relatively few individuals in the upper mode (see
Table 1 legend).
|
Metabolic profile and CTmax endpoints
The metabolic profiles of the flies during the temperature ramp resemble
those observed in a tenebrionid beetle (Gonocephalum simplex) and in
ants (Pogonomyrmex rugosus and P. californicus)
(Klok et al., 2004;
Lighton and Turner, 2004).
During the initial phase of the profile, CO2 output increases
exponentially and reaches a maximum, followed by a short plateau
(Fig. 2). The profile then
shows a `mortal fall' (Lighton and Turner,
2004), during which CO2 output drops, and oscillates
dramatically in some flies. Following the mortal fall, the pattern of
CO2 release is distinctively altered by an abrupt reduction in
variance, indicating CTmax for spiracular control
(Fig. 2). At temperatures
>CTmax, the ability to modulate spiracle opening is
apparently lost and CO2 is released continually. The release of
CO2 during this phase, termed the `postmortal peak', may be due to
the discharge of bound and dissolved CO2 or to mitochondrial
respiration that continues beyond CTmax
(Lighton and Turner, 2004).
Interestingly, preliminary observations indicate that the flies seemingly
recover when switched to a milder temperature (23°C) following 2-4
min into the postmortal peak phase, suggesting that physiological processes
are not irreversibly damaged at the onset of the postmortal peak phase. These
few minutes may constitute a window of recovery, beyond which death is
inevitable if the fly is not moved to milder thermal conditions. Following
this final peak of CO2 release, exponential decay in CO2
output was observed in all flies (Fig.
2).
The critical thermal maximum for locomotor function was estimated from the activity patterns of individual flies and was defined as the highest temperature beyond which movement was no longer detectable (Fig. 2).
The effect of knockdown selection on both CTmax endpoints, as well as on TMetMax (the temperature at which maximal metabolic rate occurred) among the HN, LN and CN groups was examined using Model I ANOVA. CTmax for locomotor function did not differ among the groups (F[2,45]=0.1228, P=0.8848), nor did CTmax for spiracular control (F[2,45]=0.2122, P=0.8096) nor TMetMax (F[2,45]=0.1262, P=0.8817). We used boxplots to summarize graphically the data for the CTmax thermal endpoints (Fig. 3A,B). Homogeneity of variances for CTmax of locomotor function among the groups was examined using a Bartlett's test, which showed that the LN lines had a significantly lower variance than the CN and HN lines for CTmax of locomotor function (P<0.001).
|
To determine whether the dual CTmax measures are functionally related within individual flies we used least squares-linear regression analysis (Fig. 4). Specifically, we tested whether CTmax for locomotory function of a fly is predictive of CTmax for its spiracular control. The relationship between the two CTmax endpoints was essentially unity for the HN and CN lines: the slopes of the regression lines were 0.99 (P=1.28x10-14) and 1.04 (P=3.72x10-7), respectively. The slope of the regression line for the LN group was not significantly different from zero (P=0.1233). The lack of significance is likely due to the exceedingly low variance in CTmax in the LN group.
|
To test for the effects of selection and sex on the pattern of
mass-specific
CO2 (µl
h-1 mg-1) over a temperature range of 32°C to
CTmax (41°C), we used a second-order orthogonal
polynomial analysis for repeated measures. Both
CO2 and the
temperature data were log-transformed to attain a normal distribution. We
tested for homogeneity of the second-order orthogonal polynomial coefficients
among the sex X selection groups and were unable to reject the null hypothesis
of homogeneity of slopes (F[4,42]=0.0088,
P=0.9998). We then fit common second-order orthogonal polynomial
coefficients to the sex X selection groups and tested for homogeneity among
the intercepts using ANCOVA. Knockdown selection did not have a significant
effect on mass-specific
CO2 over the
experimental range of temperatures (F[2,42]=0.0048,
P=1.0000), whereas sex had a strong effect
(F[1,42]=32.5884, P=1.042x10-6).
All males had a significantly higher mass-specific
CO2 when heated
than the females (Fig. 5).
|
CO2 at the
critical thermal endpoints, namely CTmax for spiracular
control, CTmax for locomotor function and
TMetMax, was tested using Model I ANOVA.
CO2 of the
treatment groups did not differ significantly at any of the critical thermal
endpoints (CTmax for spiracular control:
F[2,45]=0.4528, P=0.6387;
CTmax for locomotor function:
F[2,45]=0.2634, P=0.7696; and
TMetMax: F[2,45]=0.2501,
P=0.7798). Mean
CO2 at each
critical temperature for all selection groups is listed in
Table 1.
Q10 of metabolic rate
We used Model I ANOVA to test for the effects of sex and selection on
Q10 for CO2 production during the temperature ramp,
focusing on sensitivity of metabolic rate to increasing temperature during the
exponential phase (32-38°C). When calculating Q10, we corrected
for the <10°C change in temperature. Although sex did not affect
Q10 (F[1,42]=0.3399, P=0.5630),
selection treatment had a significant effect
(F[2,42]=4.2193, P=0.0214). The LN flies had a
lower Q10 than the HN flies (Tukey HSD, P=0.043) and the
CN flies (Tukey HSD, P=0.039). Q10 did not differ
significantly between the CN and HN flies (Tukey HSD, P=0.999). These
data suggest that the thermal sensitivity of metabolic rate in the LN flies
was relatively reduced. Q10 values for all groups are listed in
Table 2.
|
|
Discussion |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
; Folk et al.,
2006). The HN lines have evolved the ability to maintain normal
posture within a heated knockdown column at temperatures 40°C. In
contrast the LN lines fall down and out of the column at much cooler
temperatures (35°C). A primary aim of this study was to estimate the
critical thermal maxima for locomotor and spiracular function in the divergent
knockdown lines in order to explore the correlation, or lack thereof, between
various thermal endpoints. Our data indicate that, although
TKD has diverged between the HN and LN lines, the
CTmax endpoints have not shifted in accordance. These
findings underscore the importance of the notion that the "choice of
indices for study (of thermotolerance) could be critical"
(Berrigan, 2000).
Correlation between thermal endpoints
The CTmax endpoints for locomotor function and
spiracular control of each fly are essentially equivalent
(Fig. 4). The thermal ceiling
of both the locomotory and spiracular control systems are strikingly similar.
We propose that a shared physiological constraint may dictate the upper
thermal boundary of the dual CTmax endpoints. Hochachka
and Somero (Hochachka and Somero,
2002) proposed that all physiological systems participate in
setting thermotolerance limits of an organism, but that `weak links' assert
the strongest influence. They further propose that the `weakest links' in
thermotolerance are cellular membranes. Alternatively, Pörtner proposed
that at high temperatures metabolic rate may be limited by inadequate delivery
of oxygen to the mitochondria
(Pörtner, 2002). Klok et
al. provide evidence that this may not be the case in terrestrial insects
(Klok et al., 2004). Thermal
stress can disrupt membrane homeostasis by altering composition, permeability,
ion channel activity, etc. A membrane property that is highly sensitive to
thermal stress is synaptic transmission, the thermal impairment of which would
compromise both effective locomotion and control of ventilation
(Robertson, 2004). The narrow
range of the CTmax endpoints in our flies supports the
hypothesis of a common `weakest link', such as synaptic transmission
(Fig. 3A,B). The LN lines, in
particular, had very little variability for CTmax of
locomotor function. (Stabilizing selection on a limited range of lower
TKD values appears to have eliminated most of the
variability for this trait.) Overall, our findings are suggestive of a
mechanistic correlation between both measures of
CTmax.
High and low knockdown phenotypes: different traits?
Knockdown temperature has been defined generally as the "upper
temperature at which a fly falls from a Weber column"
(Huey et al., 2003). In
natural populations, the distribution for knockdown temperature is typically
bimodal (Gilchrist and Huey,
1999). Selection for High TKD causes flies to
lose the lower mode of the distribution, whereas selection for Low
TKD tends to eradicate the upper mode. The simplest
explanation for the shift to a unimodal distribution is that we are selecting
for enhanced (in HN lines) or diminished (in LN lines) performance of a
complex polymorphic trait. We propose otherwise. Specifically, we propose that
the upper and lower modes of knockdown may represent altogether different
traits. Selection for High TKD may be targeting
CTmax, the thermal ceiling for heat paralysis.
Interestingly, both TKD of the HN flies and
CTmax of the HN and LN flies are set at
41°C (Table 1). If
High TKD is essentially CTmax, then
the same mechanisms (discussed above) involved in establishing
CTmax would be involved in setting the upper limits of
knockdown temperature.
Selection on Low TKD may be targeting something altogether different, possibly behavior. When we first place the LN lines into the knockdown column during an experiment, the column temperature is moderately high (30°C). As the column temperature rises, the LN flies tend to walk along the surface of the baffles, move to the lower edge, and then drop to a lower baffle. They continue to drop to successively lower baffles, until eventually they drop out of the column. The HN flies do not display these behaviors. They localize within the top half of the column when first transferred to the column and do not tend to travel downwards during knockdown. These behavioral peculiarities have led us to question whether we are selecting for a behavioral phenotype in the LN flies. Specifically, are we selecting for negative phototaxis, positive geotaxis, or escape behavior? If this were the case, it might explain the lack of correlation between TKD and CTmax in the LN flies.
Historical selection experiments, using D. melanogaster and D.
pseudoobscura, generated flies with strong positive or negative geotactic
(also phototactic) behaviors (Hirsch and
Erlenmeyer-Kimling, 1961;
Dobzhansky and Spassky, 1962;
Del Solar, 1966). The flies had
sufficient genetic variation for these behaviors and responded quickly to
selection. Interestingly, two desert species (D. mettleri and D.
nigrospiracula) share photonegative behavior, but display contrasting
geotactic behaviors (Markow and Fogleman,
1981). Toma et al. have identified a number of genes involved in
phototaxic and geotaxic responses, providing evidence that they are highly
complex polygenic behaviors (Toma et al.,
2002). We speculate that our selection lines, in response to
selection for high or low knockdown performance, may have diverged in the
expression of such behaviors.
Evolution of thermal sensitivity of metabolism
The composite metabolic profile during the mounting heat stress was similar
among the HN, LN and CN lines (Fig.
5). Yet, as indicated by the Q10 values, the thermal
sensitivity of metabolism was significantly reduced in the LN lines
(Table 2). We are now presented
with a paradox: why do flies selected for a lower knockdown temperature have
reduced metabolic thermal sensitivity? Selection for Low
TKD performance may have resulted in photo- and geotactic
behaviors (discussed above) genetically correlated to metabolic performance.
Selection on phototaxis and geotaxis in Drosophila results in
correlated changes in multiple traits, including eye size, testis color, wing
venation and mating behavior (Del Solar,
1966; Dobzhansky and Spassky,
1969). Toma et al. compared gene expression of 250 genes in
populations of D. melanogaster selected for negative or positive
geotaxis and found that 5% of the genes were differentially expressed
(Toma et al., 2002). Further
testing strongly implicated three candidate genes, whose mechanistic
involvement in geotaxis is unclear. We speculate that selection on photo- or
geotaxis (via selection on low knockdown) may lead to genetic changes
influencing the thermal sensitivity of metabolism. An informative study would
be to select on photo- or geotaxis and monitor metabolism, particularly
Q10 values during heat stress.
In summary, ambient temperature of small ectotherms, such as Drosophila melanogaster, influences directly all physiological networks. We have explored here the thermal limits of respiratory and locomotor performance of flies. We hypothesized that the critical thermal maxima of these performances would co-evolve with knockdown temperature. The dual CTmax values were strongly correlated with each other and with knockdown temperature in the HN lines, suggesting a shared physiological `weakest link' in thermal sensitivity. The CTmax values were not correlated with knockdown temperature in the LN flies, leading us to conclude that some other `weakest link', perhaps behavioral, sets knockdown in these populations. Finally, respiratory and gross activity patterns were not altered significantly in the LN flies at TKD, resulting in an inability to detect TKD using thermolimit respirometry or activity monitoring.
|
Acknowledgments |
|---|
|
References |
|---|
|
TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
|---|
Berrigan, D. (2000). Correlations between measures of thermal stress resistance within and between species. Oikos 89,301 -304.[CrossRef]
Berrigan, D. and Hoffmann, A. A. (1998). Correlations between measures of heat resistance and acclimation in two species of Drosophila and their hybrids. Biol. J. Linn. Soc. Lond. 64,449 -462.[CrossRef]
Cowles, R. B. and Bogert, C. M. (1944). A preliminary study of the thermal requirements of desert reptiles. Bull. Am. Mus. Nat. Hist. 83,261 -296.
Del Solar, E. (1966). Sexual isolation caused
by selection for positive and negative phototaxis and geotaxis in
Drosophila pseudoobscura. Proc. Natl. Acad. Sci. USA
56,484
-487.
Dobzhansky, T. and Spassky, B. (1962).
Selection for geotaxis in monomorphic and polymorphic populations of
Drosophila pseudoobscura. Proc. Natl. Acad. Sci. USA
48,1704
-1712.
Dobzhansky, T. and Spassky, B. (1969).
Artificial and natural selection for two behavioral traits in Drosophila
pseudoobscura. Proc. Natl. Acad. Sci. USA
62, 75-80.
Folk, D. G., Zwollo, P., Rand, D. M. and Gilchrist, G. W.
(2006). Selection on knockdown performance in Drosophila
melanogaster impacts thermotolerance and heat-shock response differently
in females and males. J. Exp. Biol.
209,3964
-3973.
Gilchrist, G. W. and Huey, R. B. (1999). The direct response of Drosophila melanogaster to selection on knockdown temperature. Heredity 83, 15-29.[CrossRef][Medline]
Hirsch, J. and Erlenmeyer-Kimling, L. (1961).
Sign of taxis as a property of the genotype. Science
134,835
-836.
Hochachka, P. W. and Somero, G. N. (2002). Biochemical Adaptation: Mechanism and Process in Physiological Evolution. New York: Oxford University Press.
Hoffmann, A. A., Dagher, H., Hercus, M. and Berrigan, D. (1997). Comparing different measures of heat resistance in selected lines of Drosophila melanogaster. J. Insect Physiol. 43,393 -405.[CrossRef][Medline]
Hoffmann, A. A., Sørensen, J. G. and Loeschcke, V. (2003). Adaptation of Drosophila to temperature extremes: bringing together quantitative and molecular approaches. J. Therm. Biol. 28,175 -216.[CrossRef]
Houghton, J. T., Ding, Y., Griggs, D. J., Noguer, M., van der Linden, P. J., Dai, X., Maskell, K. and Johnson, C. A. (ed.) (2001). IPCC, 2001, Climate Change 2001, The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, NY, USA: Cambridge University Press.
Huey, R. B. and Bennett, A. F. (1990). Physiological adjustments to fluctuating thermal environments: an ecological and evolutionary perspective. In Stress Proteins in Biology and Medicine (ed. A. Tissieres, R. I. Morimoto and C. Georgopoulos), pp. 37-59. New York: Cold Spring Harbor Laboratory Press.
Huey, R., Partridge, L. and Fowler, K. (1991). Thermal sensitivity of Drosophila melanogaster responds rapidly to laboratory natural selection. Evolution 45,751 -756.[CrossRef]
Huey, R. B., Crill, W. D., Kingsolver, J. G. and Weber, K. E. (1992). A method for rapid measurement of heat or cold resistance of small insects. Funct. Ecol. 6, 489-494.[CrossRef]
Huey, R. B., Gilchrist, G. W., Ward, K., Maves, L., Pepin, D.
and Houle, D. (2003). Mutation accumulation, performance,
fitness. Integr. Comp. Biol.
43,387
-395.
Kellett, M., Hoffmann, A. A. and McKechnie, S. W. (2005). Hardening capacity in the Drosophila melanogaster species group is constrained by basal thermotolerance. Funct. Ecol. 19,853 -858.[CrossRef]
Klok, J. C., Sinclair, B. J. and Chown, S. L.
(2004). Upper thermal tolerance and oxygen limitation in
terrestrial arthropods. J. Exp. Biol.
207,2361
-2370.
Krebs, R. A., Roberts, S. P., Bettencourt, B. R. and Feder, M. E. (2001). Changes in thermotolerance and Hsp70 expression with domestication in Drosophila melanogaster. J. Evol. Biol. 14,75 -82.[CrossRef]
Lighton, J. R. B. and Turner, R. J. (2004).
Thermolimit respirometry: an objective assessment of critical thermal maxima
in two sympatric desert harvester ants, Pogonomyrmex rugosus and
P. californicus. J. Exp. Biol.
207,1903
-1913.
Lutterschmidt, W. I. and Hutchison, V. H. (1997). The critical thermal maximum: history and critique. Can. J. Zool. 75,1561 -1574.
Markow, T. A. and Fogleman, J. C. (1981). Behavioral differentiation between two species of cactiphilic Drosophila. 1. Adult geotaxis and phototaxis. Cell. Mol. Life Sci. 37,145 -146.
McColl, G., Hoffmann, A. A. and McKechnie, S. W. (1996). Response of two heat shock genes to selection for knockdown heat resistance in Drosophila melanogaster.Genetics 143,1615 -1627.[Abstract]
Newman, A. E. M., Xiao, C. and Robertson, R. M. (2005). Synaptic thermoprotection in a desert-dwelling Drosophila species. J. Neurobiol. 64,170 -180.[CrossRef][Medline]
Pörtner, H.-O. (2002). Climate variations and the physiological basis of temperature dependent biogeography: systemic to molecular hierarchy of thermal tolerance in animals. Comp. Biochem. Physiol. 132A,739 -761.[CrossRef][Medline]
R Development Core Team (2006). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.
Rashkovetsky, E., Iliadi, K., Michalak, P., Lupu, A., Nevo, E., Feder, M. E. and Korol, A. (2006). Adaptive differentiation of thermotolerance in Drosophila along a microclimatic gradient. Heredity 96,353 -359.[CrossRef][Medline]
Roberts, S. P., Marden, J. H. and Feder, M. E. (2003). Dropping like flies: environmentally induced impairment and protection of locomotor performance in adult Drosophila melanogaster.Physiol. Biochem. Zool. 76,615 -621.[CrossRef][Medline]
Robertson, R. M. (2004). Thermal stress and neural function: adaptive mechanisms in insect model systems. J. Therm. Biol. 29,351 -358.[CrossRef]
Sørensen, J. G., Dahlgaard, J. and Loeschcke, V. (2001). Genetic variation in thermal tolerance among natural populations of Drosophila buzzatii: down regulation of Hsp70 expression and variation in heat stress resistance traits. Funct. Ecol. 15,289 -293.[CrossRef]
Stratman, R. and Markow, T. A. (1998). Resistance to thermal stress in desert Drosophila. Funct. Ecol. 12,965 -970.[CrossRef]
Toma, D. P., White, K. P., Hirsch, J. and Greenspan, R. J. (2002). Identification of genes involved in Drosophila melanogaster geotaxis, a complex behavioral trait. Nat. Genet. 31,349 -353.[CrossRef][Medline]
Weber, K. E. (1988). An apparatus for measurement of resistance to gas-phase agents. Drosoph. Inf. Serv. 67,91 .
Zatsepina, O. G., Velikodvorskaia, V. V., Molodtsov, V. B.,
Garbuz, D., Lerman, D. N., Bettencourt, B. R., Feder, M. E. and Evgenev, M.
B. (2001). A Drosophila melanogaster strain from
sub-equatorial Africa has exceptional thermotolerance but decreased Hsp70
expression. J. Exp. Biol.
204,1869
-1881.
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
